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4
.coveragerc
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[run] [run]
branch = True branch = True
source = camelot
include = */camelot/*
omit =
*/setup.py

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.github/FUNDING.yml vendored
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open_collective: camelot

57
.github/ISSUE_TEMPLATE/bug_report.md vendored
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@ -1,57 +0,0 @@
---
name: Bug report
about: Please follow this template to submit bug reports.
title: ''
labels: bug
assignees: ''
---
<!-- Please read the filing issues section of the contributor's guide first: https://camelot-py.readthedocs.io/en/master/dev/contributing.html -->
**Describe the bug**
<!-- A clear and concise description of what the bug is. -->
**Steps to reproduce the bug**
<!-- Steps used to install `camelot`:
1. Add step here (you can add more steps too) -->
<!-- Steps to be used to reproduce behavior:
1. Add step here (you can add more steps too) -->
**Expected behavior**
<!-- A clear and concise description of what you expected to happen. -->
**Code**
<!-- Add the Camelot code snippet that you used. -->
```
import camelot
# add your code here
```
**PDF**
<!-- Add the PDF file that you want to extract tables from. -->
**Screenshots**
<!-- If applicable, add screenshots to help explain your problem. -->
**Environment**
- OS: [e.g. macOS]
- Python version:
- Numpy version:
- OpenCV version:
- Ghostscript version:
- Camelot version:
**Additional context**
<!-- Add any other context about the problem here. -->

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.github/workflows/tests.yml vendored
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name: tests
on: [pull_request]
jobs:
test:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: [3.6, 3.7, 3.8]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Install camelot with dependencies
run: |
make install
- name: Test with pytest
run: |
make test
test_latest:
name: Test on ${{ matrix.os }} with Python 3.9
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ubuntu-latest, macos-latest, windows-latest]
python-version: [3.9]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Install camelot with dependencies
run: |
make install
- name: Test with pytest
run: |
make test

9
.gitignore vendored
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fontconfig/
__pycache__/ __pycache__/
*.py[cod] *.py[cod]
*.so *.so
@ -6,15 +5,7 @@ __pycache__/
build/ build/
dist/ dist/
*.egg-info/ *.egg-info/
.eggs/
.coverage .coverage
coverage.xml
.pytest_cache/ .pytest_cache/
_build/ _build/
.venv/
htmlcov/
# vscode
.vscode

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.readthedocs.yml
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# .readthedocs.yml
# Read the Docs configuration file
# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
# Required
version: 2
# Build documentation in the docs/ directory with Sphinx
sphinx:
configuration: docs/conf.py
# Build documentation with MkDocs
#mkdocs:
# configuration: mkdocs.yml
# Optionally build your docs in additional formats such as PDF
formats:
- pdf
# Optionally set the version of Python and requirements required to build your docs
python:
version: 3.8
install:
- method: pip
path: .
extra_requirements:
- dev

28
CONTRIBUTING.md
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@ -2,7 +2,7 @@
If you're reading this, you're probably looking to contributing to Camelot. *Time is the only real currency*, and the fact that you're considering spending some here is *very* generous of you. Thank you very much! If you're reading this, you're probably looking to contributing to Camelot. *Time is the only real currency*, and the fact that you're considering spending some here is *very* generous of you. Thank you very much!
This document will help you get started with contributing documentation, code, testing and filing issues. If you have any questions, feel free to reach out to [Vinayak Mehta](https://vinayak-mehta.github.io), the author and maintainer. This document will help you get started with contributing documentation, code, testing and filing issues. If you have any questions, feel free to reach out to [Vinayak Mehta](http://vinayak-mehta.github.io), the author and maintainer.
## Code Of Conduct ## Code Of Conduct
@ -14,29 +14,31 @@ Kenneth Reitz has also written an [essay](https://www.kennethreitz.org/essays/be
As the [Requests Code Of Conduct](http://docs.python-requests.org/en/master/dev/contributing/#be-cordial) states, **all contributions are welcome**, as long as everyone involved is treated with respect. As the [Requests Code Of Conduct](http://docs.python-requests.org/en/master/dev/contributing/#be-cordial) states, **all contributions are welcome**, as long as everyone involved is treated with respect.
## Your first contribution ## Your First Contribution
A great way to start contributing to Camelot is to pick an issue tagged with the [help wanted](https://github.com/camelot-dev/camelot/labels/help%20wanted) tag or the [good first issue](https://github.com/camelot-dev/camelot/labels/good%20first%20issue) tag. If you're unable to find a good first issue, feel free to contact the maintainer. A great way to start contributing to Camelot is to pick an issue tagged with the [Contributor Friendly](https://github.com/socialcopsdev/camelot/labels/Contributor%20Friendly) tag or the [Level: Easy](https://github.com/socialcopsdev/camelot/labels/Level%3A%20Easy) tag. If you're unable to find a good first issue, feel free to contact the maintainer.
## Setting up a development environment ## Setting up a development environment
To install the dependencies needed for development, you can use pip: To install the dependencies needed for development, you can use pip:
<pre> <pre>
$ pip install "camelot-py[dev]" $ pip install camelot-py[dev]
</pre> </pre>
Alternatively, you can clone the project repository, and install using pip: ### Alternatively
You can clone the project repository, and install using pip:
<pre> <pre>
$ pip install ".[dev]" $ pip install .[dev]
</pre> </pre>
## Pull Requests ## Pull Requests
### Submit a pull request ### Submit a Pull Request
The preferred workflow for contributing to Camelot is to fork the [project repository](https://github.com/camelot-dev/camelot) on GitHub, clone, develop on a branch and then finally submit a pull request. Here are the steps: The preferred workflow for contributing to Camelot is to fork the [project repository](https://github.com/socialcopsdev/camelot) on GitHub, clone, develop on a branch and then finally submit a pull request. Steps:
1. Fork the project repository. Click on the ‘Fork’ button near the top of the page. This creates a copy of the code under your account on the GitHub. 1. Fork the project repository. Click on the ‘Fork’ button near the top of the page. This creates a copy of the code under your account on the GitHub.
@ -71,7 +73,7 @@ $ git push -u origin my-feature
Now it's time to go to the your fork of Camelot and create a pull request! You can [follow these instructions](https://help.github.com/articles/creating-a-pull-request-from-a-fork/) to do this. Now it's time to go to the your fork of Camelot and create a pull request! You can [follow these instructions](https://help.github.com/articles/creating-a-pull-request-from-a-fork/) to do this.
### Work on your pull request ### Work on your Pull Request
We recommend that your pull request complies with the following rules: We recommend that your pull request complies with the following rules:
@ -79,7 +81,7 @@ We recommend that your pull request complies with the following rules:
- In case your pull request contains function docstrings, make sure you follow the [numpydoc](https://numpydoc.readthedocs.io/en/latest/format.html) format. All function docstrings in Camelot follow this format. Moreover, following the format will make sure that the API documentation is generated flawlessly. - In case your pull request contains function docstrings, make sure you follow the [numpydoc](https://numpydoc.readthedocs.io/en/latest/format.html) format. All function docstrings in Camelot follow this format. Moreover, following the format will make sure that the API documentation is generated flawlessly.
- Make sure your commit messages follow [the seven rules of a great git commit message](https://chris.beams.io/posts/git-commit/): - Make sure your commit messages follow [the seven rules of a great git commit message](https://chris.beams.io/posts/git-commit/).
- Separate subject from body with a blank line - Separate subject from body with a blank line
- Limit the subject line to 50 characters - Limit the subject line to 50 characters
- Capitalize the subject line - Capitalize the subject line
@ -102,15 +104,15 @@ Writing documentation, function docstrings, examples and tutorials is a great wa
It is written in [reStructuredText](https://en.wikipedia.org/wiki/ReStructuredText), with [Sphinx](http://www.sphinx-doc.org/en/master/) used to generate these lovely HTML files that you're currently reading (unless you're reading this on GitHub). You can edit the documentation using any text editor and then generate the HTML output by running `make html` in the `docs/` directory. It is written in [reStructuredText](https://en.wikipedia.org/wiki/ReStructuredText), with [Sphinx](http://www.sphinx-doc.org/en/master/) used to generate these lovely HTML files that you're currently reading (unless you're reading this on GitHub). You can edit the documentation using any text editor and then generate the HTML output by running `make html` in the `docs/` directory.
The function docstrings are written using the [numpydoc](https://numpydoc.readthedocs.io/en/latest/format.html) extension for Sphinx. Make sure you check out its format guidelines before you start writing one. The function docstrings are written using the [numpydoc](https://numpydoc.readthedocs.io/en/latest/format.html) extension for Sphinx. Make sure you check out its format guidelines, before you start writing one.
## Filing Issues ## Filing Issues
We use [GitHub issues](https://github.com/camelot-dev/camelot/issues) to keep track of all issues and pull requests. Before opening an issue (which asks a question or reports a bug), please use GitHub search to look for existing issues (both open and closed) that may be similar. We use [GitHub issues](https://docs.pytest.org/en/latest/) to keep track of all issues and pull requests. Before opening an issue (which asks a question or reports a bug), it is advisable to use GitHub search to look for existing issues (both open and closed) that may be similar.
### Questions ### Questions
Please don't use GitHub issues for support questions. A better place for them would be [Stack Overflow](http://stackoverflow.com). Make sure you tag them using the `python-camelot` tag. Please don't use GitHub issues for support questions, a better place for them would be [Stack Overflow](http://stackoverflow.com). Make sure you tag them using the `python-camelot` tag.
### Bug Reports ### Bug Reports

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HISTORY.md
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Release History
===============
master
------
0.10.1 (2021-07-11)
------------------
- Change extra requirements from `cv` to `base`. You can use `pip install "camelot-py[base]"` to install everything required to run camelot.
0.10.0 (2021-07-11)
------------------
**Improvements**
- Add support for multiple image conversion backends. [#198](https://github.com/camelot-dev/camelot/pull/198) and [#253](https://github.com/camelot-dev/camelot/pull/253) by Vinayak Mehta.
- Add markdown export format. [#222](https://github.com/camelot-dev/camelot/pull/222/) by [Lucas Cimon](https://github.com/Lucas-C).
**Documentation**
- Add faq section. [#216](https://github.com/camelot-dev/camelot/pull/216) by [Stefano Fiorucci](https://github.com/anakin87).
0.9.0 (2021-06-15)
------------------
**Bugfixes**
- Fix use of resolution argument to generate image with ghostscript. [#231](https://github.com/camelot-dev/camelot/pull/231) by [Tiago Samaha Cordeiro](https://github.com/tiagosamaha).
- [#15](https://github.com/camelot-dev/camelot/issues/15) Fix duplicate strings being assigned to the same cell. [#206](https://github.com/camelot-dev/camelot/pull/206) by [Eduardo Gonzalez Lopez de Murillas](https://github.com/edugonza).
- Save plot when filename is specified. [#121](https://github.com/camelot-dev/camelot/pull/121) by [Jens Diemer](https://github.com/jedie).
- Close file streams explicitly. [#202](https://github.com/camelot-dev/camelot/pull/202) by [Martin Abente Lahaye](https://github.com/tchx84).
- Use correct re.sub signature. [#186](https://github.com/camelot-dev/camelot/pull/186) by [pevisscher](https://github.com/pevisscher).
- [#183](https://github.com/camelot-dev/camelot/issues/183) Fix UnicodeEncodeError when using Stream flavor by adding encoding kwarg to `to_html`. [#188](https://github.com/camelot-dev/camelot/pull/188) by [Stefano Fiorucci](https://github.com/anakin87).
- [#179](https://github.com/camelot-dev/camelot/issues/179) Fix `max() arg is an empty sequence` error on PDFs with blank pages. [#189](https://github.com/camelot-dev/camelot/pull/189) by Vinayak Mehta.
**Improvements**
- Add `line_overlap` and `boxes_flow` to `LAParams`. [#219](https://github.com/camelot-dev/camelot/pull/219) by [Arnie97](https://github.com/Arnie97).
- [Add bug report template.](https://github.com/camelot-dev/camelot/commit/0a3944e54d133b701edfe9c7546ff11289301ba8)
- Move from [Travis to GitHub Actions](https://github.com/camelot-dev/camelot/pull/241).
- Update `.readthedocs.yml` and [remove requirements.txt](https://github.com/camelot-dev/camelot/commit/7ab5db39d07baa4063f975e9e00f6073340e04c1#diff-cde814ef2f549dc093f5b8fc533b7e8f47e7b32a8081e0760e57d5c25a1139d9)
**Documentation**
- [#193](https://github.com/camelot-dev/camelot/issues/193) Add better checks to confirm proper installation of ghostscript. [#196](https://github.com/camelot-dev/camelot/pull/196) by [jimhall](https://github.com/jimhall).
- Update `advanced.rst` plotting examples. [#119](https://github.com/camelot-dev/camelot/pull/119) by [Jens Diemer](https://github.com/jedie).
0.8.2 (2020-07-27)
------------------
* Revert the changes in `0.8.1`.
0.8.1 (2020-07-21)
------------------
**Bugfixes**
* [#169](https://github.com/camelot-dev/camelot/issues/169) Fix import error caused by `pdfminer.six==20200720`. [#171](https://github.com/camelot-dev/camelot/pull/171) by Vinayak Mehta.
0.8.0 (2020-05-24)
------------------
**Improvements**
* Drop Python 2 support!
* Remove Python 2.7 and 3.5 support.
* Replace all instances of `.format` with f-strings.
* Remove all `__future__` imports.
* Fix HTTP 403 forbidden exception in read_pdf(url) and remove Python 2 urllib support.
* Fix test data.
**Bugfixes**
* Fix library discovery on Windows. [#32](https://github.com/camelot-dev/camelot/pull/32) by [KOLANICH](https://github.com/KOLANICH).
* Fix calling convention of callback functions. [#34](https://github.com/camelot-dev/camelot/pull/34) by [KOLANICH](https://github.com/KOLANICH).
0.7.3 (2019-07-07)
------------------
**Improvements**
* Camelot now follows the Black code style! [#1](https://github.com/camelot-dev/camelot/pull/1) and [#3](https://github.com/camelot-dev/camelot/pull/3).
**Bugfixes**
* Fix Click.HelpFormatter monkey-patch. [#5](https://github.com/camelot-dev/camelot/pull/5) by [Dimiter Naydenov](https://github.com/dimitern).
* Fix strip_text argument getting ignored. [#4](https://github.com/camelot-dev/camelot/pull/4) by [Dimiter Naydenov](https://github.com/dimitern).
* [#25](https://github.com/camelot-dev/camelot/issues/25) edge_tol skipped in read_pdf. [#26](https://github.com/camelot-dev/camelot/pull/26) by Vinayak Mehta.
* Fix pytest deprecation warning. [#2](https://github.com/camelot-dev/camelot/pull/2) by Vinayak Mehta.
* [#293](https://github.com/socialcopsdev/camelot/issues/293) Split text ignores all text to the right of last cut. [#294](https://github.com/socialcopsdev/camelot/pull/294) by Vinayak Mehta.
* [#277](https://github.com/socialcopsdev/camelot/issues/277) Sort TableList by order of tables in PDF. [#283](https://github.com/socialcopsdev/camelot/pull/283) by [Sym Roe](https://github.com/symroe).
* [#312](https://github.com/socialcopsdev/camelot/issues/312) `table_regions` throws `ValueError` when `flavor='stream'`. [#332](https://github.com/socialcopsdev/camelot/pull/332) by Vinayak Mehta.
0.7.2 (2019-01-10)
------------------
**Bugfixes**
* [#245](https://github.com/socialcopsdev/camelot/issues/245) Fix AttributeError for encrypted files. [#251](https://github.com/socialcopsdev/camelot/pull/251) by Yatin Taluja.
0.7.1 (2019-01-06)
------------------
**Bugfixes**
* Move ghostscript import to inside the function so Anaconda builds don't fail.
0.7.0 (2019-01-05)
------------------
**Improvements**
* [#240](https://github.com/socialcopsdev/camelot/issues/209) Add support to analyze only certain page regions to look for tables. [#243](https://github.com/socialcopsdev/camelot/pull/243) by Vinayak Mehta.
* You can use `table_regions` in `read_pdf()` to specify approximate page regions which may contain tables.
* Kwarg `line_size_scaling` is now called `line_scale`.
* [#212](https://github.com/socialcopsdev/camelot/issues/212) Add support to export as sqlite database. [#244](https://github.com/socialcopsdev/camelot/pull/244) by Vinayak Mehta.
* [#239](https://github.com/socialcopsdev/camelot/issues/239) Raise warning if PDF is image-based. [#240](https://github.com/socialcopsdev/camelot/pull/240) by Vinayak Mehta.
**Documentation**
* Remove mention of old mesh kwarg from docs. [#241](https://github.com/socialcopsdev/camelot/pull/241) by [fte10kso](https://github.com/fte10kso).
**Note**: The python wrapper to Ghostscript's C API is now vendorized under the `ext` module. This was done due to unavailability of the [ghostscript](https://pypi.org/project/ghostscript/) package on Anaconda. The code should be removed after we submit a recipe for it to conda-forge. With this release, the user doesn't need to ensure that the Ghostscript executable is available on the PATH variable.
0.6.0 (2018-12-24)
------------------
**Improvements**
* [#91](https://github.com/socialcopsdev/camelot/issues/91) Add support to read from url. [#236](https://github.com/socialcopsdev/camelot/pull/236) by Vinayak Mehta.
* [#229](https://github.com/socialcopsdev/camelot/issues/229), [#230](https://github.com/socialcopsdev/camelot/issues/230) and [#233](https://github.com/socialcopsdev/camelot/issues/233) New configuration parameters. [#234](https://github.com/socialcopsdev/camelot/pull/234) by Vinayak Mehta.
* `strip_text`: To define characters that should be stripped from each string.
* `edge_tol`: Tolerance parameter for extending textedges vertically.
* `resolution`: Resolution used for PDF to PNG conversion.
* Check out the [advanced docs](https://camelot-py.readthedocs.io/en/master/user/advanced.html#strip-characters-from-text) for usage details.
* [#170](https://github.com/socialcopsdev/camelot/issues/170) Add option to pass pdfminer layout kwargs. [#232](https://github.com/socialcopsdev/camelot/pull/232) by Vinayak Mehta.
* Keyword arguments for [pdfminer.layout.LAParams](https://github.com/euske/pdfminer/blob/master/pdfminer/layout.py#L33) can now be passed using `layout_kwargs` in `read_pdf()`.
* The `margins` keyword argument in `read_pdf()` is now deprecated.
0.5.0 (2018-12-13)
------------------
**Improvements**
* [#207](https://github.com/socialcopsdev/camelot/issues/207) Add a plot type for Stream text edges and detected table areas. [#224](https://github.com/socialcopsdev/camelot/pull/224) by Vinayak Mehta.
* [#204](https://github.com/socialcopsdev/camelot/issues/204) `suppress_warnings` is now called `suppress_stdout`. [#225](https://github.com/socialcopsdev/camelot/pull/225) by Vinayak Mehta.
**Bugfixes**
* [#217](https://github.com/socialcopsdev/camelot/issues/217) Fix IndexError when scale is large.
* [#105](https://github.com/socialcopsdev/camelot/issues/105), [#192](https://github.com/socialcopsdev/camelot/issues/192) and [#215](https://github.com/socialcopsdev/camelot/issues/215) in [#227](https://github.com/socialcopsdev/camelot/pull/227) by Vinayak Mehta.
**Documentation**
* Add pdfplumber comparison and update Tabula (stream) comparison. Check out the [wiki page](https://github.com/socialcopsdev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools).
0.4.1 (2018-12-05)
------------------
**Bugfixes**
* Add chardet to `install_requires` to fix [#210](https://github.com/socialcopsdev/camelot/issues/210). More details in [pdfminer.six#213](https://github.com/pdfminer/pdfminer.six/issues/213).
0.4.0 (2018-11-23)
------------------
**Improvements**
* [#102](https://github.com/socialcopsdev/camelot/issues/102) Detect tables automatically when Stream is used. [#206](https://github.com/socialcopsdev/camelot/pull/206) Add implementation of Anssi Nurminen's table detection algorithm by Vinayak Mehta.
0.3.2 (2018-11-04)
------------------
**Improvements**
* [#186](https://github.com/socialcopsdev/camelot/issues/186) Add `_bbox` attribute to table. [#193](https://github.com/socialcopsdev/camelot/pull/193) by Vinayak Mehta.
* You can use `table._bbox` to get coordinates of the detected table.
0.3.1 (2018-11-02)
------------------
**Improvements**
* Matplotlib is now an optional requirement. [#190](https://github.com/socialcopsdev/camelot/pull/190) by Vinayak Mehta.
* You can install it using `$ pip install camelot-py[plot]`.
* [#127](https://github.com/socialcopsdev/camelot/issues/127) Add tests for plotting. Coverage is now at 87%! [#179](https://github.com/socialcopsdev/camelot/pull/179) by [Suyash Behera](https://github.com/Suyash458).
0.3.0 (2018-10-28)
------------------
**Improvements**
* [#162](https://github.com/socialcopsdev/camelot/issues/162) Add password keyword argument. [#180](https://github.com/socialcopsdev/camelot/pull/180) by [rbares](https://github.com/rbares).
* An encrypted PDF can now be decrypted by passing `password='<PASSWORD>'` to `read_pdf` or `--password <PASSWORD>` to the command-line interface. (Limited encryption algorithm support from PyPDF2.)
* [#139](https://github.com/socialcopsdev/camelot/issues/139) Add suppress_warnings keyword argument. [#155](https://github.com/socialcopsdev/camelot/pull/155) by [Jonathan Lloyd](https://github.com/jonathanlloyd).
* Warnings raised by Camelot can now be suppressed by passing `suppress_warnings=True` to `read_pdf` or `--quiet` to the command-line interface.
* [#154](https://github.com/socialcopsdev/camelot/issues/154) The CLI can now be run using `python -m`. Try `python -m camelot --help`. [#159](https://github.com/socialcopsdev/camelot/pull/159) by [Parth P Panchal](https://github.com/pqrth).
* [#165](https://github.com/socialcopsdev/camelot/issues/165) Rename `table_area` to `table_areas`. [#171](https://github.com/socialcopsdev/camelot/pull/171) by [Parth P Panchal](https://github.com/pqrth).
**Bugfixes**
* Raise error if the ghostscript executable is not on the PATH variable. [#166](https://github.com/socialcopsdev/camelot/pull/166) by Vinayak Mehta.
* Convert filename to lowercase to check for PDF extension. [#169](https://github.com/socialcopsdev/camelot/pull/169) by [Vinicius Mesel](https://github.com/vmesel).
**Files**
* [#114](https://github.com/socialcopsdev/camelot/issues/114) Add Makefile and make codecov run only once. [#132](https://github.com/socialcopsdev/camelot/pull/132) by [Vaibhav Mule](https://github.com/vaibhavmule).
* Add .editorconfig. [#151](https://github.com/socialcopsdev/camelot/pull/151) by [KOLANICH](https://github.com/KOLANICH).
* Downgrade numpy version from 1.15.2 to 1.13.3.
* Add requirements.txt for readthedocs.
**Documentation**
* Add "Using conda" section to installation instructions.
* Add readthedocs badge.
0.2.3 (2018-10-08)
------------------
* Remove hard dependencies on requirements versions.
0.2.2 (2018-10-08)
------------------
**Bugfixes**
* Move opencv-python to extra\_requires. [#134](https://github.com/socialcopsdev/camelot/pull/134) by Vinayak Mehta.
0.2.1 (2018-10-05)
------------------
**Bugfixes**
* [#121](https://github.com/socialcopsdev/camelot/issues/121) Fix ghostscript subprocess call for Windows. [#124](https://github.com/socialcopsdev/camelot/pull/124) by Vinayak Mehta.
**Improvements**
* [#123](https://github.com/socialcopsdev/camelot/issues/123) Make PEP8 compatible. [#125](https://github.com/socialcopsdev/camelot/pull/125) by [Oshawk](https://github.com/Oshawk).
* [#110](https://github.com/socialcopsdev/camelot/issues/110) Add more tests. Coverage is now at 84%!
* Add tests for `__repr__`. [#128](https://github.com/socialcopsdev/camelot/pull/128) by [Vaibhav Mule](https://github.com/vaibhavmule).
* Add tests for CLI. [#122](https://github.com/socialcopsdev/camelot/pull/122) by [Vaibhav Mule](https://github.com/vaibhavmule) and [#117](https://github.com/socialcopsdev/camelot/pull/117) by Vinayak Mehta.
* Add tests for errors/warnings. [#113](https://github.com/socialcopsdev/camelot/pull/113) by Vinayak Mehta.
* Add tests for output formats and parser kwargs. [#126](https://github.com/socialcopsdev/camelot/pull/126) by Vinayak Mehta.
* Add Python 3.5 and 3.7 support. [#119](https://github.com/socialcopsdev/camelot/pull/119) by Vinayak Mehta.
* Add logging and warnings.
**Documentation**
* Copyedit all documentation. [#112](https://github.com/socialcopsdev/camelot/pull/112) by [Christine Garcia](https://github.com/christinegarcia).
* [#115](https://github.com/socialcopsdev/camelot/issues/115) Update issue labels in contributor's guide. [#116](https://github.com/socialcopsdev/camelot/pull/116) by [Johnny Metz](https://github.com/johnnymetz).
* Update installation instructions for Windows. [#124](https://github.com/socialcopsdev/camelot/pull/124) by Vinayak Mehta.
**Note**: This release also bumps the version for numpy from 1.13.3 to 1.15.2 and adds a MANIFEST.in. Also, openpyxl==2.5.8 is a new requirement and pytest-cov==2.6.0 is a new dev requirement.
0.2.0 (2018-09-28)
------------------
**Improvements**
* [#81](https://github.com/socialcopsdev/camelot/issues/81) Add Python 3.6 support. [#109](https://github.com/socialcopsdev/camelot/pull/109) by Vinayak Mehta.
0.1.2 (2018-09-25)
------------------
**Improvements**
* [#85](https://github.com/socialcopsdev/camelot/issues/85) Add Travis and Codecov.
0.1.1 (2018-09-24)
------------------
**Documentation**
* Add documentation fixes.
0.1.0 (2018-09-24)
------------------
* Rebirth!

3
LICENSE
View File

@ -1,7 +1,6 @@
MIT License MIT License
Copyright (c) 2019-2021 Camelot Developers Copyright (c) 2018 Peeply Private Ltd (Singapore)
Copyright (c) 2018-2019 Peeply Private Ltd (Singapore)
Permission is hereby granted, free of charge, to any person obtaining a copy Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal of this software and associated documentation files (the "Software"), to deal

1
MANIFEST.in
View File

@ -1 +0,0 @@
include MANIFEST.in README.md HISTORY.md LICENSE setup.py setup.cfg

28
Makefile
View File

@ -1,28 +0,0 @@
.PHONY: docs
INSTALL :=
UNAME_S := $(shell uname -s)
ifeq ($(UNAME_S),Linux)
INSTALL := @sudo apt install python-tk python3-tk ghostscript
else ifeq ($(UNAME_S),Darwin)
INSTALL := @brew install tcl-tk ghostscript
else
INSTALL := @echo "Please install tk and ghostscript"
endif
install:
$(INSTALL)
pip install --upgrade pip
pip install ".[dev]"
test:
pytest --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot --mpl
docs:
cd docs && make html
@echo "\033[95m\n\nBuild successful! View the docs homepage at docs/_build/html/index.html.\n\033[0m"
publish:
pip install twine
python setup.py sdist
twine upload dist/*
rm -fr build dist .egg camelot_py.egg-info

98
README.md
View File

@ -1,28 +1,21 @@
<p align="center">
<img src="https://raw.githubusercontent.com/camelot-dev/camelot/master/docs/_static/camelot.png" width="200">
</p>
# Camelot: PDF Table Extraction for Humans # Camelot: PDF Table Extraction for Humans
[![tests](https://github.com/camelot-dev/camelot/actions/workflows/tests.yml/badge.svg)](https://github.com/camelot-dev/camelot/actions/workflows/tests.yml) [![Documentation Status](https://readthedocs.org/projects/camelot-py/badge/?version=master)](https://camelot-py.readthedocs.io/en/master/) ![license](https://img.shields.io/badge/license-MIT-lightgrey.svg) ![python-version](https://img.shields.io/badge/python-2.7-blue.svg)
[![codecov.io](https://codecov.io/github/camelot-dev/camelot/badge.svg?branch=master&service=github)](https://codecov.io/github/camelot-dev/camelot?branch=master)
[![image](https://img.shields.io/pypi/v/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![image](https://img.shields.io/pypi/l/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![image](https://img.shields.io/pypi/pyversions/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![Gitter chat](https://badges.gitter.im/camelot-dev/Lobby.png)](https://gitter.im/camelot-dev/Lobby)
[![image](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)
**Camelot** is a Python library that can help you extract tables from PDFs! **Camelot** is a Python library which makes it easy for *anyone* to extract tables from PDF files!
**Note:** You can also check out [Excalibur](https://github.com/camelot-dev/excalibur), the web interface to Camelot! ![camelot-logo](docs/_static/png/camelot-logo.png)
--- ---
**Here's how you can extract tables from PDFs.** You can check out the PDF used in this example [here](https://github.com/camelot-dev/camelot/blob/master/docs/_static/pdf/foo.pdf). **Here's how you can extract tables from PDF files.** Check out the PDF used in this example, [here](docs/_static/pdf/foo.pdf).
<pre> <pre>
>>> import camelot >>> import camelot
>>> tables = camelot.read_pdf('foo.pdf') >>> tables = camelot.read_pdf('foo.pdf')
>>> tables >>> tables
&lt;TableList n=1&gt; &lt;TableList tables=1&gt;
>>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html, markdown, sqlite >>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html
>>> tables[0] >>> tables[0]
&lt;Table shape=(7, 7)&gt; &lt;Table shape=(7, 7)&gt;
>>> tables[0].parsing_report >>> tables[0].parsing_report
@ -32,7 +25,7 @@
'order': 1, 'order': 1,
'page': 1 'page': 1
} }
>>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html, to_markdown, to_sqlite >>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html
>>> tables[0].df # get a pandas DataFrame! >>> tables[0].df # get a pandas DataFrame!
</pre> </pre>
@ -45,73 +38,78 @@
| 2032_2 | 0.17 | 57.8 | 21.7% | 0.3% | 2.7% | 1.2% | | 2032_2 | 0.17 | 57.8 | 21.7% | 0.3% | 2.7% | 1.2% |
| 4171_1 | 0.07 | 173.9 | 58.1% | 1.6% | 2.1% | 0.5% | | 4171_1 | 0.07 | 173.9 | 58.1% | 1.6% | 2.1% | 0.5% |
Camelot also comes packaged with a [command-line interface](https://camelot-py.readthedocs.io/en/master/user/cli.html)! There's a [command-line interface](http://camelot-py.readthedocs.io/en/master/user/cli.html) too!
**Note:** Camelot only works with text-based PDFs and not scanned documents. (As Tabula [explains](https://github.com/tabulapdf/tabula#why-tabula), "If you can click and drag to select text in your table in a PDF viewer, then your PDF is text-based".)
You can check out some frequently asked questions [here](https://camelot-py.readthedocs.io/en/master/user/faq.html).
## Why Camelot? ## Why Camelot?
- **Configurability**: Camelot gives you control over the table extraction process with [tweakable settings](https://camelot-py.readthedocs.io/en/master/user/advanced.html). - **You are in control**: Unlike other libraries and tools which either give a nice output or fail miserably (with no in-between), Camelot gives you the power to tweak table extraction. (Since everything in the real world, including PDF table extraction, is fuzzy.)
- **Metrics**: You can discard bad tables based on metrics like accuracy and whitespace, without having to manually look at each table. - **Metrics**: *Bad* tables can be discarded based on metrics like accuracy and whitespace, without ever having to manually look at each table.
- **Output**: Each table is extracted into a **pandas DataFrame**, which seamlessly integrates into [ETL and data analysis workflows](https://gist.github.com/vinayak-mehta/e5949f7c2410a0e12f25d3682dc9e873). You can also export tables to multiple formats, which include CSV, JSON, Excel, HTML, Markdown, and Sqlite. - Each table is a **pandas DataFrame**, which enables seamless integration into [ETL and data analysis workflows](https://gist.github.com/vinayak-mehta/e5949f7c2410a0e12f25d3682dc9e873).
- **Export** to multiple formats, including json, excel and html.
See [comparison with similar libraries and tools](https://github.com/camelot-dev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools). See [comparison with other PDF table extraction libraries and tools](https://github.com/socialcopsdev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools).
## Support the development
If Camelot has helped you, please consider supporting its development with a one-time or monthly donation [on OpenCollective](https://opencollective.com/camelot).
## Installation ## Installation
### Using conda After [installing the dependencies](http://camelot-py.readthedocs.io/en/master/user/install.html), [tk](https://packages.ubuntu.com/trusty/python-tk) and [ghostscript](https://www.ghostscript.com/), you can simply use pip to install Camelot:
The easiest way to install Camelot is with [conda](https://conda.io/docs/), which is a package manager and environment management system for the [Anaconda](http://docs.continuum.io/anaconda/) distribution.
<pre> <pre>
$ conda install -c conda-forge camelot-py $ pip install camelot-py
</pre> </pre>
### Using pip ### Alternatively
After [installing the dependencies](https://camelot-py.readthedocs.io/en/master/user/install-deps.html) ([tk](https://packages.ubuntu.com/bionic/python/python-tk) and [ghostscript](https://www.ghostscript.com/)), you can also just use pip to install Camelot: After [installing the dependencies](http://camelot-py.readthedocs.io/en/master/user/install.html), clone the repo using:
<pre> <pre>
$ pip install "camelot-py[base]" $ git clone https://www.github.com/socialcopsdev/camelot
</pre>
### From the source code
After [installing the dependencies](https://camelot-py.readthedocs.io/en/master/user/install.html#using-pip), clone the repo using:
<pre>
$ git clone https://www.github.com/camelot-dev/camelot
</pre> </pre>
and install Camelot using pip: and install Camelot using pip:
<pre> <pre>
$ cd camelot $ cd camelot
$ pip install ".[base]" $ pip install .
</pre> </pre>
Note: Use a [virtualenv](https://virtualenv.pypa.io/en/stable/) if you don't want to affect your global Python installation.
## Documentation ## Documentation
The documentation is available at [http://camelot-py.readthedocs.io/](http://camelot-py.readthedocs.io/). Great documentation is available at [http://camelot-py.readthedocs.io/](http://camelot-py.readthedocs.io/).
## Wrappers ## Development
- [camelot-php](https://github.com/randomstate/camelot-php) provides a [PHP](https://www.php.net/) wrapper on Camelot. The [Contributor's Guide](CONTRIBUTING.md) has detailed information about contributing code, documentation, tests and more. We've included some basic information in this README.
## Contributing ### Source code
The [Contributor's Guide](https://camelot-py.readthedocs.io/en/master/dev/contributing.html) has detailed information about contributing issues, documentation, code, and tests. You can check the latest sources with:
<pre>
$ git clone https://www.github.com/socialcopsdev/camelot
</pre>
### Setting up a development environment
You can install the development dependencies easily, using pip:
<pre>
$ pip install camelot-py[dev]
</pre>
### Testing
After installation, you can run tests using:
<pre>
$ python setup.py test
</pre>
## Versioning ## Versioning
Camelot uses [Semantic Versioning](https://semver.org/). For the available versions, see the tags on this repository. For the changelog, you can check out [HISTORY.md](https://github.com/camelot-dev/camelot/blob/master/HISTORY.md). Camelot uses [Semantic Versioning](https://semver.org/). For the available versions, see the tags on this repository.
## License ## License
This project is licensed under the MIT License, see the [LICENSE](https://github.com/camelot-dev/camelot/blob/master/LICENSE) file for details. This project is licensed under the MIT License, see the [LICENSE](LICENSE) file for details.

18
camelot/__init__.py
View File

@ -1,21 +1,5 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import logging
from .__version__ import __version__ from .__version__ import __version__
from .io import read_pdf
from .plotting import PlotMethods
from .io import read_pdf
# set up logging
logger = logging.getLogger("camelot")
format_string = "%(asctime)s - %(levelname)s - %(message)s"
formatter = logging.Formatter(format_string, datefmt="%Y-%m-%dT%H:%M:%S")
handler = logging.StreamHandler()
handler.setFormatter(formatter)
logger.addHandler(handler)
# instantiate plot method
plot = PlotMethods()

14
camelot/__main__.py
View File

@ -1,14 +0,0 @@
# -*- coding: utf-8 -*-
__all__ = ("main",)
def main():
from camelot.cli import cli
cli()
if __name__ == "__main__":
main()

28
camelot/__version__.py
View File

@ -1,23 +1,11 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
VERSION = (0, 10, 1) VERSION = (0, 1, 0)
PRERELEASE = None # alpha, beta or rc
REVISION = None
__title__ = 'camelot-py'
def generate_version(version, prerelease=None, revision=None): __description__ = 'PDF Table Extraction for Humans.'
version_parts = [".".join(map(str, version))] __url__ = 'http://camelot-py.readthedocs.io/'
if prerelease is not None: __version__ = '.'.join(map(str, VERSION))
version_parts.append(f"-{prerelease}") __author__ = 'Vinayak Mehta'
if revision is not None: __author_email__ = 'vmehta94@gmail.com'
version_parts.append(f".{revision}") __license__ = 'MIT License'
return "".join(version_parts)
__title__ = "camelot-py"
__description__ = "PDF Table Extraction for Humans."
__url__ = "http://camelot-py.readthedocs.io/"
__version__ = generate_version(VERSION, prerelease=PRERELEASE, revision=REVISION)
__author__ = "Vinayak Mehta"
__author_email__ = "vmehta94@gmail.com"
__license__ = "MIT License"

3
camelot/backends/__init__.py
View File

@ -1,3 +0,0 @@
# -*- coding: utf-8 -*-
from .image_conversion import ImageConversionBackend

47
camelot/backends/ghostscript_backend.py
View File

@ -1,47 +0,0 @@
# -*- coding: utf-8 -*-
import sys
import ctypes
from ctypes.util import find_library
def installed_posix():
library = find_library("gs")
return library is not None
def installed_windows():
library = find_library(
"".join(("gsdll", str(ctypes.sizeof(ctypes.c_voidp) * 8), ".dll"))
)
return library is not None
class GhostscriptBackend(object):
def installed(self):
if sys.platform in ["linux", "darwin"]:
return installed_posix()
elif sys.platform == "win32":
return installed_windows()
else:
return installed_posix()
def convert(self, pdf_path, png_path, resolution=300):
if not self.installed():
raise OSError(
"Ghostscript is not installed. You can install it using the instructions"
" here: https://camelot-py.readthedocs.io/en/master/user/install-deps.html"
)
import ghostscript
gs_command = [
"gs",
"-q",
"-sDEVICE=png16m",
"-o",
png_path,
f"-r{resolution}",
pdf_path,
]
ghostscript.Ghostscript(*gs_command)

40
camelot/backends/image_conversion.py
View File

@ -1,40 +0,0 @@
# -*- coding: utf-8 -*-
from .poppler_backend import PopplerBackend
from .ghostscript_backend import GhostscriptBackend
BACKENDS = {"poppler": PopplerBackend, "ghostscript": GhostscriptBackend}
class ImageConversionBackend(object):
def __init__(self, backend="poppler", use_fallback=True):
if backend not in BACKENDS.keys():
raise ValueError(f"Image conversion backend '{backend}' not supported")
self.backend = backend
self.use_fallback = use_fallback
self.fallbacks = list(filter(lambda x: x != backend, BACKENDS.keys()))
def convert(self, pdf_path, png_path):
try:
converter = BACKENDS[self.backend]()
converter.convert(pdf_path, png_path)
except Exception as e:
import sys
if self.use_fallback:
for fallback in self.fallbacks:
try:
converter = BACKENDS[fallback]()
converter.convert(pdf_path, png_path)
except Exception as e:
raise type(e)(
str(e) + f" with image conversion backend '{fallback}'"
).with_traceback(sys.exc_info()[2])
continue
else:
break
else:
raise type(e)(
str(e) + f" with image conversion backend '{self.backend}'"
).with_traceback(sys.exc_info()[2])

22
camelot/backends/poppler_backend.py
View File

@ -1,22 +0,0 @@
# -*- coding: utf-8 -*-
import shutil
import subprocess
class PopplerBackend(object):
def convert(self, pdf_path, png_path):
pdftopng_executable = shutil.which("pdftopng")
if pdftopng_executable is None:
raise OSError(
"pdftopng is not installed. You can install it using the 'pip install pdftopng' command."
)
pdftopng_command = [pdftopng_executable, pdf_path, png_path]
try:
subprocess.check_output(
" ".join(pdftopng_command), stderr=subprocess.STDOUT, shell=True
)
except subprocess.CalledProcessError as e:
raise ValueError(e.output)

360
camelot/cli.py
View File

@ -1,25 +1,15 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import logging from pprint import pprint
import click import click
try: from . import __version__
import matplotlib.pyplot as plt from .io import read_pdf
except ImportError:
_HAS_MPL = False
else:
_HAS_MPL = True
from . import __version__, read_pdf, plot
logger = logging.getLogger("camelot")
logger.setLevel(logging.INFO)
class Config(object): class Config(object):
def __init__(self): def __init__(self):
self.config = {} self.config = {}
def set_config(self, key, value): def set_config(self, key, value):
@ -29,276 +19,134 @@ class Config(object):
pass_config = click.make_pass_decorator(Config) pass_config = click.make_pass_decorator(Config)
@click.group(name="camelot") @click.group()
@click.version_option(version=__version__) @click.version_option(version=__version__)
@click.option("-q", "--quiet", is_flag=False, help="Suppress logs and warnings.") @click.option('-p', '--pages', default='1', help='Comma-separated page numbers.'
@click.option( ' Example: 1,3,4 or 1,4-end.')
"-p", @click.option('-o', '--output', help='Output file path.')
"--pages", @click.option('-f', '--format',
default="1", type=click.Choice(['csv', 'json', 'excel', 'html']),
help="Comma-separated page numbers." " Example: 1,3,4 or 1,4-end or all.", help='Output file format.')
) @click.option('-z', '--zip', is_flag=True, help='Create ZIP archive.')
@click.option("-pw", "--password", help="Password for decryption.") @click.option('-split', '--split_text', is_flag=True,
@click.option("-o", "--output", help="Output file path.") help='Split text that spans across multiple cells.')
@click.option( @click.option('-flag', '--flag_size', is_flag=True, help='Flag text based on'
"-f", ' font size. Useful to detect super/subscripts.')
"--format", @click.option('-M', '--margins', nargs=3, default=(1.0, 0.5, 0.1),
type=click.Choice(["csv", "excel", "html", "json", "markdown", "sqlite"]), help='PDFMiner char_margin, line_margin and word_margin.')
help="Output file format.",
)
@click.option("-z", "--zip", is_flag=True, help="Create ZIP archive.")
@click.option(
"-split",
"--split_text",
is_flag=True,
help="Split text that spans across multiple cells.",
)
@click.option(
"-flag",
"--flag_size",
is_flag=True,
help="Flag text based on" " font size. Useful to detect super/subscripts.",
)
@click.option(
"-strip",
"--strip_text",
help="Characters that should be stripped from a string before"
" assigning it to a cell.",
)
@click.option(
"-M",
"--margins",
nargs=3,
default=(1.0, 0.5, 0.1),
help="PDFMiner char_margin, line_margin and word_margin.",
)
@click.pass_context @click.pass_context
def cli(ctx, *args, **kwargs): def cli(ctx, *args, **kwargs):
"""Camelot: PDF Table Extraction for Humans""" """Camelot: PDF Table Extraction for Humans"""
ctx.obj = Config() ctx.obj = Config()
for key, value in kwargs.items(): for key, value in kwargs.iteritems():
ctx.obj.set_config(key, value) ctx.obj.set_config(key, value)
@cli.command("lattice") @cli.command('lattice')
@click.option( @click.option('-T', '--table_area', default=[], multiple=True,
"-R", help='Table areas to process. Example: x1,y1,x2,y2'
"--table_regions", ' where x1, y1 -> left-top and x2, y2 -> right-bottom.')
default=[], @click.option('-back', '--process_background', is_flag=True,
multiple=True, help='Process background lines.')
help="Page regions to analyze. Example: x1,y1,x2,y2" @click.option('-scale', '--line_size_scaling', default=15,
" where x1, y1 -> left-top and x2, y2 -> right-bottom.", help='Line size scaling factor. The larger the value,'
) ' the smaller the detected lines.')
@click.option( @click.option('-copy', '--copy_text', default=[], type=click.Choice(['h', 'v']),
"-T", multiple=True, help='Direction in which text in a spanning cell'
"--table_areas", ' will be copied over.')
default=[], @click.option('-shift', '--shift_text', default=['l', 't'],
multiple=True, type=click.Choice(['', 'l', 'r', 't', 'b']), multiple=True,
help="Table areas to process. Example: x1,y1,x2,y2" help='Direction in which text in a spanning cell will flow.')
" where x1, y1 -> left-top and x2, y2 -> right-bottom.", @click.option('-l', '--line_close_tol', default=2,
) help='Tolerance parameter used to merge close vertical'
@click.option( ' and horizontal lines.')
"-back", "--process_background", is_flag=True, help="Process background lines." @click.option('-j', '--joint_close_tol', default=2,
) help='Tolerance parameter used to decide whether'
@click.option( ' the detected lines and points lie close to each other.')
"-scale", @click.option('-block', '--threshold_blocksize', default=15,
"--line_scale", help='For adaptive thresholding, size of a pixel'
default=15, ' neighborhood that is used to calculate a threshold value for'
help="Line size scaling factor. The larger the value," ' the pixel. Example: 3, 5, 7, and so on.')
" the smaller the detected lines.", @click.option('-const', '--threshold_constant', default=-2,
) help='For adaptive thresholding, constant subtracted'
@click.option( ' from the mean or weighted mean. Normally, it is positive but'
"-copy", ' may be zero or negative as well.')
"--copy_text", @click.option('-I', '--iterations', default=0,
default=[], help='Number of times for erosion/dilation will be applied.')
type=click.Choice(["h", "v"]), @click.option('-plot', '--plot_type',
multiple=True, type=click.Choice(['text', 'table', 'contour', 'joint', 'line']),
help="Direction in which text in a spanning cell" " will be copied over.", help='Plot geometry found on PDF page, for debugging.')
) @click.argument('filepath', type=click.Path(exists=True))
@click.option(
"-shift",
"--shift_text",
default=["l", "t"],
type=click.Choice(["", "l", "r", "t", "b"]),
multiple=True,
help="Direction in which text in a spanning cell will flow.",
)
@click.option(
"-l",
"--line_tol",
default=2,
help="Tolerance parameter used to merge close vertical" " and horizontal lines.",
)
@click.option(
"-j",
"--joint_tol",
default=2,
help="Tolerance parameter used to decide whether"
" the detected lines and points lie close to each other.",
)
@click.option(
"-block",
"--threshold_blocksize",
default=15,
help="For adaptive thresholding, size of a pixel"
" neighborhood that is used to calculate a threshold value for"
" the pixel. Example: 3, 5, 7, and so on.",
)
@click.option(
"-const",
"--threshold_constant",
default=-2,
help="For adaptive thresholding, constant subtracted"
" from the mean or weighted mean. Normally, it is positive but"
" may be zero or negative as well.",
)
@click.option(
"-I",
"--iterations",
default=0,
help="Number of times for erosion/dilation will be applied.",
)
@click.option(
"-res",
"--resolution",
default=300,
help="Resolution used for PDF to PNG conversion.",
)
@click.option(
"-plot",
"--plot_type",
type=click.Choice(["text", "grid", "contour", "joint", "line"]),
help="Plot elements found on PDF page for visual debugging.",
)
@click.argument("filepath", type=click.Path(exists=True))
@pass_config @pass_config
def lattice(c, *args, **kwargs): def lattice(c, *args, **kwargs):
"""Use lines between text to parse the table.""" """Use lines between text to parse the table."""
conf = c.config conf = c.config
pages = conf.pop("pages") pages = conf.pop('pages')
output = conf.pop("output") output = conf.pop('output')
f = conf.pop("format") f = conf.pop('format')
compress = conf.pop("zip") compress = conf.pop('zip')
quiet = conf.pop("quiet") plot_type = kwargs.pop('plot_type')
plot_type = kwargs.pop("plot_type") filepath = kwargs.pop('filepath')
filepath = kwargs.pop("filepath")
kwargs.update(conf) kwargs.update(conf)
table_regions = list(kwargs["table_regions"]) table_area = list(kwargs['table_area'])
kwargs["table_regions"] = None if not table_regions else table_regions kwargs['table_area'] = None if not table_area else table_area
table_areas = list(kwargs["table_areas"]) copy_text = list(kwargs['copy_text'])
kwargs["table_areas"] = None if not table_areas else table_areas kwargs['copy_text'] = None if not copy_text else copy_text
copy_text = list(kwargs["copy_text"]) kwargs['shift_text'] = list(kwargs['shift_text'])
kwargs["copy_text"] = None if not copy_text else copy_text
kwargs["shift_text"] = list(kwargs["shift_text"])
if plot_type is not None: tables = read_pdf(filepath, pages=pages, flavor='lattice', **kwargs)
if not _HAS_MPL: click.echo('Found {} tables'.format(tables.n))
raise ImportError("matplotlib is required for plotting.")
else:
if output is None:
raise click.UsageError("Please specify output file path using --output")
if f is None:
raise click.UsageError("Please specify output file format using --format")
tables = read_pdf(
filepath, pages=pages, flavor="lattice", suppress_stdout=quiet, **kwargs
)
click.echo(f"Found {tables.n} tables")
if plot_type is not None: if plot_type is not None:
for table in tables: for table in tables:
plot(table, kind=plot_type) table.plot(plot_type)
plt.show()
else: else:
if output is None:
raise click.UsageError('Please specify output file path using --output')
if f is None:
raise click.UsageError('Please specify output file format using --format')
tables.export(output, f=f, compress=compress) tables.export(output, f=f, compress=compress)
@cli.command("stream") @cli.command('stream')
@click.option( @click.option('-T', '--table_area', default=[], multiple=True,
"-R", help='Table areas to process. Example: x1,y1,x2,y2'
"--table_regions", ' where x1, y1 -> left-top and x2, y2 -> right-bottom.')
default=[], @click.option('-C', '--columns', default=[], multiple=True,
multiple=True, help='X coordinates of column separators.')
help="Page regions to analyze. Example: x1,y1,x2,y2" @click.option('-r', '--row_close_tol', default=2, help='Tolerance parameter'
" where x1, y1 -> left-top and x2, y2 -> right-bottom.", ' used to combine text vertically, to generate rows.')
) @click.option('-c', '--col_close_tol', default=0, help='Tolerance parameter'
@click.option( ' used to combine text horizontally, to generate columns.')
"-T", @click.option('-plot', '--plot_type',
"--table_areas", type=click.Choice(['text', 'table']),
default=[], help='Plot geometry found on PDF page for debugging.')
multiple=True, @click.argument('filepath', type=click.Path(exists=True))
help="Table areas to process. Example: x1,y1,x2,y2"
" where x1, y1 -> left-top and x2, y2 -> right-bottom.",
)
@click.option(
"-C",
"--columns",
default=[],
multiple=True,
help="X coordinates of column separators.",
)
@click.option(
"-e",
"--edge_tol",
default=50,
help="Tolerance parameter" " for extending textedges vertically.",
)
@click.option(
"-r",
"--row_tol",
default=2,
help="Tolerance parameter" " used to combine text vertically, to generate rows.",
)
@click.option(
"-c",
"--column_tol",
default=0,
help="Tolerance parameter"
" used to combine text horizontally, to generate columns.",
)
@click.option(
"-plot",
"--plot_type",
type=click.Choice(["text", "grid", "contour", "textedge"]),
help="Plot elements found on PDF page for visual debugging.",
)
@click.argument("filepath", type=click.Path(exists=True))
@pass_config @pass_config
def stream(c, *args, **kwargs): def stream(c, *args, **kwargs):
"""Use spaces between text to parse the table.""" """Use spaces between text to parse the table."""
conf = c.config conf = c.config
pages = conf.pop("pages") pages = conf.pop('pages')
output = conf.pop("output") output = conf.pop('output')
f = conf.pop("format") f = conf.pop('format')
compress = conf.pop("zip") compress = conf.pop('zip')
quiet = conf.pop("quiet") plot_type = kwargs.pop('plot_type')
plot_type = kwargs.pop("plot_type") filepath = kwargs.pop('filepath')
filepath = kwargs.pop("filepath")
kwargs.update(conf) kwargs.update(conf)
table_regions = list(kwargs["table_regions"]) table_area = list(kwargs['table_area'])
kwargs["table_regions"] = None if not table_regions else table_regions kwargs['table_area'] = None if not table_area else table_area
table_areas = list(kwargs["table_areas"]) columns = list(kwargs['columns'])
kwargs["table_areas"] = None if not table_areas else table_areas kwargs['columns'] = None if not columns else columns
columns = list(kwargs["columns"])
kwargs["columns"] = None if not columns else columns
if plot_type is not None: tables = read_pdf(filepath, pages=pages, flavor='stream', **kwargs)
if not _HAS_MPL: click.echo('Found {} tables'.format(tables.n))
raise ImportError("matplotlib is required for plotting.")
else:
if output is None:
raise click.UsageError("Please specify output file path using --output")
if f is None:
raise click.UsageError("Please specify output file format using --format")
tables = read_pdf(
filepath, pages=pages, flavor="stream", suppress_stdout=quiet, **kwargs
)
click.echo(f"Found {tables.n} tables")
if plot_type is not None: if plot_type is not None:
for table in tables: for table in tables:
plot(table, kind=plot_type) table.plot(plot_type)
plt.show()
else: else:
tables.export(output, f=f, compress=compress) if output is None:
raise click.UsageError('Please specify output file path using --output')
if f is None:
raise click.UsageError('Please specify output file format using --format')
tables.export(output, f=f, compress=compress)

