Fix merge conflict
Vinayak Mehta
commit
9aa219695f
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@ -0,0 +1,10 @@
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root = true
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[*]
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end_of_line = lf
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insert_final_newline = true
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[*.py]
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charset = utf-8
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indent_style = space
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indent_size = 4
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43
.travis.yml
43
.travis.yml
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@ -1,23 +1,32 @@
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sudo: false
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sudo: true
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language: python
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cache: pip
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python:
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- "2.7"
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- "3.5"
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- "3.6"
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matrix:
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include:
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- python: 3.7
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dist: xenial
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sudo: true
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before_install:
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- sudo apt-get install python-tk python3-tk ghostscript
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addons:
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apt:
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update: true
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install:
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- pip install ".[dev]"
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script:
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- pytest --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot tests
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after_success:
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- codecov --verbose
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- make install
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jobs:
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include:
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- stage: test
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script:
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- make test
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python: '2.7'
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- stage: test
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script:
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- make test
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python: '3.5'
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- stage: test
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script:
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- make test
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python: '3.6'
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- stage: test
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script:
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- make test
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python: '3.7'
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dist: xenial
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- stage: coverage
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python: '3.6'
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script:
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- make test
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- codecov --verbose
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94
HISTORY.md
94
HISTORY.md
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@ -1,6 +1,98 @@
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Release History
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===============
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master
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------
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0.5.0 (2018-12-13)
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------------------
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**Improvements**
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* [#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.
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* [#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.
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**Bugfixes**
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* [#217](https://github.com/socialcopsdev/camelot/issues/217) Fix IndexError when scale is large.
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* [#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.
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**Documentation**
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* 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).
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0.4.1 (2018-12-05)
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------------------
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**Bugfixes**
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* 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).
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0.4.0 (2018-11-23)
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------------------
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**Improvements**
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* [#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.
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0.3.2 (2018-11-04)
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------------------
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**Improvements**
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* [#186](https://github.com/socialcopsdev/camelot/issues/186) Add `_bbox` attribute to table. [#193](https://github.com/socialcopsdev/camelot/pull/193) by Vinayak Mehta.
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* You can use `table._bbox` to get coordinates of the detected table.
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0.3.1 (2018-11-02)
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------------------
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**Improvements**
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* Matplotlib is now an optional requirement. [#190](https://github.com/socialcopsdev/camelot/pull/190) by Vinayak Mehta.
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* You can install it using `$ pip install camelot-py[plot]`.
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* [#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).
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0.3.0 (2018-10-28)
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------------------
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**Improvements**
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* [#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).
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* 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.)
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* [#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).
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* Warnings raised by Camelot can now be suppressed by passing `suppress_warnings=True` to `read_pdf` or `--quiet` to the command-line interface.
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* [#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).
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* [#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).
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**Bugfixes**
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* Raise error if the ghostscript executable is not on the PATH variable. [#166](https://github.com/socialcopsdev/camelot/pull/166) by Vinayak Mehta.
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* Convert filename to lowercase to check for PDF extension. [#169](https://github.com/socialcopsdev/camelot/pull/169) by [Vinicius Mesel](https://github.com/vmesel).
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**Files**
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* [#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).
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* Add .editorconfig. [#151](https://github.com/socialcopsdev/camelot/pull/151) by [KOLANICH](https://github.com/KOLANICH).
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* Downgrade numpy version from 1.15.2 to 1.13.3.
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* Add requirements.txt for readthedocs.
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**Documentation**
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* Add "Using conda" section to installation instructions.
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* Add readthedocs badge.
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0.2.3 (2018-10-08)
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------------------
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* Remove hard dependencies on requirements versions.
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0.2.2 (2018-10-08)
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------------------
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**Bugfixes**
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* Move opencv-python to extra\_requires. [#134](https://github.com/socialcopsdev/camelot/pull/134) by Vinayak Mehta.
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0.2.1 (2018-10-05)
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------------------
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@ -51,4 +143,4 @@ Release History
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0.1.0 (2018-09-24)
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------------------
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* Birth!
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* Rebirth!