466
camelot/core.py
View File

@ -1,231 +1,14 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import os import os
import sqlite3 import json
import zipfile import zipfile
import tempfile import tempfile
from itertools import chain
from operator import itemgetter
import numpy as np import numpy as np
import pandas as pd import pandas as pd
from .plotting import *
# minimum number of vertical textline intersections for a textedge
# to be considered valid
TEXTEDGE_REQUIRED_ELEMENTS = 4
# padding added to table area on the left, right and bottom
TABLE_AREA_PADDING = 10
class TextEdge(object):
"""Defines a text edge coordinates relative to a left-bottom
origin. (PDF coordinate space)
Parameters
----------
x : float
x-coordinate of the text edge.
y0 : float
y-coordinate of bottommost point.
y1 : float
y-coordinate of topmost point.
align : string, optional (default: 'left')
{'left', 'right', 'middle'}
Attributes
----------
intersections: int
Number of intersections with horizontal text rows.
is_valid: bool
A text edge is valid if it intersections with at least
TEXTEDGE_REQUIRED_ELEMENTS horizontal text rows.
"""
def __init__(self, x, y0, y1, align="left"):
self.x = x
self.y0 = y0
self.y1 = y1
self.align = align
self.intersections = 0
self.is_valid = False
def __repr__(self):
x = round(self.x, 2)
y0 = round(self.y0, 2)
y1 = round(self.y1, 2)
return (
f"<TextEdge x={x} y0={y0} y1={y1} align={self.align} valid={self.is_valid}>"
)
def update_coords(self, x, y0, edge_tol=50):
"""Updates the text edge's x and bottom y coordinates and sets
the is_valid attribute.
"""
if np.isclose(self.y0, y0, atol=edge_tol):
self.x = (self.intersections * self.x + x) / float(self.intersections + 1)
self.y0 = y0
self.intersections += 1
# a textedge is valid only if it extends uninterrupted
# over a required number of textlines
if self.intersections > TEXTEDGE_REQUIRED_ELEMENTS:
self.is_valid = True
class TextEdges(object):
"""Defines a dict of left, right and middle text edges found on
the PDF page. The dict has three keys based on the alignments,
and each key's value is a list of camelot.core.TextEdge objects.
"""
def __init__(self, edge_tol=50):
self.edge_tol = edge_tol
self._textedges = {"left": [], "right": [], "middle": []}
@staticmethod
def get_x_coord(textline, align):
"""Returns the x coordinate of a text row based on the
specified alignment.
"""
x_left = textline.x0
x_right = textline.x1
x_middle = x_left + (x_right - x_left) / 2.0
x_coord = {"left": x_left, "middle": x_middle, "right": x_right}
return x_coord[align]
def find(self, x_coord, align):
"""Returns the index of an existing text edge using
the specified x coordinate and alignment.
"""
for i, te in enumerate(self._textedges[align]):
if np.isclose(te.x, x_coord, atol=0.5):
return i
return None
def add(self, textline, align):
"""Adds a new text edge to the current dict."""
x = self.get_x_coord(textline, align)
y0 = textline.y0
y1 = textline.y1
te = TextEdge(x, y0, y1, align=align)
self._textedges[align].append(te)
def update(self, textline):
"""Updates an existing text edge in the current dict."""
for align in ["left", "right", "middle"]:
x_coord = self.get_x_coord(textline, align)
idx = self.find(x_coord, align)
if idx is None:
self.add(textline, align)
else:
self._textedges[align][idx].update_coords(
x_coord, textline.y0, edge_tol=self.edge_tol
)
def generate(self, textlines):
"""Generates the text edges dict based on horizontal text
rows.
"""
for tl in textlines:
if len(tl.get_text().strip()) > 1: # TODO: hacky
self.update(tl)
def get_relevant(self):
"""Returns the list of relevant text edges (all share the same
alignment) based on which list intersects horizontal text rows
the most.
"""
intersections_sum = {
"left": sum(
te.intersections for te in self._textedges["left"] if te.is_valid
),
"right": sum(
te.intersections for te in self._textedges["right"] if te.is_valid
),
"middle": sum(
te.intersections for te in self._textedges["middle"] if te.is_valid
),
}
# TODO: naive
# get vertical textedges that intersect maximum number of
# times with horizontal textlines
relevant_align = max(intersections_sum.items(), key=itemgetter(1))[0]
return self._textedges[relevant_align]
def get_table_areas(self, textlines, relevant_textedges):
"""Returns a dict of interesting table areas on the PDF page
calculated using relevant text edges.
"""
def pad(area, average_row_height):
x0 = area[0] - TABLE_AREA_PADDING
y0 = area[1] - TABLE_AREA_PADDING
x1 = area[2] + TABLE_AREA_PADDING
# add a constant since table headers can be relatively up
y1 = area[3] + average_row_height * 5
return (x0, y0, x1, y1)
# sort relevant textedges in reading order
relevant_textedges.sort(key=lambda te: (-te.y0, te.x))
table_areas = {}
for te in relevant_textedges:
if te.is_valid:
if not table_areas:
table_areas[(te.x, te.y0, te.x, te.y1)] = None
else:
found = None
for area in table_areas:
# check for overlap
if te.y1 >= area[1] and te.y0 <= area[3]:
found = area
break
if found is None:
table_areas[(te.x, te.y0, te.x, te.y1)] = None
else:
table_areas.pop(found)
updated_area = (
found[0],
min(te.y0, found[1]),
max(found[2], te.x),
max(found[3], te.y1),
)
table_areas[updated_area] = None
# extend table areas based on textlines that overlap
# vertically. it's possible that these textlines were
# eliminated during textedges generation since numbers and
# chars/words/sentences are often aligned differently.
# drawback: table areas that have paragraphs on their sides
# will include the paragraphs too.
sum_textline_height = 0
for tl in textlines:
sum_textline_height += tl.y1 - tl.y0
found = None
for area in table_areas:
# check for overlap
if tl.y0 >= area[1] and tl.y1 <= area[3]:
found = area
break
if found is not None:
table_areas.pop(found)
updated_area = (
min(tl.x0, found[0]),
min(tl.y0, found[1]),
max(found[2], tl.x1),
max(found[3], tl.y1),
)
table_areas[updated_area] = None
average_textline_height = sum_textline_height / float(len(textlines))
# add some padding to table areas
table_areas_padded = {}
for area in table_areas:
table_areas_padded[pad(area, average_textline_height)] = None
return table_areas_padded
class Cell(object): class Cell(object):
@ -285,14 +68,11 @@ class Cell(object):
self.bottom = False self.bottom = False
self.hspan = False self.hspan = False
self.vspan = False self.vspan = False
self._text = "" self._text = ''
def __repr__(self): def __repr__(self):
x1 = round(self.x1) return '<Cell x1={} y1={} x2={} y2={}>'.format(
y1 = round(self.y1) self.x1, self.y1, self.x2, self.y2)
x2 = round(self.x2)
y2 = round(self.y2)
return f"<Cell x1={x1} y1={y1} x2={x2} y2={y2}>"
@property @property
def text(self): def text(self):
@ -300,11 +80,12 @@ class Cell(object):
@text.setter @text.setter
def text(self, t): def text(self, t):
self._text = "".join([self._text, t]) self._text = ''.join([self._text, t])
@property @property
def bound(self): def bound(self):
"""The number of sides on which the cell is bounded.""" """The number of sides on which the cell is bounded.
"""
return self.top + self.bottom + self.left + self.right return self.top + self.bottom + self.left + self.right
@ -336,11 +117,11 @@ class Table(object):
PDF page number. PDF page number.
""" """
def __init__(self, cols, rows): def __init__(self, cols, rows):
self.cols = cols self.cols = cols
self.rows = rows self.rows = rows
self.cells = [[Cell(c[0], r[1], c[1], r[0]) for c in cols] for r in rows] self.cells = [[Cell(c[0], r[1], c[1], r[0])
for c in cols] for r in rows]
self.df = None self.df = None
self.shape = (0, 0) self.shape = (0, 0)
self.accuracy = 0 self.accuracy = 0
@ -349,18 +130,12 @@ class Table(object):
self.page = None self.page = None
def __repr__(self): def __repr__(self):
return f"<{self.__class__.__name__} shape={self.shape}>" return '<{} shape={}>'.format(self.__class__.__name__, self.shape)
def __lt__(self, other):
if self.page == other.page:
if self.order < other.order:
return True
if self.page < other.page:
return True
@property @property
def data(self): def data(self):
"""Returns two-dimensional list of strings in table.""" """Returns two-dimensional list of strings in table.
"""
d = [] d = []
for row in self.cells: for row in self.cells:
d.append([cell.text.strip() for cell in row]) d.append([cell.text.strip() for cell in row])
@ -373,21 +148,22 @@ class Table(object):
""" """
# pretty? # pretty?
report = { report = {
"accuracy": round(self.accuracy, 2), 'accuracy': round(self.accuracy, 2),
"whitespace": round(self.whitespace, 2), 'whitespace': round(self.whitespace, 2),
"order": self.order, 'order': self.order,
"page": self.page, 'page': self.page
} }
return report return report
def set_all_edges(self): def set_all_edges(self):
"""Sets all table edges to True.""" """Sets all table edges to True.
"""
for row in self.cells: for row in self.cells:
for cell in row: for cell in row:
cell.left = cell.right = cell.top = cell.bottom = True cell.left = cell.right = cell.top = cell.bottom = True
return self return self
def set_edges(self, vertical, horizontal, joint_tol=2): def set_edges(self, vertical, horizontal, joint_close_tol=2):
"""Sets a cell's edges to True depending on whether the cell's """Sets a cell's edges to True depending on whether the cell's
coordinates overlap with the line's coordinates within a coordinates overlap with the line's coordinates within a
tolerance. tolerance.
@ -403,21 +179,12 @@ class Table(object):
for v in vertical: for v in vertical:
# find closest x coord # find closest x coord
# iterate over y coords and find closest start and end points # iterate over y coords and find closest start and end points
i = [ i = [i for i, t in enumerate(self.cols)
i if np.isclose(v[0], t[0], atol=joint_close_tol)]
for i, t in enumerate(self.cols) j = [j for j, t in enumerate(self.rows)
if np.isclose(v[0], t[0], atol=joint_tol) if np.isclose(v[3], t[0], atol=joint_close_tol)]
] k = [k for k, t in enumerate(self.rows)
j = [ if np.isclose(v[1], t[0], atol=joint_close_tol)]
j
for j, t in enumerate(self.rows)
if np.isclose(v[3], t[0], atol=joint_tol)
]
k = [
k
for k, t in enumerate(self.rows)
if np.isclose(v[1], t[0], atol=joint_tol)
]
if not j: if not j:
continue continue
J = j[0] J = j[0]
@ -463,21 +230,12 @@ class Table(object):
for h in horizontal: for h in horizontal:
# find closest y coord # find closest y coord
# iterate over x coords and find closest start and end points # iterate over x coords and find closest start and end points
i = [ i = [i for i, t in enumerate(self.rows)
i if np.isclose(h[1], t[0], atol=joint_close_tol)]
for i, t in enumerate(self.rows) j = [j for j, t in enumerate(self.cols)
if np.isclose(h[1], t[0], atol=joint_tol) if np.isclose(h[0], t[0], atol=joint_close_tol)]
] k = [k for k, t in enumerate(self.cols)
j = [ if np.isclose(h[2], t[0], atol=joint_close_tol)]
j
for j, t in enumerate(self.cols)
if np.isclose(h[0], t[0], atol=joint_tol)
]
k = [
k
for k, t in enumerate(self.cols)
if np.isclose(h[2], t[0], atol=joint_tol)
]
if not j: if not j:
continue continue
J = j[0] J = j[0]
@ -494,7 +252,7 @@ class Table(object):
self.cells[L][J].top = True self.cells[L][J].top = True
J += 1 J += 1
elif i == []: # only bottom edge elif i == []: # only bottom edge
L = len(self.rows) - 1 I = len(self.rows) - 1
if k: if k:
K = k[0] K = k[0]
while J < K: while J < K:
@ -523,7 +281,8 @@ class Table(object):
return self return self
def set_border(self): def set_border(self):
"""Sets table border edges to True.""" """Sets table border edges to True.
"""
for r in range(len(self.rows)): for r in range(len(self.rows)):
self.cells[r][0].left = True self.cells[r][0].left = True
self.cells[r][len(self.cols) - 1].right = True self.cells[r][len(self.cols) - 1].right = True
@ -563,6 +322,33 @@ class Table(object):
cell.hspan = True cell.hspan = True
return self return self
def plot(self, geometry_type):
"""Plot geometry found on PDF page based on geometry_type
specified, useful for debugging and playing with different
parameters to get the best output.
Parameters
----------
geometry_type : str
The geometry type for which a plot should be generated.
Can be 'text', 'table', 'contour', 'joint', 'line'
"""
if self.flavor == 'stream' and geometry_type in ['contour', 'joint', 'line']:
raise NotImplementedError("{} cannot be plotted with flavor='stream'".format(
geometry_type))
if geometry_type == 'text':
plot_text(self._text)
elif geometry_type == 'table':
plot_table(self)
elif geometry_type == 'contour':
plot_contour(self._image)
elif geometry_type == 'joint':
plot_joint(self._image)
elif geometry_type == 'line':
plot_line(self._segments)
def to_csv(self, path, **kwargs): def to_csv(self, path, **kwargs):
"""Writes Table to a comma-separated values (csv) file. """Writes Table to a comma-separated values (csv) file.
@ -574,7 +360,12 @@ class Table(object):
Output filepath. Output filepath.
""" """
kw = {"encoding": "utf-8", "index": False, "header": False, "quoting": 1} kw = {
'encoding': 'utf-8',
'index': False,
'header': False,
'quoting': 1
}
kw.update(kwargs) kw.update(kwargs)
self.df.to_csv(path, **kw) self.df.to_csv(path, **kw)
@ -589,10 +380,12 @@ class Table(object):
Output filepath. Output filepath.
""" """
kw = {"orient": "records"} kw = {
'orient': 'records'
}
kw.update(kwargs) kw.update(kwargs)
json_string = self.df.to_json(**kw) json_string = self.df.to_json(**kw)
with open(path, "w") as f: with open(path, 'w') as f:
f.write(json_string) f.write(json_string)
def to_excel(self, path, **kwargs): def to_excel(self, path, **kwargs):
@ -607,8 +400,8 @@ class Table(object):
""" """
kw = { kw = {
"sheet_name": f"page-{self.page}-table-{self.order}", 'sheet_name': 'page-{}-table-{}'.format(self.page, self.order),
"encoding": "utf-8", 'encoding': 'utf-8'
} }
kw.update(kwargs) kw.update(kwargs)
writer = pd.ExcelWriter(path) writer = pd.ExcelWriter(path)
@ -627,43 +420,9 @@ class Table(object):
""" """
html_string = self.df.to_html(**kwargs) html_string = self.df.to_html(**kwargs)
with open(path, "w", encoding="utf-8") as f: with open(path, 'w') as f:
f.write(html_string) f.write(html_string)
def to_markdown(self, path, **kwargs):
"""Writes Table to a Markdown file.
For kwargs, check :meth:`pandas.DataFrame.to_markdown`.
Parameters
----------
path : str
Output filepath.
"""
md_string = self.df.to_markdown(**kwargs)
with open(path, "w", encoding="utf-8") as f:
f.write(md_string)
def to_sqlite(self, path, **kwargs):
"""Writes Table to sqlite database.
For kwargs, check :meth:`pandas.DataFrame.to_sql`.
Parameters
----------
path : str
Output filepath.
"""
kw = {"if_exists": "replace", "index": False}
kw.update(kwargs)
conn = sqlite3.connect(path)
table_name = f"page-{self.page}-table-{self.order}"
self.df.to_sql(table_name, conn, **kw)
conn.commit()
conn.close()
class TableList(object): class TableList(object):
"""Defines a list of camelot.core.Table objects. Each table can """Defines a list of camelot.core.Table objects. Each table can
@ -675,12 +434,12 @@ class TableList(object):
Number of tables in the list. Number of tables in the list.
""" """
def __init__(self, tables): def __init__(self, tables):
self._tables = tables self._tables = tables
def __repr__(self): def __repr__(self):
return f"<{self.__class__.__name__} n={self.n}>" return '<{} tables={}>'.format(
self.__class__.__name__, len(self._tables))
def __len__(self): def __len__(self):
return len(self._tables) return len(self._tables)
@ -688,37 +447,51 @@ class TableList(object):
def __getitem__(self, idx): def __getitem__(self, idx):
return self._tables[idx] return self._tables[idx]
def __iter__(self):
self._n = 0
return self
def next(self):
if self._n < len(self):
r = self._tables[self._n]
self._n += 1
return r
else:
raise StopIteration
@staticmethod @staticmethod
def _format_func(table, f): def _format_func(table, f):
return getattr(table, f"to_{f}") return getattr(table, 'to_{}'.format(f))
@property @property
def n(self): def n(self):
return len(self) return len(self)
def _write_file(self, f=None, **kwargs): def _write_file(self, f=None, **kwargs):
dirname = kwargs.get("dirname") dirname = kwargs.get('dirname')
root = kwargs.get("root") root = kwargs.get('root')
ext = kwargs.get("ext") ext = kwargs.get('ext')
for table in self._tables: for table in self._tables:
filename = f"{root}-page-{table.page}-table-{table.order}{ext}" filename = os.path.join('{}-page-{}-table-{}{}'.format(
root, table.page, table.order, ext))
filepath = os.path.join(dirname, filename) filepath = os.path.join(dirname, filename)
to_format = self._format_func(table, f) to_format = self._format_func(table, f)
to_format(filepath) to_format(filepath)
def _compress_dir(self, **kwargs): def _compress_dir(self, **kwargs):
path = kwargs.get("path") path = kwargs.get('path')
dirname = kwargs.get("dirname") dirname = kwargs.get('dirname')
root = kwargs.get("root") root = kwargs.get('root')
ext = kwargs.get("ext") ext = kwargs.get('ext')
zipname = os.path.join(os.path.dirname(path), root) + ".zip" zipname = os.path.join(os.path.dirname(path), root) + '.zip'
with zipfile.ZipFile(zipname, "w", allowZip64=True) as z: with zipfile.ZipFile(zipname, 'w', allowZip64=True) as z:
for table in self._tables: for table in self._tables:
filename = f"{root}-page-{table.page}-table-{table.order}{ext}" filename = os.path.join('{}-page-{}-table-{}{}'.format(
root, table.page, table.order, ext))
filepath = os.path.join(dirname, filename) filepath = os.path.join(dirname, filename)
z.write(filepath, os.path.basename(filepath)) z.write(filepath, os.path.basename(filepath))
def export(self, path, f="csv", compress=False): def export(self, path, f='csv', compress=False):
"""Exports the list of tables to specified file format. """Exports the list of tables to specified file format.
Parameters Parameters
@ -726,7 +499,7 @@ class TableList(object):
path : str path : str
Output filepath. Output filepath.
f : str f : str
File format. Can be csv, excel, html, json, markdown or sqlite. File format. Can be csv, json, excel and html.
compress : bool compress : bool
Whether or not to add files to a ZIP archive. Whether or not to add files to a ZIP archive.
@ -737,28 +510,25 @@ class TableList(object):
if compress: if compress:
dirname = tempfile.mkdtemp() dirname = tempfile.mkdtemp()
kwargs = {"path": path, "dirname": dirname, "root": root, "ext": ext} kwargs = {
'path': path,
'dirname': dirname,
'root': root,
'ext': ext
}
if f in ["csv", "html", "json", "markdown"]: if f in ['csv', 'json', 'html']:
self._write_file(f=f, **kwargs) self._write_file(f=f, **kwargs)
if compress: if compress:
self._compress_dir(**kwargs) self._compress_dir(**kwargs)
elif f == "excel": elif f == 'excel':
filepath = os.path.join(dirname, basename) filepath = os.path.join(dirname, basename)
writer = pd.ExcelWriter(filepath) writer = pd.ExcelWriter(filepath)
for table in self._tables: for table in self._tables:
sheet_name = f"page-{table.page}-table-{table.order}" sheet_name = 'page-{}-table-{}'.format(table.page, table.order)
table.df.to_excel(writer, sheet_name=sheet_name, encoding="utf-8") table.df.to_excel(writer, sheet_name=sheet_name, encoding='utf-8')
writer.save() writer.save()
if compress: if compress:
zipname = os.path.join(os.path.dirname(path), root) + ".zip" zipname = os.path.join(os.path.dirname(path), root) + '.zip'
with zipfile.ZipFile(zipname, "w", allowZip64=True) as z: with zipfile.ZipFile(zipname, 'w', allowZip64=True) as z:
z.write(filepath, os.path.basename(filepath)) z.write(filepath, os.path.basename(filepath))
elif f == "sqlite":
filepath = os.path.join(dirname, basename)
for table in self._tables:
table.to_sqlite(filepath)
if compress:
zipname = os.path.join(os.path.dirname(path), root) + ".zip"
with zipfile.ZipFile(zipname, "w", allowZip64=True) as z:
z.write(filepath, os.path.basename(filepath))

146
camelot/handlers.py
View File

@ -1,20 +1,13 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import os import os
import sys
from PyPDF2 import PdfFileReader, PdfFileWriter from PyPDF2 import PdfFileReader, PdfFileWriter
from .core import TableList from .core import TableList
from .parsers import Stream, Lattice from .parsers import Stream, Lattice
from .utils import ( from .utils import (TemporaryDirectory, get_page_layout, get_text_objects,
TemporaryDirectory, get_rotation)
get_page_layout,
get_text_objects,
get_rotation,
is_url,
download_url,
)
class PDFHandler(object): class PDFHandler(object):
@ -24,41 +17,29 @@ class PDFHandler(object):
Parameters Parameters
---------- ----------
filepath : str filename : str
Filepath or URL of the PDF file. Path to PDF file.
pages : str, optional (default: '1') pages : str, optional (default: '1')
Comma-separated page numbers. Comma-separated page numbers.
Example: '1,3,4' or '1,4-end' or 'all'. Example: 1,3,4 or 1,4-end.
password : str, optional (default: None)
Password for decryption.
""" """
def __init__(self, filename, pages='1'):
self.filename = filename
if not self.filename.endswith('.pdf'):
raise TypeError("File format not supported.")
self.pages = self._get_pages(self.filename, pages)
def __init__(self, filepath, pages="1", password=None): def _get_pages(self, filename, pages):
if is_url(filepath):
filepath = download_url(filepath)
self.filepath = filepath
# if not filepath.lower().endswith(".pdf"):
# raise NotImplementedError("File format not supported")
if password is None:
self.password = ""
else:
self.password = password
if sys.version_info[0] < 3:
self.password = self.password.encode("ascii")
self.pages = self._get_pages(pages)
def _get_pages(self, pages):
"""Converts pages string to list of ints. """Converts pages string to list of ints.
Parameters Parameters
---------- ----------
filepath : str filename : str
Filepath or URL of the PDF file. Path to PDF file.
pages : str, optional (default: '1') pages : str, optional (default: '1')
Comma-separated page numbers. Comma-separated page numbers.
Example: '1,3,4' or '1,4-end' or 'all'. Example: 1,3,4 or 1,4-end.
Returns Returns
------- -------
@ -67,84 +48,73 @@ class PDFHandler(object):
""" """
page_numbers = [] page_numbers = []
if pages == '1':
if pages == "1": page_numbers.append({'start': 1, 'end': 1})
page_numbers.append({"start": 1, "end": 1})
else: else:
with open(self.filepath, "rb") as f: infile = PdfFileReader(open(filename, 'rb'), strict=False)
infile = PdfFileReader(f, strict=False) if pages == 'all':
page_numbers.append({'start': 1, 'end': infile.getNumPages()})
if infile.isEncrypted: else:
infile.decrypt(self.password) for r in pages.split(','):
if '-' in r:
if pages == "all": a, b = r.split('-')
page_numbers.append({"start": 1, "end": infile.getNumPages()}) if b == 'end':
else: b = infile.getNumPages()
for r in pages.split(","): page_numbers.append({'start': int(a), 'end': int(b)})
if "-" in r: else:
a, b = r.split("-") page_numbers.append({'start': int(r), 'end': int(r)})
if b == "end":
b = infile.getNumPages()
page_numbers.append({"start": int(a), "end": int(b)})
else:
page_numbers.append({"start": int(r), "end": int(r)})
P = [] P = []
for p in page_numbers: for p in page_numbers:
P.extend(range(p["start"], p["end"] + 1)) P.extend(range(p['start'], p['end'] + 1))
return sorted(set(P)) return sorted(set(P))
def _save_page(self, filepath, page, temp): def _save_page(self, filename, page, temp):
"""Saves specified page from PDF into a temporary directory. """Saves specified page from PDF into a temporary directory.
Parameters Parameters
---------- ----------
filepath : str filename : str
Filepath or URL of the PDF file. Path to PDF file.
page : int page : int
Page number. Page number.
temp : str temp : str
Tmp directory. Tmp directory.
""" """
with open(filepath, "rb") as fileobj: with open(filename, 'rb') as fileobj:
infile = PdfFileReader(fileobj, strict=False) infile = PdfFileReader(fileobj, strict=False)
if infile.isEncrypted: if infile.isEncrypted:
infile.decrypt(self.password) infile.decrypt('')
fpath = os.path.join(temp, f"page-{page}.pdf") fpath = os.path.join(temp, 'page-{0}.pdf'.format(page))
froot, fext = os.path.splitext(fpath) froot, fext = os.path.splitext(fpath)
p = infile.getPage(page - 1) p = infile.getPage(page - 1)
outfile = PdfFileWriter() outfile = PdfFileWriter()
outfile.addPage(p) outfile.addPage(p)
with open(fpath, "wb") as f: with open(fpath, 'wb') as f:
outfile.write(f) outfile.write(f)
layout, dim = get_page_layout(fpath) layout, dim = get_page_layout(fpath)
# fix rotated PDF # fix rotated PDF
chars = get_text_objects(layout, ltype="char") lttextlh = get_text_objects(layout, ltype="lh")
horizontal_text = get_text_objects(layout, ltype="horizontal_text") lttextlv = get_text_objects(layout, ltype="lv")
vertical_text = get_text_objects(layout, ltype="vertical_text") ltchar = get_text_objects(layout, ltype="char")
rotation = get_rotation(chars, horizontal_text, vertical_text) rotation = get_rotation(lttextlh, lttextlv, ltchar)
if rotation != "": if rotation != '':
fpath_new = "".join([froot.replace("page", "p"), "_rotated", fext]) fpath_new = ''.join([froot.replace('page', 'p'), '_rotated', fext])
os.rename(fpath, fpath_new) os.rename(fpath, fpath_new)
instream = open(fpath_new, "rb") infile = PdfFileReader(open(fpath_new, 'rb'), strict=False)
infile = PdfFileReader(instream, strict=False)
if infile.isEncrypted: if infile.isEncrypted:
infile.decrypt(self.password) infile.decrypt('')
outfile = PdfFileWriter() outfile = PdfFileWriter()
p = infile.getPage(0) p = infile.getPage(0)
if rotation == "anticlockwise": if rotation == 'anticlockwise':
p.rotateClockwise(90) p.rotateClockwise(90)
elif rotation == "clockwise": elif rotation == 'clockwise':
p.rotateCounterClockwise(90) p.rotateCounterClockwise(90)
outfile.addPage(p) outfile.addPage(p)
with open(fpath, "wb") as f: with open(fpath, 'wb') as f:
outfile.write(f) outfile.write(f)
instream.close()
def parse( def parse(self, flavor='lattice', **kwargs):
self, flavor="lattice", suppress_stdout=False, layout_kwargs={}, **kwargs
):
"""Extracts tables by calling parser.get_tables on all single """Extracts tables by calling parser.get_tables on all single
page PDFs. page PDFs.
@ -153,10 +123,6 @@ class PDFHandler(object):
flavor : str (default: 'lattice') flavor : str (default: 'lattice')
The parsing method to use ('lattice' or 'stream'). The parsing method to use ('lattice' or 'stream').
Lattice is used by default. Lattice is used by default.
suppress_stdout : str (default: False)
Suppress logs and warnings.
layout_kwargs : dict, optional (default: {})
A dict of `pdfminer.layout.LAParams <https://github.com/euske/pdfminer/blob/master/pdfminer/layout.py#L33>`_ kwargs.
kwargs : dict kwargs : dict
See camelot.read_pdf kwargs. See camelot.read_pdf kwargs.
@ -164,17 +130,19 @@ class PDFHandler(object):
------- -------
tables : camelot.core.TableList tables : camelot.core.TableList
List of tables found in PDF. List of tables found in PDF.
geometry : camelot.core.GeometryList
List of geometry objects (contours, lines, joints) found
in PDF.
""" """
tables = [] tables = []
with TemporaryDirectory() as tempdir: with TemporaryDirectory() as tempdir:
for p in self.pages: for p in self.pages:
self._save_page(self.filepath, p, tempdir) self._save_page(self.filename, p, tempdir)
pages = [os.path.join(tempdir, f"page-{p}.pdf") for p in self.pages] pages = [os.path.join(tempdir, 'page-{0}.pdf'.format(p))
parser = Lattice(**kwargs) if flavor == "lattice" else Stream(**kwargs) for p in self.pages]
parser = Lattice(**kwargs) if flavor == 'lattice' else Stream(**kwargs)
for p in pages: for p in pages:
t = parser.extract_tables( t = parser.extract_tables(p)
p, suppress_stdout=suppress_stdout, layout_kwargs=layout_kwargs
)
tables.extend(t) tables.extend(t)
return TableList(sorted(tables)) return TableList(tables)

157
camelot/image_processing.py
View File

@ -1,8 +1,14 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
from __future__ import division
from itertools import groupby
from operator import itemgetter
import cv2 import cv2
import numpy as np import numpy as np
from .utils import merge_tuples
def adaptive_threshold(imagename, process_background=False, blocksize=15, c=-2): def adaptive_threshold(imagename, process_background=False, blocksize=15, c=-2):
"""Thresholds an image using OpenCV's adaptiveThreshold. """Thresholds an image using OpenCV's adaptiveThreshold.
@ -36,24 +42,15 @@ def adaptive_threshold(imagename, process_background=False, blocksize=15, c=-2):
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
if process_background: if process_background:
threshold = cv2.adaptiveThreshold( threshold = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, blocksize, c cv2.THRESH_BINARY, blocksize, c)
)
else: else:
threshold = cv2.adaptiveThreshold( threshold = cv2.adaptiveThreshold(np.invert(gray), 255,
np.invert(gray), cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, blocksize, c)
255,
cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
cv2.THRESH_BINARY,
blocksize,
c,
)
return img, threshold return img, threshold
def find_lines( def find_lines(threshold, direction='horizontal', line_size_scaling=15, iterations=0):
threshold, regions=None, direction="horizontal", line_scale=15, iterations=0
):
"""Finds horizontal and vertical lines by applying morphological """Finds horizontal and vertical lines by applying morphological
transformations on an image. transformations on an image.
@ -61,13 +58,9 @@ def find_lines(
---------- ----------
threshold : object threshold : object
numpy.ndarray representing the thresholded image. numpy.ndarray representing the thresholded image.
regions : list, optional (default: None)
List of page regions that may contain tables of the form x1,y1,x2,y2
where (x1, y1) -> left-top and (x2, y2) -> right-bottom
in image coordinate space.
direction : string, optional (default: 'horizontal') direction : string, optional (default: 'horizontal')
Specifies whether to find vertical or horizontal lines. Specifies whether to find vertical or horizontal lines.
line_scale : int, optional (default: 15) line_size_scaling : int, optional (default: 15)
Factor by which the page dimensions will be divided to get Factor by which the page dimensions will be divided to get
smallest length of lines that should be detected. smallest length of lines that should be detected.
@ -91,21 +84,15 @@ def find_lines(
""" """
lines = [] lines = []
if direction == "vertical": if direction == 'vertical':
size = threshold.shape[0] // line_scale size = threshold.shape[0] // line_size_scaling
el = cv2.getStructuringElement(cv2.MORPH_RECT, (1, size)) el = cv2.getStructuringElement(cv2.MORPH_RECT, (1, size))
elif direction == "horizontal": elif direction == 'horizontal':
size = threshold.shape[1] // line_scale size = threshold.shape[1] // line_size_scaling
el = cv2.getStructuringElement(cv2.MORPH_RECT, (size, 1)) el = cv2.getStructuringElement(cv2.MORPH_RECT, (size, 1))
elif direction is None: elif direction is None:
raise ValueError("Specify direction as either 'vertical' or 'horizontal'") raise ValueError("Specify direction as either 'vertical' or"
" 'horizontal'")
if regions is not None:
region_mask = np.zeros(threshold.shape)
for region in regions:
x, y, w, h = region
region_mask[y : y + h, x : x + w] = 1
threshold = np.multiply(threshold, region_mask)
threshold = cv2.erode(threshold, el) threshold = cv2.erode(threshold, el)
threshold = cv2.dilate(threshold, el) threshold = cv2.dilate(threshold, el)
@ -113,27 +100,24 @@ def find_lines(
try: try:
_, contours, _ = cv2.findContours( _, contours, _ = cv2.findContours(
threshold.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
)
except ValueError: except ValueError:
# for opencv backward compatibility
contours, _ = cv2.findContours( contours, _ = cv2.findContours(
threshold.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
)
for c in contours: for c in contours:
x, y, w, h = cv2.boundingRect(c) x, y, w, h = cv2.boundingRect(c)
x1, x2 = x, x + w x1, x2 = x, x + w
y1, y2 = y, y + h y1, y2 = y, y + h
if direction == "vertical": if direction == 'vertical':
lines.append(((x1 + x2) // 2, y2, (x1 + x2) // 2, y1)) lines.append(((x1 + x2) // 2, y2, (x1 + x2) // 2, y1))
elif direction == "horizontal": elif direction == 'horizontal':
lines.append((x1, (y1 + y2) // 2, x2, (y1 + y2) // 2)) lines.append((x1, (y1 + y2) // 2, x2, (y1 + y2) // 2))
return dmask, lines return dmask, lines
def find_contours(vertical, horizontal): def find_table_contours(vertical, horizontal):
"""Finds table boundaries using OpenCV's findContours. """Finds table boundaries using OpenCV's findContours.
Parameters Parameters
@ -155,14 +139,10 @@ def find_contours(vertical, horizontal):
try: try:
__, contours, __ = cv2.findContours( __, contours, __ = cv2.findContours(
mask.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
)
except ValueError: except ValueError:
# for opencv backward compatibility
contours, __ = cv2.findContours( contours, __ = cv2.findContours(
mask.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
)
# sort in reverse based on contour area and use first 10 contours
contours = sorted(contours, key=cv2.contourArea, reverse=True)[:10] contours = sorted(contours, key=cv2.contourArea, reverse=True)[:10]
cont = [] cont = []
@ -173,7 +153,7 @@ def find_contours(vertical, horizontal):
return cont return cont
def find_joints(contours, vertical, horizontal): def find_table_joints(contours, vertical, horizontal):
"""Finds joints/intersections present inside each table boundary. """Finds joints/intersections present inside each table boundary.
Parameters Parameters
@ -196,20 +176,17 @@ def find_joints(contours, vertical, horizontal):
and (x2, y2) -> rt in image coordinate space. and (x2, y2) -> rt in image coordinate space.
""" """
joints = np.multiply(vertical, horizontal) joints = np.bitwise_and(vertical, horizontal)
tables = {} tables = {}
for c in contours: for c in contours:
x, y, w, h = c x, y, w, h = c
roi = joints[y : y + h, x : x + w] roi = joints[y : y + h, x : x + w]
try: try:
__, jc, __ = cv2.findContours( __, jc, __ = cv2.findContours(
roi.astype(np.uint8), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE roi, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
)
except ValueError: except ValueError:
# for opencv backward compatibility
jc, __ = cv2.findContours( jc, __ = cv2.findContours(
roi.astype(np.uint8), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE roi, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
)
if len(jc) <= 4: # remove contours with less than 4 joints if len(jc) <= 4: # remove contours with less than 4 joints
continue continue
joint_coords = [] joint_coords = []
@ -220,3 +197,79 @@ def find_joints(contours, vertical, horizontal):
tables[(x, y + h, x + w, y)] = joint_coords tables[(x, y + h, x + w, y)] = joint_coords
return tables return tables
def remove_lines(threshold, line_size_scaling=15):
"""Removes lines from a thresholded image.
Parameters
----------
threshold : object
numpy.ndarray representing the thresholded image.
line_size_scaling : int, optional (default: 15)
Factor by which the page dimensions will be divided to get
smallest length of lines that should be detected.
The larger this value, smaller the detected lines. Making it
too large will lead to text being detected as lines.
Returns
-------
threshold : object
numpy.ndarray representing the thresholded image
with horizontal and vertical lines removed.
"""
size = threshold.shape[0] // line_size_scaling
vertical_erode_el = cv2.getStructuringElement(cv2.MORPH_RECT, (1, size))
horizontal_erode_el = cv2.getStructuringElement(cv2.MORPH_RECT, (size, 1))
dilate_el = cv2.getStructuringElement(cv2.MORPH_RECT, (10, 10))
vertical = cv2.erode(threshold, vertical_erode_el)
vertical = cv2.dilate(vertical, dilate_el)
horizontal = cv2.erode(threshold, horizontal_erode_el)
horizontal = cv2.dilate(horizontal, dilate_el)
threshold = np.bitwise_and(threshold, np.invert(vertical))
threshold = np.bitwise_and(threshold, np.invert(horizontal))
return threshold
def find_cuts(threshold, char_size_scaling=200):
"""Finds cuts made by text projections on y-axis.
Parameters
----------
threshold : object
numpy.ndarray representing the thresholded image.
line_size_scaling : int, optional (default: 200)
Factor by which the page dimensions will be divided to get
smallest length of lines that should be detected.
The larger this value, smaller the detected lines. Making it
too large will lead to text being detected as lines.
Returns
-------
y_cuts : list
List of cuts on y-axis.
"""
size = threshold.shape[0] // char_size_scaling
char_el = cv2.getStructuringElement(cv2.MORPH_RECT, (1, size))
threshold = cv2.erode(threshold, char_el)
threshold = cv2.dilate(threshold, char_el)
try:
__, contours, __ = cv2.findContours(threshold, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
except ValueError:
contours, __ = cv2.findContours(threshold, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
contours = [cv2.boundingRect(c) for c in contours]
y_cuts = [(c[1], c[1] + c[3]) for c in contours]
y_cuts = list(merge_tuples(sorted(y_cuts)))
y_cuts = [(y_cuts[i][0] + y_cuts[i - 1][1]) // 2 for i in range(1, len(y_cuts))]
return sorted(y_cuts, reverse=True)

69
camelot/io.py
View File

@ -1,20 +1,10 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import warnings
from .handlers import PDFHandler from .handlers import PDFHandler
from .utils import validate_input, remove_extra from .utils import validate_input, remove_extra
def read_pdf( def read_pdf(filepath, pages='1', flavor='lattice', **kwargs):
filepath,
pages="1",
password=None,
flavor="lattice",
suppress_stdout=False,
layout_kwargs={},
**kwargs
):
"""Read PDF and return extracted tables. """Read PDF and return extracted tables.
Note: kwargs annotated with ^ can only be used with flavor='stream' Note: kwargs annotated with ^ can only be used with flavor='stream'
@ -23,20 +13,14 @@ def read_pdf(
Parameters Parameters
---------- ----------
filepath : str filepath : str
Filepath or URL of the PDF file. Path to PDF file.
pages : str, optional (default: '1') pages : str, optional (default: '1')
Comma-separated page numbers. Comma-separated page numbers.
Example: '1,3,4' or '1,4-end' or 'all'. Example: 1,3,4 or 1,4-end.
password : str, optional (default: None)
Password for decryption.
flavor : str (default: 'lattice') flavor : str (default: 'lattice')
The parsing method to use ('lattice' or 'stream'). The parsing method to use ('lattice' or 'stream').
Lattice is used by default. Lattice is used by default.
suppress_stdout : bool, optional (default: True) table_area : list, optional (default: None)
Print all logs and warnings.
layout_kwargs : dict, optional (default: {})
A dict of `pdfminer.layout.LAParams <https://github.com/euske/pdfminer/blob/master/pdfminer/layout.py#L33>`_ kwargs.
table_areas : list, optional (default: None)
List of table area strings of the form x1,y1,x2,y2 List of table area strings of the form x1,y1,x2,y2
where (x1, y1) -> left-top and (x2, y2) -> right-bottom where (x1, y1) -> left-top and (x2, y2) -> right-bottom
in PDF coordinate space. in PDF coordinate space.
@ -48,18 +32,15 @@ def read_pdf(
flag_size : bool, optional (default: False) flag_size : bool, optional (default: False)
Flag text based on font size. Useful to detect Flag text based on font size. Useful to detect
super/subscripts. Adds <s></s> around flagged text. super/subscripts. Adds <s></s> around flagged text.
strip_text : str, optional (default: '') row_close_tol^ : int, optional (default: 2)
Characters that should be stripped from a string before
assigning it to a cell.
row_tol^ : int, optional (default: 2)
Tolerance parameter used to combine text vertically, Tolerance parameter used to combine text vertically,
to generate rows. to generate rows.
column_tol^ : int, optional (default: 0) col_close_tol^ : int, optional (default: 0)
Tolerance parameter used to combine text horizontally, Tolerance parameter used to combine text horizontally,
to generate columns. to generate columns.
process_background* : bool, optional (default: False) process_background* : bool, optional (default: False)
Process background lines. Process background lines.
line_scale* : int, optional (default: 15) line_size_scaling* : int, optional (default: 15)
Line size scaling factor. The larger the value the smaller Line size scaling factor. The larger the value the smaller
the detected lines. Making it very large will lead to text the detected lines. Making it very large will lead to text
being detected as lines. being detected as lines.
@ -70,10 +51,10 @@ def read_pdf(
shift_text* : list, optional (default: ['l', 't']) shift_text* : list, optional (default: ['l', 't'])
{'l', 'r', 't', 'b'} {'l', 'r', 't', 'b'}
Direction in which text in a spanning cell will flow. Direction in which text in a spanning cell will flow.
line_tol* : int, optional (default: 2) line_close_tol* : int, optional (default: 2)
Tolerance parameter used to merge close vertical and horizontal Tolerance parameter used to merge close vertical and horizontal
lines. lines.
joint_tol* : int, optional (default: 2) joint_close_tol* : int, optional (default: 2)
Tolerance parameter used to decide whether the detected lines Tolerance parameter used to decide whether the detected lines
and points lie close to each other. and points lie close to each other.
threshold_blocksize* : int, optional (default: 15) threshold_blocksize* : int, optional (default: 15)
@ -90,30 +71,22 @@ def read_pdf(
Number of times for erosion/dilation is applied. Number of times for erosion/dilation is applied.
For more information, refer `OpenCV's dilate <https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html#dilate>`_. For more information, refer `OpenCV's dilate <https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html#dilate>`_.
resolution* : int, optional (default: 300) margins : tuple
Resolution used for PDF to PNG conversion. PDFMiner char_margin, line_margin and word_margin.
For more information, refer `PDFMiner docs <https://euske.github.io/pdfminer/>`_.
Returns Returns
------- -------
tables : camelot.core.TableList tables : camelot.core.TableList
""" """
if flavor not in ["lattice", "stream"]: if flavor not in ['lattice', 'stream']:
raise NotImplementedError( raise NotImplementedError("Unknown flavor specified."
"Unknown flavor specified." " Use either 'lattice' or 'stream'" " Use either 'lattice' or 'stream'")
)
with warnings.catch_warnings(): validate_input(kwargs, flavor=flavor)
if suppress_stdout: p = PDFHandler(filepath, pages)
warnings.simplefilter("ignore") kwargs = remove_extra(kwargs, flavor=flavor)
tables = p.parse(flavor=flavor, **kwargs)
validate_input(kwargs, flavor=flavor) return tables
p = PDFHandler(filepath, pages=pages, password=password)
kwargs = remove_extra(kwargs, flavor=flavor)
tables = p.parse(
flavor=flavor,
suppress_stdout=suppress_stdout,
layout_kwargs=layout_kwargs,
**kwargs
)
return tables

2
camelot/parsers/__init__.py
View File

@ -1,4 +1,4 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
from .stream import Stream from .stream import Stream
from .lattice import Lattice from .lattice import Lattice

21
camelot/parsers/base.py
View File

@ -6,15 +6,16 @@ from ..utils import get_page_layout, get_text_objects
class BaseParser(object): class BaseParser(object):
"""Defines a base parser.""" """Defines a base parser.
"""
def _generate_layout(self, filename, layout_kwargs): def _generate_layout(self, filename):
self.filename = filename self.filename = filename
self.layout_kwargs = layout_kwargs self.layout, self.dimensions = get_page_layout(
self.layout, self.dimensions = get_page_layout(filename, **layout_kwargs) self.filename,
self.images = get_text_objects(self.layout, ltype="image") char_margin=self.char_margin,
self.horizontal_text = get_text_objects(self.layout, ltype="horizontal_text") line_margin=self.line_margin,
self.vertical_text = get_text_objects(self.layout, ltype="vertical_text") word_margin=self.word_margin)
self.horizontal_text = get_text_objects(self.layout, ltype="lh")
self.vertical_text = get_text_objects(self.layout, ltype="lv")
self.pdf_width, self.pdf_height = self.dimensions self.pdf_width, self.pdf_height = self.dimensions
self.rootname, __ = os.path.splitext(self.filename) self.rootname, __ = os.path.splitext(self.filename)
self.imagename = "".join([self.rootname, ".png"])

307
camelot/parsers/lattice.py
View File

@ -1,37 +1,24 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
from __future__ import division
import os import os
import sys
import copy import copy
import locale
import logging import logging
import warnings import subprocess
import numpy as np import numpy as np
import pandas as pd import pandas as pd
from .base import BaseParser from .base import BaseParser
from ..core import Table from ..core import Table
from ..utils import ( from ..utils import (scale_image, scale_pdf, segments_in_bbox, text_in_bbox,
scale_image, merge_close_lines, get_table_index, compute_accuracy,
scale_pdf, compute_whitespace, setup_logging, encode_)
segments_in_bbox, from ..image_processing import (adaptive_threshold, find_lines,
text_in_bbox, find_table_contours, find_table_joints)
merge_close_lines,
get_table_index,
compute_accuracy,
compute_whitespace,
)
from ..image_processing import (
adaptive_threshold,
find_lines,
find_contours,
find_joints,
)
from ..backends.image_conversion import BACKENDS
logger = logging.getLogger("camelot") logger = setup_logging(__name__)
class Lattice(BaseParser): class Lattice(BaseParser):
@ -40,17 +27,13 @@ class Lattice(BaseParser):
Parameters Parameters
---------- ----------
table_regions : list, optional (default: None) table_area : list, optional (default: None)
List of page regions that may contain tables of the form x1,y1,x2,y2
where (x1, y1) -> left-top and (x2, y2) -> right-bottom
in PDF coordinate space.
table_areas : list, optional (default: None)
List of table area strings of the form x1,y1,x2,y2 List of table area strings of the form x1,y1,x2,y2
where (x1, y1) -> left-top and (x2, y2) -> right-bottom where (x1, y1) -> left-top and (x2, y2) -> right-bottom
in PDF coordinate space. in PDF coordinate space.
process_background : bool, optional (default: False) process_background : bool, optional (default: False)
Process background lines. Process background lines.
line_scale : int, optional (default: 15) line_size_scaling : int, optional (default: 15)
Line size scaling factor. The larger the value the smaller Line size scaling factor. The larger the value the smaller
the detected lines. Making it very large will lead to text the detected lines. Making it very large will lead to text
being detected as lines. being detected as lines.
@ -66,13 +49,10 @@ class Lattice(BaseParser):
flag_size : bool, optional (default: False) flag_size : bool, optional (default: False)
Flag text based on font size. Useful to detect Flag text based on font size. Useful to detect
super/subscripts. Adds <s></s> around flagged text. super/subscripts. Adds <s></s> around flagged text.
strip_text : str, optional (default: '') line_close_tol : int, optional (default: 2)
Characters that should be stripped from a string before
assigning it to a cell.
line_tol : int, optional (default: 2)
Tolerance parameter used to merge close vertical and horizontal Tolerance parameter used to merge close vertical and horizontal
lines. lines.
joint_tol : int, optional (default: 2) joint_close_tol : int, optional (default: 2)
Tolerance parameter used to decide whether the detected lines Tolerance parameter used to decide whether the detected lines
and points lie close to each other. and points lie close to each other.
threshold_blocksize : int, optional (default: 15) threshold_blocksize : int, optional (default: 15)
@ -89,77 +69,30 @@ class Lattice(BaseParser):
Number of times for erosion/dilation is applied. Number of times for erosion/dilation is applied.
For more information, refer `OpenCV's dilate <https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html#dilate>`_. For more information, refer `OpenCV's dilate <https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html#dilate>`_.
resolution : int, optional (default: 300) margins : tuple
Resolution used for PDF to PNG conversion. PDFMiner char_margin, line_margin and word_margin.
For more information, refer `PDFMiner docs <https://euske.github.io/pdfminer/>`_.
""" """
def __init__(self, table_area=None, process_background=False,
def __init__( line_size_scaling=15, copy_text=None, shift_text=['l', 't'],
self, split_text=False, flag_size=False, line_close_tol=2,
table_regions=None, joint_close_tol=2, threshold_blocksize=15, threshold_constant=-2,
table_areas=None, iterations=0, margins=(1.0, 0.5, 0.1), **kwargs):
process_background=False, self.table_area = table_area
line_scale=15,
copy_text=None,
shift_text=["l", "t"],
split_text=False,
flag_size=False,
strip_text="",
line_tol=2,
joint_tol=2,
threshold_blocksize=15,
threshold_constant=-2,
iterations=0,
resolution=300,
backend="ghostscript",
**kwargs,
):
self.table_regions = table_regions
self.table_areas = table_areas
self.process_background = process_background self.process_background = process_background
self.line_scale = line_scale self.line_size_scaling = line_size_scaling
self.copy_text = copy_text self.copy_text = copy_text
self.shift_text = shift_text self.shift_text = shift_text
self.split_text = split_text self.split_text = split_text
self.flag_size = flag_size self.flag_size = flag_size
self.strip_text = strip_text self.line_close_tol = line_close_tol
self.line_tol = line_tol self.joint_close_tol = joint_close_tol
self.joint_tol = joint_tol
self.threshold_blocksize = threshold_blocksize self.threshold_blocksize = threshold_blocksize
self.threshold_constant = threshold_constant self.threshold_constant = threshold_constant
self.iterations = iterations self.iterations = iterations
self.resolution = resolution self.char_margin, self.line_margin, self.word_margin = margins
self.backend = Lattice._get_backend(backend)
@staticmethod
def _get_backend(backend):
def implements_convert():
methods = [
method for method in dir(backend) if method.startswith("__") is False
]
return "convert" in methods
if isinstance(backend, str):
if backend not in BACKENDS.keys():
raise NotImplementedError(
f"Unknown backend '{backend}' specified. Please use either 'poppler' or 'ghostscript'."
)
if backend == "ghostscript":
warnings.warn(
"'ghostscript' will be replaced by 'poppler' as the default image conversion"
" backend in v0.12.0. You can try out 'poppler' with backend='poppler'.",
DeprecationWarning,
)
return BACKENDS[backend]()
else:
if not implements_convert():
raise NotImplementedError(
f"'{backend}' must implement a 'convert' method"
)
return backend
@staticmethod @staticmethod
def _reduce_index(t, idx, shift_text): def _reduce_index(t, idx, shift_text):
@ -187,19 +120,19 @@ class Lattice(BaseParser):
indices = [] indices = []
for r_idx, c_idx, text in idx: for r_idx, c_idx, text in idx:
for d in shift_text: for d in shift_text:
if d == "l": if d == 'l':
if t.cells[r_idx][c_idx].hspan: if t.cells[r_idx][c_idx].hspan:
while not t.cells[r_idx][c_idx].left: while not t.cells[r_idx][c_idx].left:
c_idx -= 1 c_idx -= 1
if d == "r": if d == 'r':
if t.cells[r_idx][c_idx].hspan: if t.cells[r_idx][c_idx].hspan:
while not t.cells[r_idx][c_idx].right: while not t.cells[r_idx][c_idx].right:
c_idx += 1 c_idx += 1
if d == "t": if d == 't':
if t.cells[r_idx][c_idx].vspan: if t.cells[r_idx][c_idx].vspan:
while not t.cells[r_idx][c_idx].top: while not t.cells[r_idx][c_idx].top:
r_idx -= 1 r_idx -= 1
if d == "b": if d == 'b':
if t.cells[r_idx][c_idx].vspan: if t.cells[r_idx][c_idx].vspan:
while not t.cells[r_idx][c_idx].bottom: while not t.cells[r_idx][c_idx].bottom:
r_idx += 1 r_idx += 1
@ -228,37 +161,33 @@ class Lattice(BaseParser):
if f == "h": if f == "h":
for i in range(len(t.cells)): for i in range(len(t.cells)):
for j in range(len(t.cells[i])): for j in range(len(t.cells[i])):
if t.cells[i][j].text.strip() == "": if t.cells[i][j].text.strip() == '':
if t.cells[i][j].hspan and not t.cells[i][j].left: if t.cells[i][j].hspan and not t.cells[i][j].left:
t.cells[i][j].text = t.cells[i][j - 1].text t.cells[i][j].text = t.cells[i][j - 1].text
elif f == "v": elif f == "v":
for i in range(len(t.cells)): for i in range(len(t.cells)):
for j in range(len(t.cells[i])): for j in range(len(t.cells[i])):
if t.cells[i][j].text.strip() == "": if t.cells[i][j].text.strip() == '':
if t.cells[i][j].vspan and not t.cells[i][j].top: if t.cells[i][j].vspan and not t.cells[i][j].top:
t.cells[i][j].text = t.cells[i - 1][j].text t.cells[i][j].text = t.cells[i - 1][j].text
return t return t
def _generate_image(self):
self.imagename = ''.join([self.rootname, '.png'])
gs_call = [
"-q", "-sDEVICE=png16m", "-o", self.imagename, "-r600", self.filename
]
if "ghostscript" in subprocess.check_output(["gs", "-version"]).lower():
gs_call.insert(0, "gs")
else:
gs_call.insert(0, "gsc")
subprocess.call(gs_call, stdout=open(os.devnull, 'w'),
stderr=subprocess.STDOUT)
def _generate_table_bbox(self): def _generate_table_bbox(self):
def scale_areas(areas):
scaled_areas = []
for area in areas:
x1, y1, x2, y2 = area.split(",")
x1 = float(x1)
y1 = float(y1)
x2 = float(x2)
y2 = float(y2)
x1, y1, x2, y2 = scale_pdf((x1, y1, x2, y2), image_scalers)
scaled_areas.append((x1, y1, abs(x2 - x1), abs(y2 - y1)))
return scaled_areas
self.image, self.threshold = adaptive_threshold( self.image, self.threshold = adaptive_threshold(
self.imagename, self.imagename, process_background=self.process_background,
process_background=self.process_background, blocksize=self.threshold_blocksize, c=self.threshold_constant)
blocksize=self.threshold_blocksize,
c=self.threshold_constant,
)
image_width = self.image.shape[1] image_width = self.image.shape[1]
image_height = self.image.shape[0] image_height = self.image.shape[0]
image_width_scaler = image_width / float(self.pdf_width) image_width_scaler = image_width / float(self.pdf_width)
@ -268,110 +197,85 @@ class Lattice(BaseParser):
image_scalers = (image_width_scaler, image_height_scaler, self.pdf_height) image_scalers = (image_width_scaler, image_height_scaler, self.pdf_height)
pdf_scalers = (pdf_width_scaler, pdf_height_scaler, image_height) pdf_scalers = (pdf_width_scaler, pdf_height_scaler, image_height)
if self.table_areas is None: vertical_mask, vertical_segments = find_lines(
regions = None self.threshold, direction='vertical',
if self.table_regions is not None: line_size_scaling=self.line_size_scaling, iterations=self.iterations)
regions = scale_areas(self.table_regions) horizontal_mask, horizontal_segments = find_lines(
self.threshold, direction='horizontal',
line_size_scaling=self.line_size_scaling, iterations=self.iterations)
vertical_mask, vertical_segments = find_lines( if self.table_area is not None:
self.threshold, areas = []
regions=regions, for area in self.table_area:
direction="vertical", x1, y1, x2, y2 = area.split(",")
line_scale=self.line_scale, x1 = float(x1)
iterations=self.iterations, y1 = float(y1)
) x2 = float(x2)
horizontal_mask, horizontal_segments = find_lines( y2 = float(y2)
self.threshold, x1, y1, x2, y2 = scale_pdf((x1, y1, x2, y2), image_scalers)
regions=regions, areas.append((x1, y1, abs(x2 - x1), abs(y2 - y1)))
direction="horizontal", table_bbox = find_table_joints(areas, vertical_mask, horizontal_mask)
line_scale=self.line_scale,
iterations=self.iterations,
)
contours = find_contours(vertical_mask, horizontal_mask)
table_bbox = find_joints(contours, vertical_mask, horizontal_mask)
else: else:
vertical_mask, vertical_segments = find_lines( contours = find_table_contours(vertical_mask, horizontal_mask)
self.threshold, table_bbox = find_table_joints(contours, vertical_mask, horizontal_mask)
direction="vertical",
line_scale=self.line_scale,
iterations=self.iterations,
)
horizontal_mask, horizontal_segments = find_lines(
self.threshold,
direction="horizontal",
line_scale=self.line_scale,
iterations=self.iterations,
)
areas = scale_areas(self.table_areas)
table_bbox = find_joints(areas, vertical_mask, horizontal_mask)
self.table_bbox_unscaled = copy.deepcopy(table_bbox) self.table_bbox_unscaled = copy.deepcopy(table_bbox)
self.table_bbox, self.vertical_segments, self.horizontal_segments = scale_image( self.table_bbox, self.vertical_segments, self.horizontal_segments = scale_image(
table_bbox, vertical_segments, horizontal_segments, pdf_scalers table_bbox, vertical_segments, horizontal_segments, pdf_scalers)
)
def _generate_columns_and_rows(self, table_idx, tk): def _generate_columns_and_rows(self, table_idx, tk):
# select elements which lie within table_bbox # select elements which lie within table_bbox
t_bbox = {} t_bbox = {}
v_s, h_s = segments_in_bbox( v_s, h_s = segments_in_bbox(
tk, self.vertical_segments, self.horizontal_segments tk, self.vertical_segments, self.horizontal_segments)
) t_bbox['horizontal'] = text_in_bbox(tk, self.horizontal_text)
t_bbox["horizontal"] = text_in_bbox(tk, self.horizontal_text) t_bbox['vertical'] = text_in_bbox(tk, self.vertical_text)
t_bbox["vertical"] = text_in_bbox(tk, self.vertical_text)
t_bbox["horizontal"].sort(key=lambda x: (-x.y0, x.x0))
t_bbox["vertical"].sort(key=lambda x: (x.x0, -x.y0))
self.t_bbox = t_bbox self.t_bbox = t_bbox
for direction in t_bbox:
t_bbox[direction].sort(key=lambda x: (-x.y0, x.x0))
cols, rows = zip(*self.table_bbox[tk]) cols, rows = zip(*self.table_bbox[tk])
cols, rows = list(cols), list(rows) cols, rows = list(cols), list(rows)
cols.extend([tk[0], tk[2]]) cols.extend([tk[0], tk[2]])
rows.extend([tk[1], tk[3]]) rows.extend([tk[1], tk[3]])
# sort horizontal and vertical segments # sort horizontal and vertical segments
cols = merge_close_lines(sorted(cols), line_tol=self.line_tol) cols = merge_close_lines(
rows = merge_close_lines(sorted(rows, reverse=True), line_tol=self.line_tol) sorted(cols), line_close_tol=self.line_close_tol)
rows = merge_close_lines(
sorted(rows, reverse=True), line_close_tol=self.line_close_tol)
# make grid using x and y coord of shortlisted rows and cols # make grid using x and y coord of shortlisted rows and cols
cols = [(cols[i], cols[i + 1]) for i in range(0, len(cols) - 1)] cols = [(cols[i], cols[i + 1])
rows = [(rows[i], rows[i + 1]) for i in range(0, len(rows) - 1)] for i in range(0, len(cols) - 1)]
rows = [(rows[i], rows[i + 1])
for i in range(0, len(rows) - 1)]
return cols, rows, v_s, h_s return cols, rows, v_s, h_s
def _generate_table(self, table_idx, cols, rows, **kwargs): def _generate_table(self, table_idx, cols, rows, **kwargs):
v_s = kwargs.get("v_s") v_s = kwargs.get('v_s')
h_s = kwargs.get("h_s") h_s = kwargs.get('h_s')
if v_s is None or h_s is None: if v_s is None or h_s is None:
raise ValueError("No segments found on {}".format(self.rootname)) raise ValueError('No segments found on {}'.format(self.rootname))
table = Table(cols, rows) table = Table(cols, rows)
# set table edges to True using ver+hor lines # set table edges to True using ver+hor lines
table = table.set_edges(v_s, h_s, joint_tol=self.joint_tol) table = table.set_edges(v_s, h_s, joint_close_tol=self.joint_close_tol)
# set table border edges to True # set table border edges to True
table = table.set_border() table = table.set_border()
# set spanning cells to True # set spanning cells to True
table = table.set_span() table = table.set_span()
pos_errors = [] pos_errors = []
# TODO: have a single list in place of two directional ones? for direction in self.t_bbox:
# sorted on x-coordinate based on reading order i.e. LTR or RTL
for direction in ["vertical", "horizontal"]:
for t in self.t_bbox[direction]: for t in self.t_bbox[direction]:
indices, error = get_table_index( indices, error = get_table_index(
table, table, t, direction, split_text=self.split_text,
t, flag_size=self.flag_size)
direction,
split_text=self.split_text,
flag_size=self.flag_size,
strip_text=self.strip_text,
)
if indices[:2] != (-1, -1): if indices[:2] != (-1, -1):
pos_errors.append(error) pos_errors.append(error)
indices = Lattice._reduce_index( indices = Lattice._reduce_index(table, indices, shift_text=self.shift_text)
table, indices, shift_text=self.shift_text
)
for r_idx, c_idx, text in indices: for r_idx, c_idx, text in indices:
table.cells[r_idx][c_idx].text = text table.cells[r_idx][c_idx].text = text
accuracy = compute_accuracy([[100, pos_errors]]) accuracy = compute_accuracy([[100, pos_errors]])
@ -380,15 +284,16 @@ class Lattice(BaseParser):
table = Lattice._copy_spanning_text(table, copy_text=self.copy_text) table = Lattice._copy_spanning_text(table, copy_text=self.copy_text)
data = table.data data = table.data
data = encode_(data)
table.df = pd.DataFrame(data) table.df = pd.DataFrame(data)
table.shape = table.df.shape table.shape = table.df.shape
whitespace = compute_whitespace(data) whitespace = compute_whitespace(data)
table.flavor = "lattice" table.flavor = 'lattice'
table.accuracy = accuracy table.accuracy = accuracy
table.whitespace = whitespace table.whitespace = whitespace
table.order = table_idx + 1 table.order = table_idx + 1
table.page = int(os.path.basename(self.rootname).replace("page-", "")) table.page = int(os.path.basename(self.rootname).replace('page-', ''))
# for plotting # for plotting
_text = [] _text = []
@ -397,39 +302,27 @@ class Lattice(BaseParser):
table._text = _text table._text = _text
table._image = (self.image, self.table_bbox_unscaled) table._image = (self.image, self.table_bbox_unscaled)
table._segments = (self.vertical_segments, self.horizontal_segments) table._segments = (self.vertical_segments, self.horizontal_segments)
table._textedges = None
return table return table
def extract_tables(self, filename, suppress_stdout=False, layout_kwargs={}): def extract_tables(self, filename):
self._generate_layout(filename, layout_kwargs) logger.info('Processing {}'.format(os.path.basename(filename)))
if not suppress_stdout: self._generate_layout(filename)
logger.info("Processing {}".format(os.path.basename(self.rootname)))
if not self.horizontal_text: if not self.horizontal_text:
if self.images: logger.info("No tables found on {}".format(
warnings.warn( os.path.basename(self.rootname)))
"{} is image-based, camelot only works on"
" text-based pages.".format(os.path.basename(self.rootname))
)
else:
warnings.warn(
"No tables found on {}".format(os.path.basename(self.rootname))
)
return [] return []
self.backend.convert(self.filename, self.imagename) self._generate_image()
self._generate_table_bbox() self._generate_table_bbox()
_tables = [] _tables = []
# sort tables based on y-coord # sort tables based on y-coord
for table_idx, tk in enumerate( for table_idx, tk in enumerate(sorted(self.table_bbox.keys(),
sorted(self.table_bbox.keys(), key=lambda x: x[1], reverse=True) key=lambda x: x[1], reverse=True)):
):
cols, rows, v_s, h_s = self._generate_columns_and_rows(table_idx, tk) cols, rows, v_s, h_s = self._generate_columns_and_rows(table_idx, tk)
table = self._generate_table(table_idx, cols, rows, v_s=v_s, h_s=h_s) table = self._generate_table(table_idx, cols, rows, v_s=v_s, h_s=h_s)
table._bbox = tk
_tables.append(table) _tables.append(table)
return _tables return _tables

276
camelot/parsers/stream.py
View File

@ -1,18 +1,19 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
from __future__ import division
import os import os
import logging import logging
import warnings
import numpy as np import numpy as np
import pandas as pd import pandas as pd
from .base import BaseParser from .base import BaseParser
from ..core import TextEdges, Table from ..core import Table
from ..utils import text_in_bbox, get_table_index, compute_accuracy, compute_whitespace from ..utils import (text_in_bbox, get_table_index, compute_accuracy,
compute_whitespace, setup_logging, encode_)
logger = logging.getLogger("camelot") logger = setup_logging(__name__)
class Stream(BaseParser): class Stream(BaseParser):
@ -24,11 +25,7 @@ class Stream(BaseParser):
Parameters Parameters
---------- ----------
table_regions : list, optional (default: None) table_area : list, optional (default: None)
List of page regions that may contain tables of the form x1,y1,x2,y2
where (x1, y1) -> left-top and (x2, y2) -> right-bottom
in PDF coordinate space.
table_areas : list, optional (default: None)
List of table area strings of the form x1,y1,x2,y2 List of table area strings of the form x1,y1,x2,y2
where (x1, y1) -> left-top and (x2, y2) -> right-bottom where (x1, y1) -> left-top and (x2, y2) -> right-bottom
in PDF coordinate space. in PDF coordinate space.
@ -40,43 +37,29 @@ class Stream(BaseParser):
flag_size : bool, optional (default: False) flag_size : bool, optional (default: False)
Flag text based on font size. Useful to detect Flag text based on font size. Useful to detect
super/subscripts. Adds <s></s> around flagged text. super/subscripts. Adds <s></s> around flagged text.
strip_text : str, optional (default: '') row_close_tol : int, optional (default: 2)
Characters that should be stripped from a string before
assigning it to a cell.
edge_tol : int, optional (default: 50)
Tolerance parameter for extending textedges vertically.
row_tol : int, optional (default: 2)
Tolerance parameter used to combine text vertically, Tolerance parameter used to combine text vertically,
to generate rows. to generate rows.
column_tol : int, optional (default: 0) col_close_tol : int, optional (default: 0)
Tolerance parameter used to combine text horizontally, Tolerance parameter used to combine text horizontally,
to generate columns. to generate columns.
margins : tuple, optional (default: (1.0, 0.5, 0.1))
PDFMiner char_margin, line_margin and word_margin.
For more information, refer `PDFMiner docs <https://euske.github.io/pdfminer/>`_.
""" """
def __init__(self, table_area=None, columns=None, split_text=False,
def __init__( flag_size=False, row_close_tol=2, col_close_tol=0,
self, margins=(1.0, 0.5, 0.1), **kwargs):
table_regions=None, self.table_area = table_area
table_areas=None,
columns=None,
split_text=False,
flag_size=False,
strip_text="",
edge_tol=50,
row_tol=2,
column_tol=0,
**kwargs,
):
self.table_regions = table_regions
self.table_areas = table_areas
self.columns = columns self.columns = columns
self._validate_columns() self._validate_columns()
self.split_text = split_text self.split_text = split_text
self.flag_size = flag_size self.flag_size = flag_size
self.strip_text = strip_text self.row_close_tol = row_close_tol
self.edge_tol = edge_tol self.col_close_tol = col_close_tol
self.row_tol = row_tol self.char_margin, self.line_margin, self.word_margin = margins
self.column_tol = column_tol
@staticmethod @staticmethod
def _text_bbox(t_bbox): def _text_bbox(t_bbox):
@ -102,7 +85,7 @@ class Stream(BaseParser):
return text_bbox return text_bbox
@staticmethod @staticmethod
def _group_rows(text, row_tol=2): def _group_rows(text, row_close_tol=2):
"""Groups PDFMiner text objects into rows vertically """Groups PDFMiner text objects into rows vertically
within a tolerance. within a tolerance.
@ -110,7 +93,7 @@ class Stream(BaseParser):
---------- ----------
text : list text : list
List of PDFMiner text objects. List of PDFMiner text objects.
row_tol : int, optional (default: 2) row_close_tol : int, optional (default: 2)
Returns Returns
------- -------
@ -121,25 +104,22 @@ class Stream(BaseParser):
row_y = 0 row_y = 0
rows = [] rows = []
temp = [] temp = []
for t in text: for t in text:
# is checking for upright necessary? # is checking for upright necessary?
# if t.get_text().strip() and all([obj.upright for obj in t._objs if # if t.get_text().strip() and all([obj.upright for obj in t._objs if
# type(obj) is LTChar]): # type(obj) is LTChar]):
if t.get_text().strip(): if t.get_text().strip():
if not np.isclose(row_y, t.y0, atol=row_tol): if not np.isclose(row_y, t.y0, atol=row_close_tol):
rows.append(sorted(temp, key=lambda t: t.x0)) rows.append(sorted(temp, key=lambda t: t.x0))
temp = [] temp = []
row_y = t.y0 row_y = t.y0
temp.append(t) temp.append(t)
rows.append(sorted(temp, key=lambda t: t.x0)) rows.append(sorted(temp, key=lambda t: t.x0))
if len(rows) > 1: __ = rows.pop(0) # hacky
__ = rows.pop(0) # TODO: hacky
return rows return rows
@staticmethod @staticmethod
def _merge_columns(l, column_tol=0): def _merge_columns(l, col_close_tol=0):
"""Merges column boundaries horizontally if they overlap """Merges column boundaries horizontally if they overlap
or lie within a tolerance. or lie within a tolerance.
@ -147,7 +127,7 @@ class Stream(BaseParser):
---------- ----------
l : list l : list
List of column x-coordinate tuples. List of column x-coordinate tuples.
column_tol : int, optional (default: 0) col_close_tol : int, optional (default: 0)
Returns Returns
------- -------
@ -161,18 +141,17 @@ class Stream(BaseParser):
merged.append(higher) merged.append(higher)
else: else:
lower = merged[-1] lower = merged[-1]
if column_tol >= 0: if col_close_tol >= 0:
if higher[0] <= lower[1] or np.isclose( if (higher[0] <= lower[1] or
higher[0], lower[1], atol=column_tol np.isclose(higher[0], lower[1], atol=col_close_tol)):
):
upper_bound = max(lower[1], higher[1]) upper_bound = max(lower[1], higher[1])
lower_bound = min(lower[0], higher[0]) lower_bound = min(lower[0], higher[0])
merged[-1] = (lower_bound, upper_bound) merged[-1] = (lower_bound, upper_bound)
else: else:
merged.append(higher) merged.append(higher)
elif column_tol < 0: elif col_close_tol < 0:
if higher[0] <= lower[1]: if higher[0] <= lower[1]:
if np.isclose(higher[0], lower[1], atol=abs(column_tol)): if np.isclose(higher[0], lower[1], atol=abs(col_close_tol)):
merged.append(higher) merged.append(higher)
else: else:
upper_bound = max(lower[1], higher[1]) upper_bound = max(lower[1], higher[1])
@ -199,18 +178,17 @@ class Stream(BaseParser):
List of continuous row y-coordinate tuples. List of continuous row y-coordinate tuples.
""" """
row_mids = [ row_mids = [sum([(t.y0 + t.y1) / 2 for t in r]) / len(r)
sum([(t.y0 + t.y1) / 2 for t in r]) / len(r) if len(r) > 0 else 0 if len(r) > 0 else 0 for r in rows_grouped]
for r in rows_grouped
]
rows = [(row_mids[i] + row_mids[i - 1]) / 2 for i in range(1, len(row_mids))] rows = [(row_mids[i] + row_mids[i - 1]) / 2 for i in range(1, len(row_mids))]
rows.insert(0, text_y_max) rows.insert(0, text_y_max)
rows.append(text_y_min) rows.append(text_y_min)
rows = [(rows[i], rows[i + 1]) for i in range(0, len(rows) - 1)] rows = [(rows[i], rows[i + 1])
for i in range(0, len(rows) - 1)]
return rows return rows
@staticmethod @staticmethod
def _add_columns(cols, text, row_tol): def _add_columns(cols, text, row_close_tol):
"""Adds columns to existing list by taking into account """Adds columns to existing list by taking into account
the text that lies outside the current column x-coordinates. the text that lies outside the current column x-coordinates.
@ -229,11 +207,10 @@ class Stream(BaseParser):
""" """
if text: if text:
text = Stream._group_rows(text, row_tol=row_tol) text = Stream._group_rows(text, row_close_tol=row_close_tol)
elements = [len(r) for r in text] elements = [len(r) for r in text]
new_cols = [ new_cols = [(t.x0, t.x1)
(t.x0, t.x1) for r in text if len(r) == max(elements) for t in r for r in text if len(r) == max(elements) for t in r]
]
cols.extend(Stream._merge_columns(sorted(new_cols))) cols.extend(Stream._merge_columns(sorted(new_cols)))
return cols return cols
@ -258,80 +235,42 @@ class Stream(BaseParser):
cols = [(cols[i][0] + cols[i - 1][1]) / 2 for i in range(1, len(cols))] cols = [(cols[i][0] + cols[i - 1][1]) / 2 for i in range(1, len(cols))]
cols.insert(0, text_x_min) cols.insert(0, text_x_min)
cols.append(text_x_max) cols.append(text_x_max)
cols = [(cols[i], cols[i + 1]) for i in range(0, len(cols) - 1)] cols = [(cols[i], cols[i + 1])
for i in range(0, len(cols) - 1)]
return cols return cols
def _validate_columns(self): def _validate_columns(self):
if self.table_areas is not None and self.columns is not None: if self.table_area is not None and self.columns is not None:
if len(self.table_areas) != len(self.columns): if len(self.table_area) != len(self.columns):
raise ValueError("Length of table_areas and columns" " should be equal") raise ValueError("Length of table_area and columns"
" should be equal")
def _nurminen_table_detection(self, textlines):
"""A general implementation of the table detection algorithm
described by Anssi Nurminen's master's thesis.
Link: https://dspace.cc.tut.fi/dpub/bitstream/handle/123456789/21520/Nurminen.pdf?sequence=3
Assumes that tables are situated relatively far apart
vertically.
"""
# TODO: add support for arabic text #141
# sort textlines in reading order
textlines.sort(key=lambda x: (-x.y0, x.x0))
textedges = TextEdges(edge_tol=self.edge_tol)
# generate left, middle and right textedges
textedges.generate(textlines)
# select relevant edges
relevant_textedges = textedges.get_relevant()
self.textedges.extend(relevant_textedges)
# guess table areas using textlines and relevant edges
table_bbox = textedges.get_table_areas(textlines, relevant_textedges)
# treat whole page as table area if no table areas found
if not len(table_bbox):
table_bbox = {(0, 0, self.pdf_width, self.pdf_height): None}
return table_bbox
def _generate_table_bbox(self): def _generate_table_bbox(self):
self.textedges = [] if self.table_area is not None:
if self.table_areas is None:
hor_text = self.horizontal_text
if self.table_regions is not None:
# filter horizontal text
hor_text = []
for region in self.table_regions:
x1, y1, x2, y2 = region.split(",")
x1 = float(x1)
y1 = float(y1)
x2 = float(x2)
y2 = float(y2)
region_text = text_in_bbox((x1, y2, x2, y1), self.horizontal_text)
hor_text.extend(region_text)
# find tables based on nurminen's detection algorithm
table_bbox = self._nurminen_table_detection(hor_text)
else:
table_bbox = {} table_bbox = {}
for area in self.table_areas: for area in self.table_area:
x1, y1, x2, y2 = area.split(",") x1, y1, x2, y2 = area.split(",")
x1 = float(x1) x1 = float(x1)
y1 = float(y1) y1 = float(y1)
x2 = float(x2) x2 = float(x2)
y2 = float(y2) y2 = float(y2)
table_bbox[(x1, y2, x2, y1)] = None table_bbox[(x1, y2, x2, y1)] = None
else:
table_bbox = {(0, 0, self.pdf_width, self.pdf_height): None}
self.table_bbox = table_bbox self.table_bbox = table_bbox
def _generate_columns_and_rows(self, table_idx, tk): def _generate_columns_and_rows(self, table_idx, tk):
# select elements which lie within table_bbox # select elements which lie within table_bbox
t_bbox = {} t_bbox = {}
t_bbox["horizontal"] = text_in_bbox(tk, self.horizontal_text) t_bbox['horizontal'] = text_in_bbox(tk, self.horizontal_text)
t_bbox["vertical"] = text_in_bbox(tk, self.vertical_text) t_bbox['vertical'] = text_in_bbox(tk, self.vertical_text)
t_bbox["horizontal"].sort(key=lambda x: (-x.y0, x.x0))
t_bbox["vertical"].sort(key=lambda x: (x.x0, -x.y0))
self.t_bbox = t_bbox self.t_bbox = t_bbox
for direction in self.t_bbox:
self.t_bbox[direction].sort(key=lambda x: (-x.y0, x.x0))
text_x_min, text_y_min, text_x_max, text_y_max = self._text_bbox(self.t_bbox) text_x_min, text_y_min, text_x_max, text_y_max = self._text_bbox(self.t_bbox)
rows_grouped = self._group_rows(self.t_bbox["horizontal"], row_tol=self.row_tol) rows_grouped = self._group_rows(self.t_bbox['horizontal'], row_close_tol=self.row_close_tol)
rows = self._join_rows(rows_grouped, text_y_max, text_y_min) rows = self._join_rows(rows_grouped, text_y_max, text_y_min)
elements = [len(r) for r in rows_grouped] elements = [len(r) for r in rows_grouped]
@ -340,74 +279,43 @@ class Stream(BaseParser):
# take (0, pdf_width) by default # take (0, pdf_width) by default
# similar to else condition # similar to else condition
# len can't be 1 # len can't be 1
cols = self.columns[table_idx].split(",") cols = self.columns[table_idx].split(',')
cols = [float(c) for c in cols] cols = [float(c) for c in cols]
cols.insert(0, text_x_min) cols.insert(0, text_x_min)
cols.append(text_x_max) cols.append(text_x_max)
cols = [(cols[i], cols[i + 1]) for i in range(0, len(cols) - 1)] cols = [(cols[i], cols[i + 1]) for i in range(0, len(cols) - 1)]
else: else:
# calculate mode of the list of number of elements in ncols = max(set(elements), key=elements.count)
# each row to guess the number of columns if ncols == 1:
if not len(elements): logger.info("No tables found on {}".format(
cols = [(text_x_min, text_x_max)] os.path.basename(self.rootname)))
else: cols = [(t.x0, t.x1) for r in rows_grouped if len(r) == ncols for t in r]
ncols = max(set(elements), key=elements.count) cols = self._merge_columns(sorted(cols), col_close_tol=self.col_close_tol)
if ncols == 1: inner_text = []
# if mode is 1, the page usually contains not tables for i in range(1, len(cols)):
# but there can be cases where the list can be skewed, left = cols[i - 1][1]
# try to remove all 1s from list in this case and right = cols[i][0]
# see if the list contains elements, if yes, then use inner_text.extend([t for direction in self.t_bbox
# the mode after removing 1s for t in self.t_bbox[direction]
elements = list(filter(lambda x: x != 1, elements)) if t.x0 > left and t.x1 < right])
if len(elements): outer_text = [t for direction in self.t_bbox
ncols = max(set(elements), key=elements.count)
else:
warnings.warn(f"No tables found in table area {table_idx + 1}")
cols = [
(t.x0, t.x1) for r in rows_grouped if len(r) == ncols for t in r
]
cols = self._merge_columns(sorted(cols), column_tol=self.column_tol)
inner_text = []
for i in range(1, len(cols)):
left = cols[i - 1][1]
right = cols[i][0]
inner_text.extend(
[
t
for direction in self.t_bbox
for t in self.t_bbox[direction] for t in self.t_bbox[direction]
if t.x0 > left and t.x1 < right if t.x0 > cols[-1][1] or t.x1 < cols[0][0]]
] inner_text.extend(outer_text)
) cols = self._add_columns(cols, inner_text, self.row_close_tol)
outer_text = [ cols = self._join_columns(cols, text_x_min, text_x_max)
t
for direction in self.t_bbox
for t in self.t_bbox[direction]
if t.x0 > cols[-1][1] or t.x1 < cols[0][0]
]
inner_text.extend(outer_text)
cols = self._add_columns(cols, inner_text, self.row_tol)
cols = self._join_columns(cols, text_x_min, text_x_max)
return cols, rows return cols, rows
def _generate_table(self, table_idx, cols, rows, **kwargs): def _generate_table(self, table_idx, cols, rows, **kwargs):
table = Table(cols, rows) table = Table(cols, rows)
table = table.set_all_edges() table = table.set_all_edges()
pos_errors = [] pos_errors = []
# TODO: have a single list in place of two directional ones? for direction in self.t_bbox:
# sorted on x-coordinate based on reading order i.e. LTR or RTL
for direction in ["vertical", "horizontal"]:
for t in self.t_bbox[direction]: for t in self.t_bbox[direction]:
indices, error = get_table_index( indices, error = get_table_index(
table, table, t, direction, split_text=self.split_text,
t, flag_size=self.flag_size)
direction,
split_text=self.split_text,
flag_size=self.flag_size,
strip_text=self.strip_text,
)
if indices[:2] != (-1, -1): if indices[:2] != (-1, -1):
pos_errors.append(error) pos_errors.append(error)
for r_idx, c_idx, text in indices: for r_idx, c_idx, text in indices:
@ -415,15 +323,16 @@ class Stream(BaseParser):
accuracy = compute_accuracy([[100, pos_errors]]) accuracy = compute_accuracy([[100, pos_errors]])
data = table.data data = table.data
data = encode_(data)
table.df = pd.DataFrame(data) table.df = pd.DataFrame(data)
table.shape = table.df.shape table.shape = table.df.shape
whitespace = compute_whitespace(data) whitespace = compute_whitespace(data)
table.flavor = "stream" table.flavor = 'stream'
table.accuracy = accuracy table.accuracy = accuracy
table.whitespace = whitespace table.whitespace = whitespace
table.order = table_idx + 1 table.order = table_idx + 1
table.page = int(os.path.basename(self.rootname).replace("page-", "")) table.page = int(os.path.basename(self.rootname).replace('page-', ''))
# for plotting # for plotting
_text = [] _text = []
@ -432,37 +341,26 @@ class Stream(BaseParser):
table._text = _text table._text = _text
table._image = None table._image = None
table._segments = None table._segments = None
table._textedges = self.textedges
return table return table
def extract_tables(self, filename, suppress_stdout=False, layout_kwargs={}): def extract_tables(self, filename):
self._generate_layout(filename, layout_kwargs) logger.info('Processing {}'.format(os.path.basename(filename)))
base_filename = os.path.basename(self.rootname) self._generate_layout(filename)
if not suppress_stdout:
logger.info(f"Processing {base_filename}")
if not self.horizontal_text: if not self.horizontal_text:
if self.images: logger.info("No tables found on {}".format(
warnings.warn( os.path.basename(self.rootname)))
f"{base_filename} is image-based, camelot only works on"
" text-based pages."
)
else:
warnings.warn(f"No tables found on {base_filename}")
return [] return []
self._generate_table_bbox() self._generate_table_bbox()
_tables = [] _tables = []
# sort tables based on y-coord # sort tables based on y-coord
for table_idx, tk in enumerate( for table_idx, tk in enumerate(sorted(self.table_bbox.keys(),
sorted(self.table_bbox.keys(), key=lambda x: x[1], reverse=True) key=lambda x: x[1], reverse=True)):
):
cols, rows = self._generate_columns_and_rows(table_idx, tk) cols, rows = self._generate_columns_and_rows(table_idx, tk)
table = self._generate_table(table_idx, cols, rows) table = self._generate_table(table_idx, cols, rows)
table._bbox = tk
_tables.append(table) _tables.append(table)
return _tables return _tables

293
camelot/plotting.py
View File

@ -1,225 +1,108 @@
# -*- coding: utf-8 -*- import cv2
import matplotlib.pyplot as plt
try: import matplotlib.patches as patches
import matplotlib.pyplot as plt
import matplotlib.patches as patches
except ImportError:
_HAS_MPL = False
else:
_HAS_MPL = True
class PlotMethods(object): def plot_text(text):
def __call__(self, table, kind="text", filename=None): """Generates a plot for all text present on the PDF page.
"""Plot elements found on PDF page based on kind
specified, useful for debugging and playing with different
parameters to get the best output.
Parameters Parameters
---------- ----------
table: camelot.core.Table text : list
A Camelot Table.
kind : str, optional (default: 'text')
{'text', 'grid', 'contour', 'joint', 'line'}
The element type for which a plot should be generated.
filepath: str, optional (default: None)
Absolute path for saving the generated plot.
Returns """
------- fig = plt.figure()
fig : matplotlib.fig.Figure ax = fig.add_subplot(111, aspect='equal')
xs, ys = [], []
""" for t in text:
if not _HAS_MPL: xs.extend([t[0], t[2]])
raise ImportError("matplotlib is required for plotting.") ys.extend([t[1], t[3]])
ax.add_patch(
if table.flavor == "lattice" and kind in ["textedge"]: patches.Rectangle(
raise NotImplementedError(f"Lattice flavor does not support kind='{kind}'") (t[0], t[1]),
elif table.flavor == "stream" and kind in ["joint", "line"]: t[2] - t[0],
raise NotImplementedError(f"Stream flavor does not support kind='{kind}'") t[3] - t[1]
plot_method = getattr(self, kind)
fig = plot_method(table)
if filename is not None:
fig.savefig(filename)
return None
return fig
def text(self, table):
"""Generates a plot for all text elements present
on the PDF page.
Parameters
----------
table : camelot.core.Table
Returns
-------
fig : matplotlib.fig.Figure
"""
fig = plt.figure()
ax = fig.add_subplot(111, aspect="equal")
xs, ys = [], []
for t in table._text:
xs.extend([t[0], t[2]])
ys.extend([t[1], t[3]])
ax.add_patch(patches.Rectangle((t[0], t[1]), t[2] - t[0], t[3] - t[1]))
ax.set_xlim(min(xs) - 10, max(xs) + 10)
ax.set_ylim(min(ys) - 10, max(ys) + 10)
return fig
def grid(self, table):
"""Generates a plot for the detected table grids
on the PDF page.
Parameters
----------
table : camelot.core.Table
Returns
-------
fig : matplotlib.fig.Figure
"""
fig = plt.figure()
ax = fig.add_subplot(111, aspect="equal")
for row in table.cells:
for cell in row:
if cell.left:
ax.plot([cell.lb[0], cell.lt[0]], [cell.lb[1], cell.lt[1]])
if cell.right:
ax.plot([cell.rb[0], cell.rt[0]], [cell.rb[1], cell.rt[1]])
if cell.top:
ax.plot([cell.lt[0], cell.rt[0]], [cell.lt[1], cell.rt[1]])
if cell.bottom:
ax.plot([cell.lb[0], cell.rb[0]], [cell.lb[1], cell.rb[1]])
return fig
def contour(self, table):
"""Generates a plot for all table boundaries present
on the PDF page.
Parameters
----------
table : camelot.core.Table
Returns
-------
fig : matplotlib.fig.Figure
"""
try:
img, table_bbox = table._image
_FOR_LATTICE = True
except TypeError:
img, table_bbox = (None, {table._bbox: None})
_FOR_LATTICE = False
fig = plt.figure()
ax = fig.add_subplot(111, aspect="equal")
xs, ys = [], []
if not _FOR_LATTICE:
for t in table._text:
xs.extend([t[0], t[2]])
ys.extend([t[1], t[3]])
ax.add_patch(
patches.Rectangle(
(t[0], t[1]), t[2] - t[0], t[3] - t[1], color="blue"
)
)
for t in table_bbox.keys():
ax.add_patch(
patches.Rectangle(
(t[0], t[1]), t[2] - t[0], t[3] - t[1], fill=False, color="red"
)
) )
if not _FOR_LATTICE: )
xs.extend([t[0], t[2]]) ax.set_xlim(min(xs) - 10, max(xs) + 10)
ys.extend([t[1], t[3]]) ax.set_ylim(min(ys) - 10, max(ys) + 10)
ax.set_xlim(min(xs) - 10, max(xs) + 10) plt.show()
ax.set_ylim(min(ys) - 10, max(ys) + 10)
if _FOR_LATTICE:
ax.imshow(img)
return fig
def textedge(self, table): def plot_table(table):
"""Generates a plot for relevant textedges. """Generates a plot for the table.
Parameters Parameters
---------- ----------
table : camelot.core.Table table : camelot.core.Table
Returns """
------- for row in table.cells:
fig : matplotlib.fig.Figure for cell in row:
if cell.left:
plt.plot([cell.lb[0], cell.lt[0]],
[cell.lb[1], cell.lt[1]])
if cell.right:
plt.plot([cell.rb[0], cell.rt[0]],
[cell.rb[1], cell.rt[1]])
if cell.top:
plt.plot([cell.lt[0], cell.rt[0]],
[cell.lt[1], cell.rt[1]])
if cell.bottom:
plt.plot([cell.lb[0], cell.rb[0]],
[cell.lb[1], cell.rb[1]])
plt.show()
"""
fig = plt.figure()
ax = fig.add_subplot(111, aspect="equal")
xs, ys = [], []
for t in table._text:
xs.extend([t[0], t[2]])
ys.extend([t[1], t[3]])
ax.add_patch(
patches.Rectangle((t[0], t[1]), t[2] - t[0], t[3] - t[1], color="blue")
)
ax.set_xlim(min(xs) - 10, max(xs) + 10)
ax.set_ylim(min(ys) - 10, max(ys) + 10)
for te in table._textedges: def plot_contour(image):
ax.plot([te.x, te.x], [te.y0, te.y1]) """Generates a plot for all table boundaries present on the
PDF page.
return fig Parameters
----------
image : tuple
def joint(self, table): """
"""Generates a plot for all line intersections present img, table_bbox = image
on the PDF page. for t in table_bbox.keys():
cv2.rectangle(img, (t[0], t[1]),
(t[2], t[3]), (255, 0, 0), 20)
plt.imshow(img)
plt.show()
Parameters
----------
table : camelot.core.Table
Returns def plot_joint(image):
------- """Generates a plot for all line intersections present on the
fig : matplotlib.fig.Figure PDF page.
""" Parameters
img, table_bbox = table._image ----------
fig = plt.figure() image : tuple
ax = fig.add_subplot(111, aspect="equal")
x_coord = []
y_coord = []
for k in table_bbox.keys():
for coord in table_bbox[k]:
x_coord.append(coord[0])
y_coord.append(coord[1])
ax.plot(x_coord, y_coord, "ro")
ax.imshow(img)
return fig
def line(self, table): """
"""Generates a plot for all line segments present img, table_bbox = image
on the PDF page. x_coord = []
y_coord = []
for k in table_bbox.keys():
for coord in table_bbox[k]:
x_coord.append(coord[0])
y_coord.append(coord[1])
plt.plot(x_coord, y_coord, 'ro')
plt.imshow(img)
plt.show()
Parameters
----------
table : camelot.core.Table
Returns def plot_line(segments):
------- """Generates a plot for all line segments present on the PDF page.
fig : matplotlib.fig.Figure
""" Parameters
fig = plt.figure() ----------
ax = fig.add_subplot(111, aspect="equal") segments : tuple
vertical, horizontal = table._segments
for v in vertical: """
ax.plot([v[0], v[2]], [v[1], v[3]]) vertical, horizontal = segments
for h in horizontal: for v in vertical:
ax.plot([h[0], h[2]], [h[1], h[3]]) plt.plot([v[0], v[2]], [v[1], v[3]])
return fig for h in horizontal:
plt.plot([h[0], h[2]], [h[1], h[3]])
plt.show()

659
camelot/utils.py
View File

@ -1,129 +1,62 @@
# -*- coding: utf-8 -*- from __future__ import division
import os import os
import re
import random
import shutil import shutil
import string import logging
import tempfile import tempfile
import warnings
from itertools import groupby from itertools import groupby
from operator import itemgetter from operator import itemgetter
import numpy as np import numpy as np
from pdfminer.pdfparser import PDFParser from pdfminer.pdfparser import PDFParser
from pdfminer.pdfdocument import PDFDocument from pdfminer.pdfdocument import PDFDocument
from pdfminer.pdfpage import PDFPage from pdfminer.pdfpage import PDFPage
from pdfminer.pdfpage import PDFTextExtractionNotAllowed from pdfminer.pdfpage import PDFTextExtractionNotAllowed
from pdfminer.pdfinterp import PDFResourceManager from pdfminer.pdfinterp import PDFResourceManager
from pdfminer.pdfinterp import PDFPageInterpreter from pdfminer.pdfinterp import PDFPageInterpreter
from pdfminer.pdfdevice import PDFDevice
from pdfminer.converter import PDFPageAggregator from pdfminer.converter import PDFPageAggregator
from pdfminer.layout import ( from pdfminer.layout import (LAParams, LTAnno, LTChar, LTTextLineHorizontal,
LAParams, LTTextLineVertical)
LTAnno,
LTChar,
LTTextLineHorizontal,
LTTextLineVertical,
LTImage,
)
from urllib.request import Request, urlopen
from urllib.parse import urlparse as parse_url
from urllib.parse import uses_relative, uses_netloc, uses_params
_VALID_URLS = set(uses_relative + uses_netloc + uses_params) stream_kwargs = [
_VALID_URLS.discard("") 'columns',
'row_close_tol',
'col_close_tol'
# https://github.com/pandas-dev/pandas/blob/master/pandas/io/common.py ]
def is_url(url):
"""Check to see if a URL has a valid protocol.
Parameters
----------
url : str or unicode
Returns
-------
isurl : bool
If url has a valid protocol return True otherwise False.
"""
try:
return parse_url(url).scheme in _VALID_URLS
except Exception:
return False
def random_string(length):
ret = ""
while length:
ret += random.choice(
string.digits + string.ascii_lowercase + string.ascii_uppercase
)
length -= 1
return ret
def download_url(url):
"""Download file from specified URL.
Parameters
----------
url : str or unicode
Returns
-------
filepath : str or unicode
Temporary filepath.
"""
filename = f"{random_string(6)}.pdf"
with tempfile.NamedTemporaryFile("wb", delete=False) as f:
headers = {"User-Agent": "Mozilla/5.0"}
request = Request(url, None, headers)
obj = urlopen(request)
content_type = obj.info().get_content_type()
if content_type != "application/pdf":
raise NotImplementedError("File format not supported")
f.write(obj.read())
filepath = os.path.join(os.path.dirname(f.name), filename)
shutil.move(f.name, filepath)
return filepath
stream_kwargs = ["columns", "edge_tol", "row_tol", "column_tol"]
lattice_kwargs = [ lattice_kwargs = [
"process_background", 'process_background',
"line_scale", 'line_size_scaling',
"copy_text", 'copy_text',
"shift_text", 'shift_text',
"line_tol", 'line_close_tol',
"joint_tol", 'joint_close_tol',
"threshold_blocksize", 'threshold_blocksize',
"threshold_constant", 'threshold_constant',
"iterations", 'iterations'
"resolution",
] ]
def validate_input(kwargs, flavor="lattice"): def validate_input(kwargs, flavor='lattice', geometry_type=False):
def check_intersection(parser_kwargs, input_kwargs): def check_intersection(parser_kwargs, input_kwargs):
isec = set(parser_kwargs).intersection(set(input_kwargs.keys())) isec = set(parser_kwargs).intersection(set(input_kwargs.keys()))
if isec: if isec:
raise ValueError( raise ValueError("{} cannot be used with flavor='{}'".format(
f"{','.join(sorted(isec))} cannot be used with flavor='{flavor}'" ",".join(sorted(isec)), flavor))
)
if flavor == "lattice": if flavor == 'lattice':
check_intersection(stream_kwargs, kwargs) check_intersection(stream_kwargs, kwargs)
else: else:
check_intersection(lattice_kwargs, kwargs) check_intersection(lattice_kwargs, kwargs)
if geometry_type:
if flavor != 'lattice' and geometry_type in ['contour', 'joint', 'line']:
raise ValueError("Use geometry_type='{}' with flavor='lattice'".format(
geometry_type))
def remove_extra(kwargs, flavor="lattice"): def remove_extra(kwargs, flavor='lattice'):
if flavor == "lattice": if flavor == 'lattice':
for key in kwargs.keys(): for key in kwargs.keys():
if key in stream_kwargs: if key in stream_kwargs:
kwargs.pop(key) kwargs.pop(key)
@ -144,6 +77,35 @@ class TemporaryDirectory(object):
shutil.rmtree(self.name) shutil.rmtree(self.name)
def setup_logging(name):
"""Sets up a logger with StreamHandler.
Parameters
----------
name : str
Returns
-------
logger : logging.Logger
"""
logger = logging.getLogger(name)
format_string = '%(asctime)s - %(levelname)s - %(funcName)s - %(message)s'
formatter = logging.Formatter(format_string, datefmt='%Y-%m-%dT%H:%M:%S')
handler = logging.StreamHandler()
handler.setLevel(logging.INFO)
handler.setFormatter(formatter)
logger.addHandler(handler)
return logger
logger = setup_logging(__name__)
def translate(x1, x2): def translate(x1, x2):
"""Translates x2 by x1. """Translates x2 by x1.
@ -178,6 +140,35 @@ def scale(x, s):
return x return x
def rotate(x1, y1, x2, y2, angle):
"""Rotates point x2, y2 about point x1, y1 by angle.
Parameters
----------
x1 : float
y1 : float
x2 : float
y2 : float
angle : float
Angle in radians.
Returns
-------
xnew : float
ynew : float
"""
s = np.sin(angle)
c = np.cos(angle)
x2 = translate(-x1, x2)
y2 = translate(-y1, y2)
xnew = c * x2 - s * y2
ynew = s * x2 + c * y2
xnew = translate(x1, xnew)
ynew = translate(y1, ynew)
return xnew, ynew
def scale_pdf(k, factors): def scale_pdf(k, factors):
"""Translates and scales pdf coordinate space to image """Translates and scales pdf coordinate space to image
coordinate space. coordinate space.
@ -253,33 +244,29 @@ def scale_image(tables, v_segments, h_segments, factors):
v_segments_new = [] v_segments_new = []
for v in v_segments: for v in v_segments:
x1, x2 = scale(v[0], scaling_factor_x), scale(v[2], scaling_factor_x) x1, x2 = scale(v[0], scaling_factor_x), scale(v[2], scaling_factor_x)
y1, y2 = ( y1, y2 = scale(abs(translate(-img_y, v[1])), scaling_factor_y), scale(
scale(abs(translate(-img_y, v[1])), scaling_factor_y), abs(translate(-img_y, v[3])), scaling_factor_y)
scale(abs(translate(-img_y, v[3])), scaling_factor_y),
)
v_segments_new.append((x1, y1, x2, y2)) v_segments_new.append((x1, y1, x2, y2))
h_segments_new = [] h_segments_new = []
for h in h_segments: for h in h_segments:
x1, x2 = scale(h[0], scaling_factor_x), scale(h[2], scaling_factor_x) x1, x2 = scale(h[0], scaling_factor_x), scale(h[2], scaling_factor_x)
y1, y2 = ( y1, y2 = scale(abs(translate(-img_y, h[1])), scaling_factor_y), scale(
scale(abs(translate(-img_y, h[1])), scaling_factor_y), abs(translate(-img_y, h[3])), scaling_factor_y)
scale(abs(translate(-img_y, h[3])), scaling_factor_y),
)
h_segments_new.append((x1, y1, x2, y2)) h_segments_new.append((x1, y1, x2, y2))
return tables_new, v_segments_new, h_segments_new return tables_new, v_segments_new, h_segments_new
def get_rotation(chars, horizontal_text, vertical_text): def get_rotation(lttextlh, lttextlv, ltchar):
"""Detects if text in table is rotated or not using the current """Detects if text in table is rotated or not using the current
transformation matrix (CTM) and returns its orientation. transformation matrix (CTM) and returns its orientation.
Parameters Parameters
---------- ----------
horizontal_text : list lttextlh : list
List of PDFMiner LTTextLineHorizontal objects. List of PDFMiner LTTextLineHorizontal objects.
vertical_text : list lttextlv : list
List of PDFMiner LTTextLineVertical objects. List of PDFMiner LTTextLineVertical objects.
ltchar : list ltchar : list
List of PDFMiner LTChar objects. List of PDFMiner LTChar objects.
@ -292,13 +279,13 @@ def get_rotation(chars, horizontal_text, vertical_text):
rotated 90 degree clockwise. rotated 90 degree clockwise.
""" """
rotation = "" rotation = ''
hlen = len([t for t in horizontal_text if t.get_text().strip()]) hlen = len([t for t in lttextlh if t.get_text().strip()])
vlen = len([t for t in vertical_text if t.get_text().strip()]) vlen = len([t for t in lttextlv if t.get_text().strip()])
if hlen < vlen: if hlen < vlen:
clockwise = sum(t.matrix[1] < 0 and t.matrix[2] > 0 for t in chars) clockwise = sum(t.matrix[1] < 0 and t.matrix[2] > 0 for t in ltchar)
anticlockwise = sum(t.matrix[1] > 0 and t.matrix[2] < 0 for t in chars) anticlockwise = sum(t.matrix[1] > 0 and t.matrix[2] < 0 for t in ltchar)
rotation = "anticlockwise" if clockwise < anticlockwise else "clockwise" rotation = 'anticlockwise' if clockwise < anticlockwise else 'clockwise'
return rotation return rotation
@ -326,16 +313,10 @@ def segments_in_bbox(bbox, v_segments, h_segments):
""" """
lb = (bbox[0], bbox[1]) lb = (bbox[0], bbox[1])
rt = (bbox[2], bbox[3]) rt = (bbox[2], bbox[3])
v_s = [ v_s = [v for v in v_segments if v[1] > lb[1] - 2 and
v v[3] < rt[1] + 2 and lb[0] - 2 <= v[0] <= rt[0] + 2]
for v in v_segments h_s = [h for h in h_segments if h[0] > lb[0] - 2 and
if v[1] > lb[1] - 2 and v[3] < rt[1] + 2 and lb[0] - 2 <= v[0] <= rt[0] + 2 h[2] < rt[0] + 2 and lb[1] - 2 <= h[1] <= rt[1] + 2]
]
h_s = [
h
for h in h_segments
if h[0] > lb[0] - 2 and h[2] < rt[0] + 2 and lb[1] - 2 <= h[1] <= rt[1] + 2
]
return v_s, h_s return v_s, h_s
@ -346,125 +327,32 @@ def text_in_bbox(bbox, text):
---------- ----------
bbox : tuple bbox : tuple
Tuple (x1, y1, x2, y2) representing a bounding box where Tuple (x1, y1, x2, y2) representing a bounding box where
(x1, y1) -> lb and (x2, y2) -> rt in the PDF coordinate (x1, y1) -> lb and (x2, y2) -> rt in PDFMiner coordinate
space. space.
text : List of PDFMiner text objects. text : List of PDFMiner text objects.
Returns Returns
------- -------
t_bbox : list t_bbox : list
List of PDFMiner text objects that lie inside table, discarding the overlapping ones List of PDFMiner text objects that lie inside table.
""" """
lb = (bbox[0], bbox[1]) lb = (bbox[0], bbox[1])
rt = (bbox[2], bbox[3]) rt = (bbox[2], bbox[3])
t_bbox = [ t_bbox = [t for t in text if lb[0] - 2 <= (t.x0 + t.x1) / 2.0
t <= rt[0] + 2 and lb[1] - 2 <= (t.y0 + t.y1) / 2.0
for t in text <= rt[1] + 2]
if lb[0] - 2 <= (t.x0 + t.x1) / 2.0 <= rt[0] + 2 return t_bbox
and lb[1] - 2 <= (t.y0 + t.y1) / 2.0 <= rt[1] + 2
]
# Avoid duplicate text by discarding overlapping boxes
rest = {t for t in t_bbox}
for ba in t_bbox:
for bb in rest.copy():
if ba == bb:
continue
if bbox_intersect(ba, bb):
# if the intersection is larger than 80% of ba's size, we keep the longest
if (bbox_intersection_area(ba, bb) / bbox_area(ba)) > 0.8:
if bbox_longer(bb, ba):
rest.discard(ba)
unique_boxes = list(rest)
return unique_boxes
def bbox_intersection_area(ba, bb) -> float: def remove_close_lines(ar, line_close_tol=2):
"""Returns area of the intersection of the bounding boxes of two PDFMiner objects. """Removes lines which are within a tolerance, based on their x or
y axis projections.
Parameters
----------
ba : PDFMiner text object
bb : PDFMiner text object
Returns
-------
intersection_area : float
Area of the intersection of the bounding boxes of both objects
"""
x_left = max(ba.x0, bb.x0)
y_top = min(ba.y1, bb.y1)
x_right = min(ba.x1, bb.x1)
y_bottom = max(ba.y0, bb.y0)
if x_right < x_left or y_bottom > y_top:
return 0.0
intersection_area = (x_right - x_left) * (y_top - y_bottom)
return intersection_area
def bbox_area(bb) -> float:
"""Returns area of the bounding box of a PDFMiner object.
Parameters
----------
bb : PDFMiner text object
Returns
-------
area : float
Area of the bounding box of the object
"""
return (bb.x1 - bb.x0) * (bb.y1 - bb.y0)
def bbox_intersect(ba, bb) -> bool:
"""Returns True if the bounding boxes of two PDFMiner objects intersect.
Parameters
----------
ba : PDFMiner text object
bb : PDFMiner text object
Returns
-------
overlaps : bool
True if the bounding boxes intersect
"""
return ba.x1 >= bb.x0 and bb.x1 >= ba.x0 and ba.y1 >= bb.y0 and bb.y1 >= ba.y0
def bbox_longer(ba, bb) -> bool:
"""Returns True if the bounding box of the first PDFMiner object is longer or equal to the second.
Parameters
----------
ba : PDFMiner text object
bb : PDFMiner text object
Returns
-------
longer : bool
True if the bounding box of the first object is longer or equal
"""
return (ba.x1 - ba.x0) >= (bb.x1 - bb.x0)
def merge_close_lines(ar, line_tol=2):
"""Merges lines which are within a tolerance by calculating a
moving mean, based on their x or y axis projections.
Parameters Parameters
---------- ----------
ar : list ar : list
line_tol : int, optional (default: 2) line_close_tol : int, optional (default: 2)
Returns Returns
------- -------
@ -477,7 +365,34 @@ def merge_close_lines(ar, line_tol=2):
ret.append(a) ret.append(a)
else: else:
temp = ret[-1] temp = ret[-1]
if np.isclose(temp, a, atol=line_tol): if np.isclose(temp, a, atol=line_close_tol):
pass
else:
ret.append(a)
return ret
def merge_close_lines(ar, line_close_tol=2):
"""Merges lines which are within a tolerance by calculating a
moving mean, based on their x or y axis projections.
Parameters
----------
ar : list
line_close_tol : int, optional (default: 2)
Returns
-------
ret : list
"""
ret = []
for a in ar:
if not ret:
ret.append(a)
else:
temp = ret[-1]
if np.isclose(temp, a, atol=line_close_tol):
temp = (temp + a) / 2.0 temp = (temp + a) / 2.0
ret[-1] = temp ret[-1] = temp
else: else:
@ -485,33 +400,7 @@ def merge_close_lines(ar, line_tol=2):
return ret return ret
def text_strip(text, strip=""): def flag_font_size(textline, direction):
"""Strips any characters in `strip` that are present in `text`.
Parameters
----------
text : str
Text to process and strip.
strip : str, optional (default: '')
Characters that should be stripped from `text`.
Returns
-------
stripped : str
"""
if not strip:
return text
stripped = re.sub(
fr"[{''.join(map(re.escape, strip))}]", "", text, flags=re.UNICODE
)
return stripped
# TODO: combine the following functions into a TextProcessor class which
# applies corresponding transformations sequentially
# (inspired from sklearn.pipeline.Pipeline)
def flag_font_size(textline, direction, strip_text=""):
"""Flags super/subscripts in text by enclosing them with <s></s>. """Flags super/subscripts in text by enclosing them with <s></s>.
May give false positives. May give false positives.
@ -521,27 +410,16 @@ def flag_font_size(textline, direction, strip_text=""):
List of PDFMiner LTChar objects. List of PDFMiner LTChar objects.
direction : string direction : string
Direction of the PDFMiner LTTextLine object. Direction of the PDFMiner LTTextLine object.
strip_text : str, optional (default: '')
Characters that should be stripped from a string before
assigning it to a cell.
Returns Returns
------- -------
fstring : string fstring : string
""" """
if direction == "horizontal": if direction == 'horizontal':
d = [ d = [(t.get_text(), np.round(t.height, decimals=6)) for t in textline if not isinstance(t, LTAnno)]
(t.get_text(), np.round(t.height, decimals=6)) elif direction == 'vertical':
for t in textline d = [(t.get_text(), np.round(t.width, decimals=6)) for t in textline if not isinstance(t, LTAnno)]
if not isinstance(t, LTAnno)
]
elif direction == "vertical":
d = [
(t.get_text(), np.round(t.width, decimals=6))
for t in textline
if not isinstance(t, LTAnno)
]
l = [np.round(size, decimals=6) for text, size in d] l = [np.round(size, decimals=6) for text, size in d]
if len(set(l)) > 1: if len(set(l)) > 1:
flist = [] flist = []
@ -549,21 +427,21 @@ def flag_font_size(textline, direction, strip_text=""):
for key, chars in groupby(d, itemgetter(1)): for key, chars in groupby(d, itemgetter(1)):
if key == min_size: if key == min_size:
fchars = [t[0] for t in chars] fchars = [t[0] for t in chars]
if "".join(fchars).strip(): if ''.join(fchars).strip():
fchars.insert(0, "<s>") fchars.insert(0, '<s>')
fchars.append("</s>") fchars.append('</s>')
flist.append("".join(fchars)) flist.append(''.join(fchars))
else: else:
fchars = [t[0] for t in chars] fchars = [t[0] for t in chars]
if "".join(fchars).strip(): if ''.join(fchars).strip():
flist.append("".join(fchars)) flist.append(''.join(fchars))
fstring = "".join(flist) fstring = ''.join(flist).strip('\n')
else: else:
fstring = "".join([t.get_text() for t in textline]) fstring = ''.join([t.get_text() for t in textline]).strip('\n')
return text_strip(fstring, strip_text) return fstring
def split_textline(table, textline, direction, flag_size=False, strip_text=""): def split_textline(table, textline, direction, flag_size=False):
"""Splits PDFMiner LTTextLine into substrings if it spans across """Splits PDFMiner LTTextLine into substrings if it spans across
multiple rows/columns. multiple rows/columns.
@ -578,9 +456,6 @@ def split_textline(table, textline, direction, flag_size=False, strip_text=""):
Whether or not to highlight a substring using <s></s> Whether or not to highlight a substring using <s></s>
if its size is different from rest of the string. (Useful for if its size is different from rest of the string. (Useful for
super and subscripts.) super and subscripts.)
strip_text : str, optional (default: '')
Characters that should be stripped from a string before
assigning it to a cell.
Returns Returns
------- -------
@ -593,70 +468,38 @@ def split_textline(table, textline, direction, flag_size=False, strip_text=""):
cut_text = [] cut_text = []
bbox = textline.bbox bbox = textline.bbox
try: try:
if direction == "horizontal" and not textline.is_empty(): if direction == 'horizontal' and not textline.is_empty():
x_overlap = [ x_overlap = [i for i, x in enumerate(table.cols) if x[0] <= bbox[2] and bbox[0] <= x[1]]
i r_idx = [j for j, r in enumerate(table.rows) if r[1] <= (bbox[1] + bbox[3]) / 2 <= r[0]]
for i, x in enumerate(table.cols)
if x[0] <= bbox[2] and bbox[0] <= x[1]
]
r_idx = [
j
for j, r in enumerate(table.rows)
if r[1] <= (bbox[1] + bbox[3]) / 2 <= r[0]
]
r = r_idx[0] r = r_idx[0]
x_cuts = [ x_cuts = [(c, table.cells[r][c].x2) for c in x_overlap if table.cells[r][c].right]
(c, table.cells[r][c].x2) for c in x_overlap if table.cells[r][c].right
]
if not x_cuts: if not x_cuts:
x_cuts = [(x_overlap[0], table.cells[r][-1].x2)] x_cuts = [(x_overlap[0], table.cells[r][-1].x2)]
for obj in textline._objs: for obj in textline._objs:
row = table.rows[r] row = table.rows[r]
for cut in x_cuts: for cut in x_cuts:
if isinstance(obj, LTChar): if isinstance(obj, LTChar):
if ( if (row[1] <= (obj.y0 + obj.y1) / 2 <= row[0] and
row[1] <= (obj.y0 + obj.y1) / 2 <= row[0] (obj.x0 + obj.x1) / 2 <= cut[1]):
and (obj.x0 + obj.x1) / 2 <= cut[1]
):
cut_text.append((r, cut[0], obj)) cut_text.append((r, cut[0], obj))
break break
else:
# TODO: add test
if cut == x_cuts[-1]:
cut_text.append((r, cut[0] + 1, obj))
elif isinstance(obj, LTAnno): elif isinstance(obj, LTAnno):
cut_text.append((r, cut[0], obj)) cut_text.append((r, cut[0], obj))
elif direction == "vertical" and not textline.is_empty(): elif direction == 'vertical' and not textline.is_empty():
y_overlap = [ y_overlap = [j for j, y in enumerate(table.rows) if y[1] <= bbox[3] and bbox[1] <= y[0]]
j c_idx = [i for i, c in enumerate(table.cols) if c[0] <= (bbox[0] + bbox[2]) / 2 <= c[1]]
for j, y in enumerate(table.rows)
if y[1] <= bbox[3] and bbox[1] <= y[0]
]
c_idx = [
i
for i, c in enumerate(table.cols)
if c[0] <= (bbox[0] + bbox[2]) / 2 <= c[1]
]
c = c_idx[0] c = c_idx[0]
y_cuts = [ y_cuts = [(r, table.cells[r][c].y1) for r in y_overlap if table.cells[r][c].bottom]
(r, table.cells[r][c].y1) for r in y_overlap if table.cells[r][c].bottom
]
if not y_cuts: if not y_cuts:
y_cuts = [(y_overlap[0], table.cells[-1][c].y1)] y_cuts = [(y_overlap[0], table.cells[-1][c].y1)]
for obj in textline._objs: for obj in textline._objs:
col = table.cols[c] col = table.cols[c]
for cut in y_cuts: for cut in y_cuts:
if isinstance(obj, LTChar): if isinstance(obj, LTChar):
if ( if (col[0] <= (obj.x0 + obj.x1) / 2 <= col[1] and
col[0] <= (obj.x0 + obj.x1) / 2 <= col[1] (obj.y0 + obj.y1) / 2 >= cut[1]):
and (obj.y0 + obj.y1) / 2 >= cut[1]
):
cut_text.append((cut[0], c, obj)) cut_text.append((cut[0], c, obj))
break break
else:
# TODO: add test
if cut == y_cuts[-1]:
cut_text.append((cut[0] - 1, c, obj))
elif isinstance(obj, LTAnno): elif isinstance(obj, LTAnno):
cut_text.append((cut[0], c, obj)) cut_text.append((cut[0], c, obj))
except IndexError: except IndexError:
@ -664,26 +507,14 @@ def split_textline(table, textline, direction, flag_size=False, strip_text=""):
grouped_chars = [] grouped_chars = []
for key, chars in groupby(cut_text, itemgetter(0, 1)): for key, chars in groupby(cut_text, itemgetter(0, 1)):
if flag_size: if flag_size:
grouped_chars.append( grouped_chars.append((key[0], key[1], flag_font_size([t[2] for t in chars], direction)))
(
key[0],
key[1],
flag_font_size(
[t[2] for t in chars], direction, strip_text=strip_text
),
)
)
else: else:
gchars = [t[2].get_text() for t in chars] gchars = [t[2].get_text() for t in chars]
grouped_chars.append( grouped_chars.append((key[0], key[1], ''.join(gchars).strip('\n')))
(key[0], key[1], text_strip("".join(gchars), strip_text))
)
return grouped_chars return grouped_chars
def get_table_index( def get_table_index(table, t, direction, split_text=False, flag_size=False):
table, t, direction, split_text=False, flag_size=False, strip_text=""
):
"""Gets indices of the table cell where given text object lies by """Gets indices of the table cell where given text object lies by
comparing their y and x-coordinates. comparing their y and x-coordinates.
@ -701,9 +532,6 @@ def get_table_index(
Whether or not to highlight a substring using <s></s> Whether or not to highlight a substring using <s></s>
if its size is different from rest of the string. (Useful for if its size is different from rest of the string. (Useful for
super and subscripts) super and subscripts)
strip_text : str, optional (default: '')
Characters that should be stripped from a string before
assigning it to a cell.
Returns Returns
------- -------
@ -722,9 +550,8 @@ def get_table_index(
""" """
r_idx, c_idx = [-1] * 2 r_idx, c_idx = [-1] * 2
for r in range(len(table.rows)): for r in range(len(table.rows)):
if (t.y0 + t.y1) / 2.0 < table.rows[r][0] and (t.y0 + t.y1) / 2.0 > table.rows[ if ((t.y0 + t.y1) / 2.0 < table.rows[r][0] and
r (t.y0 + t.y1) / 2.0 > table.rows[r][1]):
][1]:
lt_col_overlap = [] lt_col_overlap = []
for c in table.cols: for c in table.cols:
if c[0] <= t.x1 and c[1] >= t.x0: if c[0] <= t.x1 and c[1] >= t.x0:
@ -733,13 +560,12 @@ def get_table_index(
lt_col_overlap.append(abs(left - right) / abs(c[0] - c[1])) lt_col_overlap.append(abs(left - right) / abs(c[0] - c[1]))
else: else:
lt_col_overlap.append(-1) lt_col_overlap.append(-1)
if len(list(filter(lambda x: x != -1, lt_col_overlap))) == 0: if len(filter(lambda x: x != -1, lt_col_overlap)) == 0:
text = t.get_text().strip("\n") text = t.get_text().strip('\n')
text_range = (t.x0, t.x1) text_range = (t.x0, t.x1)
col_range = (table.cols[0][0], table.cols[-1][1]) col_range = (table.cols[0][0], table.cols[-1][1])
warnings.warn( logger.info("{} {} does not lie in column range {}".format(
f"{text} {text_range} does not lie in column range {col_range}" text, text_range, col_range))
)
r_idx = r r_idx = r
c_idx = lt_col_overlap.index(max(lt_col_overlap)) c_idx = lt_col_overlap.index(max(lt_col_overlap))
break break
@ -760,26 +586,12 @@ def get_table_index(
error = ((X * (y0_offset + y1_offset)) + (Y * (x0_offset + x1_offset))) / charea error = ((X * (y0_offset + y1_offset)) + (Y * (x0_offset + x1_offset))) / charea
if split_text: if split_text:
return ( return split_textline(table, t, direction, flag_size=flag_size), error
split_textline(
table, t, direction, flag_size=flag_size, strip_text=strip_text
),
error,
)
else: else:
if flag_size: if flag_size:
return ( return [(r_idx, c_idx, flag_font_size(t._objs, direction))], error
[
(
r_idx,
c_idx,
flag_font_size(t._objs, direction, strip_text=strip_text),
)
],
error,
)
else: else:
return [(r_idx, c_idx, text_strip(t.get_text(), strip_text))], error return [(r_idx, c_idx, t.get_text().strip('\n'))], error
def compute_accuracy(error_weights): def compute_accuracy(error_weights):
@ -830,35 +642,62 @@ def compute_whitespace(d):
r_nempty_cells, c_nempty_cells = [], [] r_nempty_cells, c_nempty_cells = [], []
for i in d: for i in d:
for j in i: for j in i:
if j.strip() == "": if j.strip() == '':
whitespace += 1 whitespace += 1
whitespace = 100 * (whitespace / float(len(d) * len(d[0]))) whitespace = 100 * (whitespace / float(len(d) * len(d[0])))
return whitespace return whitespace
def get_page_layout( def remove_empty(d):
filename, """Removes empty rows and columns from a two-dimensional list.
line_overlap=0.5,
char_margin=1.0, Parameters
line_margin=0.5, ----------
word_margin=0.1, d : list
boxes_flow=0.5,
detect_vertical=True, Returns
all_texts=True, -------
): d : list
"""
for i, row in enumerate(d):
if row == [''] * len(row):
d.pop(i)
d = zip(*d)
d = [list(row) for row in d if any(row)]
d = zip(*d)
return d
def encode_(ar):
"""Encodes two-dimensional list into unicode.
Parameters
----------
ar : list
Returns
-------
ar : list
"""
ar = [[r.encode('utf-8') for r in row] for row in ar]
return ar
def get_page_layout(filename, char_margin=1.0, line_margin=0.5, word_margin=0.1,
detect_vertical=True, all_texts=True):
"""Returns a PDFMiner LTPage object and page dimension of a single """Returns a PDFMiner LTPage object and page dimension of a single
page pdf. To get the definitions of kwargs, see page pdf. See https://euske.github.io/pdfminer/ to get definitions
https://pdfminersix.rtfd.io/en/latest/reference/composable.html. of kwargs.
Parameters Parameters
---------- ----------
filename : string filename : string
Path to pdf file. Path to pdf file.
line_overlap : float
char_margin : float char_margin : float
line_margin : float line_margin : float
word_margin : float word_margin : float
boxes_flow : float
detect_vertical : bool detect_vertical : bool
all_texts : bool all_texts : bool
@ -870,22 +709,16 @@ def get_page_layout(
Dimension of pdf page in the form (width, height). Dimension of pdf page in the form (width, height).
""" """
with open(filename, "rb") as f: with open(filename, 'r') as f:
parser = PDFParser(f) parser = PDFParser(f)
document = PDFDocument(parser) document = PDFDocument(parser)
if not document.is_extractable: if not document.is_extractable:
raise PDFTextExtractionNotAllowed( raise PDFTextExtractionNotAllowed
f"Text extraction is not allowed: {filename}" laparams = LAParams(char_margin=char_margin,
) line_margin=line_margin,
laparams = LAParams( word_margin=word_margin,
line_overlap=line_overlap, detect_vertical=detect_vertical,
char_margin=char_margin, all_texts=all_texts)
line_margin=line_margin,
word_margin=word_margin,
boxes_flow=boxes_flow,
detect_vertical=detect_vertical,
all_texts=all_texts,
)
rsrcmgr = PDFResourceManager() rsrcmgr = PDFResourceManager()
device = PDFPageAggregator(rsrcmgr, laparams=laparams) device = PDFPageAggregator(rsrcmgr, laparams=laparams)
interpreter = PDFPageInterpreter(rsrcmgr, device) interpreter = PDFPageInterpreter(rsrcmgr, device)
@ -919,11 +752,9 @@ def get_text_objects(layout, ltype="char", t=None):
""" """
if ltype == "char": if ltype == "char":
LTObject = LTChar LTObject = LTChar
elif ltype == "image": elif ltype == "lh":
LTObject = LTImage
elif ltype == "horizontal_text":
LTObject = LTTextLineHorizontal LTObject = LTTextLineHorizontal
elif ltype == "vertical_text": elif ltype == "lv":
LTObject = LTTextLineVertical LTObject = LTTextLineVertical
if t is None: if t is None:
t = [] t = []
@ -936,3 +767,27 @@ def get_text_objects(layout, ltype="char", t=None):
except AttributeError: except AttributeError:
pass pass
return t return t
def merge_tuples(tuples):
"""Merges a list of overlapping tuples.
Parameters
----------
tuples : list
List of tuples where a tuple is a single axis coordinate pair.
Yields
------
tuple
"""
merged = list(tuples[0])
for s, e in tuples:
if s <= merged[1]:
merged[1] = max(merged[1], e)
else:
yield tuple(merged)
merged[0] = s
merged[1] = e
yield tuple(merged)

4
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@ -1,4 +0,0 @@
"Età dell’Assicuratoall’epoca del decesso","Misura % dimaggiorazione"
"18-75","1,00%"
"76-80","0,50%"
"81 in poi","0,10%"
1 Età dell’Assicuratoall’epoca del decesso Misura % dimaggiorazione
2 18-75 1,00%
3 76-80 0,50%
4 81 in poi 0,10%

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@ -1,5 +1,5 @@
<style type="text/css"> <style type="text/css">
div.section h1 {font-size: 210%;} div.section h1 {font-size: 225%;}
/* "Quick Search" should be capitalized. */ /* "Quick Search" should be capitalized. */
div#searchbox h3 {text-transform: capitalize;} div#searchbox h3 {text-transform: capitalize;}
/* Make the document a little wider, less code is cut-off. */ /* Make the document a little wider, less code is cut-off. */

8
docs/_templates/sidebarintro.html vendored
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@ -4,13 +4,13 @@
</a> </a>
</p> </p>
<p> <p>
<iframe src="https://ghbtns.com/github-btn.html?user=camelot-dev&repo=camelot&type=watch&count=true&size=large" <iframe src="https://ghbtns.com/github-btn.html?user=socialcopsdev&repo=camelot&type=watch&count=true&size=large"
allowtransparency="true" frameborder="0" scrolling="0" width="200px" height="35px"></iframe> allowtransparency="true" frameborder="0" scrolling="0" width="200px" height="35px"></iframe>
</p> </p>
<h3>Useful Links</h3> <h3>Useful Links</h3>
<ul> <ul>
<li><a href="https://github.com/camelot-dev/camelot">Camelot @ GitHub</a></li> <li><a href="https://github.com/socialcopsdev/camelot">Camelot @ GitHub</a></li>
<li><a href="https://pypi.org/project/camelot-py/">Camelot @ PyPI</a></li> <li><a href="https://pypi.org/project/camelot-py/">Camelot @ PyPI</a></li>
<li><a href="https://github.com/camelot-dev/camelot/issues">Issue Tracker</a></li> <li><a href="https://github.com/socialcopsdev/camelot/issues">Issue Tracker</a></li>
</ul> </ul>

4
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@ -4,6 +4,6 @@
</a> </a>
</p> </p>
<p> <p>
<iframe src="https://ghbtns.com/github-btn.html?user=camelot-dev&repo=camelot&type=watch&count=true&size=large" <iframe src="https://ghbtns.com/github-btn.html?user=socialcopsdev&repo=camelot&type=watch&count=true&size=large"
allowtransparency="true" frameborder="0" scrolling="0" width="200px" height="35px"></iframe> allowtransparency="true" frameborder="0" scrolling="0" width="200px" height="35px"></iframe>
</p> </p>

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@ -1,19 +1,7 @@
# flasky pygments style based on tango style # flasky pygments style based on tango style
from pygments.style import Style from pygments.style import Style
from pygments.token import ( from pygments.token import Keyword, Name, Comment, String, Error, \
Keyword, Number, Operator, Generic, Whitespace, Punctuation, Other, Literal
Name,
Comment,
String,
Error,
Number,
Operator,
Generic,
Whitespace,
Punctuation,
Other,
Literal,
)
class FlaskyStyle(Style): class FlaskyStyle(Style):
@ -22,68 +10,77 @@ class FlaskyStyle(Style):
styles = { styles = {
# No corresponding class for the following: # No corresponding class for the following:
# Text: "", # class: '' #Text: "", # class: ''
Whitespace: "underline #f8f8f8", # class: 'w' Whitespace: "underline #f8f8f8", # class: 'w'
Error: "#a40000 border:#ef2929", # class: 'err' Error: "#a40000 border:#ef2929", # class: 'err'
Other: "#000000", # class 'x' Other: "#000000", # class 'x'
Comment: "italic #8f5902", # class: 'c'
Comment.Preproc: "noitalic", # class: 'cp' Comment: "italic #8f5902", # class: 'c'
Keyword: "bold #004461", # class: 'k' Comment.Preproc: "noitalic", # class: 'cp'
Keyword.Constant: "bold #004461", # class: 'kc'
Keyword.Declaration: "bold #004461", # class: 'kd' Keyword: "bold #004461", # class: 'k'
Keyword.Namespace: "bold #004461", # class: 'kn' Keyword.Constant: "bold #004461", # class: 'kc'
Keyword.Pseudo: "bold #004461", # class: 'kp' Keyword.Declaration: "bold #004461", # class: 'kd'
Keyword.Reserved: "bold #004461", # class: 'kr' Keyword.Namespace: "bold #004461", # class: 'kn'
Keyword.Type: "bold #004461", # class: 'kt' Keyword.Pseudo: "bold #004461", # class: 'kp'
Operator: "#582800", # class: 'o' Keyword.Reserved: "bold #004461", # class: 'kr'
Operator.Word: "bold #004461", # class: 'ow' - like keywords Keyword.Type: "bold #004461", # class: 'kt'
Punctuation: "bold #000000", # class: 'p'
Operator: "#582800", # class: 'o'
Operator.Word: "bold #004461", # class: 'ow' - like keywords
Punctuation: "bold #000000", # class: 'p'
# because special names such as Name.Class, Name.Function, etc. # because special names such as Name.Class, Name.Function, etc.
# are not recognized as such later in the parsing, we choose them # are not recognized as such later in the parsing, we choose them
# to look the same as ordinary variables. # to look the same as ordinary variables.
Name: "#000000", # class: 'n' Name: "#000000", # class: 'n'
Name.Attribute: "#c4a000", # class: 'na' - to be revised Name.Attribute: "#c4a000", # class: 'na' - to be revised
Name.Builtin: "#004461", # class: 'nb' Name.Builtin: "#004461", # class: 'nb'
Name.Builtin.Pseudo: "#3465a4", # class: 'bp' Name.Builtin.Pseudo: "#3465a4", # class: 'bp'
Name.Class: "#000000", # class: 'nc' - to be revised Name.Class: "#000000", # class: 'nc' - to be revised
Name.Constant: "#000000", # class: 'no' - to be revised Name.Constant: "#000000", # class: 'no' - to be revised
Name.Decorator: "#888", # class: 'nd' - to be revised Name.Decorator: "#888", # class: 'nd' - to be revised
Name.Entity: "#ce5c00", # class: 'ni' Name.Entity: "#ce5c00", # class: 'ni'
Name.Exception: "bold #cc0000", # class: 'ne' Name.Exception: "bold #cc0000", # class: 'ne'
Name.Function: "#000000", # class: 'nf' Name.Function: "#000000", # class: 'nf'
Name.Property: "#000000", # class: 'py' Name.Property: "#000000", # class: 'py'
Name.Label: "#f57900", # class: 'nl' Name.Label: "#f57900", # class: 'nl'
Name.Namespace: "#000000", # class: 'nn' - to be revised Name.Namespace: "#000000", # class: 'nn' - to be revised
Name.Other: "#000000", # class: 'nx' Name.Other: "#000000", # class: 'nx'
Name.Tag: "bold #004461", # class: 'nt' - like a keyword Name.Tag: "bold #004461", # class: 'nt' - like a keyword
Name.Variable: "#000000", # class: 'nv' - to be revised Name.Variable: "#000000", # class: 'nv' - to be revised
Name.Variable.Class: "#000000", # class: 'vc' - to be revised Name.Variable.Class: "#000000", # class: 'vc' - to be revised
Name.Variable.Global: "#000000", # class: 'vg' - to be revised Name.Variable.Global: "#000000", # class: 'vg' - to be revised
Name.Variable.Instance: "#000000", # class: 'vi' - to be revised Name.Variable.Instance: "#000000", # class: 'vi' - to be revised
Number: "#990000", # class: 'm'
Literal: "#000000", # class: 'l' Number: "#990000", # class: 'm'
Literal.Date: "#000000", # class: 'ld'
String: "#4e9a06", # class: 's' Literal: "#000000", # class: 'l'
String.Backtick: "#4e9a06", # class: 'sb' Literal.Date: "#000000", # class: 'ld'
String.Char: "#4e9a06", # class: 'sc'
String.Doc: "italic #8f5902", # class: 'sd' - like a comment String: "#4e9a06", # class: 's'
String.Double: "#4e9a06", # class: 's2' String.Backtick: "#4e9a06", # class: 'sb'
String.Escape: "#4e9a06", # class: 'se' String.Char: "#4e9a06", # class: 'sc'
String.Heredoc: "#4e9a06", # class: 'sh' String.Doc: "italic #8f5902", # class: 'sd' - like a comment
String.Interpol: "#4e9a06", # class: 'si' String.Double: "#4e9a06", # class: 's2'
String.Other: "#4e9a06", # class: 'sx' String.Escape: "#4e9a06", # class: 'se'
String.Regex: "#4e9a06", # class: 'sr' String.Heredoc: "#4e9a06", # class: 'sh'
String.Single: "#4e9a06", # class: 's1' String.Interpol: "#4e9a06", # class: 'si'
String.Symbol: "#4e9a06", # class: 'ss' String.Other: "#4e9a06", # class: 'sx'
Generic: "#000000", # class: 'g' String.Regex: "#4e9a06", # class: 'sr'
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Generic.Heading: "bold #000080", # class: 'gh' Generic: "#000000", # class: 'g'
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96
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@ -1,96 +0,0 @@
"0","1","2","3","4","5","6","7","8","9","10"
"Sl.
No.","District","n
o
i
t
a
l3
opu2-1hs)
P1k
d 20 la
er n
cto(I
ef
j
o
r
P","%
8
8
o )
s
ult t tkh
dna
Aalen l
v(I
i
u
q
E",")
y
n a
umptiomentadult/donnes)
nsres/h t
ouimk
Cqga
al re00n L
ot 4(I
T @
(","menteds, age)nes)
uireg sewastton
qn h
Reudis &ak
al cld L
tnen
To(Ife(I","","","","",""
"","","","","","","f
i
r
a
h
K","i
b
a
R","l
a
t
o
T","e
c
i
R","y
d
d
a
P"
"1","Balasore","23.65","20.81","3.04","3.47","2.78","0.86","3.64","0.17","0.25"
"2","Bhadrak","15.34","13.50","1.97","2.25","3.50","0.05","3.55","1.30","1.94"
"3","Balangir","17.01","14.97","2.19","2.50","6.23","0.10","6.33","3.83","5.72"
"4","Subarnapur","6.70","5.90","0.86","0.98","4.48","1.13","5.61","4.63","6.91"
"5","Cuttack","26.63","23.43","3.42","3.91","3.75","0.06","3.81","-0.10","-0.15"
"6","Jagatsingpur","11.49","10.11","1.48","1.69","2.10","0.02","2.12","0.43","0.64"
"7","Jajpur","18.59","16.36","2.39","2.73","2.13","0.04","2.17","-0.56","-0.84"
"8","Kendrapara","14.62","12.87","1.88","2.15","2.60","0.07","2.67","0.52","0.78"
"9","Dhenkanal","12.13","10.67","1.56","1.78","2.26","0.02","2.28","0.50","0.75"
"10","Angul","12.93","11.38","1.66","1.90","1.73","0.02","1.75","-0.15","-0.22"
"11","Ganjam","35.77","31.48","4.60","5.26","4.57","0.00","4.57","-0.69","-1.03"
"12","Gajapati","5.85","5.15","0.75","0.86","0.68","0.01","0.69","-0.17","-0.25"
"13","Kalahandi","16.12","14.19","2.07","2.37","5.42","1.13","6.55","4.18","6.24"
"14","Nuapada","6.18","5.44","0.79","0.90","1.98","0.08","2.06","1.16","1.73"
"15","Keonjhar","18.42","16.21","2.37","2.71","2.76","0.08","2.84","0.13","0.19"
"16","Koraput","14.09","12.40","1.81","2.07","2.08","0.34","2.42","0.35","0.52"
"17","Malkangiri","6.31","5.55","0.81","0.93","1.78","0.04","1.82","0.89","1.33"
"18","Nabarangpur","12.50","11.00","1.61","1.84","3.26","0.02","3.28","1.44","2.15"
"19","Rayagada","9.83","8.65","1.26","1.44","1.15","0.03","1.18","-0.26","-0.39"
"20","Mayurbhanj","25.61","22.54","3.29","3.76","4.90","0.06","4.96","1.20","1.79"
"21","Kandhamal","7.45","6.56","0.96","1.10","0.70","0.01","0.71","-0.39","-0.58"
"22","Boudh","4.51","3.97","0.58","0.66","1.73","0.03","1.76","1.10","1.64"
"23","Puri","17.29","15.22","2.22","2.54","2.45","0.99","3.44","0.90","1.34"
"24","Khordha","23.08","20.31","2.97","3.39","2.02","0.03","2.05","-1.34","-2.00"
"25","Nayagarh","9.78","8.61","1.26","1.44","2.10","0.00","2.10","0.66","0.99"
"26","Sambalpur","10.62","9.35","1.37","1.57","3.45","0.71","4.16","2.59","3.87"
"27","Bargarh","15.00","13.20","1.93","2.21","6.87","2.65","9.52","7.31","10.91"
"28","Deogarh","3.18","2.80","0.41","0.47","1.12","0.07","1.19","0.72","1.07"
"29","Jharsuguda","5.91","5.20","0.76","0.87","0.99","0.01","1.00","0.13","0.19"
"30","","","18.66","2.72","3.11","4.72","0.02","4.74","1.63","2.43"
1 0 1 2 3 4 5 6 7 8 9 10
2 Sl. No. District n o i t a l3 opu2-1hs) P1k d 20 la er n cto(I ef j o r P % 8 8 o ) s ult t tkh dna Aalen l v(I i u q E ) y n a umptiomentadult/donnes) nsres/h t ouimk Cqga al re00n L ot 4(I T @ ( menteds, age)nes) uireg sewastton qn h Reudis &ak al cld L tnen To(Ife(I
3 f i r a h K i b a R l a t o T e c i R y d d a P
4 1 Balasore 23.65 20.81 3.04 3.47 2.78 0.86 3.64 0.17 0.25
5 2 Bhadrak 15.34 13.50 1.97 2.25 3.50 0.05 3.55 1.30 1.94
6 3 Balangir 17.01 14.97 2.19 2.50 6.23 0.10 6.33 3.83 5.72
7 4 Subarnapur 6.70 5.90 0.86 0.98 4.48 1.13 5.61 4.63 6.91
8 5 Cuttack 26.63 23.43 3.42 3.91 3.75 0.06 3.81 -0.10 -0.15
9 6 Jagatsingpur 11.49 10.11 1.48 1.69 2.10 0.02 2.12 0.43 0.64
10 7 Jajpur 18.59 16.36 2.39 2.73 2.13 0.04 2.17 -0.56 -0.84
11 8 Kendrapara 14.62 12.87 1.88 2.15 2.60 0.07 2.67 0.52 0.78
12 9 Dhenkanal 12.13 10.67 1.56 1.78 2.26 0.02 2.28 0.50 0.75
13 10 Angul 12.93 11.38 1.66 1.90 1.73 0.02 1.75 -0.15 -0.22
14 11 Ganjam 35.77 31.48 4.60 5.26 4.57 0.00 4.57 -0.69 -1.03
15 12 Gajapati 5.85 5.15 0.75 0.86 0.68 0.01 0.69 -0.17 -0.25
16 13 Kalahandi 16.12 14.19 2.07 2.37 5.42 1.13 6.55 4.18 6.24
17 14 Nuapada 6.18 5.44 0.79 0.90 1.98 0.08 2.06 1.16 1.73
18 15 Keonjhar 18.42 16.21 2.37 2.71 2.76 0.08 2.84 0.13 0.19
19 16 Koraput 14.09 12.40 1.81 2.07 2.08 0.34 2.42 0.35 0.52
20 17 Malkangiri 6.31 5.55 0.81 0.93 1.78 0.04 1.82 0.89 1.33
21 18 Nabarangpur 12.50 11.00 1.61 1.84 3.26 0.02 3.28 1.44 2.15
22 19 Rayagada 9.83 8.65 1.26 1.44 1.15 0.03 1.18 -0.26 -0.39
23 20 Mayurbhanj 25.61 22.54 3.29 3.76 4.90 0.06 4.96 1.20 1.79
24 21 Kandhamal 7.45 6.56 0.96 1.10 0.70 0.01 0.71 -0.39 -0.58
25 22 Boudh 4.51 3.97 0.58 0.66 1.73 0.03 1.76 1.10 1.64
26 23 Puri 17.29 15.22 2.22 2.54 2.45 0.99 3.44 0.90 1.34
27 24 Khordha 23.08 20.31 2.97 3.39 2.02 0.03 2.05 -1.34 -2.00
28 25 Nayagarh 9.78 8.61 1.26 1.44 2.10 0.00 2.10 0.66 0.99
29 26 Sambalpur 10.62 9.35 1.37 1.57 3.45 0.71 4.16 2.59 3.87
30 27 Bargarh 15.00 13.20 1.93 2.21 6.87 2.65 9.52 7.31 10.91
31 28 Deogarh 3.18 2.80 0.41 0.47 1.12 0.07 1.19 0.72 1.07
32 29 Jharsuguda 5.91 5.20 0.76 0.87 0.99 0.01 1.00 0.13 0.19
33 30 18.66 2.72 3.11 4.72 0.02 4.74 1.63 2.43

56
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@ -1,56 +0,0 @@
"0","1","2","3","4","5","6","7"
"Rate of Accidental Deaths & Suicides and Population Growth During 1967 to 2013","","","","","","",""
"Sl.
No.","Year","Population
(in Lakh)","Accidental Deaths","","Suicides","","Percentage
Population
growth"
"","","","Incidence","Rate","Incidence","Rate",""
"(1)","(2)","(3)","(4)","(5)","(6)","(7)","(8)"
"1.","1967","4999","126762","25.4","38829","7.8","2.2"
"2.","1968","5111","126232","24.7","40688","8.0","2.2"
"3.","1969","5225","130755","25.0","43633","8.4","2.2"
"4.","1970","5343","139752","26.2","48428","9.1","2.3"
"5.","1971","5512","105601","19.2","43675","7.9","3.2"
"6.","1972","5635","106184","18.8","43601","7.7","2.2"
"7.","1973","5759","130654","22.7","40807","7.1","2.2"
"8.","1974","5883","110624","18.8","46008","7.8","2.2"
"9.","1975","6008","113016","18.8","42890","7.1","2.1"
"10.","1976","6136","111611","18.2","41415","6.7","2.1"
"11.","1977","6258","117338","18.8","39718","6.3","2.0"
"12.","1978","6384","118594","18.6","40207","6.3","2.0"
"13.","1979","6510","108987","16.7","38217","5.9","2.0"
"14.","1980","6636","116912","17.6","41663","6.3","1.9"
"15.","1981","6840","122221","17.9","40245","5.9","3.1"
"16.","1982","7052","125993","17.9","44732","6.3","3.1"
"17.","1983","7204","128576","17.8","46579","6.5","2.2"
"18.","1984","7356","134628","18.3","50571","6.9","2.1"
"19.","1985","7509","139657","18.6","52811","7.0","2.1"
"20.","1986","7661","147023","19.2","54357","7.1","2.0"
"21.","1987","7814","152314","19.5","58568","7.5","2.0"
"22.","1988","7966","163522","20.5","64270","8.1","1.9"
"23.","1989","8118","169066","20.8","68744","8.5","1.9"
"24.","1990","8270","174401","21.1","73911","8.9","1.9"
"25.","1991","8496","188003","22.1","78450","9.2","2.7"
"26.","1992","8677","194910","22.5","80149","9.2","2.1"
"27.","1993","8838","192357","21.8","84244","9.5","1.9"
"28.","1994","8997","190435","21.2","89195","9.9","1.8"
"29.","1995","9160","222487","24.3","89178","9.7","1.8"
"30.","1996","9319","220094","23.6","88241","9.5","1.7"
"31.","1997","9552","233903","24.5","95829","10.0","2.5"
"32.","1998","9709","258409","26.6","104713","10.8","1.6"
"33.","1999","9866","271918","27.6","110587","11.2","1.6"
"34.","2000","10021","255883","25.5","108593","10.8","1.6"
"35.","2001","10270","271019","26.4","108506","10.6","2.5"
"36.","2002","10506","260122","24.8","110417","10.5","2.3"
"37.","2003","10682","259625","24.3","110851","10.4","1.7"
"38.","2004","10856","277263","25.5","113697","10.5","1.6"
"39.","2005","11028","294175","26.7","113914","10.3","1.6"
"40.","2006","11198","314704","28.1","118112","10.5","1.5"
"41.","2007","11366","340794","30.0","122637","10.8","1.5"
"42.","2008","11531","342309","29.7","125017","10.8","1.4"
"43.","2009","11694","357021","30.5","127151","10.9","1.4"
"44.","2010","11858","384649","32.4","134599","11.4","1.4"
"45.","2011","12102","390884","32.3","135585","11.2","2.1"
"46.","2012","12134","394982","32.6","135445","11.2","1.0"
"47.","2013","12288","400517","32.6","134799","11.0","1.0"
1 0 1 2 3 4 5 6 7
2 Rate of Accidental Deaths & Suicides and Population Growth During 1967 to 2013
3 Sl. No. Year Population (in Lakh) Accidental Deaths Suicides Percentage Population growth
4 Incidence Rate Incidence Rate
5 (1) (2) (3) (4) (5) (6) (7) (8)
6 1. 1967 4999 126762 25.4 38829 7.8 2.2
7 2. 1968 5111 126232 24.7 40688 8.0 2.2
8 3. 1969 5225 130755 25.0 43633 8.4 2.2
9 4. 1970 5343 139752 26.2 48428 9.1 2.3
10 5. 1971 5512 105601 19.2 43675 7.9 3.2
11 6. 1972 5635 106184 18.8 43601 7.7 2.2
12 7. 1973 5759 130654 22.7 40807 7.1 2.2
13 8. 1974 5883 110624 18.8 46008 7.8 2.2
14 9. 1975 6008 113016 18.8 42890 7.1 2.1
15 10. 1976 6136 111611 18.2 41415 6.7 2.1
16 11. 1977 6258 117338 18.8 39718 6.3 2.0
17 12. 1978 6384 118594 18.6 40207 6.3 2.0
18 13. 1979 6510 108987 16.7 38217 5.9 2.0
19 14. 1980 6636 116912 17.6 41663 6.3 1.9
20 15. 1981 6840 122221 17.9 40245 5.9 3.1
21 16. 1982 7052 125993 17.9 44732 6.3 3.1
22 17. 1983 7204 128576 17.8 46579 6.5 2.2
23 18. 1984 7356 134628 18.3 50571 6.9 2.1
24 19. 1985 7509 139657 18.6 52811 7.0 2.1
25 20. 1986 7661 147023 19.2 54357 7.1 2.0
26 21. 1987 7814 152314 19.5 58568 7.5 2.0
27 22. 1988 7966 163522 20.5 64270 8.1 1.9
28 23. 1989 8118 169066 20.8 68744 8.5 1.9
29 24. 1990 8270 174401 21.1 73911 8.9 1.9
30 25. 1991 8496 188003 22.1 78450 9.2 2.7
31 26. 1992 8677 194910 22.5 80149 9.2 2.1
32 27. 1993 8838 192357 21.8 84244 9.5 1.9
33 28. 1994 8997 190435 21.2 89195 9.9 1.8
34 29. 1995 9160 222487 24.3 89178 9.7 1.8
35 30. 1996 9319 220094 23.6 88241 9.5 1.7
36 31. 1997 9552 233903 24.5 95829 10.0 2.5
37 32. 1998 9709 258409 26.6 104713 10.8 1.6
38 33. 1999 9866 271918 27.6 110587 11.2 1.6
39 34. 2000 10021 255883 25.5 108593 10.8 1.6
40 35. 2001 10270 271019 26.4 108506 10.6 2.5
41 36. 2002 10506 260122 24.8 110417 10.5 2.3
42 37. 2003 10682 259625 24.3 110851 10.4 1.7
43 38. 2004 10856 277263 25.5 113697 10.5 1.6
44 39. 2005 11028 294175 26.7 113914 10.3 1.6
45 40. 2006 11198 314704 28.1 118112 10.5 1.5
46 41. 2007 11366 340794 30.0 122637 10.8 1.5
47 42. 2008 11531 342309 29.7 125017 10.8 1.4
48 43. 2009 11694 357021 30.5 127151 10.9 1.4
49 44. 2010 11858 384649 32.4 134599 11.4 1.4
50 45. 2011 12102 390884 32.3 135585 11.2 2.1
51 46. 2012 12134 394982 32.6 135445 11.2 1.0
52 47. 2013 12288 400517 32.6 134799 11.0 1.0

18
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@ -1,18 +0,0 @@
"0","1","2"
"","e
bl
a
ail
v
a
t
o
n
a
t
a
D
*",""
1 0 1 2
2 e bl a ail v a t o n a t a D *

3
docs/benchmark/lattice/twotables_1/twotables_1-data-pdfplumber.csv
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@ -1,3 +0,0 @@
"0"
"Sl."
"No."
1 0
2 Sl.
3 No.

3
docs/benchmark/lattice/twotables_2/twotables_2-data-pdfplumber.csv
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@ -1,3 +0,0 @@
"0"
"Table 6 : DISTRIBUTION (%) OF HOUSEHOLDS BY LITERACY STATUS OF"
"MALE HEAD OF THE HOUSEHOLD"
1 0
2 Table 6 : DISTRIBUTION (%) OF HOUSEHOLDS BY LITERACY STATUS OF
3 MALE HEAD OF THE HOUSEHOLD

5
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View File

@ -1,7 +1,3 @@
"[In thousands (11,062.6 represents 11,062,600) For year ending December 31. Based on Uniform Crime Reporting (UCR)","","","","","","","","",""
"Program. Represents arrests reported (not charged) by 12,910 agencies with a total population of 247,526,916 as estimated","","","","","","","","",""
"by the FBI. Some persons may be arrested more than once during a year, therefore, the data in this table, in some cases,","","","","","","","","",""
"could represent multiple arrests of the same person. See text, this section and source]","","","","","","","","",""
"","","Total","","","Male","","","Female","" "","","Total","","","Male","","","Female",""
"Offense charged","","Under 18","18 years","","Under 18","18 years","","Under 18","18 years" "Offense charged","","Under 18","18 years","","Under 18","18 years","","Under 18","18 years"
"","Total","years","and over","Total","years","and over","Total","years","and over" "","Total","years","and over","Total","years","and over","Total","years","and over"
@ -40,4 +36,3 @@
"Curfew and loitering law violations ..","91.0","91.0","(X)","63.1","63.1","(X)","28.0","28.0","(X)" "Curfew and loitering law violations ..","91.0","91.0","(X)","63.1","63.1","(X)","28.0","28.0","(X)"
"Runaways . . . . . . . .. .. .. .. .. ....","75.8","75.8","(X)","34.0","34.0","(X)","41.8","41.8","(X)" "Runaways . . . . . . . .. .. .. .. .. ....","75.8","75.8","(X)","34.0","34.0","(X)","41.8","41.8","(X)"
"","– Represents zero. X Not applicable. 1 Buying, receiving, possessing stolen property. 2 Except forcible rape and prostitution.","","","","","","","","" "","– Represents zero. X Not applicable. 1 Buying, receiving, possessing stolen property. 2 Except forcible rape and prostitution.","","","","","","","",""
"","Source: U.S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports, Arrests Master Files.","","","","","","","",""

1 [In thousands (11,062.6 represents 11,062,600) For year ending December 31. Based on Uniform Crime Reporting (UCR) Total Male Female
[In thousands (11,062.6 represents 11,062,600) For year ending December 31. Based on Uniform Crime Reporting (UCR)
Program. Represents arrests reported (not charged) by 12,910 agencies with a total population of 247,526,916 as estimated
by the FBI. Some persons may be arrested more than once during a year, therefore, the data in this table, in some cases,
could represent multiple arrests of the same person. See text, this section and source]
1 Total Total Male Male Female Female
2 Offense charged Offense charged Under 18 Under 18 18 years Under 18 Under 18 18 years 18 years Under 18 Under 18 18 years 18 years
3 Total years Total years and over Total years years and over and over Total years years and over Total and over
36 Curfew and loitering law violations .. 91.0 Curfew and loitering law violations .. 91.0 91.0 (X) 63.1 63.1 63.1 (X) (X) 28.0 28.0 28.0 (X) 28.0 (X)
37 Runaways . . . . . . . .. .. .. .. .. .... 75.8 Runaways . . . . . . . .. .. .. .. .. .... 75.8 75.8 (X) 34.0 34.0 34.0 (X) (X) 41.8 41.8 41.8 (X) 41.8 (X)
38 – Represents zero. X Not applicable. 1 Buying, receiving, possessing stolen property. 2 Except forcible rape and prostitution. – Represents zero. X Not applicable. 1 Buying, receiving, possessing stolen property. 2 Except forcible rape and prostitution.
Source: U.S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports, Arrests Master Files.

5
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View File

@ -1,7 +1,3 @@
"","Source: U.S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports, Arrests Master Files.","","","",""
"Table 325. Arrests by Race: 2009","","","","",""
"[Based on Uniform Crime Reporting (UCR) Program. Represents arrests reported (not charged) by 12,371 agencies","","","","",""
"with a total population of 239,839,971 as estimated by the FBI. See headnote, Table 324]","","","","",""
"","","","","American","" "","","","","American",""
"Offense charged","","","","Indian/Alaskan","Asian Pacific" "Offense charged","","","","Indian/Alaskan","Asian Pacific"
"","Total","White","Black","Native","Islander" "","Total","White","Black","Native","Islander"
@ -38,4 +34,3 @@
"Curfew and loitering law violations . .. ... .. ....","89,578","54,439","33,207","872","1,060" "Curfew and loitering law violations . .. ... .. ....","89,578","54,439","33,207","872","1,060"
"Runaways . . . . . . . .. .. .. .. .. .. .... .. ..... .","73,616","48,343","19,670","1,653","3,950" "Runaways . . . . . . . .. .. .. .. .. .. .... .. ..... .","73,616","48,343","19,670","1,653","3,950"
"1 Except forcible rape and prostitution.","","","","","" "1 Except forcible rape and prostitution.","","","","",""
"","Source: U.S. Department of Justice, Federal Bureau of Investigation, “Crime in the United States, Arrests,” September 2010,","","","",""

1 Source: U.S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports, Arrests Master Files. American
Source: U.S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports, Arrests Master Files.
Table 325. Arrests by Race: 2009
[Based on Uniform Crime Reporting (UCR) Program. Represents arrests reported (not charged) by 12,371 agencies
with a total population of 239,839,971 as estimated by the FBI. See headnote, Table 324]
1 American American
2 Offense charged Indian/Alaskan Indian/Alaskan Asian Pacific
3 Total White Total Black White Native Black Native Islander
34 Curfew and loitering law violations . .. ... .. .... 89,578 54,439 89,578 33,207 54,439 872 33,207 872 1,060
35 Runaways . . . . . . . .. .. .. .. .. .. .... .. ..... . 73,616 48,343 73,616 19,670 48,343 1,653 19,670 1,653 3,950
36 1 Except forcible rape and prostitution.
Source: U.S. Department of Justice, Federal Bureau of Investigation, “Crime in the United States, Arrests,” September 2010,

78
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@ -1,43 +1,35 @@
"","2012 BETTER VARIETIES Harvest Report for Minnesota Central [ MNCE ]2012 BETTER VARIETIES Harvest Report for Minnesota Central [ MNCE ]","","","","","","","","","","","","ALL SEASON TESTALL SEASON TEST","" "","","","","","SCN","Seed","Yield","Moisture","Lodgingg","g","Stand","","Gross"
"","Doug Toreen, Renville County, MN 55310 [ BIRD ISLAND ]Doug Toreen, Renville County, MN 55310","","","","","[ BIRD ISLAND ]","","","","","","","1.3 - 2.0 MAT. GROUP1.3 - 2.0 MAT. GROUP","" "Company/Brandpy","","Product/Brand†","Technol.†","Mat.","Resist.","Trmt.†","Bu/A","%","%","","(x 1000)(",")","Income"
"PREVPREV. CROP/HERB:","CROP/HERB","C/ S","Corn / Surpass, RoundupR","d","","","","","","","","","","S2MNCE01S2MNCE01" "KrugerKruger","","K2-1901K2 1901","RR2YRR2Y","1.91.9","RR","Ac,PVAc,PV","56.456.4","7.67.6","00","","126.3126.3","","$846$846"
"SOIL DESCRIPTION:","","C","Canisteo clay loam, mod. well drained, non-irrigated","","","","","","","","","","","" "StineStine","","19RA02 §19RA02 §","RR2YRR2Y","1 91.9","RR","CMBCMB","55.355.3","7 67.6","00","","120 0120.0","","$830$830"
"SOIL CONDITIONS:","","","High P, high K, 6.7 pH, 3.9% OM, Low SCN","","","","","","","","","","","30"" ROW SPACING" "WensmanWensman","","W 3190NR2W 3190NR2","RR2YRR2Y","1 91.9","RR","AcAc","54 554.5","7 67.6","00","","119 5119.5","","$818$818"
"TILLAGE/CULTIVATION:TILLAGE/CULTIVATION:","","","conventional w/ fall tillconventional w/ fall till","","","","","","","","","","","" "H ftHefty","","H17Y12H17Y12","RR2YRR2Y","1 71.7","MRMR","II","53 753.7","7 77.7","00","","124 4124.4","","$806$806"
"PEST MANAGEMENT:PEST MANAGEMENT:","","Roundup twiceRoundup twice","","","","","","","","","","","","" "Dyna-Gro","","S15RY53","RR2Y","1.5","R","Ac","53.6","7.7","0","","126.8","","$804"
"SEEDED - RATE:","","May 15M15","140,000 /A140 000 /A","","","","","","","","TOP 30 foTOP 30 for YIELD of 63 TESTED","","YIELD of 63 TESTED","" "LG SeedsLG Seeds","","C2050R2C2050R2","RR2YRR2Y","2.12.1","RR","AcAc","53.653.6","7.77.7","00","","123.9123.9","","$804$804"
"HARVESTEDHARVESTED - STAND:","STAND","O t 3Oct 3","122 921 /A122,921 /A","","","","","","","","","AVERAGE of (3) REPLICATIONSAVERAGE of (3) REPLICATIONS","","" "Titan ProTitan Pro","","19M4219M42","RR2YRR2Y","1.91.9","RR","CMBCMB","53.653.6","7.77.7","00","","121.0121.0","","$804$804"
"","","","","","","SCN","Seed","Yield","Moisture","Lodgingg","g","Stand","","Gross" "StineStine","","19RA02 (2) §19RA02 (2) §","RR2YRR2Y","1 91.9","RR","CMBCMB","53 453.4","7 77.7","00","","123 9123.9","","$801$801"
"","Company/Brandpy","Product/Brand†","","Technol.†","Mat.","Resist.","Trmt.†","Bu/A","%","%","","(x 1000)(",")","Income" "AsgrowAsgrow","","AG1832 §AG1832 §","RR2YRR2Y","1 81.8","MRMR","Ac PVAc,PV","52 952.9","7 77.7","00","","122 0122.0","","$794$794"
"","KrugerKruger","K2-1901K2 1901","","RR2YRR2Y","1.91.9","RR","Ac,PVAc,PV","56.456.4","7.67.6","00","","126.3126.3","","$846$846" "Prairie Brandiid","","PB-1566R2662","RR2Y2","1.5","R","CMB","52.8","7.7","0","","122.9","","$792$"
"","StineStine","19RA02 §19RA02 §","","RR2YRR2Y","1 91.9","RR","CMBCMB","55.355.3","7 67.6","00","","120 0120.0","","$830$830" "Channel","","1901R2","RR2Y","1.9","R","Ac,PV,","52.8","7.6","0","","123.4","","$791$"
"","WensmanWensman","W 3190NR2W 3190NR2","","RR2YRR2Y","1 91.9","RR","AcAc","54 554.5","7 67.6","00","","119 5119.5","","$818$818" "Titan ProTitan Pro","","20M120M1","RR2YRR2Y","2.02.0","RR","AmAm","52.552.5","7.57.5","00","","124.4124.4","","$788$788"
"","H ftHefty","H17Y12H17Y12","","RR2YRR2Y","1 71.7","MRMR","II","53 753.7","7 77.7","00","","124 4124.4","","$806$806" "KrugerKruger","","K2-2002K2-2002","RR2YRR2Y","2 02.0","RR","Ac PVAc,PV","52 452.4","7 97.9","00","","125 4125.4","","$786$786"
"","Dyna-Gro","S15RY53","","RR2Y","1.5","R","Ac","53.6","7.7","0","","126.8","","$804" "ChannelChannel","","1700R21700R2","RR2YRR2Y","1 71.7","RR","Ac PVAc,PV","52 352.3","7 97.9","00","","123 9123.9","","$784$784"
"","LG SeedsLG Seeds","C2050R2C2050R2","","RR2YRR2Y","2.12.1","RR","AcAc","53.653.6","7.77.7","00","","123.9123.9","","$804$804" "H ftHefty","","H16Y11H16Y11","RR2YRR2Y","1 61.6","MRMR","II","51 451.4","7 67.6","00","","123 9123.9","","$771$771"
"","Titan ProTitan Pro","19M4219M42","","RR2YRR2Y","1.91.9","RR","CMBCMB","53.653.6","7.77.7","00","","121.0121.0","","$804$804" "Anderson","","162R2Y","RR2Y","1.6","R","None","51.3","7.5","0","","119.5","","$770"
"","StineStine","19RA02 (2) §19RA02 (2) §","","RR2YRR2Y","1 91.9","RR","CMBCMB","53 453.4","7 77.7","00","","123 9123.9","","$801$801" "Titan ProTitan Pro","","15M2215M22","RR2YRR2Y","1.51.5","RR","CMBCMB","51.351.3","7.87.8","00","","125.4125.4","","$769$769"
"","AsgrowAsgrow","AG1832 §AG1832 §","","RR2YRR2Y","1 81.8","MRMR","Ac PVAc,PV","52 952.9","7 77.7","00","","122 0122.0","","$794$794" "DairylandDairyland","","DSR-1710R2YDSR-1710R2Y","RR2YRR2Y","1 71.7","RR","CMBCMB","51 351.3","7 77.7","00","","122 0122.0","","$769$769"
"","Prairie Brandiid","PB-1566R2662","","RR2Y2","1.5","R","CMB","52.8","7.7","0","","122.9","","$792$" "HeftyHefty","","H20R3H20R3","RR2YRR2Y","2 02.0","MRMR","II","50 550.5","8 28.2","00","","121 0121.0","","$757$757"
"","Channel","1901R2","","RR2Y","1.9","R","Ac,PV,","52.8","7.6","0","","123.4","","$791$" "PPrairie BrandiiBd","","PB 1743R2PB-1743R2","RR2YRR2Y","1 71.7","RR","CMBCMB","50 250.2","7 77.7","00","","125 8125.8","","$752$752"
"","Titan ProTitan Pro","20M120M1","","RR2YRR2Y","2.02.0","RR","AmAm","52.552.5","7.57.5","00","","124.4124.4","","$788$788" "Gold Country","","1741","RR2Y","1.7","R","Ac","50.1","7.8","0","","123.9","","$751"
"","KrugerKruger","K2-2002K2-2002","","RR2YRR2Y","2 02.0","RR","Ac PVAc,PV","52 452.4","7 97.9","00","","125 4125.4","","$786$786" "Trelaye ay","","20RR4303","RR2Y","2.00","R","Ac,Exc,","49.99 9","7.66","00","","127.88","","$749$9"
"","ChannelChannel","1700R21700R2","","RR2YRR2Y","1 71.7","RR","Ac PVAc,PV","52 352.3","7 97.9","00","","123 9123.9","","$784$784" "HeftyHefty","","H14R3H14R3","RR2YRR2Y","1.41.4","MRMR","II","49.749.7","7.77.7","00","","122.9122.9","","$746$746"
"","H ftHefty","H16Y11H16Y11","","RR2YRR2Y","1 61.6","MRMR","II","51 451.4","7 67.6","00","","123 9123.9","","$771$771" "Prairie BrandPrairie Brand","","PB-2099NRR2PB-2099NRR2","RR2YRR2Y","2 02.0","RR","CMBCMB","49 649.6","7 87.8","00","","126 3126.3","","$743$743"
"","Anderson","162R2Y","","RR2Y","1.6","R","None","51.3","7.5","0","","119.5","","$770" "WensmanWensman","","W 3174NR2W 3174NR2","RR2YRR2Y","1 71.7","RR","AcAc","49 349.3","7 67.6","00","","122 5122.5","","$740$740"
"","Titan ProTitan Pro","15M2215M22","","RR2YRR2Y","1.51.5","RR","CMBCMB","51.351.3","7.87.8","00","","125.4125.4","","$769$769" "KKruger","","K2 1602K2-1602","RR2YRR2Y","1 61.6","R","Ac,PV","48.78","7.66","00","","125.412","","$731$31"
"","DairylandDairyland","DSR-1710R2YDSR-1710R2Y","","RR2YRR2Y","1 71.7","RR","CMBCMB","51 351.3","7 77.7","00","","122 0122.0","","$769$769" "NK Brand","","S18-C2 §§","RR2Y","1.8","R","CMB","48.7","7.7","0","","126.8","","$731$"
"","HeftyHefty","H20R3H20R3","","RR2YRR2Y","2 02.0","MRMR","II","50 550.5","8 28.2","00","","121 0121.0","","$757$757" "KrugerKruger","","K2-1902K2 1902","RR2YRR2Y","1.91.9","RR","Ac,PVAc,PV","48.748.7","7.57.5","00","","124.4124.4","","$730$730"
"","PPrairie BrandiiBd","PB 1743R2PB-1743R2","","RR2YRR2Y","1 71.7","RR","CMBCMB","50 250.2","7 77.7","00","","125 8125.8","","$752$752" "Prairie BrandPrairie Brand","","PB-1823R2PB-1823R2","RR2YRR2Y","1 81.8","RR","NoneNone","48 548.5","7 67.6","00","","121 0121.0","","$727$727"
"","Gold Country","1741","","RR2Y","1.7","R","Ac","50.1","7.8","0","","123.9","","$751" "Gold CountryGold Country","","15411541","RR2YRR2Y","1 51.5","RR","AcAc","48 448.4","7 67.6","00","","110 4110.4","","$726$726"
"","Trelaye ay","20RR4303","","RR2Y","2.00","R","Ac,Exc,","49.99 9","7.66","00","","127.88","","$749$9" "","","","","","","Test Average =","47 647.6","7 77.7","00","","122 9122.9","","$713$713"
"","HeftyHefty","H14R3H14R3","","RR2YRR2Y","1.41.4","MRMR","II","49.749.7","7.77.7","00","","122.9122.9","","$746$746" "","","","","","","LSD (0.10) =","5.7","0.3","ns","","37.8","","566.4"
"","Prairie BrandPrairie Brand","PB-2099NRR2PB-2099NRR2","","RR2YRR2Y","2 02.0","RR","CMBCMB","49 649.6","7 87.8","00","","126 3126.3","","$743$743" "","F.I.R.S.T. Managerg","","","","","C.V. =","8.8","2.9","","","56.4","","846.2"
"","WensmanWensman","W 3174NR2W 3174NR2","","RR2YRR2Y","1 71.7","RR","AcAc","49 349.3","7 67.6","00","","122 5122.5","","$740$740"
"","KKruger","K2 1602K2-1602","","RR2YRR2Y","1 61.6","R","Ac,PV","48.78","7.66","00","","125.412","","$731$31"
"","NK Brand","S18-C2 §§","","RR2Y","1.8","R","CMB","48.7","7.7","0","","126.8","","$731$"
"","KrugerKruger","K2-1902K2 1902","","RR2YRR2Y","1.91.9","RR","Ac,PVAc,PV","48.748.7","7.57.5","00","","124.4124.4","","$730$730"
"","Prairie BrandPrairie Brand","PB-1823R2PB-1823R2","","RR2YRR2Y","1 81.8","RR","NoneNone","48 548.5","7 67.6","00","","121 0121.0","","$727$727"
"","Gold CountryGold Country","15411541","","RR2YRR2Y","1 51.5","RR","AcAc","48 448.4","7 67.6","00","","110 4110.4","","$726$726"
"","","","","","","","Test Average =","47 647.6","7 77.7","00","","122 9122.9","","$713$713"
"","","","","","","","LSD (0.10) =","5.7","0.3","ns","","37.8","","566.4"

1 2012 BETTER VARIETIES Harvest Report for Minnesota Central [ MNCE ]2012 BETTER VARIETIES Harvest Report for Minnesota Central [ MNCE ] SCN Seed Yield Moisture Lodgingg g Stand ALL SEASON TESTALL SEASON TEST Gross
2 Company/Brandpy Doug Toreen, Renville County, MN 55310 [ BIRD ISLAND ]Doug Toreen, Renville County, MN 55310 Product/Brand† Technol.† Mat. Resist. Trmt.† Bu/A % % (x 1000)( [ BIRD ISLAND ] ) 1.3 - 2.0 MAT. GROUP1.3 - 2.0 MAT. GROUP Income
3 PREVPREV. CROP/HERB: KrugerKruger CROP/HERB C/ S Corn / Surpass, RoundupR K2-1901K2 1901 d RR2YRR2Y 1.91.9 RR Ac,PVAc,PV 56.456.4 7.67.6 00 126.3126.3 $846$846 S2MNCE01S2MNCE01
4 SOIL DESCRIPTION: StineStine C Canisteo clay loam, mod. well drained, non-irrigated 19RA02 §19RA02 § RR2YRR2Y 1 91.9 RR CMBCMB 55.355.3 7 67.6 00 120 0120.0 $830$830
5 SOIL CONDITIONS: WensmanWensman High P, high K, 6.7 pH, 3.9% OM, Low SCN W 3190NR2W 3190NR2 RR2YRR2Y 1 91.9 RR AcAc 54 554.5 7 67.6 00 119 5119.5 $818$818 30" ROW SPACING
6 TILLAGE/CULTIVATION:TILLAGE/CULTIVATION: H ftHefty conventional w/ fall tillconventional w/ fall till H17Y12H17Y12 RR2YRR2Y 1 71.7 MRMR II 53 753.7 7 77.7 00 124 4124.4 $806$806
7 PEST MANAGEMENT:PEST MANAGEMENT: Dyna-Gro Roundup twiceRoundup twice S15RY53 RR2Y 1.5 R Ac 53.6 7.7 0 126.8 $804
8 SEEDED - RATE: LG SeedsLG Seeds May 15M15 140,000 /A140 000 /A C2050R2C2050R2 RR2YRR2Y 2.12.1 RR AcAc 53.653.6 7.77.7 00 TOP 30 foTOP 30 for YIELD of 63 TESTED 123.9123.9 YIELD of 63 TESTED $804$804
9 HARVESTEDHARVESTED - STAND: Titan ProTitan Pro STAND O t 3Oct 3 122 921 /A122,921 /A 19M4219M42 RR2YRR2Y 1.91.9 RR CMBCMB 53.653.6 7.77.7 00 121.0121.0 AVERAGE of (3) REPLICATIONSAVERAGE of (3) REPLICATIONS $804$804
10 StineStine 19RA02 (2) §19RA02 (2) § RR2YRR2Y 1 91.9 RR CMBCMB 53 453.4 Yield 7 77.7 Moisture 00 Lodgingg Seed g 123 9123.9 Stand SCN $801$801 Gross
11 AsgrowAsgrow Company/Brandpy Product/Brand† AG1832 §AG1832 § Technol.† RR2YRR2Y Mat. 1 81.8 MRMR Ac PVAc,PV 52 952.9 Bu/A 7 77.7 % 00 % Trmt.† 122 0122.0 (x 1000)( Resist. ) $794$794 Income
12 Prairie Brandiid KrugerKruger K2-1901K2 1901 PB-1566R2662 RR2YRR2Y RR2Y2 1.91.9 1.5 R CMB 52.8 56.456.4 7.7 7.67.6 0 00 Ac,PVAc,PV 122.9 126.3126.3 RR $792$ $846$846
13 Channel StineStine 19RA02 §19RA02 § 1901R2 RR2YRR2Y RR2Y 1 91.9 1.9 R Ac,PV, 52.8 55.355.3 7.6 7 67.6 0 00 CMBCMB 123.4 120 0120.0 RR $791$ $830$830
14 Titan ProTitan Pro WensmanWensman W 3190NR2W 3190NR2 20M120M1 RR2YRR2Y 1 91.9 2.02.0 RR AmAm 52.552.5 54 554.5 7.57.5 7 67.6 00 00 AcAc 124.4124.4 119 5119.5 RR $788$788 $818$818
15 KrugerKruger H ftHefty H17Y12H17Y12 K2-2002K2-2002 RR2YRR2Y 1 71.7 2 02.0 RR Ac PVAc,PV 52 452.4 53 753.7 7 97.9 7 77.7 00 00 II 125 4125.4 124 4124.4 MRMR $786$786 $806$806
16 ChannelChannel Dyna-Gro S15RY53 1700R21700R2 RR2Y RR2YRR2Y 1.5 1 71.7 RR Ac PVAc,PV 52 352.3 53.6 7 97.9 7.7 00 0 Ac 123 9123.9 126.8 R $784$784 $804
17 H ftHefty LG SeedsLG Seeds C2050R2C2050R2 H16Y11H16Y11 RR2YRR2Y 2.12.1 1 61.6 MRMR II 51 451.4 53.653.6 7 67.6 7.77.7 00 00 AcAc 123 9123.9 123.9123.9 RR $771$771 $804$804
18 Anderson Titan ProTitan Pro 19M4219M42 162R2Y RR2YRR2Y RR2Y 1.91.9 1.6 R None 51.3 53.653.6 7.5 7.77.7 0 00 CMBCMB 119.5 121.0121.0 RR $770 $804$804
19 Titan ProTitan Pro StineStine 19RA02 (2) §19RA02 (2) § 15M2215M22 RR2YRR2Y 1 91.9 1.51.5 RR CMBCMB 51.351.3 53 453.4 7.87.8 7 77.7 00 00 CMBCMB 125.4125.4 123 9123.9 RR $769$769 $801$801
20 DairylandDairyland AsgrowAsgrow AG1832 §AG1832 § DSR-1710R2YDSR-1710R2Y RR2YRR2Y 1 81.8 1 71.7 RR CMBCMB 51 351.3 52 952.9 7 77.7 7 77.7 00 00 Ac PVAc,PV 122 0122.0 122 0122.0 MRMR $769$769 $794$794
21 HeftyHefty Prairie Brandiid PB-1566R2662 H20R3H20R3 RR2Y2 RR2YRR2Y 1.5 2 02.0 MRMR II 50 550.5 52.8 8 28.2 7.7 00 0 CMB 121 0121.0 122.9 R $757$757 $792$
22 PPrairie BrandiiBd Channel 1901R2 PB 1743R2PB-1743R2 RR2Y RR2YRR2Y 1.9 1 71.7 RR CMBCMB 50 250.2 52.8 7 77.7 7.6 00 0 Ac,PV, 125 8125.8 123.4 R $752$752 $791$
23 Gold Country Titan ProTitan Pro 20M120M1 1741 RR2YRR2Y RR2Y 2.02.0 1.7 R Ac 50.1 52.552.5 7.8 7.57.5 0 00 AmAm 123.9 124.4124.4 RR $751 $788$788
24 Trelaye ay KrugerKruger K2-2002K2-2002 20RR4303 RR2YRR2Y RR2Y 2 02.0 2.00 R Ac,Exc, 49.99 9 52 452.4 7.66 7 97.9 00 00 Ac PVAc,PV 127.88 125 4125.4 RR $749$9 $786$786
25 HeftyHefty ChannelChannel 1700R21700R2 H14R3H14R3 RR2YRR2Y 1 71.7 1.41.4 MRMR II 49.749.7 52 352.3 7.77.7 7 97.9 00 00 Ac PVAc,PV 122.9122.9 123 9123.9 RR $746$746 $784$784
26 Prairie BrandPrairie Brand H ftHefty H16Y11H16Y11 PB-2099NRR2PB-2099NRR2 RR2YRR2Y 1 61.6 2 02.0 RR CMBCMB 49 649.6 51 451.4 7 87.8 7 67.6 00 00 II 126 3126.3 123 9123.9 MRMR $743$743 $771$771
27 WensmanWensman Anderson 162R2Y W 3174NR2W 3174NR2 RR2Y RR2YRR2Y 1.6 1 71.7 RR AcAc 49 349.3 51.3 7 67.6 7.5 00 0 None 122 5122.5 119.5 R $740$740 $770
28 KKruger Titan ProTitan Pro 15M2215M22 K2 1602K2-1602 RR2YRR2Y 1.51.5 1 61.6 R Ac,PV 48.78 51.351.3 7.66 7.87.8 00 00 CMBCMB 125.412 125.4125.4 RR $731$31 $769$769
29 NK Brand DairylandDairyland DSR-1710R2YDSR-1710R2Y S18-C2 §§ RR2YRR2Y RR2Y 1 71.7 1.8 R CMB 48.7 51 351.3 7.7 7 77.7 0 00 CMBCMB 126.8 122 0122.0 RR $731$ $769$769
30 KrugerKruger HeftyHefty H20R3H20R3 K2-1902K2 1902 RR2YRR2Y 2 02.0 1.91.9 RR Ac,PVAc,PV 48.748.7 50 550.5 7.57.5 8 28.2 00 00 II 124.4124.4 121 0121.0 MRMR $730$730 $757$757
31 Prairie BrandPrairie Brand PPrairie BrandiiBd PB 1743R2PB-1743R2 PB-1823R2PB-1823R2 RR2YRR2Y 1 71.7 1 81.8 RR NoneNone 48 548.5 50 250.2 7 67.6 7 77.7 00 00 CMBCMB 121 0121.0 125 8125.8 RR $727$727 $752$752
32 Gold CountryGold Country Gold Country 1741 15411541 RR2Y RR2YRR2Y 1.7 1 51.5 RR AcAc 48 448.4 50.1 7 67.6 7.8 00 0 Ac 110 4110.4 123.9 R $726$726 $751
33 Trelaye ay 20RR4303 RR2Y 2.00 Test Average = 47 647.6 49.99 9 7 77.7 7.66 00 00 Ac,Exc, 122 9122.9 127.88 R $713$713 $749$9
34 HeftyHefty H14R3H14R3 RR2YRR2Y 1.41.4 LSD (0.10) = 5.7 49.749.7 0.3 7.77.7 ns 00 II 37.8 122.9122.9 MRMR 566.4 $746$746
35 Prairie BrandPrairie Brand PB-2099NRR2PB-2099NRR2 F.I.R.S.T. Managerg RR2YRR2Y 2 02.0 C.V. = 8.8 49 649.6 2.9 7 87.8 00 CMBCMB 56.4 126 3126.3 RR 846.2 $743$743
WensmanWensman W 3174NR2W 3174NR2 RR2YRR2Y 1 71.7 49 349.3 7 67.6 00 AcAc 122 5122.5 RR $740$740
KKruger K2 1602K2-1602 RR2YRR2Y 1 61.6 48.78 7.66 00 Ac,PV 125.412 R $731$31
NK Brand S18-C2 §§ RR2Y 1.8 48.7 7.7 0 CMB 126.8 R $731$
KrugerKruger K2-1902K2 1902 RR2YRR2Y 1.91.9 48.748.7 7.57.5 00 Ac,PVAc,PV 124.4124.4 RR $730$730
Prairie BrandPrairie Brand PB-1823R2PB-1823R2 RR2YRR2Y 1 81.8 48 548.5 7 67.6 00 NoneNone 121 0121.0 RR $727$727
Gold CountryGold Country 15411541 RR2YRR2Y 1 51.5 48 448.4 7 67.6 00 AcAc 110 4110.4 RR $726$726
47 647.6 7 77.7 00 Test Average = 122 9122.9 $713$713
5.7 0.3 ns LSD (0.10) = 37.8 566.4

39
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@ -1,39 +0,0 @@
"TILLAGE/CULTIVATION:TILLAGE/CULTIVATION:","","conventional w/ fall tillconventional w/ fall till","","","","","","","","","","",""
"PEST MANAGEMENT:PEST MANAGEMENT:","","Roundup twiceRoundup twice","","","","","","","","","","",""
"SEEDED - RATE:","","May 15M15","140,000 /A140 000 /A","","","","","","","TOP 30 foTOP 30 for YIELD of 63 TESTED","","YIELD of 63 TESTED",""
"HARVESTEDHARVESTED - STAND:STAND","","O t 3Oct 3","122 921 /A122,921 /A","","","","","","","","AVERAGE of (3) REPLICATIONSAVERAGE of (3) REPLICATIONS","",""
"","","","","","SCN","Seed","Yield","Moisture","Lodgingg","g","Stand","","Gross"
"Company/Brandpy","","Product/Brand†","Technol.†","Mat.","Resist.","Trmt.†","Bu/A","%","%","","(x 1000)(",")","Income"
"KrugerKruger","","K2-1901K2 1901","RR2YRR2Y","1.91.9","RR","Ac,PVAc,PV","56.456.4","7.67.6","00","","126.3126.3","","$846$846"
"StineStine","","19RA02 §19RA02 §","RR2YRR2Y","1 91.9","RR","CMBCMB","55.355.3","7 67.6","00","","120 0120.0","","$830$830"
"WensmanWensman","","W 3190NR2W 3190NR2","RR2YRR2Y","1 91.9","RR","AcAc","54 554.5","7 67.6","00","","119 5119.5","","$818$818"
"H ftHefty","","H17Y12H17Y12","RR2YRR2Y","1 71.7","MRMR","II","53 753.7","7 77.7","00","","124 4124.4","","$806$806"
"Dyna-Gro","","S15RY53","RR2Y","1.5","R","Ac","53.6","7.7","0","","126.8","","$804"
"LG SeedsLG Seeds","","C2050R2C2050R2","RR2YRR2Y","2.12.1","RR","AcAc","53.653.6","7.77.7","00","","123.9123.9","","$804$804"
"Titan ProTitan Pro","","19M4219M42","RR2YRR2Y","1.91.9","RR","CMBCMB","53.653.6","7.77.7","00","","121.0121.0","","$804$804"
"StineStine","","19RA02 (2) §19RA02 (2) §","RR2YRR2Y","1 91.9","RR","CMBCMB","53 453.4","7 77.7","00","","123 9123.9","","$801$801"
"AsgrowAsgrow","","AG1832 §AG1832 §","RR2YRR2Y","1 81.8","MRMR","Ac PVAc,PV","52 952.9","7 77.7","00","","122 0122.0","","$794$794"
"Prairie Brandiid","","PB-1566R2662","RR2Y2","1.5","R","CMB","52.8","7.7","0","","122.9","","$792$"
"Channel","","1901R2","RR2Y","1.9","R","Ac,PV,","52.8","7.6","0","","123.4","","$791$"
"Titan ProTitan Pro","","20M120M1","RR2YRR2Y","2.02.0","RR","AmAm","52.552.5","7.57.5","00","","124.4124.4","","$788$788"
"KrugerKruger","","K2-2002K2-2002","RR2YRR2Y","2 02.0","RR","Ac PVAc,PV","52 452.4","7 97.9","00","","125 4125.4","","$786$786"
"ChannelChannel","","1700R21700R2","RR2YRR2Y","1 71.7","RR","Ac PVAc,PV","52 352.3","7 97.9","00","","123 9123.9","","$784$784"
"H ftHefty","","H16Y11H16Y11","RR2YRR2Y","1 61.6","MRMR","II","51 451.4","7 67.6","00","","123 9123.9","","$771$771"
"Anderson","","162R2Y","RR2Y","1.6","R","None","51.3","7.5","0","","119.5","","$770"
"Titan ProTitan Pro","","15M2215M22","RR2YRR2Y","1.51.5","RR","CMBCMB","51.351.3","7.87.8","00","","125.4125.4","","$769$769"
"DairylandDairyland","","DSR-1710R2YDSR-1710R2Y","RR2YRR2Y","1 71.7","RR","CMBCMB","51 351.3","7 77.7","00","","122 0122.0","","$769$769"
"HeftyHefty","","H20R3H20R3","RR2YRR2Y","2 02.0","MRMR","II","50 550.5","8 28.2","00","","121 0121.0","","$757$757"
"PPrairie BrandiiBd","","PB 1743R2PB-1743R2","RR2YRR2Y","1 71.7","RR","CMBCMB","50 250.2","7 77.7","00","","125 8125.8","","$752$752"
"Gold Country","","1741","RR2Y","1.7","R","Ac","50.1","7.8","0","","123.9","","$751"
"Trelaye ay","","20RR4303","RR2Y","2.00","R","Ac,Exc,","49.99 9","7.66","00","","127.88","","$749$9"
"HeftyHefty","","H14R3H14R3","RR2YRR2Y","1.41.4","MRMR","II","49.749.7","7.77.7","00","","122.9122.9","","$746$746"
"Prairie BrandPrairie Brand","","PB-2099NRR2PB-2099NRR2","RR2YRR2Y","2 02.0","RR","CMBCMB","49 649.6","7 87.8","00","","126 3126.3","","$743$743"
"WensmanWensman","","W 3174NR2W 3174NR2","RR2YRR2Y","1 71.7","RR","AcAc","49 349.3","7 67.6","00","","122 5122.5","","$740$740"
"KKruger","","K2 1602K2-1602","RR2YRR2Y","1 61.6","R","Ac,PV","48.78","7.66","00","","125.412","","$731$31"
"NK Brand","","S18-C2 §§","RR2Y","1.8","R","CMB","48.7","7.7","0","","126.8","","$731$"
"KrugerKruger","","K2-1902K2 1902","RR2YRR2Y","1.91.9","RR","Ac,PVAc,PV","48.748.7","7.57.5","00","","124.4124.4","","$730$730"
"Prairie BrandPrairie Brand","","PB-1823R2PB-1823R2","RR2YRR2Y","1 81.8","RR","NoneNone","48 548.5","7 67.6","00","","121 0121.0","","$727$727"
"Gold CountryGold Country","","15411541","RR2YRR2Y","1 51.5","RR","AcAc","48 448.4","7 67.6","00","","110 4110.4","","$726$726"
"","","","","","","Test Average =","47 647.6","7 77.7","00","","122 9122.9","","$713$713"
"","","","","","","LSD (0.10) =","5.7","0.3","ns","","37.8","","566.4"
"","F.I.R.S.T. Managerg","","","","","C.V. =","8.8","2.9","","","56.4","","846.2"
1 TILLAGE/CULTIVATION:TILLAGE/CULTIVATION: conventional w/ fall tillconventional w/ fall till
2 PEST MANAGEMENT:PEST MANAGEMENT: Roundup twiceRoundup twice
3 SEEDED - RATE: May 15M15 140,000 /A140 000 /A TOP 30 foTOP 30 for YIELD of 63 TESTED YIELD of 63 TESTED
4 HARVESTEDHARVESTED - STAND:STAND O t 3Oct 3 122 921 /A122,921 /A AVERAGE of (3) REPLICATIONSAVERAGE of (3) REPLICATIONS
5 SCN Seed Yield Moisture Lodgingg g Stand Gross
6 Company/Brandpy Product/Brand† Technol.† Mat. Resist. Trmt.† Bu/A % % (x 1000)( ) Income
7 KrugerKruger K2-1901K2 1901 RR2YRR2Y 1.91.9 RR Ac,PVAc,PV 56.456.4 7.67.6 00 126.3126.3 $846$846
8 StineStine 19RA02 §19RA02 § RR2YRR2Y 1 91.9 RR CMBCMB 55.355.3 7 67.6 00 120 0120.0 $830$830
9 WensmanWensman W 3190NR2W 3190NR2 RR2YRR2Y 1 91.9 RR AcAc 54 554.5 7 67.6 00 119 5119.5 $818$818
10 H ftHefty H17Y12H17Y12 RR2YRR2Y 1 71.7 MRMR II 53 753.7 7 77.7 00 124 4124.4 $806$806
11 Dyna-Gro S15RY53 RR2Y 1.5 R Ac 53.6 7.7 0 126.8 $804
12 LG SeedsLG Seeds C2050R2C2050R2 RR2YRR2Y 2.12.1 RR AcAc 53.653.6 7.77.7 00 123.9123.9 $804$804
13 Titan ProTitan Pro 19M4219M42 RR2YRR2Y 1.91.9 RR CMBCMB 53.653.6 7.77.7 00 121.0121.0 $804$804
14 StineStine 19RA02 (2) §19RA02 (2) § RR2YRR2Y 1 91.9 RR CMBCMB 53 453.4 7 77.7 00 123 9123.9 $801$801
15 AsgrowAsgrow AG1832 §AG1832 § RR2YRR2Y 1 81.8 MRMR Ac PVAc,PV 52 952.9 7 77.7 00 122 0122.0 $794$794
16 Prairie Brandiid PB-1566R2662 RR2Y2 1.5 R CMB 52.8 7.7 0 122.9 $792$
17 Channel 1901R2 RR2Y 1.9 R Ac,PV, 52.8 7.6 0 123.4 $791$
18 Titan ProTitan Pro 20M120M1 RR2YRR2Y 2.02.0 RR AmAm 52.552.5 7.57.5 00 124.4124.4 $788$788
19 KrugerKruger K2-2002K2-2002 RR2YRR2Y 2 02.0 RR Ac PVAc,PV 52 452.4 7 97.9 00 125 4125.4 $786$786
20 ChannelChannel 1700R21700R2 RR2YRR2Y 1 71.7 RR Ac PVAc,PV 52 352.3 7 97.9 00 123 9123.9 $784$784
21 H ftHefty H16Y11H16Y11 RR2YRR2Y 1 61.6 MRMR II 51 451.4 7 67.6 00 123 9123.9 $771$771
22 Anderson 162R2Y RR2Y 1.6 R None 51.3 7.5 0 119.5 $770
23 Titan ProTitan Pro 15M2215M22 RR2YRR2Y 1.51.5 RR CMBCMB 51.351.3 7.87.8 00 125.4125.4 $769$769
24 DairylandDairyland DSR-1710R2YDSR-1710R2Y RR2YRR2Y 1 71.7 RR CMBCMB 51 351.3 7 77.7 00 122 0122.0 $769$769
25 HeftyHefty H20R3H20R3 RR2YRR2Y 2 02.0 MRMR II 50 550.5 8 28.2 00 121 0121.0 $757$757
26 PPrairie BrandiiBd PB 1743R2PB-1743R2 RR2YRR2Y 1 71.7 RR CMBCMB 50 250.2 7 77.7 00 125 8125.8 $752$752
27 Gold Country 1741 RR2Y 1.7 R Ac 50.1 7.8 0 123.9 $751
28 Trelaye ay 20RR4303 RR2Y 2.00 R Ac,Exc, 49.99 9 7.66 00 127.88 $749$9
29 HeftyHefty H14R3H14R3 RR2YRR2Y 1.41.4 MRMR II 49.749.7 7.77.7 00 122.9122.9 $746$746
30 Prairie BrandPrairie Brand PB-2099NRR2PB-2099NRR2 RR2YRR2Y 2 02.0 RR CMBCMB 49 649.6 7 87.8 00 126 3126.3 $743$743
31 WensmanWensman W 3174NR2W 3174NR2 RR2YRR2Y 1 71.7 RR AcAc 49 349.3 7 67.6 00 122 5122.5 $740$740
32 KKruger K2 1602K2-1602 RR2YRR2Y 1 61.6 R Ac,PV 48.78 7.66 00 125.412 $731$31
33 NK Brand S18-C2 §§ RR2Y 1.8 R CMB 48.7 7.7 0 126.8 $731$
34 KrugerKruger K2-1902K2 1902 RR2YRR2Y 1.91.9 RR Ac,PVAc,PV 48.748.7 7.57.5 00 124.4124.4 $730$730
35 Prairie BrandPrairie Brand PB-1823R2PB-1823R2 RR2YRR2Y 1 81.8 RR NoneNone 48 548.5 7 67.6 00 121 0121.0 $727$727
36 Gold CountryGold Country 15411541 RR2YRR2Y 1 51.5 RR AcAc 48 448.4 7 67.6 00 110 4110.4 $726$726
37 Test Average = 47 647.6 7 77.7 00 122 9122.9 $713$713
38 LSD (0.10) = 5.7 0.3 ns 37.8 566.4
39 F.I.R.S.T. Managerg C.V. = 8.8 2.9 56.4 846.2

66
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@ -1,66 +0,0 @@
"0","1","2","3","4"
"","DLHS-4 (2012-13)","","DLHS-3 (2007-08)",""
"Indicators","TOTAL","RURAL","TOTAL","RURAL"
"Child feeding practices (based on last-born child in the reference period) (%)","","","",""
"Children age 0-5 months exclusively breastfed9 .......................................................................... 76.9 80.0
Children age 6-9 months receiving solid/semi-solid food and breast milk .................................... 78.6 75.0
Children age 12-23 months receiving breast feeding along with complementary feeding ........... 31.8 24.2
Children age 6-35 months exclusively breastfed for at least 6 months ........................................ 4.7 3.4
Children under 3 years breastfed within one hour of birth ............................................................ 42.9 46.5","","","NA","NA"
"","","","85.9","89.3"
"","","","NA","NA"
"","","","30.0","27.7"
"","","","50.6","52.9"
"Birth Weight (%) (age below 36 months)","","","",""
"Percentage of Children weighed at birth ...................................................................................... 38.8 41.0 NA NA
Percentage of Children with low birth weight (out of those who weighted) ( below 2.5 kg) ......... 12.8 14.6 NA NA","","","",""
"Awareness about Diarrhoea (%)","","","",""
"Women know about what to do when a child gets diarrhoea ..................................................... 96.3 96.2","","","94.4","94.2"
"Awareness about ARI (%)","","","",""
"Women aware about danger signs of ARI10 ................................................................................. 55.9 59.7","","","32.8","34.7"
"Treatment of childhood diseases (based on last two surviving children born during the","","","",""
"","","","",""
"reference period) (%)","","","",""
"","","","",""
"Prevalence of diarrhoea in last 2 weeks for under 5 years old children ....................................... 1.6 1.3 6.5 7.0
Children with diarrhoea in the last 2 weeks and received ORS11 ................................................. 100.0 100.0 54.8 53.3
Children with diarrhoea in the last 2 weeks and sought advice/treatment ................................... 100.0 50.0 72.9 73.3
Prevalence of ARI in last 2 weeks for under 5 years old children ............................................ 4.3 3.9 3.9 4.2
Children with acute respiratory infection or fever in last 2 weeks and sought advice/treatment 37.5 33.3 69.8 68.0
Children with diarrhoea in the last 2 weeks given Zinc along with ORS ...................................... 66.6 50.0 NA NA","","","6.5","7.0"
"","","","54.8","53.3"
"","","","72.9","73.3"
"","","","3.9","4.2"
"","","","69.8","68.0"
"Awareness of RTI/STI and HIV/AIDS (%)","","","",""
"Women who have heard of RTI/STI ............................................................................................. 55.8 57.1
Women who have heard of HIV/AIDS .......................................................................................... 98.9 99.0
Women who have any symptoms of RTI/STI .............................................................................. 13.9 13.5
Women who know the place to go for testing of HIV/AIDS12 ....................................................... 59.9 57.1
Women underwent test for detecting HIV/AIDS12 ........................................................................ 37.3 36.8","","","34.8","38.2"
"","","","98.3","98.1"
"","","","15.6","16.1"
"","","","48.6","46.3"
"","","","14.1","12.3"
"Utilization of Government Health Services (%)","","","",""
"Antenatal care .............................................................................................................................. 69.7 66.7 79.0 81.0
Treatment for pregnancy complications ....................................................................................... 57.1 59.3 88.0 87.8
Treatment for post-delivery complications ................................................................................... 33.3 33.3 68.4 68.4
Treatment for vaginal discharge ................................................................................................... 20.0 25.0 73.9 71.4
Treatment for children with diarrhoea13 ........................................................................................ 50.0 100.0 NA NA
Treatment for children with ARI13 ................................................................................................. NA NA NA NA","","","79.0","81.0"
"","","","88.0","87.8"
"","","","68.4","68.4"
"","","","73.9","71.4"
"Birth Registration (%)","","","",""
"Children below age 5 years having birth registration done .......................................................... 40.6 44.3 NA NA
Children below age 5 years who received birth certificate (out of those registered) .................... 65.9 63.6 NA NA","","","",""
"Personal Habits (age 15 years and above) (%)","","","",""
"Men who use any kind of smokeless tobacco ............................................................................. 74.6 74.2 NA NA
Women who use any kind of smokeless tobacco ........................................................................ 59.5 58.9 NA NA
Men who smoke ........................................................................................................................... 56.0 56.4 NA NA
Women who smoke ...................................................................................................................... 18.4 18.0 NA NA
Men who consume alcohol ........................................................................................................... 58.4 58.2 NA NA
Women who consume alcohol ..................................................................................................... 10.9 9.3 NA NA","","","",""
"9 Children Who were given nothing but breast milk till the survey date 10Acute Respiratory Infections11Oral Rehydration Solutions/Salts.12Based on","","","",""
"the women who have heard of HIV/AIDS.13 Last two weeks","","","",""
1 0 1 2 3 4
2 DLHS-4 (2012-13) DLHS-3 (2007-08)
3 Indicators TOTAL RURAL TOTAL RURAL
4 Child feeding practices (based on last-born child in the reference period) (%)
5 Children age 0-5 months exclusively breastfed9 .......................................................................... 76.9 80.0 Children age 6-9 months receiving solid/semi-solid food and breast milk .................................... 78.6 75.0 Children age 12-23 months receiving breast feeding along with complementary feeding ........... 31.8 24.2 Children age 6-35 months exclusively breastfed for at least 6 months ........................................ 4.7 3.4 Children under 3 years breastfed within one hour of birth ............................................................ 42.9 46.5 NA NA
6 85.9 89.3
7 NA NA
8 30.0 27.7
9 50.6 52.9
10 Birth Weight (%) (age below 36 months)
11 Percentage of Children weighed at birth ...................................................................................... 38.8 41.0 NA NA Percentage of Children with low birth weight (out of those who weighted) ( below 2.5 kg) ......... 12.8 14.6 NA NA
12 Awareness about Diarrhoea (%)
13 Women know about what to do when a child gets diarrhoea ..................................................... 96.3 96.2 94.4 94.2
14 Awareness about ARI (%)
15 Women aware about danger signs of ARI10 ................................................................................. 55.9 59.7 32.8 34.7
16 Treatment of childhood diseases (based on last two surviving children born during the
17
18 reference period) (%)
19
20 Prevalence of diarrhoea in last 2 weeks for under 5 years old children ....................................... 1.6 1.3 6.5 7.0 Children with diarrhoea in the last 2 weeks and received ORS11 ................................................. 100.0 100.0 54.8 53.3 Children with diarrhoea in the last 2 weeks and sought advice/treatment ................................... 100.0 50.0 72.9 73.3 Prevalence of ARI in last 2 weeks for under 5 years old children ............................................ 4.3 3.9 3.9 4.2 Children with acute respiratory infection or fever in last 2 weeks and sought advice/treatment 37.5 33.3 69.8 68.0 Children with diarrhoea in the last 2 weeks given Zinc along with ORS ...................................... 66.6 50.0 NA NA 6.5 7.0
21 54.8 53.3
22 72.9 73.3
23 3.9 4.2
24 69.8 68.0
25 Awareness of RTI/STI and HIV/AIDS (%)
26 Women who have heard of RTI/STI ............................................................................................. 55.8 57.1 Women who have heard of HIV/AIDS .......................................................................................... 98.9 99.0 Women who have any symptoms of RTI/STI .............................................................................. 13.9 13.5 Women who know the place to go for testing of HIV/AIDS12 ....................................................... 59.9 57.1 Women underwent test for detecting HIV/AIDS12 ........................................................................ 37.3 36.8 34.8 38.2
27 98.3 98.1
28 15.6 16.1
29 48.6 46.3
30 14.1 12.3
31 Utilization of Government Health Services (%)
32 Antenatal care .............................................................................................................................. 69.7 66.7 79.0 81.0 Treatment for pregnancy complications ....................................................................................... 57.1 59.3 88.0 87.8 Treatment for post-delivery complications ................................................................................... 33.3 33.3 68.4 68.4 Treatment for vaginal discharge ................................................................................................... 20.0 25.0 73.9 71.4 Treatment for children with diarrhoea13 ........................................................................................ 50.0 100.0 NA NA Treatment for children with ARI13 ................................................................................................. NA NA NA NA 79.0 81.0
33 88.0 87.8
34 68.4 68.4
35 73.9 71.4
36 Birth Registration (%)
37 Children below age 5 years having birth registration done .......................................................... 40.6 44.3 NA NA Children below age 5 years who received birth certificate (out of those registered) .................... 65.9 63.6 NA NA
38 Personal Habits (age 15 years and above) (%)
39 Men who use any kind of smokeless tobacco ............................................................................. 74.6 74.2 NA NA Women who use any kind of smokeless tobacco ........................................................................ 59.5 58.9 NA NA Men who smoke ........................................................................................................................... 56.0 56.4 NA NA Women who smoke ...................................................................................................................... 18.4 18.0 NA NA Men who consume alcohol ........................................................................................................... 58.4 58.2 NA NA Women who consume alcohol ..................................................................................................... 10.9 9.3 NA NA
40 9 Children Who were given nothing but breast milk till the survey date 10Acute Respiratory Infections11Oral Rehydration Solutions/Salts.12Based on
41 the women who have heard of HIV/AIDS.13 Last two weeks

44
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@ -1,44 +0,0 @@
"0","1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20","21","22","23"
"","Table: 5 Public Health Outlay 2012-13 (Budget Estimates) (Rs. in 000)","","","","","","","","","","","","","","","","","","","","","",""
"","States-A","","","Revenue","","","","","","Capital","","","","","","Total","","","Others(1)","","","Total",""
"","","","","","","","","","","","","","","","","Revenue &","","","","","","",""
"","","","Medical & Family Medical & Family
Public Welfare Public Welfare
Health Health","","","","","","","","","","","","","","","","","","","",""
"","","","","","","","","","","","","","","","","Capital","","","","","","",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"","Andhra Pradesh","","","47,824,589","","","9,967,837","","","1,275,000","","","15,000","","","59,082,426","","","14,898,243","","","73,980,669",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"Arunachal Pradesh 2,241,609 107,549 23,000 0 2,372,158 86,336 2,458,494","","","","","","","","","","","","","","","","","","","","","","",""
"","Assam","","","14,874,821","","","2,554,197","","","161,600","","","0","","","17,590,618","","","4,408,505","","","21,999,123",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"Bihar 21,016,708 4,332,141 5,329,000 0 30,677,849 2,251,571 32,929,420","","","","","","","","","","","","","","","","","","","","","","",""
"","Chhattisgarh","","","11,427,311","","","1,415,660","","","2,366,592","","","0","","","15,209,563","","","311,163","","","15,520,726",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"Delhi 28,084,780 411,700 4,550,000 0 33,046,480 5,000 33,051,480","","","","","","","","","","","","","","","","","","","","","","",""
"","Goa","","","4,055,567","","","110,000","","","330,053","","","0","","","4,495,620","","","12,560","","","4,508,180",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"Gujarat 26,328,400 6,922,900 12,664,000 42,000 45,957,300 455,860 46,413,160","","","","","","","","","","","","","","","","","","","","","","",""
"","Haryana","","","15,156,681","","","1,333,527","","","40,100","","","0","","","16,530,308","","","1,222,698","","","17,753,006",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"Himachal Pradesh 8,647,229 1,331,529 580,800 0 10,559,558 725,315 11,284,873","","","","","","","","","","","","","","","","","","","","","","",""
"","Jammu & Kashmir","","","14,411,984","","","270,840","","","3,188,550","","","0","","","17,871,374","","","166,229","","","18,037,603",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"Jharkhand 8,185,079 3,008,077 3,525,558 0 14,718,714 745,139 15,463,853","","","","","","","","","","","","","","","","","","","","","","",""
"","Karnataka","","","34,939,843","","","4,317,801","","","3,669,700","","","0","","","42,927,344","","","631,088","","","43,558,432",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"Kerala 27,923,965 3,985,473 929,503 0 32,838,941 334,640 33,173,581","","","","","","","","","","","","","","","","","","","","","","",""
"","Madhya Pradesh","","","28,459,540","","","4,072,016","","","3,432,711","","","0","","","35,964,267","","","472,139","","","36,436,406",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"Maharashtra 55,011,100 6,680,721 5,038,576 0 66,730,397 313,762 67,044,159","","","","","","","","","","","","","","","","","","","","","","",""
"","Manipur","","","2,494,600","","","187,700","","","897,400","","","0","","","3,579,700","","","0","","","3,579,700",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"Meghalaya 2,894,093 342,893 705,500 5,000 3,947,486 24,128 3,971,614","","","","","","","","","","","","","","","","","","","","","","",""
"","Mizoram","","","1,743,501","","","84,185","","","10,250","","","0","","","1,837,936","","","17,060","","","1,854,996",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"Nagaland 2,368,724 204,329 226,400 0 2,799,453 783,054 3,582,507","","","","","","","","","","","","","","","","","","","","","","",""
"","Odisha","","","14,317,179","","","2,552,292","","","1,107,250","","","0","","","17,976,721","","","451,438","","","18,428,159",""
"","","","","","","","","","","","","","","","","","","","","","","",""
"Puducherry 4,191,757 52,249 192,400 0 4,436,406 2,173 4,438,579","","","","","","","","","","","","","","","","","","","","","","",""
"","Punjab","","","19,775,485","","","2,208,343","","","2,470,882","","","0","","","24,454,710","","","1,436,522","","","25,891,232",""
"","","","","","","","","","","","","","","","","","","","","","","",""
1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
2 Table: 5 Public Health Outlay 2012-13 (Budget Estimates) (Rs. in 000)
3 States-A Revenue Capital Total Others(1) Total
4 Revenue &
5 Medical & Family Medical & Family Public Welfare Public Welfare Health Health
6 Capital
7
8 Andhra Pradesh 47,824,589 9,967,837 1,275,000 15,000 59,082,426 14,898,243 73,980,669
9
10 Arunachal Pradesh 2,241,609 107,549 23,000 0 2,372,158 86,336 2,458,494
11 Assam 14,874,821 2,554,197 161,600 0 17,590,618 4,408,505 21,999,123
12
13 Bihar 21,016,708 4,332,141 5,329,000 0 30,677,849 2,251,571 32,929,420
14 Chhattisgarh 11,427,311 1,415,660 2,366,592 0 15,209,563 311,163 15,520,726
15
16 Delhi 28,084,780 411,700 4,550,000 0 33,046,480 5,000 33,051,480
17 Goa 4,055,567 110,000 330,053 0 4,495,620 12,560 4,508,180
18
19 Gujarat 26,328,400 6,922,900 12,664,000 42,000 45,957,300 455,860 46,413,160
20 Haryana 15,156,681 1,333,527 40,100 0 16,530,308 1,222,698 17,753,006
21
22 Himachal Pradesh 8,647,229 1,331,529 580,800 0 10,559,558 725,315 11,284,873
23 Jammu & Kashmir 14,411,984 270,840 3,188,550 0 17,871,374 166,229 18,037,603
24
25 Jharkhand 8,185,079 3,008,077 3,525,558 0 14,718,714 745,139 15,463,853
26 Karnataka 34,939,843 4,317,801 3,669,700 0 42,927,344 631,088 43,558,432
27
28 Kerala 27,923,965 3,985,473 929,503 0 32,838,941 334,640 33,173,581
29 Madhya Pradesh 28,459,540 4,072,016 3,432,711 0 35,964,267 472,139 36,436,406
30
31 Maharashtra 55,011,100 6,680,721 5,038,576 0 66,730,397 313,762 67,044,159
32 Manipur 2,494,600 187,700 897,400 0 3,579,700 0 3,579,700
33
34 Meghalaya 2,894,093 342,893 705,500 5,000 3,947,486 24,128 3,971,614
35 Mizoram 1,743,501 84,185 10,250 0 1,837,936 17,060 1,854,996
36
37 Nagaland 2,368,724 204,329 226,400 0 2,799,453 783,054 3,582,507
38 Odisha 14,317,179 2,552,292 1,107,250 0 17,976,721 451,438 18,428,159
39
40 Puducherry 4,191,757 52,249 192,400 0 4,436,406 2,173 4,438,579
41 Punjab 19,775,485 2,208,343 2,470,882 0 24,454,710 1,436,522 25,891,232
42

71
docs/benchmark/stream/missing_values/missing_values-data-pdfplumber.csv
View File

@ -1,71 +0,0 @@
"0","1","2","3","4"
"","DLHS-4 (2012-13)","","DLHS-3 (2007-08)",""
"Indicators","TOTAL","RURAL","TOTAL","RURAL"
"Reported Prevalence of Morbidity","","","",""
"Any Injury ..................................................................................................................................... 1.9 2.1
Acute Illness ................................................................................................................................. 4.5 5.6
Chronic Illness .............................................................................................................................. 5.1 4.1","","","",""
"","","","",""
"","","","",""
"Reported Prevalence of Chronic Illness during last one year (%)","","","",""
"Disease of respiratory system ...................................................................................................... 11.7 15.0
Disease of cardiovascular system ................................................................................................ 8.9 9.3
Persons suffering from tuberculosis ............................................................................................. 2.2 1.5","","","",""
"","","","",""
"","","","",""
"Anaemia Status by Haemoglobin Level14 (%)","","","",""
"Children (6-59 months) having anaemia ...................................................................................... 68.5 71.9
Children (6-59 months) having severe anaemia .......................................................................... 6.7 9.4
Children (6-9 Years) having anaemia - Male ................................................................................ 67.1 71.4
Children (6-9 Years) having severe anaemia - Male .................................................................... 4.4 2.4
Children (6-9 Years) having anaemia - Female ........................................................................... 52.4 48.8
Children (6-9 Years) having severe anaemia - Female ................................................................ 1.2 0.0
Children (6-14 years) having anaemia - Male ............................................................................. 50.8 62.5
Children (6-14 years) having severe anaemia - Male .................................................................. 3.7 3.6
Children (6-14 years) having anaemia - Female ......................................................................... 48.3 50.0
Children (6-14 years) having severe anaemia - Female .............................................................. 4.3 6.1
Children (10-19 Years15) having anaemia - Male ......................................................................... 37.9 51.2
Children (10-19 Years15) having severe anaemia - Male ............................................................. 3.5 4.0
Children (10-19 Years15) having anaemia - Female ..................................................................... 46.6 52.1
Children (10-19 Years15) having severe anaemia - Female ......................................................... 6.4 6.5
Adolescents (15-19 years) having anaemia ................................................................................ 39.4 46.5
Adolescents (15-19 years) having severe anaemia ..................................................................... 5.4 5.1
Pregnant women (15-49 aged) having anaemia .......................................................................... 48.8 51.5
Pregnant women (15-49 aged) having severe anaemia .............................................................. 7.1 8.8
Women (15-49 aged) having anaemia ......................................................................................... 45.2 51.7
Women (15-49 aged) having severe anaemia ............................................................................. 4.8 5.9
Persons (20 years and above) having anaemia ........................................................................... 37.8 42.1
Persons (20 years and above) having Severe anaemia .............................................................. 4.6 4.8","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"","","","",""
"Blood Sugar Level (age 18 years and above) (%)","","","",""
"Blood Sugar Level >140 mg/dl (high) ........................................................................................... 12.9 11.1
Blood Sugar Level >160 mg/dl (very high) ................................................................................... 7.0 5.1","","","",""
"","","","",""
"Hypertension (age 18 years and above) (%)","","","",""
"Above Normal Range (Systolic >140 mm of Hg & Diastolic >90 mm of Hg ) .............................. 23.8 22.8
Moderately High (Systolic >160 mm of Hg & Diastolic >100 mm of Hg ) ..................................... 8.2 7.1
Very High (Systolic >180 mm of Hg & Diastolic >110 mm of Hg ) ............................................... 3.7 3.1","","","",""
"","","","",""
"","","","",""
"14 Any anaemia below 11g/dl, severe anaemia below 7g/dl. 15 Excluding age group 19 years","","","",""
"Chronic Illness :Any person with symptoms persisting for longer than one month is defined as suffering from chronic illness","","","",""
1 0 1 2 3 4
2 DLHS-4 (2012-13) DLHS-3 (2007-08)
3 Indicators TOTAL RURAL TOTAL RURAL
4 Reported Prevalence of Morbidity
5 Any Injury ..................................................................................................................................... 1.9 2.1 Acute Illness ................................................................................................................................. 4.5 5.6 Chronic Illness .............................................................................................................................. 5.1 4.1
6
7
8 Reported Prevalence of Chronic Illness during last one year (%)
9 Disease of respiratory system ...................................................................................................... 11.7 15.0 Disease of cardiovascular system ................................................................................................ 8.9 9.3 Persons suffering from tuberculosis ............................................................................................. 2.2 1.5
10
11
12 Anaemia Status by Haemoglobin Level14 (%)
13 Children (6-59 months) having anaemia ...................................................................................... 68.5 71.9 Children (6-59 months) having severe anaemia .......................................................................... 6.7 9.4 Children (6-9 Years) having anaemia - Male ................................................................................ 67.1 71.4 Children (6-9 Years) having severe anaemia - Male .................................................................... 4.4 2.4 Children (6-9 Years) having anaemia - Female ........................................................................... 52.4 48.8 Children (6-9 Years) having severe anaemia - Female ................................................................ 1.2 0.0 Children (6-14 years) having anaemia - Male ............................................................................. 50.8 62.5 Children (6-14 years) having severe anaemia - Male .................................................................. 3.7 3.6 Children (6-14 years) having anaemia - Female ......................................................................... 48.3 50.0 Children (6-14 years) having severe anaemia - Female .............................................................. 4.3 6.1 Children (10-19 Years15) having anaemia - Male ......................................................................... 37.9 51.2 Children (10-19 Years15) having severe anaemia - Male ............................................................. 3.5 4.0 Children (10-19 Years15) having anaemia - Female ..................................................................... 46.6 52.1 Children (10-19 Years15) having severe anaemia - Female ......................................................... 6.4 6.5 Adolescents (15-19 years) having anaemia ................................................................................ 39.4 46.5 Adolescents (15-19 years) having severe anaemia ..................................................................... 5.4 5.1 Pregnant women (15-49 aged) having anaemia .......................................................................... 48.8 51.5 Pregnant women (15-49 aged) having severe anaemia .............................................................. 7.1 8.8 Women (15-49 aged) having anaemia ......................................................................................... 45.2 51.7 Women (15-49 aged) having severe anaemia ............................................................................. 4.8 5.9 Persons (20 years and above) having anaemia ........................................................................... 37.8 42.1 Persons (20 years and above) having Severe anaemia .............................................................. 4.6 4.8
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35 Blood Sugar Level (age 18 years and above) (%)
36 Blood Sugar Level >140 mg/dl (high) ........................................................................................... 12.9 11.1 Blood Sugar Level >160 mg/dl (very high) ................................................................................... 7.0 5.1
37
38 Hypertension (age 18 years and above) (%)
39 Above Normal Range (Systolic >140 mm of Hg & Diastolic >90 mm of Hg ) .............................. 23.8 22.8 Moderately High (Systolic >160 mm of Hg & Diastolic >100 mm of Hg ) ..................................... 8.2 7.1 Very High (Systolic >180 mm of Hg & Diastolic >110 mm of Hg ) ............................................... 3.7 3.1
40
41
42 14 Any anaemia below 11g/dl, severe anaemia below 7g/dl. 15 Excluding age group 19 years
43 Chronic Illness :Any person with symptoms persisting for longer than one month is defined as suffering from chronic illness

122
docs/conf.py
View File

@ -22,8 +22,8 @@ import sys
# sys.path.insert(0, os.path.abspath('..')) # sys.path.insert(0, os.path.abspath('..'))
# Insert Camelot's path into the system. # Insert Camelot's path into the system.
sys.path.insert(0, os.path.abspath("..")) sys.path.insert(0, os.path.abspath('..'))
sys.path.insert(0, os.path.abspath("_themes")) sys.path.insert(0, os.path.abspath('_themes'))
import camelot import camelot
@ -38,33 +38,33 @@ import camelot
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones. # ones.
extensions = [ extensions = [
"sphinx.ext.autodoc", 'sphinx.ext.autodoc',
"sphinx.ext.napoleon", 'sphinx.ext.napoleon',
"sphinx.ext.intersphinx", 'sphinx.ext.intersphinx',
"sphinx.ext.todo", 'sphinx.ext.todo',
"sphinx.ext.viewcode", 'sphinx.ext.viewcode',
] ]
# Add any paths that contain templates here, relative to this directory. # Add any paths that contain templates here, relative to this directory.
templates_path = ["_templates"] templates_path = ['_templates']
# The suffix(es) of source filenames. # The suffix(es) of source filenames.
# You can specify multiple suffix as a list of string: # You can specify multiple suffix as a list of string:
# #
# source_suffix = ['.rst', '.md'] # source_suffix = ['.rst', '.md']
source_suffix = ".rst" source_suffix = '.rst'
# The encoding of source files. # The encoding of source files.
# #
# source_encoding = 'utf-8-sig' # source_encoding = 'utf-8-sig'
# The master toctree document. # The master toctree document.
master_doc = "index" master_doc = 'index'
# General information about the project. # General information about the project.
project = u"Camelot" project = u'Camelot'
copyright = u"2021, Camelot Developers" copyright = u'2018, Peeply Private Ltd (Singapore)'
author = u"Vinayak Mehta" author = u'Vinayak Mehta'
# The version info for the project you're documenting, acts as replacement for # The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the # |version| and |release|, also used in various other places throughout the
@ -94,7 +94,7 @@ language = None
# List of patterns, relative to source directory, that match files and # List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files. # directories to ignore when looking for source files.
# This patterns also effect to html_static_path and html_extra_path # This patterns also effect to html_static_path and html_extra_path
exclude_patterns = ["_build"] exclude_patterns = ['_build']
# The reST default role (used for this markup: `text`) to use for all # The reST default role (used for this markup: `text`) to use for all
# documents. # documents.
@ -114,7 +114,7 @@ add_module_names = True
# show_authors = False # show_authors = False
# The name of the Pygments (syntax highlighting) style to use. # The name of the Pygments (syntax highlighting) style to use.
pygments_style = "flask_theme_support.FlaskyStyle" pygments_style = 'flask_theme_support.FlaskyStyle'
# A list of ignored prefixes for module index sorting. # A list of ignored prefixes for module index sorting.
# modindex_common_prefix = [] # modindex_common_prefix = []
@ -130,18 +130,18 @@ todo_include_todos = True
# The theme to use for HTML and HTML Help pages. See the documentation for # The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes. # a list of builtin themes.
html_theme = "alabaster" html_theme = 'alabaster'
# Theme options are theme-specific and customize the look and feel of a theme # Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the # further. For a list of options available for each theme, see the
# documentation. # documentation.
html_theme_options = { html_theme_options = {
"show_powered_by": False, 'show_powered_by': False,
"github_user": "camelot-dev", 'github_user': 'socialcopsdev',
"github_repo": "camelot", 'github_repo': 'camelot',
"github_banner": True, 'github_banner': True,
"show_related": False, 'show_related': False,
"note_bg": "#FFF59C", 'note_bg': '#FFF59C'
} }
# Add any paths that contain custom themes here, relative to this directory. # Add any paths that contain custom themes here, relative to this directory.
@ -164,12 +164,12 @@ html_theme_options = {
# The name of an image file (relative to this directory) to use as a favicon of # The name of an image file (relative to this directory) to use as a favicon of
# the docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 # the docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large. # pixels large.
html_favicon = "_static/favicon.ico" html_favicon = '_static/favicon.ico'
# Add any paths that contain custom static files (such as style sheets) here, # Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files, # relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css". # so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ["_static"] html_static_path = ['_static']
# Add any extra paths that contain custom files (such as robots.txt or # Add any extra paths that contain custom files (such as robots.txt or
# .htaccess) here, relative to this directory. These files are copied # .htaccess) here, relative to this directory. These files are copied
@ -189,21 +189,10 @@ html_use_smartypants = True
# Custom sidebar templates, maps document names to template names. # Custom sidebar templates, maps document names to template names.
html_sidebars = { html_sidebars = {
"index": [ 'index': ['sidebarintro.html', 'relations.html', 'sourcelink.html',
"sidebarintro.html", 'searchbox.html', 'hacks.html'],
"relations.html", '**': ['sidebarlogo.html', 'localtoc.html', 'relations.html',
"sourcelink.html", 'sourcelink.html', 'searchbox.html', 'hacks.html']
"searchbox.html",
"hacks.html",
],
"**": [
"sidebarlogo.html",
"localtoc.html",
"relations.html",
"sourcelink.html",
"searchbox.html",
"hacks.html",
],
} }
# Additional templates that should be rendered to pages, maps page names to # Additional templates that should be rendered to pages, maps page names to
@ -260,30 +249,34 @@ html_show_copyright = True
# html_search_scorer = 'scorer.js' # html_search_scorer = 'scorer.js'
# Output file base name for HTML help builder. # Output file base name for HTML help builder.
htmlhelp_basename = "Camelotdoc" htmlhelp_basename = 'Camelotdoc'
# -- Options for LaTeX output --------------------------------------------- # -- Options for LaTeX output ---------------------------------------------
latex_elements = { latex_elements = {
# The paper size ('letterpaper' or 'a4paper'). # The paper size ('letterpaper' or 'a4paper').
# #
# 'papersize': 'letterpaper', # 'papersize': 'letterpaper',
# The font size ('10pt', '11pt' or '12pt').
# # The font size ('10pt', '11pt' or '12pt').
# 'pointsize': '10pt', #
# Additional stuff for the LaTeX preamble. # 'pointsize': '10pt',
#
# 'preamble': '', # Additional stuff for the LaTeX preamble.
# Latex figure (float) alignment #
# # 'preamble': '',
# 'figure_align': 'htbp',
# Latex figure (float) alignment
#
# 'figure_align': 'htbp',
} }
# Grouping the document tree into LaTeX files. List of tuples # Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title, # (source start file, target name, title,
# author, documentclass [howto, manual, or own class]). # author, documentclass [howto, manual, or own class]).
latex_documents = [ latex_documents = [
(master_doc, "Camelot.tex", u"Camelot Documentation", u"Vinayak Mehta", "manual"), (master_doc, 'Camelot.tex', u'Camelot Documentation',
u'Vinayak Mehta', 'manual'),
] ]
# The name of an image file (relative to this directory) to place at the top of # The name of an image file (relative to this directory) to place at the top of
@ -323,7 +316,10 @@ latex_documents = [
# One entry per manual page. List of tuples # One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section). # (source start file, name, description, authors, manual section).
man_pages = [(master_doc, "Camelot", u"Camelot Documentation", [author], 1)] man_pages = [
(master_doc, 'Camelot', u'Camelot Documentation',
[author], 1)
]
# If true, show URL addresses after external links. # If true, show URL addresses after external links.
# #
@ -336,15 +332,9 @@ man_pages = [(master_doc, "Camelot", u"Camelot Documentation", [author], 1)]
# (source start file, target name, title, author, # (source start file, target name, title, author,
# dir menu entry, description, category) # dir menu entry, description, category)
texinfo_documents = [ texinfo_documents = [
( (master_doc, 'Camelot', u'Camelot Documentation',
master_doc, author, 'Camelot', 'One line description of project.',
"Camelot", 'Miscellaneous'),
u"Camelot Documentation",
author,
"Camelot",
"One line description of project.",
"Miscellaneous",
),
] ]
# Documents to append as an appendix to all manuals. # Documents to append as an appendix to all manuals.
@ -366,6 +356,6 @@ texinfo_documents = [
# Example configuration for intersphinx: refer to the Python standard library. # Example configuration for intersphinx: refer to the Python standard library.
intersphinx_mapping = { intersphinx_mapping = {
"https://docs.python.org/2": None, 'https://docs.python.org/2': None,
"http://pandas.pydata.org/pandas-docs/stable": None, 'http://pandas.pydata.org/pandas-docs/stable': None
} }

34
docs/dev/contributing.rst
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@ -7,7 +7,7 @@ If you're reading this, you're probably looking to contributing to Camelot. *Tim
This document will help you get started with contributing documentation, code, testing and filing issues. If you have any questions, feel free to reach out to `Vinayak Mehta`_, the author and maintainer. This document will help you get started with contributing documentation, code, testing and filing issues. If you have any questions, feel free to reach out to `Vinayak Mehta`_, the author and maintainer.
.. _Vinayak Mehta: https://www.vinayakmehta.com .. _Vinayak Mehta: http://vinayak-mehta.github.io
Code Of Conduct Code Of Conduct
--------------- ---------------
@ -24,34 +24,30 @@ As the `Requests Code Of Conduct`_ states, **all contributions are welcome**, as
.. _Requests Code Of Conduct: http://docs.python-requests.org/en/master/dev/contributing/#be-cordial .. _Requests Code Of Conduct: http://docs.python-requests.org/en/master/dev/contributing/#be-cordial
Your first contribution Your First Contribution
----------------------- -----------------------
A great way to start contributing to Camelot is to pick an issue tagged with the `help wanted`_ or the `good first issue`_ tags. If you're unable to find a good first issue, feel free to contact the maintainer. A great way to start contributing to Camelot is to pick an issue tagged with the `Contributor Friendly`_ or the `Easy`_ tags. If you're unable to find a good first issue, feel free to contact the maintainer.
.. _help wanted: https://github.com/camelot-dev/camelot/labels/help%20wanted .. _Contributor Friendly: https://github.com/socialcopsdev/camelot/labels/Contributor%20Friendly
.. _good first issue: https://github.com/camelot-dev/camelot/labels/good%20first%20issue .. _Easy: https://github.com/socialcopsdev/camelot/labels/Level%3A%20Easy
Setting up a development environment Setting up a development environment
------------------------------------ ------------------------------------
To install the dependencies needed for development, you can use pip:: To install the dependencies needed for development, you can use pip::
$ pip install "camelot-py[dev]" $ pip install camelot-py[dev]
Alternatively, you can clone the project repository, and install using pip::
$ pip install ".[dev]"
Pull Requests Pull Requests
------------- -------------
Submit a pull request Submit a Pull Request
^^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^
The preferred workflow for contributing to Camelot is to fork the `project repository`_ on GitHub, clone, develop on a branch and then finally submit a pull request. Here are the steps: The preferred workflow for contributing to Camelot is to fork the `project repository`_ on GitHub, clone, develop on a branch and then finally submit a pull request. Steps:
.. _project repository: https://github.com/camelot-dev/camelot .. _project repository: https://github.com/socialcopsdev/camelot
1. Fork the project repository. Click on the ‘Fork’ button near the top of the page. This creates a copy of the code under your account on the GitHub. 1. Fork the project repository. Click on the ‘Fork’ button near the top of the page. This creates a copy of the code under your account on the GitHub.
@ -80,7 +76,7 @@ Now it's time to go to the your fork of Camelot and create a pull request! You c
.. _follow these instructions: https://help.github.com/articles/creating-a-pull-request-from-a-fork/ .. _follow these instructions: https://help.github.com/articles/creating-a-pull-request-from-a-fork/
Work on your pull request Work on your Pull Request
^^^^^^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^
We recommend that your pull request complies with the following guidelines: We recommend that your pull request complies with the following guidelines:
@ -93,7 +89,7 @@ We recommend that your pull request complies with the following guidelines:
.. _numpydoc: https://numpydoc.readthedocs.io/en/latest/format.html .. _numpydoc: https://numpydoc.readthedocs.io/en/latest/format.html
- Make sure your commit messages follow `the seven rules of a great git commit message`_: - Make sure your commit messages follow `the seven rules of a great git commit message`_.
- Separate subject from body with a blank line - Separate subject from body with a blank line
- Limit the subject line to 50 characters - Limit the subject line to 50 characters
- Capitalize the subject line - Capitalize the subject line
@ -123,7 +119,7 @@ Writing documentation, function docstrings, examples and tutorials is a great wa
The documentation is written in `reStructuredText`_, with `Sphinx`_ used to generate these lovely HTML files that you're currently reading (unless you're reading this on GitHub). You can edit the documentation using any text editor and then generate the HTML output by running `make html` in the ``docs/`` directory. The documentation is written in `reStructuredText`_, with `Sphinx`_ used to generate these lovely HTML files that you're currently reading (unless you're reading this on GitHub). You can edit the documentation using any text editor and then generate the HTML output by running `make html` in the ``docs/`` directory.
The function docstrings are written using the `numpydoc`_ extension for Sphinx. Make sure you check out how its format guidelines before you start writing one. The function docstrings are written using the `numpydoc`_ extension for Sphinx. Make sure you check out how its format guidelines, before you start writing one.
.. _reStructuredText: https://en.wikipedia.org/wiki/ReStructuredText .. _reStructuredText: https://en.wikipedia.org/wiki/ReStructuredText
.. _Sphinx: http://www.sphinx-doc.org/en/master/ .. _Sphinx: http://www.sphinx-doc.org/en/master/
@ -132,14 +128,14 @@ The function docstrings are written using the `numpydoc`_ extension for Sphinx.
Filing Issues Filing Issues
------------- -------------
We use `GitHub issues`_ to keep track of all issues and pull requests. Before opening an issue (which asks a question or reports a bug), please use GitHub search to look for existing issues (both open and closed) that may be similar. We use `GitHub issues`_ to keep track of all issues and pull requests. Before opening an issue (which asks a question or reports a bug), it is advisable to use GitHub search to look for existing issues (both open and closed) that may be similar.
.. _GitHub issues: https://github.com/camelot-dev/camelot/issues .. _GitHub issues: https://docs.pytest.org/en/latest/
Questions Questions
^^^^^^^^^ ^^^^^^^^^
Please don't use GitHub issues for support questions. A better place for them would be `Stack Overflow`_. Make sure you tag them using the ``python-camelot`` tag. Please don't use GitHub issues for support questions, a better place for them would be `Stack Overflow`_. Make sure you tag them using the ``python-camelot`` tag.
.. _Stack Overflow: http://stackoverflow.com .. _Stack Overflow: http://stackoverflow.com

90
docs/index.rst
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@ -8,43 +8,25 @@ Camelot: PDF Table Extraction for Humans
Release v\ |version|. (:ref:`Installation <install>`) Release v\ |version|. (:ref:`Installation <install>`)
.. image:: https://travis-ci.org/camelot-dev/camelot.svg?branch=master .. image:: https://img.shields.io/badge/license-MIT-lightgrey.svg
:target: https://travis-ci.org/camelot-dev/camelot
.. image:: https://readthedocs.org/projects/camelot-py/badge/?version=master
:target: https://camelot-py.readthedocs.io/en/master/
:alt: Documentation Status
.. image:: https://codecov.io/github/camelot-dev/camelot/badge.svg?branch=master&service=github
:target: https://codecov.io/github/camelot-dev/camelot?branch=master
.. image:: https://img.shields.io/pypi/v/camelot-py.svg
:target: https://pypi.org/project/camelot-py/ :target: https://pypi.org/project/camelot-py/
.. image:: https://img.shields.io/pypi/l/camelot-py.svg .. image:: https://img.shields.io/badge/python-2.7-blue.svg
:target: https://pypi.org/project/camelot-py/ :target: https://pypi.org/project/camelot-py/
.. image:: https://img.shields.io/pypi/pyversions/camelot-py.svg **Camelot** is a Python library which makes it easy for *anyone* to extract tables from PDF files!
:target: https://pypi.org/project/camelot-py/
.. image:: https://badges.gitter.im/camelot-dev/Lobby.png .. note:: Camelot only works with:
:target: https://gitter.im/camelot-dev/Lobby
.. image:: https://img.shields.io/badge/code%20style-black-000000.svg - Python 2, with **Python 3** support `on the way`_.
:target: https://github.com/ambv/black - Text-based PDFs and not scanned documents. If you can click-and-drag to select text in your table in a PDF viewer, then your PDF is text-based. Support for image-based PDFs using **OCR** is `planned`_.
.. image:: https://img.shields.io/badge/continous%20quality-deepsource-lightgrey .. _on the way: https://github.com/socialcopsdev/camelot/issues/81
:target: https://deepsource.io/gh/camelot-dev/camelot/?ref=repository-badge .. _planned: https://github.com/socialcopsdev/camelot/issues/101
**Camelot** is a Python library that can help you extract tables from PDFs! ------------------------
.. note:: You can also check out `Excalibur`_, the web interface to Camelot! **Here's how you can extract tables from PDF files.** Check out the PDF used in this example, `here`_.
.. _Excalibur: https://github.com/camelot-dev/excalibur
----
**Here's how you can extract tables from PDFs.** You can check out the PDF used in this example `here`_.
.. _here: _static/pdf/foo.pdf .. _here: _static/pdf/foo.pdf
@ -53,8 +35,8 @@ Release v\ |version|. (:ref:`Installation <install>`)
>>> import camelot >>> import camelot
>>> tables = camelot.read_pdf('foo.pdf') >>> tables = camelot.read_pdf('foo.pdf')
>>> tables >>> tables
<TableList n=1> <TableList tables=1>
>>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html, markdown, sqlite >>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html
>>> tables[0] >>> tables[0]
<Table shape=(7, 7)> <Table shape=(7, 7)>
>>> tables[0].parsing_report >>> tables[0].parsing_report
@ -64,61 +46,48 @@ Release v\ |version|. (:ref:`Installation <install>`)
'order': 1, 'order': 1,
'page': 1 'page': 1
} }
>>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html, to_markdown, to_sqlite >>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html
>>> tables[0].df # get a pandas DataFrame! >>> tables[0].df # get a pandas DataFrame!
.. csv-table:: .. csv-table::
:file: _static/csv/foo.csv :file: _static/csv/foo.csv
Camelot also comes packaged with a :ref:`command-line interface <cli>`! There's a :ref:`command-line interface <cli>` too!
.. note:: Camelot only works with text-based PDFs and not scanned documents. (As Tabula `explains`_, "If you can click and drag to select text in your table in a PDF viewer, then your PDF is text-based".)
You can check out some frequently asked questions :ref:`here <faq>`.
.. _explains: https://github.com/tabulapdf/tabula#why-tabula
Why Camelot? Why Camelot?
------------ ------------
- **Configurability**: Camelot gives you control over the table extraction process with :ref:`tweakable settings <advanced>`. - **You are in control**: Unlike other libraries and tools which either give a nice output or fail miserably (with no in-between), Camelot gives you the power to tweak table extraction. (Since everything in the real world, including PDF table extraction, is fuzzy.)
- **Metrics**: You can discard bad tables based on metrics like accuracy and whitespace, without having to manually look at each table. - **Metrics**: *Bad* tables can be discarded based on metrics like accuracy and whitespace, without ever having to manually look at each table.
- **Output**: Each table is extracted into a **pandas DataFrame**, which seamlessly integrates into `ETL and data analysis workflows`_. You can also export tables to multiple formats, which include CSV, JSON, Excel, HTML, Markdown, and Sqlite. - Each table is a **pandas DataFrame**, which enables seamless integration into `ETL and data analysis workflows`_.
- **Export** to multiple formats, including json, excel and html.
- Simple and Elegant API, written in **Python**!
See `comparison with other PDF table extraction libraries and tools`_.
.. _ETL and data analysis workflows: https://gist.github.com/vinayak-mehta/e5949f7c2410a0e12f25d3682dc9e873 .. _ETL and data analysis workflows: https://gist.github.com/vinayak-mehta/e5949f7c2410a0e12f25d3682dc9e873
.. _comparison with other PDF table extraction libraries and tools: https://github.com/socialcopsdev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools
See `comparison with similar libraries and tools`_.
.. _comparison with similar libraries and tools: https://github.com/camelot-dev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools
Support the development
-----------------------
If Camelot has helped you, please consider supporting its development with a one-time or monthly donation `on OpenCollective`_!
.. _on OpenCollective: https://opencollective.com/camelot
The User Guide The User Guide
-------------- --------------
This part of the documentation begins with some background information about why Camelot was created, takes you through some implementation details, and then focuses on step-by-step instructions for getting the most out of Camelot. This part of the documentation, begins with some background information about why Camelot was created, takes a small dip into the implementation details and then focuses on step-by-step instructions for getting the most out of Camelot.
.. toctree:: .. toctree::
:maxdepth: 2 :maxdepth: 2
user/intro user/intro
user/install-deps
user/install user/install
user/how-it-works user/how-it-works
user/quickstart user/quickstart
user/advanced user/advanced
user/faq
user/cli user/cli
The API Documentation/Guide The API Documentation / Guide
--------------------------- -----------------------------
If you are looking for information on a specific function, class, or method, this part of the documentation is for you. If you are looking for information on a specific function, class, or method,
this part of the documentation is for you.
.. toctree:: .. toctree::
:maxdepth: 2 :maxdepth: 2
@ -128,9 +97,10 @@ If you are looking for information on a specific function, class, or method, thi
The Contributor Guide The Contributor Guide
--------------------- ---------------------
If you want to contribute to the project, this part of the documentation is for you. If you want to contribute to the project, this part of the documentation is for
you.
.. toctree:: .. toctree::
:maxdepth: 2 :maxdepth: 2
dev/contributing dev/contributing

351
docs/user/advanced.rst
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@ -8,7 +8,7 @@ This page covers some of the more advanced configurations for :ref:`Lattice <lat
Process background lines Process background lines
------------------------ ------------------------
To detect line segments, :ref:`Lattice <lattice>` needs the lines that make the table to be in the foreground. Here's an example of a table with lines in the background: To detect line segments, :ref:`Lattice <lattice>` needs the lines that make the table, to be in foreground. Here's an example of a table with lines in background.
.. figure:: ../_static/png/background_lines.png .. figure:: ../_static/png/background_lines.png
:scale: 50% :scale: 50%
@ -24,34 +24,25 @@ To process background lines, you can pass ``process_background=True``.
>>> tables = camelot.read_pdf('background_lines.pdf', process_background=True) >>> tables = camelot.read_pdf('background_lines.pdf', process_background=True)
>>> tables[1].df >>> tables[1].df
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot lattice -back background_lines.pdf
.. csv-table:: .. csv-table::
:file: ../_static/csv/background_lines.csv :file: ../_static/csv/background_lines.csv
Visual debugging Plot geometry
---------------- -------------
.. note:: Visual debugging using ``plot()`` requires `matplotlib <https://matplotlib.org/>`_ which is an optional dependency. You can install it using ``$ pip install camelot-py[plot]``. You can use a :class:`table <camelot.core.Table>` object's :meth:`plot() <camelot.core.TableList.plot>` method to plot various geometries that were detected by Camelot while processing the PDF page. This can help you select table areas, column separators and debug bad table outputs, by tweaking different configuration parameters.
You can use the :class:`plot() <camelot.plotting.PlotMethods>` method to generate a `matplotlib <https://matplotlib.org/>`_ plot of various elements that were detected on the PDF page while processing it. This can help you select table areas, column separators and debug bad table outputs, by tweaking different configuration parameters. The following geometries are available for plotting. You can pass them to the :meth:`plot() <camelot.core.TableList.plot>` method, which will then generate a `matplotlib <https://matplotlib.org/>`_ plot for the passed geometry.
You can specify the type of element you want to plot using the ``kind`` keyword argument. The generated plot can be saved to a file by passing a ``filename`` keyword argument. The following plot types are supported:
- 'text' - 'text'
- 'grid' - 'table'
- 'contour' - 'contour'
- 'line' - 'line'
- 'joint' - 'joint'
- 'textedge'
.. note:: 'line' and 'joint' can only be used with :ref:`Lattice <lattice>` and 'textedge' can only be used with :ref:`Stream <stream>`. .. note:: The last three geometries can only be used with :ref:`Lattice <lattice>`, i.e. when ``flavor='lattice'``.
Let's generate a plot for each type using this `PDF <../_static/pdf/foo.pdf>`__ as an example. First, let's get all the tables out. Let's generate a plot for each geometry using this `PDF <../_static/pdf/foo.pdf>`__ as an example. First, let's get all the tables out.
:: ::
@ -59,6 +50,8 @@ Let's generate a plot for each type using this `PDF <../_static/pdf/foo.pdf>`__
>>> tables >>> tables
<TableList n=1> <TableList n=1>
.. _geometry_text:
text text
^^^^ ^^^^
@ -66,41 +59,31 @@ Let's plot all the text present on the table's PDF page.
:: ::
>>> camelot.plot(tables[0], kind='text').show() >>> tables[0].plot('text')
.. tip:: .. figure:: ../_static/png/geometry_text.png
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot lattice -plot text foo.pdf
.. figure:: ../_static/png/plot_text.png
:height: 674 :height: 674
:width: 1366 :width: 1366
:scale: 50% :scale: 50%
:alt: A plot of all text on a PDF page :alt: A plot of all text on a PDF page
:align: left :align: left
This, as we shall later see, is very helpful with :ref:`Stream <stream>` for noting table areas and column separators, in case Stream does not guess them correctly. This, as we shall later see, is very helpful with :ref:`Stream <stream>`, for noting table areas and column separators, in case Stream does not guess them correctly.
.. note:: The *x-y* coordinates shown above change as you move your mouse cursor on the image, which can help you note coordinates. .. note:: The *x-y* coordinates shown aboe change as you move your mouse cursor on the image, which can help you note coordinates.
.. _geometry_table:
table table
^^^^^ ^^^^^
Let's plot the table (to see if it was detected correctly or not). This plot type, along with contour, line and joint is useful for debugging and improving the extraction output, in case the table wasn't detected correctly. (More on that later.) Let's plot the table (to see if it was detected correctly or not). This geometry type, along with contour, line and joint is useful for debugging and improving the extraction output, in case the table wasn't detected correctly. More on that later.
:: ::
>>> camelot.plot(tables[0], kind='grid').show() >>> tables[0].plot('table')
.. tip:: .. figure:: ../_static/png/geometry_table.png
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot lattice -plot grid foo.pdf
.. figure:: ../_static/png/plot_table.png
:height: 674 :height: 674
:width: 1366 :width: 1366
:scale: 50% :scale: 50%
@ -109,6 +92,8 @@ Let's plot the table (to see if it was detected correctly or not). This plot typ
The table is perfect! The table is perfect!
.. _geometry_contour:
contour contour
^^^^^^^ ^^^^^^^
@ -116,21 +101,17 @@ Now, let's plot all table boundaries present on the table's PDF page.
:: ::
>>> camelot.plot(tables[0], kind='contour').show() >>> tables[0].plot('contour')
.. tip:: .. figure:: ../_static/png/geometry_contour.png
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot lattice -plot contour foo.pdf
.. figure:: ../_static/png/plot_contour.png
:height: 674 :height: 674
:width: 1366 :width: 1366
:scale: 50% :scale: 50%
:alt: A plot of all contours on a PDF page :alt: A plot of all contours on a PDF page
:align: left :align: left
.. _geometry_line:
line line
^^^^ ^^^^
@ -138,21 +119,17 @@ Cool, let's plot all line segments present on the table's PDF page.
:: ::
>>> camelot.plot(tables[0], kind='line').show() >>> tables[0].plot('line')
.. tip:: .. figure:: ../_static/png/geometry_line.png
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot lattice -plot line foo.pdf
.. figure:: ../_static/png/plot_line.png
:height: 674 :height: 674
:width: 1366 :width: 1366
:scale: 50% :scale: 50%
:alt: A plot of all lines on a PDF page :alt: A plot of all lines on a PDF page
:align: left :align: left
.. _geometry_joint:
joint joint
^^^^^ ^^^^^
@ -160,111 +137,50 @@ Finally, let's plot all line intersections present on the table's PDF page.
:: ::
>>> camelot.plot(tables[0], kind='joint').show() >>> tables[0].plot('joint')
.. tip:: .. figure:: ../_static/png/geometry_joint.png
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot lattice -plot joint foo.pdf
.. figure:: ../_static/png/plot_joint.png
:height: 674 :height: 674
:width: 1366 :width: 1366
:scale: 50% :scale: 50%
:alt: A plot of all line intersections on a PDF page :alt: A plot of all line intersections on a PDF page
:align: left :align: left
textedge
^^^^^^^^
You can also visualize the textedges found on a page by specifying ``kind='textedge'``. To know more about what a "textedge" is, you can see pages 20, 35 and 40 of `Anssi Nurminen's master's thesis <http://dspace.cc.tut.fi/dpub/bitstream/handle/123456789/21520/Nurminen.pdf?sequence=3>`_.
::
>>> camelot.plot(tables[0], kind='textedge').show()
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot stream -plot textedge foo.pdf
.. figure:: ../_static/png/plot_textedge.png
:height: 674
:width: 1366
:scale: 50%
:alt: A plot of relevant textedges on a PDF page
:align: left
Specify table areas Specify table areas
------------------- -------------------
In cases such as `these <../_static/pdf/table_areas.pdf>`__, it can be useful to specify exact table boundaries. You can plot the text on this page and note the top left and bottom right coordinates of the table. Since :ref:`Stream <stream>` treats the whole page as a table, `for now`_, it's useful to specify table boundaries in cases such as `these <../_static/pdf/table_areas.pdf>`__. You can :ref:`plot the text <geometry_text>` on this page and note the left-top and right-bottom coordinates of the table.
Table areas that you want Camelot to analyze can be passed as a list of comma-separated strings to :meth:`read_pdf() <camelot.read_pdf>`, using the ``table_areas`` keyword argument. Table areas that you want Camelot to analyze can be passed as a list of comma-separated strings to :meth:`read_pdf() <camelot.read_pdf>`, using the ``table_areas`` keyword argument.
.. _for now: https://github.com/socialcopsdev/camelot/issues/102
:: ::
>>> tables = camelot.read_pdf('table_areas.pdf', flavor='stream', table_areas=['316,499,566,337']) >>> tables = camelot.read_pdf('table_areas.pdf', flavor='stream', table_areas=['316,499,566,337'])
>>> tables[0].df >>> tables[0].df
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot stream -T 316,499,566,337 table_areas.pdf
.. csv-table:: .. csv-table::
:file: ../_static/csv/table_areas.csv :file: ../_static/csv/table_areas.csv
.. note:: ``table_areas`` accepts strings of the form x1,y1,x2,y2 where (x1, y1) -> top-left and (x2, y2) -> bottom-right in PDF coordinate space. In PDF coordinate space, the bottom-left corner of the page is the origin, with coordinates (0, 0).
Specify table regions
---------------------
However there may be cases like `[1] <../_static/pdf/table_regions.pdf>`__ and `[2] <https://github.com/camelot-dev/camelot/blob/master/tests/files/tableception.pdf>`__, where the table might not lie at the exact coordinates every time but in an approximate region.
You can use the ``table_regions`` keyword argument to :meth:`read_pdf() <camelot.read_pdf>` to solve for such cases. When ``table_regions`` is specified, Camelot will only analyze the specified regions to look for tables.
::
>>> tables = camelot.read_pdf('table_regions.pdf', table_regions=['170,370,560,270'])
>>> tables[0].df
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot lattice -R 170,370,560,270 table_regions.pdf
.. csv-table::
:file: ../_static/csv/table_regions.csv
Specify column separators Specify column separators
------------------------- -------------------------
In cases like `these <../_static/pdf/column_separators.pdf>`__, where the text is very close to each other, it is possible that Camelot may guess the column separators' coordinates incorrectly. To correct this, you can explicitly specify the *x* coordinate for each column separator by plotting the text on the page. In cases like `these <../_static/pdf/column_separators.pdf>`__, where the text is very close to each other, it is possible that Camelot may guess the column separators' coordinates incorrectly. To correct this, you can explicitly specify the *x* coordinate for each column separator by :ref:`plotting the text <geometry_text>` on the page.
You can pass the column separators as a list of comma-separated strings to :meth:`read_pdf() <camelot.read_pdf>`, using the ``columns`` keyword argument. You can pass the column separators as a list of comma-separated strings to :meth:`read_pdf() <camelot.read_pdf>`, using the ``columns`` keyword argument.
In case you passed a single column separators string list, and no table area is specified, the separators will be applied to the whole page. When a list of table areas is specified and you need to specify column separators as well, **the length of both lists should be equal**. Each table area will be mapped to each column separators' string using their indices. In case you passed a single column separators string list, and no table area is specified, the separators will be applied to the whole page. When a list of table areas is specified and there is a need to specify column separators as well, **the length of both lists should be equal**. Each table area will be mapped to each column separators' string using their indices.
For example, if you have specified two table areas, ``table_areas=['12,54,43,23', '20,67,55,33']``, and only want to specify column separators for the first table, you can pass an empty string for the second table in the column separators' list like this, ``columns=['10,120,200,400', '']``. For example, if you have specified two table areas, ``table_areas=['12,23,43,54', '20,33,55,67']``, and only want to specify column separators for the first table, you can pass an empty string for the second table in the column separators' list, like this, ``columns=['10,120,200,400', '']``.
Let's get back to the *x* coordinates we got from plotting the text that exists on this `PDF <../_static/pdf/column_separators.pdf>`__, and get the table out! Let's get back to the *x* coordinates we got from :ref:`plotting text <geometry_text>` that exists on this `PDF <../_static/pdf/column_separators.pdf>`__, and get the table out!
:: ::
>>> tables = camelot.read_pdf('column_separators.pdf', flavor='stream', columns=['72,95,209,327,442,529,566,606,683']) >>> tables = camelot.read_pdf('column_separators.pdf', flavor='stream', columns=['72,95,209,327,442,529,566,606,683'])
>>> tables[0].df >>> tables[0].df
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot stream -C 72,95,209,327,442,529,566,606,683 column_separators.pdf
.. csv-table:: .. csv-table::
"...","...","...","...","...","...","...","...","...","..." "...","...","...","...","...","...","...","...","...","..."
@ -272,24 +188,18 @@ Let's get back to the *x* coordinates we got from plotting the text that exists
"NUMBER TYPE DBA NAME","","","LICENSEE NAME","ADDRESS","CITY","ST","ZIP","PHONE NUMBER","EXPIRES" "NUMBER TYPE DBA NAME","","","LICENSEE NAME","ADDRESS","CITY","ST","ZIP","PHONE NUMBER","EXPIRES"
"...","...","...","...","...","...","...","...","...","..." "...","...","...","...","...","...","...","...","...","..."
Ah! Since `PDFMiner <https://euske.github.io/pdfminer/>`_ merged the strings, "NUMBER", "TYPE" and "DBA NAME", all of them were assigned to the same cell. Let's see how we can fix this in the next section. Ah! Since `PDFMiner <https://euske.github.io/pdfminer/>`_ merged the strings, "NUMBER", "TYPE" and "DBA NAME"; all of them were assigned to the same cell. Let's see how we can fix this in the next section.
Split text along separators Split text along separators
--------------------------- ---------------------------
To deal with cases like the output from the previous section, you can pass ``split_text=True`` to :meth:`read_pdf() <camelot.read_pdf>`, which will split any strings that lie in different cells but have been assigned to a single cell (as a result of being merged together by `PDFMiner <https://euske.github.io/pdfminer/>`_). To deal with cases like the output from the previous section, you can pass ``split_text=True`` to :meth:`read_pdf() <camelot.read_pdf>`, which will split any strings that lie in different cells but have been assigned to the a single cell (as a result of being merged together by `PDFMiner <https://euske.github.io/pdfminer/>`_).
:: ::
>>> tables = camelot.read_pdf('column_separators.pdf', flavor='stream', columns=['72,95,209,327,442,529,566,606,683'], split_text=True) >>> tables = camelot.read_pdf('column_separators.pdf', flavor='stream', columns=['72,95,209,327,442,529,566,606,683'], split_text=True)
>>> tables[0].df >>> tables[0].df
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot -split stream -C 72,95,209,327,442,529,566,606,683 column_separators.pdf
.. csv-table:: .. csv-table::
"...","...","...","...","...","...","...","...","...","..." "...","...","...","...","...","...","...","...","...","..."
@ -300,29 +210,23 @@ To deal with cases like the output from the previous section, you can pass ``spl
Flag superscripts and subscripts Flag superscripts and subscripts
-------------------------------- --------------------------------
There might be cases where you want to differentiate between the text and superscripts or subscripts, like this `PDF <../_static/pdf/superscript.pdf>`_. There might be cases where you want to differentiate between the text, and superscripts or subscripts, like this `PDF <../_static/pdf/superscript.pdf>`_.
.. figure:: ../_static/png/superscript.png .. figure:: ../_static/png/superscript.png
:alt: A PDF with superscripts :alt: A PDF with superscripts
:align: left :align: left
In this case, the text that `other tools`_ return, will be ``24.912``. This is relatively harmless when that decimal point is involved. But when it isn't there, you'll be left wondering why the results of your data analysis are 10x bigger! In this case, the text that `other tools`_ return, will be ``24.912``. This is harmless as long as there is that decimal point involved. But when it isn't there, you'll be left wondering why the results of your data analysis were 10x bigger!
You can solve this by passing ``flag_size=True``, which will enclose the superscripts and subscripts with ``<s></s>``, based on font size, as shown below. You can solve this by passing ``flag_size=True``, which will enclose the superscripts and subscripts with ``<s></s>``, based on font size, as shown below.
.. _other tools: https://github.com/camelot-dev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools .. _other tools: https://github.com/socialcopsdev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools
:: ::
>>> tables = camelot.read_pdf('superscript.pdf', flavor='stream', flag_size=True) >>> tables = camelot.read_pdf('superscript.pdf', flavor='stream', flag_size=True)
>>> tables[0].df >>> tables[0].df
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot -flag stream superscript.pdf
.. csv-table:: .. csv-table::
"...","...","...","...","...","...","...","...","...","...","..." "...","...","...","...","...","...","...","...","...","...","..."
@ -331,85 +235,10 @@ You can solve this by passing ``flag_size=True``, which will enclose the supersc
"Madhya Pradesh","27.13","23.57","-","-","3.56","0.38","-","1.86","-","1.28" "Madhya Pradesh","27.13","23.57","-","-","3.56","0.38","-","1.86","-","1.28"
"...","...","...","...","...","...","...","...","...","...","..." "...","...","...","...","...","...","...","...","...","...","..."
Strip characters from text Control how text is grouped into rows
-------------------------- -------------------------------------
You can strip unwanted characters like spaces, dots and newlines from a string using the ``strip_text`` keyword argument. Take a look at `this PDF <https://github.com/camelot-dev/camelot/blob/master/tests/files/tabula/12s0324.pdf>`_ as an example, the text at the start of each row contains a lot of unwanted spaces, dots and newlines. You can pass ``row_close_tol=<+int>`` to group the rows closer together, as shown below.
::
>>> tables = camelot.read_pdf('12s0324.pdf', flavor='stream', strip_text=' .\n')
>>> tables[0].df
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot -strip ' .\n' stream 12s0324.pdf
.. csv-table::
"...","...","...","...","...","...","...","...","...","..."
"Forcible rape","17.5","2.6","14.9","17.2","2.5","14.7","–","–","–"
"Robbery","102.1","25.5","76.6","90.0","22.9","67.1","12.1","2.5","9.5"
"Aggravated assault","338.4","40.1","298.3","264.0","30.2","233.8","74.4","9.9","64.5"
"Property crime","1,396 .4","338 .7","1,057 .7","875 .9","210 .8","665 .1","608 .2","127 .9","392 .6"
"Burglary","240.9","60.3","180.6","205.0","53.4","151.7","35.9","6.9","29.0"
"...","...","...","...","...","...","...","...","...","..."
Improve guessed table areas
---------------------------
While using :ref:`Stream <stream>`, automatic table detection can fail for PDFs like `this one <https://github.com/camelot-dev/camelot/blob/master/tests/files/edge_tol.pdf>`_. That's because the text is relatively far apart vertically, which can lead to shorter textedges being calculated.
.. note:: To know more about how textedges are calculated to guess table areas, you can see pages 20, 35 and 40 of `Anssi Nurminen's master's thesis <http://dspace.cc.tut.fi/dpub/bitstream/handle/123456789/21520/Nurminen.pdf?sequence=3>`_.
Let's see the table area that is detected by default.
::
>>> tables = camelot.read_pdf('edge_tol.pdf', flavor='stream')
>>> camelot.plot(tables[0], kind='contour').show()
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot stream -plot contour edge.pdf
.. figure:: ../_static/png/edge_tol_1.png
:height: 674
:width: 1366
:scale: 50%
:alt: Table area with default edge_tol
:align: left
To improve the detected area, you can increase the ``edge_tol`` (default: 50) value to counter the effect of text being placed relatively far apart vertically. Larger ``edge_tol`` will lead to longer textedges being detected, leading to an improved guess of the table area. Let's use a value of 500.
::
>>> tables = camelot.read_pdf('edge_tol.pdf', flavor='stream', edge_tol=500)
>>> camelot.plot(tables[0], kind='contour').show()
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot stream -e 500 -plot contour edge.pdf
.. figure:: ../_static/png/edge_tol_2.png
:height: 674
:width: 1366
:scale: 50%
:alt: Table area with default edge_tol
:align: left
As you can see, the guessed table area has improved!
Improve guessed table rows
--------------------------
You can pass ``row_tol=<+int>`` to group the rows closer together, as shown below.
:: ::
@ -427,15 +256,9 @@ You can pass ``row_tol=<+int>`` to group the rows closer together, as shown belo
:: ::
>>> tables = camelot.read_pdf('group_rows.pdf', flavor='stream', row_tol=10) >>> tables = camelot.read_pdf('group_rows.pdf', flavor='stream', row_close_tol=10)
>>> tables[0].df >>> tables[0].df
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot stream -r 10 group_rows.pdf
.. csv-table:: .. csv-table::
"Clave","Nombre Entidad","Clave","","Nombre Municipio","Clave","Nombre Localidad" "Clave","Nombre Entidad","Clave","","Nombre Municipio","Clave","Nombre Localidad"
@ -447,11 +270,11 @@ You can pass ``row_tol=<+int>`` to group the rows closer together, as shown belo
Detect short lines Detect short lines
------------------ ------------------
There might be cases while using :ref:`Lattice <lattice>` when smaller lines don't get detected. The size of the smallest line that gets detected is calculated by dividing the PDF page's dimensions with a scaling factor called ``line_scale``. By default, its value is 15. There might be cases while using :ref:`Lattice <lattice>` when smaller lines don't get detected. The size of the smallest line that gets detected is calculated by dividing the PDF page's dimensions with a scaling factor called ``line_size_scaling``. By default, its value is 15.
As you can guess, the larger the ``line_scale``, the smaller the size of lines getting detected. As you can guess, the larger the ``line_size_scaling``, the smaller the size of lines getting detected.
.. warning:: Making ``line_scale`` very large (>150) will lead to text getting detected as lines. .. warning:: Making ``line_size_scaling`` very large (>150) will lead to text getting detected as lines.
Here's a `PDF <../_static/pdf/short_lines.pdf>`__ where small lines separating the the headers don't get detected with the default value of 15. Here's a `PDF <../_static/pdf/short_lines.pdf>`__ where small lines separating the the headers don't get detected with the default value of 15.
@ -459,29 +282,23 @@ Here's a `PDF <../_static/pdf/short_lines.pdf>`__ where small lines separating t
:alt: A PDF table with short lines :alt: A PDF table with short lines
:align: left :align: left
Let's plot the table for this PDF. Let's :ref:`plot the table <geometry_table>` for this PDF.
:: ::
>>> tables = camelot.read_pdf('short_lines.pdf') >>> tables = camelot.read_pdf('short_lines.pdf')
>>> camelot.plot(tables[0], kind='grid').show() >>> tables[0].plot('table')
.. figure:: ../_static/png/short_lines_1.png .. figure:: ../_static/png/short_lines_1.png
:alt: A plot of the PDF table with short lines :alt: A plot of the PDF table with short lines
:align: left :align: left
Clearly, the smaller lines separating the headers, couldn't be detected. Let's try with ``line_scale=40``, and plot the table again. Clearly, the smaller lines separating the headers, couldn't be detected. Let's try with ``line_size_scaling=40``, and `plot the table <geometry_table>`_ again.
:: ::
>>> tables = camelot.read_pdf('short_lines.pdf', line_scale=40) >>> tables = camelot.read_pdf('short_lines.pdf', line_size_scaling=40)
>>> camelot.plot(tables[0], kind='grid').show() >>> tables[0].plot('table')
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot lattice -scale 40 -plot grid short_lines.pdf
.. figure:: ../_static/png/short_lines_2.png .. figure:: ../_static/png/short_lines_2.png
:alt: An improved plot of the PDF table with short lines :alt: An improved plot of the PDF table with short lines
@ -510,7 +327,7 @@ Voila! Camelot can now see those lines. Let's get our table.
Shift text in spanning cells Shift text in spanning cells
---------------------------- ----------------------------
By default, the :ref:`Lattice <lattice>` method shifts text in spanning cells, first to the left and then to the top, as you can observe in the output table above. However, this behavior can be changed using the ``shift_text`` keyword argument. Think of it as setting the *gravity* for a table — it decides the direction in which the text will move and finally come to rest. By default, the :ref:`Lattice <lattice>` method shifts text in spanning cells, first to the left and then to the top, as you can observe in the output table above. However, this behavior can be changed using the ``shift_text`` keyword argument. Think of it as setting the *gravity* for a table, it decides the direction in which the text will move and finally come to rest.
``shift_text`` expects a list with one or more characters from the following set: ``('', l', 'r', 't', 'b')``, which are then applied *in order*. The default, as we discussed above, is ``['l', 't']``. ``shift_text`` expects a list with one or more characters from the following set: ``('', l', 'r', 't', 'b')``, which are then applied *in order*. The default, as we discussed above, is ``['l', 't']``.
@ -522,7 +339,7 @@ We'll use the `PDF <../_static/pdf/short_lines.pdf>`__ from the previous example
:: ::
>>> tables = camelot.read_pdf('short_lines.pdf', line_scale=40, shift_text=['']) >>> tables = camelot.read_pdf('short_lines.pdf', line_size_scaling=40, shift_text=[''])
>>> tables[0].df >>> tables[0].df
.. csv-table:: .. csv-table::
@ -539,19 +356,13 @@ We'll use the `PDF <../_static/pdf/short_lines.pdf>`__ from the previous example
"Knowledge &Practices on HTN &","2400","Men (≥ 18 yrs)","-","-","-","1728" "Knowledge &Practices on HTN &","2400","Men (≥ 18 yrs)","-","-","-","1728"
"DM","2400","Women (≥ 18 yrs)","-","-","-","1728" "DM","2400","Women (≥ 18 yrs)","-","-","-","1728"
No surprises there — it did remain in place (observe the strings "2400" and "All the available individuals"). Let's pass ``shift_text=['r', 'b']`` to set the *gravity* to right-bottom and move the text in that direction. No surprises there, it did remain in place (observe the strings "2400" and "All the available individuals"). Let's pass ``shift_text=['r', 'b']``, to set the *gravity* to right-bottom, and move the text in that direction.
:: ::
>>> tables = camelot.read_pdf('short_lines.pdf', line_scale=40, shift_text=['r', 'b']) >>> tables = camelot.read_pdf('short_lines.pdf', line_size_scaling=40, shift_text=['r', 'b'])
>>> tables[0].df >>> tables[0].df
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot lattice -scale 40 -shift r -shift b short_lines.pdf
.. csv-table:: .. csv-table::
"Investigations","No. ofHHs","Age/Sex/Physiological Group","Preva-lence","C.I*","RelativePrecision","Sample sizeper State" "Investigations","No. ofHHs","Age/Sex/Physiological Group","Preva-lence","C.I*","RelativePrecision","Sample sizeper State"
@ -569,7 +380,7 @@ No surprises there — it did remain in place (observe the strings "2400" and "A
Copy text in spanning cells Copy text in spanning cells
--------------------------- ---------------------------
You can copy text in spanning cells when using :ref:`Lattice <lattice>`, in either the horizontal or vertical direction, or both. This behavior is disabled by default. You can copy text in spanning cells when using :ref:`Lattice <lattice>`, in either horizontal or vertical direction, or both. This behavior is disabled by default.
``copy_text`` expects a list with one or more characters from the following set: ``('v', 'h')``, which are then applied *in order*. ``copy_text`` expects a list with one or more characters from the following set: ``('v', 'h')``, which are then applied *in order*.
@ -597,12 +408,6 @@ We don't need anything else. Now, let's pass ``copy_text=['v']`` to copy text in
>>> tables = camelot.read_pdf('copy_text.pdf', copy_text=['v']) >>> tables = camelot.read_pdf('copy_text.pdf', copy_text=['v'])
>>> tables[0].df >>> tables[0].df
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot lattice -copy v copy_text.pdf
.. csv-table:: .. csv-table::
"Sl. No.","Name of State/UT","Name of District","Disease/ Illness","No. of Cases","No. of Deaths","Date of start of outbreak","Date of reporting","Current Status","..." "Sl. No.","Name of State/UT","Name of District","Disease/ Illness","No. of Cases","No. of Deaths","Date of start of outbreak","Date of reporting","Current Status","..."
@ -611,38 +416,4 @@ We don't need anything else. Now, let's pass ``copy_text=['v']`` to copy text in
"3","Odisha","Kalahandi","iii. Food Poisoning","42","0","02/01/14","03/01/14","Under control","..." "3","Odisha","Kalahandi","iii. Food Poisoning","42","0","02/01/14","03/01/14","Under control","..."
"4","West Bengal","West Medinipur","iv. Acute Diarrhoeal Disease","145","0","04/01/14","05/01/14","Under control","..." "4","West Bengal","West Medinipur","iv. Acute Diarrhoeal Disease","145","0","04/01/14","05/01/14","Under control","..."
"4","West Bengal","Birbhum","v. Food Poisoning","199","0","31/12/13","31/12/13","Under control","..." "4","West Bengal","Birbhum","v. Food Poisoning","199","0","31/12/13","31/12/13","Under control","..."
"4","West Bengal","Howrah","vi. Viral Hepatitis A &E","85","0","26/12/13","27/12/13","Under surveillance","..." "4","West Bengal","Howrah","vi. Viral Hepatitis A &E","85","0","26/12/13","27/12/13","Under surveillance","..."
Tweak layout generation
-----------------------
Camelot is built on top of PDFMiner's functionality of grouping characters on a page into words and sentences. In some cases (such as `#170 <https://github.com/camelot-dev/camelot/issues/170>`_ and `#215 <https://github.com/camelot-dev/camelot/issues/215>`_), PDFMiner can group characters that should belong to the same sentence into separate sentences.
To deal with such cases, you can tweak PDFMiner's `LAParams kwargs <https://github.com/euske/pdfminer/blob/master/pdfminer/layout.py#L33>`_ to improve layout generation, by passing the keyword arguments as a dict using ``layout_kwargs`` in :meth:`read_pdf() <camelot.read_pdf>`. To know more about the parameters you can tweak, you can check out `PDFMiner docs <https://pdfminersix.rtfd.io/en/latest/reference/composable.html>`_.
::
>>> tables = camelot.read_pdf('foo.pdf', layout_kwargs={'detect_vertical': False})
.. _image-conversion-backend:
Use alternate image conversion backends
---------------------------------------
When using the :ref:`Lattice <lattice>` flavor, Camelot uses ``ghostscript`` to convert PDF pages to images for line recognition. If you face installation issues with ``ghostscript``, you can use an alternate image conversion backend called ``poppler``. You can specify which image conversion backend you want to use with::
>>> tables = camelot.read_pdf(filename, backend="ghostscript") # default
>>> tables = camelot.read_pdf(filename, backend="poppler")
.. note:: ``ghostscript`` will be replaced by ``poppler`` as the default image conversion backend in ``v0.12.0``.
If you face issues with both ``ghostscript`` and ``poppler``, you can supply your own image conversion backend::
>>> class ConversionBackend(object):
>>> def convert(pdf_path, png_path):
>>> # read pdf page from pdf_path
>>> # convert pdf page to image
>>> # write image to png_path
>>> pass
>>>
>>> tables = camelot.read_pdf(filename, backend=ConversionBackend())

12
docs/user/cli.rst
View File

@ -1,24 +1,22 @@
.. _cli: .. _cli:
Command-Line Interface Command-line interface
====================== ======================
Camelot comes with a command-line interface. Camelot comes with a command-line interface.
You can print the help for the interface by typing ``camelot --help`` in your favorite terminal program, as shown below. Furthermore, you can print the help for each command by typing ``camelot <command> --help``. Try it out! You can print the help for the interface, by typing ``camelot --help`` in your favorite terminal program, as shown below. Furthermore, you can print the help for each command, by typing ``camelot <command> --help``, try it out!
:: ::
Usage: camelot [OPTIONS] COMMAND [ARGS]... Usage: camelot [OPTIONS] COMMAND [ARGS]...
Camelot: PDF Table Extraction for Humans Camelot: PDF Table Extraction for Humans
Options: Options:
--version Show the version and exit. --version Show the version and exit.
-q, --quiet TEXT Suppress logs and warnings.
-p, --pages TEXT Comma-separated page numbers. Example: 1,3,4 -p, --pages TEXT Comma-separated page numbers. Example: 1,3,4
or 1,4-end. or 1,4-end.
-pw, --password TEXT Password for decryption.
-o, --output TEXT Output file path. -o, --output TEXT Output file path.
-f, --format [csv|json|excel|html] -f, --format [csv|json|excel|html]
Output file format. Output file format.
@ -26,8 +24,6 @@ You can print the help for the interface by typing ``camelot --help`` in your fa
-split, --split_text Split text that spans across multiple cells. -split, --split_text Split text that spans across multiple cells.
-flag, --flag_size Flag text based on font size. Useful to -flag, --flag_size Flag text based on font size. Useful to
detect super/subscripts. detect super/subscripts.
-strip, --strip_text Characters that should be stripped from a
string before assigning it to a cell.
-M, --margins <FLOAT FLOAT FLOAT>... -M, --margins <FLOAT FLOAT FLOAT>...
PDFMiner char_margin, line_margin and PDFMiner char_margin, line_margin and
word_margin. word_margin.
@ -35,4 +31,4 @@ You can print the help for the interface by typing ``camelot --help`` in your fa
Commands: Commands:
lattice Use lines between text to parse the table. lattice Use lines between text to parse the table.
stream Use spaces between text to parse the table. stream Use spaces between text to parse the table.

70
docs/user/faq.rst
View File

@ -1,70 +0,0 @@
.. _faq:
Frequently Asked Questions
==========================
This part of the documentation answers some common questions. To add questions, please open an issue `here <https://github.com/camelot-dev/camelot/issues/new>`_.
Does Camelot work with image-based PDFs?
----------------------------------------
**No**, Camelot only works with text-based PDFs and not scanned documents. (As Tabula `explains <https://github.com/tabulapdf/tabula#why-tabula>`_, "If you can click and drag to select text in your table in a PDF viewer, then your PDF is text-based".)
How to reduce memory usage for long PDFs?
-----------------------------------------
During table extraction from long PDF documents, RAM usage can grow significantly.
A simple workaround is to divide the extraction into chunks, and save extracted data to disk at the end of every chunk.
For more details, check out this code snippet from `@anakin87 <https://github.com/anakin87>`_:
::
import camelot
def chunks(l, n):
"""Yield successive n-sized chunks from l."""
for i in range(0, len(l), n):
yield l[i : i + n]
def extract_tables(filepath, pages, chunks=50, export_path=".", params={}):
"""
Divide the extraction work into n chunks. At the end of every chunk,
save data on disk and free RAM.
filepath : str
Filepath or URL of the PDF file.
pages : str, optional (default: '1')
Comma-separated page numbers.
Example: '1,3,4' or '1,4-end' or 'all'.
"""
# get list of pages from camelot.handlers.PDFHandler
handler = camelot.handlers.PDFHandler(filepath)
page_list = handler._get_pages(filepath, pages=pages)
# chunk pages list
page_chunks = list(chunks(page_list, chunks))
# extraction and export
for chunk in page_chunks:
pages_string = str(chunk).replace("[", "").replace("]", "")
tables = camelot.read_pdf(filepath, pages=pages_string, **params)
tables.export(f"{export_path}/tables.csv")
How can I supply my own image conversion backend to Lattice?
------------------------------------------------------------
When using the :ref:`Lattice <lattice>` flavor, you can supply your own :ref:`image conversion backend <image-conversion-backend>` by creating a class with a ``convert`` method as follows::
>>> class ConversionBackend(object):
>>> def convert(pdf_path, png_path):
>>> # read pdf page from pdf_path
>>> # convert pdf page to image
>>> # write image to png_path
>>> pass
>>>
>>> tables = camelot.read_pdf(filename, backend=ConversionBackend())

36
docs/user/how-it-works.rst
View File

@ -3,35 +3,35 @@
How It Works How It Works
============ ============
This part of the documentation includes a high-level explanation of how Camelot extracts tables from PDF files. This part of the documentation details a high-level explanation of how Camelot extracts tables from PDF files.
You can choose between two table parsing methods, *Stream* and *Lattice*. These names for parsing methods inside Camelot were inspired from `Tabula <https://github.com/tabulapdf/tabula>`_. You can choose between two table parsing methods, *Stream* and *Lattice*. The naming for parsing methods inside Camelot (i.e. Stream and Lattice) was inspired from `Tabula`_.
.. _Tabula: https://github.com/tabulapdf/tabula
.. _stream: .. _stream:
Stream Stream
------ ------
Stream can be used to parse tables that have whitespaces between cells to simulate a table structure. It is built on top of PDFMiner's functionality of grouping characters on a page into words and sentences, using `margins <https://euske.github.io/pdfminer/#tools>`_. Stream can be used to parse tables that have whitespaces between cells to simulate a table structure. It looks for these spaces between text to form a table representation.
1. Words on the PDF page are grouped into text rows based on their *y* axis overlaps. It is built on top of PDFMiner's functionality of grouping characters on a page into words and sentences, using `margins`_. After getting the words given on a page, it groups them into rows based on their *y* coordinates and tries to guess the number of columns the table might have by calculating the mode of the number of words in each row. This mode is used to calculate *x* ranges for the table's columns. It then adds columns to this column range list based on any words that may lie outside or inside the current column *x* ranges.
2. Textedges are calculated and then used to guess interesting table areas on the PDF page. You can read `Anssi Nurminen's master's thesis <https://pdfs.semanticscholar.org/a9b1/67a86fb189bfcd366c3839f33f0404db9c10.pdf>`_ to know more about this table detection technique. [See pages 20, 35 and 40] .. _margins: https://euske.github.io/pdfminer/#tools
3. The number of columns inside each table area are then guessed. This is done by calculating the mode of number of words in each text row. Based on this mode, words in each text row are chosen to calculate a list of column *x* ranges. .. note:: By default, Stream treats the whole PDF page as a table, which isn't ideal when there are more than two tables on a page with different number of columns. Automatic table detection for Stream is `in the works`_.
4. Words that lie inside/outside the current column *x* ranges are then used to extend the current list of columns. .. _in the works: https://github.com/socialcopsdev/camelot/issues/102
5. Finally, a table is formed using the text rows' *y* ranges and column *x* ranges and words found on the page are assigned to the table's cells based on their *x* and *y* coordinates.
.. _lattice: .. _lattice:
Lattice Lattice
------- -------
Lattice is more deterministic in nature, and it does not rely on guesses. It can be used to parse tables that have demarcated lines between cells, and it can automatically parse multiple tables present on a page. Lattice is more deterministic in nature, and does not rely on guesses. It can be used to parse tables that have demarcated lines between cells, and can automatically parse multiple tables present on a page.
It starts by converting the PDF page to an image using ghostscript, and then processes it to get horizontal and vertical line segments by applying a set of morphological transformations (erosion and dilation) using OpenCV. It starts by converting the PDF page to an image using ghostscript and then processing it to get horizontal and vertical line segments by applying a set of morphological transformations (erosion and dilation) using OpenCV.
Let's see how Lattice processes the second page of `this PDF`_, step-by-step. Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
@ -39,7 +39,7 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
1. Line segments are detected. 1. Line segments are detected.
.. image:: ../_static/png/plot_line.png .. image:: ../_static/png/geometry_line.png
:height: 674 :height: 674
:width: 1366 :width: 1366
:scale: 50% :scale: 50%
@ -49,23 +49,23 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
.. _and: https://en.wikipedia.org/wiki/Logical_conjunction .. _and: https://en.wikipedia.org/wiki/Logical_conjunction
.. image:: ../_static/png/plot_joint.png .. image:: ../_static/png/geometry_joint.png
:height: 674 :height: 674
:width: 1366 :width: 1366
:scale: 50% :scale: 50%
:align: left :align: left
3. Table boundaries are computed by overlapping the detected line segments again, this time by "`or`_"ing their pixel intensities. 3. Table boundaries are computed, by overlapping the detected line segments again, this time by "`or`_"ing their pixel intensities.
.. _or: https://en.wikipedia.org/wiki/Logical_disjunction .. _or: https://en.wikipedia.org/wiki/Logical_disjunction
.. image:: ../_static/png/plot_contour.png .. image:: ../_static/png/geometry_contour.png
:height: 674 :height: 674
:width: 1366 :width: 1366
:scale: 50% :scale: 50%
:align: left :align: left
4. Since dimensions of the PDF page and its image vary, the detected table boundaries, line intersections, and line segments are scaled and translated to the PDF page's coordinate space, and a representation of the table is created. 4. Since dimensions of the PDF page and its image vary; the detected table boundaries, line intersections and line segments are scaled and translated to the PDF page's coordinate space, and a representation of the table is created.
.. image:: ../_static/png/table.png .. image:: ../_static/png/table.png
:height: 674 :height: 674
@ -75,10 +75,10 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
5. Spanning cells are detected using the line segments and line intersections. 5. Spanning cells are detected using the line segments and line intersections.
.. image:: ../_static/png/plot_table.png .. image:: ../_static/png/geometry_table.png
:height: 674 :height: 674
:width: 1366 :width: 1366
:scale: 50% :scale: 50%
:align: left :align: left
6. Finally, the words found on the page are assigned to the table's cells based on their *x* and *y* coordinates. 6. Finally, the words found on the page are assigned to the table's cells based on their *x* and *y* coordinates.

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@ -1,62 +0,0 @@
.. _install_deps:
Installation of dependencies
============================
The dependencies `Ghostscript <https://www.ghostscript.com>`_ and `Tkinter <https://wiki.python.org/moin/TkInter>`_ can be installed using your system's package manager or by running their installer.
OS-specific instructions
------------------------
Ubuntu
^^^^^^
::
$ apt install ghostscript python3-tk
MacOS
^^^^^
::
$ brew install ghostscript tcl-tk
Windows
^^^^^^^
For Ghostscript, you can get the installer at their `downloads page <https://www.ghostscript.com/download/gsdnld.html>`_. And for Tkinter, you can download the `ActiveTcl Community Edition <https://www.activestate.com/activetcl/downloads>`_ from ActiveState.
Checks to see if dependencies are installed correctly
-----------------------------------------------------
You can run the following checks to see if the dependencies were installed correctly.
For Ghostscript
^^^^^^^^^^^^^^^
Open the Python REPL and run the following:
For Ubuntu/MacOS::
>>> from ctypes.util import find_library
>>> find_library("gs")
"libgs.so.9"
For Windows::
>>> import ctypes
>>> from ctypes.util import find_library
>>> find_library("".join(("gsdll", str(ctypes.sizeof(ctypes.c_voidp) * 8), ".dll")))
<name-of-ghostscript-library-on-windows>
**Check:** The output of the ``find_library`` function should not be empty.
If the output is empty, then it's possible that the Ghostscript library is not available one of the ``LD_LIBRARY_PATH``/``DYLD_LIBRARY_PATH``/``PATH`` variables depending on your operating system. In this case, you may have to modify one of those path variables.
For Tkinter
^^^^^^^^^^^
Launch Python and then import Tkinter::
>>> import tkinter
**Check:** Importing ``tkinter`` should not raise an import error.

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@ -3,38 +3,40 @@
Installation of Camelot Installation of Camelot
======================= =======================
This part of the documentation covers the steps to install Camelot. This part of the documentation covers the installation of Camelot. First, you'll need to install the dependencies, which include `tk`_ and `ghostscript`_.
After :ref:`installing the dependencies <install_deps>`, which include `Ghostscript <https://www.ghostscript.com>`_ and `Tkinter <https://wiki.python.org/moin/TkInter>`_, you can use one of the following methods to install Camelot: .. _tk: https://packages.ubuntu.com/trusty/python-tk
.. _ghostscript: https://www.ghostscript.com/
.. warning:: The ``lattice`` flavor will fail to run if Ghostscript is not installed. You may run into errors as shown in `issue #193 <https://github.com/camelot-dev/camelot/issues/193>`_. These can be installed using your system's package manager. You can run the following based on your OS.
pip For Ubuntu::
---
To install Camelot from PyPI using ``pip``, please include the extra ``cv`` requirement as shown:: $ apt install python-tk ghostscript
$ pip install "camelot-py[base]" For macOS::
conda $ brew install tcl-tk ghostscript
-----
`conda`_ is a package manager and environment management system for the `Anaconda <https://anaconda.org>`_ distribution. It can be used to install Camelot from the ``conda-forge`` channel:: $ pip install camelot-py
------------------------
$ conda install -c conda-forge camelot-py After installing the dependencies, you can simply use pip to install Camelot::
From the source code $ pip install camelot-py
--------------------
After :ref:`installing the dependencies <install_deps>`, you can install Camelot from source by: Get the Source Code
-------------------
Alternatively, you can install from source by:
1. Cloning the GitHub repository. 1. Cloning the GitHub repository.
:: ::
$ git clone https://www.github.com/camelot-dev/camelot $ git clone https://www.github.com/socialcopsdev/camelot
2. And then simply using pip again. 2. And then simply using pip again.
:: ::
$ cd camelot $ cd camelot
$ pip install ".[base]" $ pip install .

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@ -6,20 +6,20 @@ Introduction
The Camelot Project The Camelot Project
------------------- -------------------
The PDF (Portable Document Format) was born out of `The Camelot Project`_ to create "a universal way to communicate documents across a wide variety of machine configurations, operating systems and communication networks". The goal was to make these documents viewable on any display and printable on any modern printers. The invention of the `PostScript`_ page description language, which enabled the creation of *fixed-layout* flat documents (with text, fonts, graphics, images encapsulated), solved this problem. The Portable Document Format (PDF) was born out of `The Camelot Project`_ when a need was felt for "a universal to communicate documents across a wide variety of machine configurations, operating systems and communication networks". The goal was to make these documents viewable on any display and printable on any modern printers. The invention of the `PostScript`_ page description language, which enabled the creation of *fixed-layout* flat documents (with text, fonts, graphics, images encapsulated), solved the problem.
At a high level, PostScript defines instructions, such as "place this character at this *x,y* coordinate on a plane". Spaces can be *simulated* by placing characters relatively far apart. Extending from that, tables can be *simulated* by placing characters (which constitute words) in two-dimensional grids. A PDF viewer just takes these instructions and draws everything for the user to view. Since a PDF is just characters on a plane, there is no table data structure that can be extracted and used for analysis! At a very high level, PostScript defines instructions, such as, "place this character at this x,y coordinate on a plane". Spaces can be *simulated* by placing characters relatively far apart. Extending from that, tables can be *simulated* by placing characters (which constitute words) in two-dimensional grids. A PDF viewer just takes these instructions and draws everything for the user to view. Since it's just characters on a plane, there is no table data structure which can be extracted and used for analysis!
Sadly, a lot of today's open data is trapped in PDF tables. Sadly, a lot of open data is given out as tables which are trapped inside PDF files.
.. _PostScript: http://www.planetpdf.com/planetpdf/pdfs/warnock_camelot.pdf .. _PostScript: http://www.planetpdf.com/planetpdf/pdfs/warnock_camelot.pdf
Why another PDF table extraction library? Why another PDF Table Extraction library?
----------------------------------------- -----------------------------------------
There are both open (`Tabula`_, `pdf-table-extract`_) and closed-source (`smallpdf`_, `PDFTables`_) tools that are widely used to extract tables from PDF files. They either give a nice output or fail miserably. There is no in between. This is not helpful since everything in the real world, including PDF table extraction, is fuzzy. This leads to the creation of ad-hoc table extraction scripts for each type of PDF table. There are both open (`Tabula`_, `pdf-table-extract`_) and closed-source (`smallpdf`_, `PDFTables`_) tools that are widely used, to extract tables from PDF files. They either give a nice output, or fail miserably. There is no in-between. This is not helpful, since everything in the real world, including PDF table extraction, is fuzzy, leading to creation of adhoc table extraction scripts for each different type of PDF that the user wants to parse.
Camelot was created to offer users complete control over table extraction. If you can't get your desired output with the default settings, you can tweak them and get the job done! Camelot was created with the goal of offering its users complete control over table extraction. If the users are not able to get the desired output with the default configuration, they should be able to tweak it and get the job done!
Here is a `comparison`_ of Camelot's output with outputs from other open-source PDF parsing libraries and tools. Here is a `comparison`_ of Camelot's output with outputs from other open-source PDF parsing libraries and tools.
@ -27,18 +27,15 @@ Here is a `comparison`_ of Camelot's output with outputs from other open-source
.. _pdf-table-extract: https://github.com/ashima/pdf-table-extract .. _pdf-table-extract: https://github.com/ashima/pdf-table-extract
.. _PDFTables: https://pdftables.com/ .. _PDFTables: https://pdftables.com/
.. _Smallpdf: https://smallpdf.com .. _Smallpdf: https://smallpdf.com
.. _comparison: https://github.com/camelot-dev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools .. _comparison: https://github.com/socialcopsdev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools
What's in a name? What's in a name?
----------------- -----------------
As you can already guess, this library is named after `The Camelot Project`_. As you can already guess, this library is named after `The Camelot Project`_. Fun fact, "Camelot" is the name of the castle in `Monty Python and the Holy Grail`_, where Arthur leads his men, the Knights of the Round Table, and then sets off elsewhere after deciding that it is "a silly place". Interestingly, the language in which this library is written (Python) was named after Monty Python.
Fun fact: In the British comedy film `Monty Python and the Holy Grail`_ (and in the `Arthurian legend`_ depicted in the film), "Camelot" is the name of the castle where Arthur leads his men, the Knights of the Round Table, and then sets off elsewhere after deciding that it is "a silly place". Interestingly, the language in which this library is written (Python) was named after Monty Python.
.. _The Camelot Project: http://www.planetpdf.com/planetpdf/pdfs/warnock_camelot.pdf .. _The Camelot Project: http://www.planetpdf.com/planetpdf/pdfs/warnock_camelot.pdf
.. _Monty Python and the Holy Grail: https://en.wikipedia.org/wiki/Monty_Python_and_the_Holy_Grail .. _Monty Python and the Holy Grail: https://en.wikipedia.org/wiki/Monty_Python_and_the_Holy_Grail
.. _Arthurian legend: https://en.wikipedia.org/wiki/King_Arthur
Camelot License Camelot License
--------------- ---------------

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@ -3,7 +3,7 @@
Quickstart Quickstart
========== ==========
In a hurry to extract tables from PDFs? This document gives a good introduction to help you get started with Camelot. In a hurry to extract tables from PDFs? This document gives a good introduction to help you get started with using Camelot.
Read the PDF Read the PDF
------------ ------------
@ -14,7 +14,7 @@ Begin by importing the Camelot module::
>>> import camelot >>> import camelot
Now, let's try to read a PDF. (You can check out the PDF used in this example `here`_.) Since the PDF has a table with clearly demarcated lines, we will use the :ref:`Lattice <lattice>` method here. Now, let's try to read a PDF. You can check out the PDF used in this example, `here`_. Since the PDF has a table with clearly demarcated lines, we will use the :ref:`Lattice <lattice>` method here. To do that we will set the ``mesh`` keyword argument to ``True``.
.. note:: :ref:`Lattice <lattice>` is used by default. You can use :ref:`Stream <stream>` with ``flavor='stream'``. .. note:: :ref:`Lattice <lattice>` is used by default. You can use :ref:`Stream <stream>` with ``flavor='stream'``.
@ -47,7 +47,7 @@ Let's print the parsing report.
'page': 1 'page': 1
} }
Woah! The accuracy is top-notch and there is less whitespace, which means the table was most likely extracted correctly. You can access the table as a pandas DataFrame by using the :class:`table <camelot.core.Table>` object's ``df`` property. Woah! The accuracy is top-notch and whitespace is less, that means the table was extracted correctly (most probably). You can access the table as a pandas DataFrame by using the :class:`table <camelot.core.Table>` object's ``df`` property.
:: ::
@ -56,7 +56,7 @@ Woah! The accuracy is top-notch and there is less whitespace, which means the ta
.. csv-table:: .. csv-table::
:file: ../_static/csv/foo.csv :file: ../_static/csv/foo.csv
Looks good! You can now export the table as a CSV file using its :meth:`to_csv() <camelot.core.Table.to_csv>` method. Alternatively you can use :meth:`to_json() <camelot.core.Table.to_json>`, :meth:`to_excel() <camelot.core.Table.to_excel>` :meth:`to_html() <camelot.core.Table.to_html>` :meth:`to_markdown() <camelot.core.Table.to_markdown>` or :meth:`to_sqlite() <camelot.core.Table.to_sqlite>` methods to export the table as JSON, Excel, HTML files or a sqlite database respectively. Looks good! You can be export the table as a CSV file using its :meth:`to_csv() <camelot.core.Table.to_csv>` method. Alternatively you can use :meth:`to_json() <camelot.core.Table.to_json>`, :meth:`to_excel() <camelot.core.Table.to_excel>` or :meth:`to_html() <camelot.core.Table.to_html>` methods to export the table as JSON, Excel and HTML files respectively.
:: ::
@ -70,13 +70,7 @@ You can also export all tables at once, using the :class:`tables <camelot.core.T
>>> tables.export('foo.csv', f='csv') >>> tables.export('foo.csv', f='csv')
.. tip:: This will export all tables as CSV files at the path specified. Alternatively, you can use ``f='json'``, ``f='excel'`` or ``f='html'``.
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot --format csv --output foo.csv lattice foo.pdf
This will export all tables as CSV files at the path specified. Alternatively, you can use ``f='json'``, ``f='excel'``, ``f='html'``, ``f='markdown'`` or ``f='sqlite'``.
.. note:: The :meth:`export() <camelot.core.TableList.export>` method exports files with a ``page-*-table-*`` suffix. In the example above, the single table in the list will be exported to ``foo-page-1-table-1.csv``. If the list contains multiple tables, multiple CSV files will be created. To avoid filling up your path with multiple files, you can use ``compress=True``, which will create a single ZIP file at your path with all the CSV files. .. note:: The :meth:`export() <camelot.core.TableList.export>` method exports files with a ``page-*-table-*`` suffix. In the example above, the single table in the list will be exported to ``foo-page-1-table-1.csv``. If the list contains multiple tables, multiple CSV files will be created. To avoid filling up your path with multiple files, you can use ``compress=True``, which will create a single ZIP file at your path with all the CSV files.
@ -91,42 +85,8 @@ By default, Camelot only uses the first page of the PDF to extract tables. To sp
>>> camelot.read_pdf('your.pdf', pages='1,2,3') >>> camelot.read_pdf('your.pdf', pages='1,2,3')
.. tip:: The ``pages`` keyword argument accepts pages as comma-separated string of page numbers. You can also specify page ranges, for example ``pages=1,4-10,20-30`` or ``pages=1,4-10,20-end``.
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot --pages 1,2,3 lattice your.pdf ------------------------
The ``pages`` keyword argument accepts pages as comma-separated string of page numbers. You can also specify page ranges — for example, ``pages=1,4-10,20-30`` or ``pages=1,4-10,20-end``. Ready for more? Check out the :ref:`advanced <advanced>` section.
Reading encrypted PDFs
----------------------
To extract tables from encrypted PDF files you must provide a password when calling :meth:`read_pdf() <camelot.read_pdf>`.
::
>>> tables = camelot.read_pdf('foo.pdf', password='userpass')
>>> tables
<TableList n=1>
.. tip::
Here's how you can do the same with the :ref:`command-line interface <cli>`.
::
$ camelot --password userpass lattice foo.pdf
Currently Camelot only supports PDFs encrypted with ASCII passwords and algorithm `code 1 or 2`_. An exception is thrown if the PDF cannot be read. This may be due to no password being provided, an incorrect password, or an unsupported encryption algorithm.
Further encryption support may be added in future, however in the meantime if your PDF files are using unsupported encryption algorithms you are advised to remove encryption before calling :meth:`read_pdf() <camelot.read_pdf>`. This can been successfully achieved with third-party tools such as `QPDF`_.
::
$ qpdf --password=<PASSWORD> --decrypt input.pdf output.pdf
.. _code 1 or 2: https://github.com/mstamy2/PyPDF2/issues/378
.. _QPDF: https://www.github.com/qpdf/qpdf
----
Ready for more? Check out the :ref:`advanced <advanced>` section.

3
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@ -0,0 +1,3 @@
pytest==3.8.0
pytest-runner==4.2
Sphinx==1.7.9

7
requirements.txt 100644
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@ -0,0 +1,7 @@
click==6.7
matplotlib==2.2.3
numpy==1.13.3
opencv-python==3.4.2.17
pandas==0.23.4
pdfminer==20140328
PyPDF2==1.26.0

2
setup.cfg
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@ -2,5 +2,5 @@
test=pytest test=pytest
[tool:pytest] [tool:pytest]
addopts = --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot --mpl addopts = --verbose
python_files = tests/test_*.py python_files = tests/test_*.py

109
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@ -2,90 +2,61 @@
import os import os
from setuptools import find_packages from setuptools import find_packages
from pkg_resources import parse_version
here = os.path.abspath(os.path.dirname(__file__)) here = os.path.abspath(os.path.dirname(__file__))
about = {} about = {}
with open(os.path.join(here, "camelot", "__version__.py"), "r") as f: with open(os.path.join(here, 'camelot', '__version__.py'), 'r') as f:
exec(f.read(), about) exec(f.read(), about)
with open("README.md", "r") as f: with open('README.md', 'r') as f:
readme = f.read() readme = f.read()
requires = [
"chardet>=3.0.4",
"click>=6.7",
"numpy>=1.13.3",
"openpyxl>=2.5.8",
"pandas>=0.23.4",
"pdfminer.six>=20200726",
"PyPDF2>=1.26.0",
"tabulate>=0.8.9",
]
base_requires = ["ghostscript>=0.7", "opencv-python>=3.4.2.17", "pdftopng>=0.2.3"]
plot_requires = [
"matplotlib>=2.2.3",
]
dev_requires = [
"codecov>=2.0.15",
"pytest>=5.4.3",
"pytest-cov>=2.10.0",
"pytest-mpl>=0.11",
"pytest-runner>=5.2",
"Sphinx>=3.1.2",
"sphinx-autobuild>=2021.3.14",
]
all_requires = base_requires + plot_requires
dev_requires = dev_requires + all_requires
def setup_package(): def setup_package():
metadata = dict( reqs = []
name=about["__title__"], with open('requirements.txt', 'r') as f:
version=about["__version__"], for line in f:
description=about["__description__"], reqs.append(line.strip())
long_description=readme,
long_description_content_type="text/markdown", dev_reqs = []
url=about["__url__"], with open('requirements-dev.txt', 'r') as f:
author=about["__author__"], for line in f:
author_email=about["__author_email__"], dev_reqs.append(line.strip())
license=about["__license__"],
packages=find_packages(exclude=("tests",)), metadata = dict(name=about['__title__'],
install_requires=requires, version=about['__version__'],
extras_require={ description=about['__description__'],
"all": all_requires, long_description=readme,
"base": base_requires, url=about['__url__'],
"cv": base_requires, # deprecate author=about['__author__'],
"dev": dev_requires, author_email=about['__author_email__'],
"plot": plot_requires, license=about['__license__'],
}, packages=find_packages(exclude=('tests',)),
entry_points={ install_requires=reqs,
"console_scripts": [ extras_require={
"camelot = camelot.cli:cli", 'dev': dev_reqs
], },
}, entry_points={
classifiers=[ 'console_scripts': [
# Trove classifiers 'camelot = camelot.cli:cli',
# Full list: https://pypi.python.org/pypi?%3Aaction=list_classifiers ],
"License :: OSI Approved :: MIT License", },
"Programming Language :: Python :: 3.6", classifiers=[
"Programming Language :: Python :: 3.7", # Trove classifiers
"Programming Language :: Python :: 3.8", # Full list: https://pypi.python.org/pypi?%3Aaction=list_classifiers
], 'License :: OSI Approved :: MIT License',
) 'Programming Language :: Python :: 2.7'
])
try: try:
from setuptools import setup from setuptools import setup
except ImportError: except:
from distutils.core import setup from distutils.core import setup
setup(**metadata) setup(**metadata)
if __name__ == "__main__": if __name__ == '__main__':
setup_package() setup_package()

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import matplotlib
matplotlib.use("agg")

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1 a b
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tests/test_cli.py
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# -*- coding: utf-8 -*-
import os
import sys
import pytest
from click.testing import CliRunner
from camelot.cli import cli
from camelot.utils import TemporaryDirectory
testdir = os.path.dirname(os.path.abspath(__file__))
testdir = os.path.join(testdir, "files")
skip_on_windows = pytest.mark.skipif(
sys.platform.startswith("win"),
reason="Ghostscript not installed in Windows test environment",
)
def test_help_output():
runner = CliRunner()
prog_name = runner.get_default_prog_name(cli)
result = runner.invoke(cli, ["--help"])
output = result.output
assert prog_name == "camelot"
assert result.output.startswith("Usage: %(prog_name)s [OPTIONS] COMMAND" % locals())
assert all(
v in result.output
for v in ["Options:", "--version", "--help", "Commands:", "lattice", "stream"]
)
@skip_on_windows
def test_cli_lattice():
with TemporaryDirectory() as tempdir:
infile = os.path.join(testdir, "foo.pdf")
outfile = os.path.join(tempdir, "foo.csv")
runner = CliRunner()
result = runner.invoke(
cli, ["--format", "csv", "--output", outfile, "lattice", infile]
)
assert result.exit_code == 0
assert "Found 1 tables" in result.output
result = runner.invoke(cli, ["--format", "csv", "lattice", infile])
output_error = "Error: Please specify output file path using --output"
assert output_error in result.output
result = runner.invoke(cli, ["--output", outfile, "lattice", infile])
format_error = "Please specify output file format using --format"
assert format_error in result.output
def test_cli_stream():
with TemporaryDirectory() as tempdir:
infile = os.path.join(testdir, "budget.pdf")
outfile = os.path.join(tempdir, "budget.csv")
runner = CliRunner()
result = runner.invoke(
cli, ["--format", "csv", "--output", outfile, "stream", infile]
)
assert result.exit_code == 0
assert result.output == "Found 1 tables\n"
result = runner.invoke(cli, ["--format", "csv", "stream", infile])
output_error = "Error: Please specify output file path using --output"
assert output_error in result.output
result = runner.invoke(cli, ["--output", outfile, "stream", infile])
format_error = "Please specify output file format using --format"
assert format_error in result.output
def test_cli_password():
with TemporaryDirectory() as tempdir:
infile = os.path.join(testdir, "health_protected.pdf")
outfile = os.path.join(tempdir, "health_protected.csv")
runner = CliRunner()
result = runner.invoke(
cli,
[
"--password",
"userpass",
"--format",
"csv",
"--output",
outfile,
"stream",
infile,
],
)
assert result.exit_code == 0
assert result.output == "Found 1 tables\n"
output_error = "file has not been decrypted"
# no password
result = runner.invoke(
cli, ["--format", "csv", "--output", outfile, "stream", infile]
)
assert output_error in str(result.exception)
# bad password
result = runner.invoke(
cli,
[
"--password",
"wrongpass",
"--format",
"csv",
"--output",
outfile,
"stream",
infile,
],
)
assert output_error in str(result.exception)
def test_cli_output_format():
with TemporaryDirectory() as tempdir:
infile = os.path.join(testdir, "health.pdf")
runner = CliRunner()
# json
outfile = os.path.join(tempdir, "health.json")
result = runner.invoke(
cli,
["--format", "json", "--output", outfile, "stream", infile],
)
assert result.exit_code == 0, f"Output: {result.output}"
# excel
outfile = os.path.join(tempdir, "health.xlsx")
result = runner.invoke(
cli,
["--format", "excel", "--output", outfile, "stream", infile],
)
assert result.exit_code == 0, f"Output: {result.output}"
# html
outfile = os.path.join(tempdir, "health.html")
result = runner.invoke(
cli,
["--format", "html", "--output", outfile, "stream", infile],
)
assert result.exit_code == 0, f"Output: {result.output}"
# markdown
outfile = os.path.join(tempdir, "health.md")
result = runner.invoke(
cli,
["--format", "markdown", "--output", outfile, "stream", infile],
)
assert result.exit_code == 0, f"Output: {result.output}"
# zip
outfile = os.path.join(tempdir, "health.csv")
result = runner.invoke(
cli,
[
"--zip",
"--format",
"csv",
"--output",
outfile,
"stream",
infile,
],
)
assert result.exit_code == 0, f"Output: {result.output}"
def test_cli_quiet():
with TemporaryDirectory() as tempdir:
infile = os.path.join(testdir, "empty.pdf")
outfile = os.path.join(tempdir, "empty.csv")
runner = CliRunner()
result = runner.invoke(
cli, ["--format", "csv", "--output", outfile, "stream", infile]
)
assert "No tables found on page-1" in result.output
result = runner.invoke(
cli, ["--quiet", "--format", "csv", "--output", outfile, "stream", infile]
)
assert "No tables found on page-1" not in result.output

204
tests/test_common.py
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# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import os import os
import sys
import pytest
import pandas as pd import pandas as pd
from pandas.testing import assert_frame_equal
import camelot import camelot
from camelot.io import PDFHandler
from camelot.core import Table, TableList
from camelot.__version__ import generate_version
from camelot.backends import ImageConversionBackend
from .data import * from test_data import *
testdir = os.path.dirname(os.path.abspath(__file__)) testdir = os.path.dirname(os.path.abspath(__file__))
testdir = os.path.join(testdir, "files") testdir = os.path.join(testdir, "files")
skip_on_windows = pytest.mark.skipif(
sys.platform.startswith("win"), def test_stream():
reason="Ghostscript not installed in Windows test environment", pass
)
def test_version_generation(): def test_stream_table_rotated():
version = (0, 7, 3) df = pd.DataFrame(data_stream_table_rotated)
assert generate_version(version, prerelease=None, revision=None) == "0.7.3"
filename = os.path.join(testdir, "clockwise_table_2.pdf")
tables = camelot.read_pdf(filename, flavor="stream")
assert df.equals(tables[0].df)
filename = os.path.join(testdir, "anticlockwise_table_2.pdf")
tables = camelot.read_pdf(filename, flavor="stream")
assert df.equals(tables[0].df)
def test_version_generation_with_prerelease_revision(): def test_stream_table_area():
version = (0, 7, 3) df = pd.DataFrame(data_stream_table_area_single)
prerelease = "alpha"
revision = 2 filename = os.path.join(testdir, "tabula/us-007.pdf")
assert ( tables = camelot.read_pdf(filename, flavor="stream", table_area=["320,500,573,335"])
generate_version(version, prerelease=prerelease, revision=revision) assert df.equals(tables[0].df)
== "0.7.3-alpha.2"
)
@skip_on_windows def test_stream_columns():
def test_parsing_report(): df = pd.DataFrame(data_stream_columns)
parsing_report = {"accuracy": 99.02, "whitespace": 12.24, "order": 1, "page": 1}
filename = os.path.join(testdir, "foo.pdf") filename = os.path.join(testdir, "mexican_towns.pdf")
tables = camelot.read_pdf(
filename, flavor="stream", columns=["67,180,230,425,475"], row_close_tol=10)
assert df.equals(tables[0].df)
def test_lattice():
df = pd.DataFrame(data_lattice)
filename = os.path.join(testdir,
"tabula/icdar2013-dataset/competition-dataset-us/us-030.pdf")
tables = camelot.read_pdf(filename, pages="2")
assert df.equals(tables[0].df)
def test_lattice_table_rotated():
df = pd.DataFrame(data_lattice_table_rotated)
filename = os.path.join(testdir, "clockwise_table_1.pdf")
tables = camelot.read_pdf(filename) tables = camelot.read_pdf(filename)
assert tables[0].parsing_report == parsing_report assert df.equals(tables[0].df)
filename = os.path.join(testdir, "anticlockwise_table_1.pdf")
tables = camelot.read_pdf(filename)
assert df.equals(tables[0].df)
def test_password(): def test_lattice_process_background():
df = pd.DataFrame(data_stream) df = pd.DataFrame(data_lattice_process_background)
filename = os.path.join(testdir, "health_protected.pdf") filename = os.path.join(testdir, "background_lines_1.pdf")
tables = camelot.read_pdf(filename, password="ownerpass", flavor="stream") tables = camelot.read_pdf(filename, process_background=True)
assert_frame_equal(df, tables[0].df) assert df.equals(tables[1].df)
tables = camelot.read_pdf(filename, password="userpass", flavor="stream")
assert_frame_equal(df, tables[0].df)
def test_repr_poppler(): def test_lattice_copy_text():
filename = os.path.join(testdir, "foo.pdf") df = pd.DataFrame(data_lattice_copy_text)
tables = camelot.read_pdf(filename, backend="poppler")
assert repr(tables) == "<TableList n=1>"
assert repr(tables[0]) == "<Table shape=(7, 7)>"
assert repr(tables[0].cells[0][0]) == "<Cell x1=120 y1=219 x2=165 y2=234>"
filename = os.path.join(testdir, "row_span_1.pdf")
@skip_on_windows tables = camelot.read_pdf(filename, line_size_scaling=60, copy_text="v")
def test_repr_ghostscript(): assert df.equals(tables[0].df)
filename = os.path.join(testdir, "foo.pdf")
tables = camelot.read_pdf(filename, backend="ghostscript")
assert repr(tables) == "<TableList n=1>"
assert repr(tables[0]) == "<Table shape=(7, 7)>"
assert repr(tables[0].cells[0][0]) == "<Cell x1=120 y1=218 x2=165 y2=234>"
def test_url_poppler():
url = "https://camelot-py.readthedocs.io/en/master/_static/pdf/foo.pdf"
tables = camelot.read_pdf(url, backend="poppler")
assert repr(tables) == "<TableList n=1>"
assert repr(tables[0]) == "<Table shape=(7, 7)>"
assert repr(tables[0].cells[0][0]) == "<Cell x1=120 y1=219 x2=165 y2=234>"
@skip_on_windows
def test_url_ghostscript():
url = "https://camelot-py.readthedocs.io/en/master/_static/pdf/foo.pdf"
tables = camelot.read_pdf(url, backend="ghostscript")
assert repr(tables) == "<TableList n=1>"
assert repr(tables[0]) == "<Table shape=(7, 7)>"
assert repr(tables[0].cells[0][0]) == "<Cell x1=120 y1=218 x2=165 y2=234>"
def test_pages_poppler():
url = "https://camelot-py.readthedocs.io/en/master/_static/pdf/foo.pdf"
tables = camelot.read_pdf(url, backend="poppler")
assert repr(tables) == "<TableList n=1>"
assert repr(tables[0]) == "<Table shape=(7, 7)>"
assert repr(tables[0].cells[0][0]) == "<Cell x1=120 y1=219 x2=165 y2=234>"
tables = camelot.read_pdf(url, pages="1-end", backend="poppler")
assert repr(tables) == "<TableList n=1>"
assert repr(tables[0]) == "<Table shape=(7, 7)>"
assert repr(tables[0].cells[0][0]) == "<Cell x1=120 y1=219 x2=165 y2=234>"
tables = camelot.read_pdf(url, pages="all", backend="poppler")
assert repr(tables) == "<TableList n=1>"
assert repr(tables[0]) == "<Table shape=(7, 7)>"
assert repr(tables[0].cells[0][0]) == "<Cell x1=120 y1=219 x2=165 y2=234>"
@skip_on_windows
def test_pages_ghostscript():
url = "https://camelot-py.readthedocs.io/en/master/_static/pdf/foo.pdf"
tables = camelot.read_pdf(url, backend="ghostscript")
assert repr(tables) == "<TableList n=1>"
assert repr(tables[0]) == "<Table shape=(7, 7)>"
assert repr(tables[0].cells[0][0]) == "<Cell x1=120 y1=218 x2=165 y2=234>"
tables = camelot.read_pdf(url, pages="1-end", backend="ghostscript")
assert repr(tables) == "<TableList n=1>"
assert repr(tables[0]) == "<Table shape=(7, 7)>"
assert repr(tables[0].cells[0][0]) == "<Cell x1=120 y1=218 x2=165 y2=234>"
tables = camelot.read_pdf(url, pages="all", backend="ghostscript")
assert repr(tables) == "<TableList n=1>"
assert repr(tables[0]) == "<Table shape=(7, 7)>"
assert repr(tables[0].cells[0][0]) == "<Cell x1=120 y1=218 x2=165 y2=234>"
def test_table_order():
def _make_table(page, order):
t = Table([], [])
t.page = page
t.order = order
return t
table_list = TableList(
[_make_table(2, 1), _make_table(1, 1), _make_table(3, 4), _make_table(1, 2)]
)
assert [(t.page, t.order) for t in sorted(table_list)] == [
(1, 1),
(1, 2),
(2, 1),
(3, 4),
]
assert [(t.page, t.order) for t in sorted(table_list, reverse=True)] == [
(3, 4),
(2, 1),
(1, 2),
(1, 1),
]
def test_handler_pages_generator():
filename = os.path.join(testdir, "foo.pdf")
handler = PDFHandler(filename)
assert handler._get_pages("1") == [1]
handler = PDFHandler(filename)
assert handler._get_pages("all") == [1]
handler = PDFHandler(filename)
assert handler._get_pages("1-end") == [1]
handler = PDFHandler(filename)
assert handler._get_pages("1,2,3,4") == [1, 2, 3, 4]
handler = PDFHandler(filename)
assert handler._get_pages("1,2,5-10") == [1, 2, 5, 6, 7, 8, 9, 10]

189
tests/test_data.py 100644
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# -*- coding: utf-8 -*-
data_stream_table_rotated = [
["","","Table 21 Current use of contraception by background characteristics—Continued","","","","","","","","","","","","","","",""],
["","","","","","","Modern method","","","","","","","Traditional method","","","",""],
["","","","Any","","","","","","","Other","Any","","","","Not","","Number"],
["","","Any","modern","Female","Male","","","","Condom/","modern","traditional","","With-","Folk","currently","","of"],
["","Background characteristic","method","method","sterilization","sterilization","Pill","IUD","Injectables","Nirodh","method","method","Rhythm","drawal","method","using","Total","women"],
["","Caste/tribe","","","","","","","","","","","","","","","",""],
["","Scheduled caste","74.8","55.8","42.9","0.9","9.7","0.0","0.2","2.2","0.0","19.0","11.2","7.4","0.4","25.2","100.0","1,363"],
["","Scheduled tribe","59.3","39.0","26.8","0.6","6.4","0.6","1.2","3.5","0.0","20.3","10.4","5.8","4.1","40.7","100.0","256"],
["","Other backward class","71.4","51.1","34.9","0.0","8.6","1.4","0.0","6.2","0.0","20.4","12.6","7.8","0.0","28.6","100.0","211"],
["","Other","71.1","48.8","28.2","0.8","13.3","0.9","0.3","5.2","0.1","22.3","12.9","9.1","0.3","28.9","100.0","3,319"],
["","Wealth index","","","","","","","","","","","","","","","",""],
["","Lowest","64.5","48.6","34.3","0.5","10.5","0.6","0.7","2.0","0.0","15.9","9.9","4.6","1.4","35.5","100.0","1,258"],
["","Second","68.5","50.4","36.2","1.1","11.4","0.5","0.1","1.1","0.0","18.1","11.2","6.7","0.2","31.5","100.0","1,317"],
["","Middle","75.5","52.8","33.6","0.6","14.2","0.4","0.5","3.4","0.1","22.7","13.4","8.9","0.4","24.5","100.0","1,018"],
["","Fourth","73.9","52.3","32.0","0.5","12.5","0.6","0.2","6.3","0.2","21.6","11.5","9.9","0.2","26.1","100.0","908"],
["","Highest","78.3","44.4","19.5","1.0","9.7","1.4","0.0","12.7","0.0","33.8","18.2","15.6","0.0","21.7","100.0","733"],
["","Number of living children","","","","","","","","","","","","","","","",""],
["","No children","25.1","7.6","0.3","0.5","2.0","0.0","0.0","4.8","0.0","17.5","9.0","8.5","0.0","74.9","100.0","563"],
["","1 child","66.5","32.1","3.7","0.7","20.1","0.7","0.1","6.9","0.0","34.3","18.9","15.2","0.3","33.5","100.0","1,190"],
["","1 son","66.8","33.2","4.1","0.7","21.1","0.5","0.3","6.6","0.0","33.5","21.2","12.3","0.0","33.2","100.0","672"],
["","No sons","66.1","30.7","3.1","0.6","18.8","0.8","0.0","7.3","0.0","35.4","15.8","19.0","0.6","33.9","100.0","517"],
["","2 children","81.6","60.5","41.8","0.9","11.6","0.8","0.3","4.8","0.2","21.1","12.2","8.3","0.6","18.4","100.0","1,576"],
["","1 or more sons","83.7","64.2","46.4","0.9","10.8","0.8","0.4","4.8","0.1","19.5","11.1","7.6","0.7","16.3","100.0","1,268"],
["","No sons","73.2","45.5","23.2","1.0","15.1","0.9","0.0","4.8","0.5","27.7","16.8","11.0","0.0","26.8","100.0","308"],
["","3 children","83.9","71.2","57.7","0.8","9.8","0.6","0.5","1.8","0.0","12.7","8.7","3.3","0.8","16.1","100.0","961"],
["","1 or more sons","85.0","73.2","60.3","0.9","9.4","0.5","0.5","1.6","0.0","11.8","8.1","3.0","0.7","15.0","100.0","860"],
["","No sons","74.7","53.8","35.3","0.0","13.7","1.6","0.0","3.2","0.0","20.9","13.4","6.1","1.5","25.3","100.0","101"],
["","4+ children","74.3","58.1","45.1","0.6","8.7","0.6","0.7","2.4","0.0","16.1","9.9","5.4","0.8","25.7","100.0","944"],
["","1 or more sons","73.9","58.2","46.0","0.7","8.3","0.7","0.7","1.9","0.0","15.7","9.4","5.5","0.8","26.1","100.0","901"],
["","No sons","(82.1)","(57.3)","(25.6)","(0.0)","(17.8)","(0.0)","(0.0)","(13.9)","(0.0)","(24.8)","(21.3)","(3.5)","(0.0)","(17.9)","100.0","43"],
["","Total","71.2","49.9","32.2","0.7","11.7","0.6","0.3","4.3","0.1","21.3","12.3","8.4","0.5","28.8","100.0","5,234"],
["","NFHS-2 (1998-99)","66.6","47.3","32.0","1.8","9.2","1.4","na","2.9","na","na","8.7","9.8","na","33.4","100.0","4,116"],
["","NFHS-1 (1992-93)","57.7","37.6","26.5","4.3","3.6","1.3","0.1","1.9","na","na","11.3","8.3","na","42.3","100.0","3,970"],
["","","Note: If more than one method is used, only the most effective method is considered in this tabulation. Total includes women for whom caste/tribe was not known or is missing, who are","","","","","","","","","","","","","","",""],
["","not shown separately.","","","","","","","","","","","","","","","",""],
["","na = Not available","","","","","","","","","","","","","","","",""],
["","","ns = Not shown; see table 2b, footnote 1","","","","","","","","","","","","","","",""],
["","( ) Based on 25-49 unweighted cases.","","","","","","","","","","","","","","","",""],
["","","","","","","","","54","","","","","","","","",""]
]
data_stream_table_area_single = [
["","One Withholding"],
["Payroll Period","Allowance"],
["Weekly","$71.15"],
["Biweekly","142.31"],
["Semimonthly","154.17"],
["Monthly","308.33"],
["Quarterly","925.00"],
["Semiannually","1,850.00"],
["Annually","3,700.00"],
["Daily or Miscellaneous","14.23"],
["(each day of the payroll period)",""]
]
data_stream_columns = [
["Clave","Nombre Entidad","Clave","Nombre Municipio","Clave","Nombre Localidad"],
["Entidad","","Municipio","","Localidad",""],
["01","Aguascalientes","001","Aguascalientes","0094","Granja Adelita"],
["01","Aguascalientes","001","Aguascalientes","0096","Agua Azul"],
["01","Aguascalientes","001","Aguascalientes","0100","Rancho Alegre"],
["01","Aguascalientes","001","Aguascalientes","0102","Los Arbolitos [Rancho]"],
["01","Aguascalientes","001","Aguascalientes","0104","Ardillas de Abajo (Las Ardillas)"],
["01","Aguascalientes","001","Aguascalientes","0106","Arellano"],
["01","Aguascalientes","001","Aguascalientes","0112","Bajío los Vázquez"],
["01","Aguascalientes","001","Aguascalientes","0113","Bajío de Montoro"],
["01","Aguascalientes","001","Aguascalientes","0114","Residencial San Nicolás [Baños la Cantera]"],
["01","Aguascalientes","001","Aguascalientes","0120","Buenavista de Peñuelas"],
["01","Aguascalientes","001","Aguascalientes","0121","Cabecita 3 Marías (Rancho Nuevo)"],
["01","Aguascalientes","001","Aguascalientes","0125","Cañada Grande de Cotorina"],
["01","Aguascalientes","001","Aguascalientes","0126","Cañada Honda [Estación]"],
["01","Aguascalientes","001","Aguascalientes","0127","Los Caños"],
["01","Aguascalientes","001","Aguascalientes","0128","El Cariñán"],
["01","Aguascalientes","001","Aguascalientes","0129","El Carmen [Granja]"],
["01","Aguascalientes","001","Aguascalientes","0135","El Cedazo (Cedazo de San Antonio)"],
["01","Aguascalientes","001","Aguascalientes","0138","Centro de Arriba (El Taray)"],
["01","Aguascalientes","001","Aguascalientes","0139","Cieneguilla (La Lumbrera)"],
["01","Aguascalientes","001","Aguascalientes","0141","Cobos"],
["01","Aguascalientes","001","Aguascalientes","0144","El Colorado (El Soyatal)"],
["01","Aguascalientes","001","Aguascalientes","0146","El Conejal"],
["01","Aguascalientes","001","Aguascalientes","0157","Cotorina de Abajo"],
["01","Aguascalientes","001","Aguascalientes","0162","Coyotes"],
["01","Aguascalientes","001","Aguascalientes","0166","La Huerta (La Cruz)"],
["01","Aguascalientes","001","Aguascalientes","0170","Cuauhtémoc (Las Palomas)"],
["01","Aguascalientes","001","Aguascalientes","0171","Los Cuervos (Los Ojos de Agua)"],
["01","Aguascalientes","001","Aguascalientes","0172","San José [Granja]"],
["01","Aguascalientes","001","Aguascalientes","0176","La Chiripa"],
["01","Aguascalientes","001","Aguascalientes","0182","Dolores"],
["01","Aguascalientes","001","Aguascalientes","0183","Los Dolores"],
["01","Aguascalientes","001","Aguascalientes","0190","El Duraznillo"],
["01","Aguascalientes","001","Aguascalientes","0191","Los Durón"],
["01","Aguascalientes","001","Aguascalientes","0197","La Escondida"],
["01","Aguascalientes","001","Aguascalientes","0201","Brande Vin [Bodegas]"],
["01","Aguascalientes","001","Aguascalientes","0207","Valle Redondo"],
["01","Aguascalientes","001","Aguascalientes","0209","La Fortuna"],
["01","Aguascalientes","001","Aguascalientes","0212","Lomas del Gachupín"],
["01","Aguascalientes","001","Aguascalientes","0213","El Carmen (Gallinas Güeras) [Rancho]"],
["01","Aguascalientes","001","Aguascalientes","0216","La Gloria"],
["01","Aguascalientes","001","Aguascalientes","0226","Hacienda Nueva"],
]
data_lattice = [
["Cycle Name","KI (1/km)","Distance (mi)","Percent Fuel Savings","","",""],
["","","","Improved Speed","Decreased Accel","Eliminate Stops","Decreased Idle"],
["2012_2","3.30","1.3","5.9%","9.5%","29.2%","17.4%"],
["2145_1","0.68","11.2","2.4%","0.1%","9.5%","2.7%"],
["4234_1","0.59","58.7","8.5%","1.3%","8.5%","3.3%"],
["2032_2","0.17","57.8","21.7%","0.3%","2.7%","1.2%"],
["4171_1","0.07","173.9","58.1%","1.6%","2.1%","0.5%"]
]
data_lattice_table_rotated = [
["State","Nutritional Assessment (No. of individuals)","","","","IYCF Practices (No. of mothers: 2011-12)","Blood Pressure (No. of adults: 2011-12)","","Fasting Blood Sugar (No. of adults:2011-12)",""],
["","1975-79","1988-90","1996-97","2011-12","","Men","Women","Men","Women"],
["Kerala","5738","6633","8864","8297","245","2161","3195","1645","2391"],
["Tamil Nadu","7387","10217","5813","7851","413","2134","2858","1119","1739"],
["Karnataka","6453","8138","12606","8958","428","2467","2894","1628","2028"],
["Andhra Pradesh","5844","9920","9545","8300","557","1899","2493","1111","1529"],
["Maharashtra","5161","7796","6883","9525","467","2368","2648","1417","1599"],
["Gujarat","4403","5374","4866","9645","477","2687","3021","2122","2503"],
["Madhya Pradesh","*","*","*","7942","470","1965","2150","1579","1709"],
["Orissa","3756","5540","12024","8473","398","2040","2624","1093","1628"],
["West Bengal","*","*","*","8047","423","2058","2743","1413","2027"],
["Uttar Pradesh","*","*","*","9860","581","2139","2415","1185","1366"],
["Pooled","38742","53618","60601","86898","4459","21918","27041","14312","18519"]
]
data_lattice_process_background = [
["State","Date","Halt stations","Halt days","Persons directly reached(in lakh)","Persons trained","Persons counseled","Persons testedfor HIV"],
["Delhi","1.12.2009","8","17","1.29","3,665","2,409","1,000"],
["Rajasthan","2.12.2009 to 19.12.2009","","","","","",""],
["Gujarat","20.12.2009 to 3.1.2010","6","13","6.03","3,810","2,317","1,453"],
["Maharashtra","4.01.2010 to 1.2.2010","13","26","1.27","5,680","9,027","4,153"],
["Karnataka","2.2.2010 to 22.2.2010","11","19","1.80","5,741","3,658","3,183"],
["Kerala","23.2.2010 to 11.3.2010","9","17","1.42","3,559","2,173","855"],
["Total","","47","92","11.81","22,455","19,584","10,644"]
]
data_lattice_copy_text = [
["Plan Type","County","Plan Name","Totals"],
["GMC","Sacramento","Anthem Blue Cross","164,380"],
["GMC","Sacramento","Health Net","126,547"],
["GMC","Sacramento","Kaiser Foundation","74,620"],
["GMC","Sacramento","Molina Healthcare","59,989"],
["GMC","San Diego","Care 1st Health Plan","71,831"],
["GMC","San Diego","Community Health Group","264,639"],
["GMC","San Diego","Health Net","72,404"],
["GMC","San Diego","Kaiser","50,415"],
["GMC","San Diego","Molina Healthcare","206,430"],
["GMC","Total GMC Enrollment","","1,091,255"],
["COHS","Marin","Partnership Health Plan of CA","36,006"],
["COHS","Mendocino","Partnership Health Plan of CA","37,243"],
["COHS","Napa","Partnership Health Plan of CA","28,398"],
["COHS","Solano","Partnership Health Plan of CA","113,220"],
["COHS","Sonoma","Partnership Health Plan of CA","112,271"],
["COHS","Yolo","Partnership Health Plan of CA","52,674"],
["COHS","Del Norte","Partnership Health Plan of CA","11,242"],
["COHS","Humboldt","Partnership Health Plan of CA","49,911"],
["COHS","Lake","Partnership Health Plan of CA","29,149"],
["COHS","Lassen","Partnership Health Plan of CA","7,360"],
["COHS","Modoc","Partnership Health Plan of CA","2,940"],
["COHS","Shasta","Partnership Health Plan of CA","61,763"],
["COHS","Siskiyou","Partnership Health Plan of CA","16,715"],
["COHS","Trinity","Partnership Health Plan of CA","4,542"],
["COHS","Merced","Central California Alliance for Health","123,907"],
["COHS","Monterey","Central California Alliance for Health","147,397"],
["COHS","Santa Cruz","Central California Alliance for Health","69,458"],
["COHS","Santa Barbara","CenCal","117,609"],
["COHS","San Luis Obispo","CenCal","55,761"],
["COHS","Orange","CalOptima","783,079"],
["COHS","San Mateo","Health Plan of San Mateo","113,202"],
["COHS","Ventura","Gold Coast Health Plan","202,217"],
["COHS","Total COHS Enrollment","","2,176,064"],
["Subtotal for Two-Plan, Regional Model, GMC and COHS","","","10,132,022"],
["PCCM","Los Angeles","AIDS Healthcare Foundation","828"],
["PCCM","San Francisco","Family Mosaic","25"],
["PCCM","Total PHP Enrollment","","853"],
["All Models Total Enrollments","","","10,132,875"],
["Source: Data Warehouse 12/14/15","","",""]
]

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