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|
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@ -1 +1 @@
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include MANIFEST.in README.md HISTORY.md LICENSE requirements.txt requirements-dev.txt setup.py setup.cfg
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include MANIFEST.in README.md HISTORY.md LICENSE setup.py setup.cfg
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|
|
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@ -0,0 +1,28 @@
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.PHONY: docs
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INSTALL :=
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UNAME_S := $(shell uname -s)
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ifeq ($(UNAME_S),Linux)
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INSTALL := @sudo apt install python-tk python3-tk ghostscript
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else ifeq ($(UNAME_S),Darwin)
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INSTALL := @brew install tcl-tk ghostscript
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else
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INSTALL := @echo "Please install tk and ghostscript"
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endif
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install:
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$(INSTALL)
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pip install --upgrade pip
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pip install ".[dev]"
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test:
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pytest --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot --mpl
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docs:
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cd docs && make html
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@echo "\033[95m\n\nBuild successful! View the docs homepage at docs/_build/html/index.html.\n\033[0m"
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publish:
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pip install twine
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python setup.py sdist
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twine upload dist/*
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rm -fr build dist .egg camelot_py.egg-info
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35
README.md
35
README.md
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@ -4,11 +4,14 @@
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# Camelot: PDF Table Extraction for Humans
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[](https://travis-ci.org/socialcopsdev/camelot) [](https://codecov.io/github/socialcopsdev/camelot?branch=master)
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[](https://pypi.org/project/camelot-py/) [](https://pypi.org/project/camelot-py/) [](https://pypi.org/project/camelot-py/)
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[](https://travis-ci.org/socialcopsdev/camelot) [](https://camelot-py.readthedocs.io/en/master/)
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[](https://codecov.io/github/socialcopsdev/camelot?branch=master)
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[](https://pypi.org/project/camelot-py/) [](https://pypi.org/project/camelot-py/) [](https://pypi.org/project/camelot-py/) [](https://gitter.im/camelot-dev/Lobby)
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**Camelot** is a Python library that makes it easy for *anyone* to extract tables from PDF files!
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**Note:** You can also check out [Excalibur](https://github.com/camelot-dev/excalibur), which is a web interface for Camelot!
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---
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**Here's how you can extract tables from PDF files.** Check out the PDF used in this example [here](https://github.com/socialcopsdev/camelot/blob/master/docs/_static/pdf/foo.pdf).
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@ -41,7 +44,7 @@
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| 2032_2 | 0.17 | 57.8 | 21.7% | 0.3% | 2.7% | 1.2% |
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| 4171_1 | 0.07 | 173.9 | 58.1% | 1.6% | 2.1% | 0.5% |
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There's a [command-line interface](https://camelot-py.readthedocs.io/en/latest/user/cli.html) too!
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There's a [command-line interface](https://camelot-py.readthedocs.io/en/master/user/cli.html) too!
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**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".)
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@ -56,15 +59,25 @@ See [comparison with other PDF table extraction libraries and tools](https://git
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## Installation
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After [installing the dependencies](https://camelot-py.readthedocs.io/en/latest/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:
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### Using conda
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The easiest way to install Camelot is to install it with [conda](https://conda.io/docs/), which is a package manager and environment management system for the [Anaconda](http://docs.continuum.io/anaconda/) distribution.
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<pre>
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$ pip install camelot-py
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$ conda install -c conda-forge camelot-py
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</pre>
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### Alternatively
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### Using pip
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After [installing the dependencies](https://camelot-py.readthedocs.io/en/latest/user/install.html), clone the repo using:
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After [installing the dependencies](https://camelot-py.readthedocs.io/en/master/user/install-deps.html) ([tk](https://packages.ubuntu.com/trusty/python-tk) and [ghostscript](https://www.ghostscript.com/)), you can simply use pip to install Camelot:
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<pre>
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$ pip install camelot-py[cv]
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</pre>
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### From the source code
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After [installing the dependencies](https://camelot-py.readthedocs.io/en/master/user/install.html#using-pip), clone the repo using:
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<pre>
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$ git clone https://www.github.com/socialcopsdev/camelot
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@ -74,18 +87,16 @@ and install Camelot using pip:
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<pre>
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$ cd camelot
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$ pip install .
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$ pip install ".[cv]"
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</pre>
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**Note:** Use a [virtualenv](https://virtualenv.pypa.io/en/stable/) if you don't want to affect your global Python installation.
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|
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## Documentation
|
||||
|
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Great documentation is available at [http://camelot-py.readthedocs.io/](http://camelot-py.readthedocs.io/).
|
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|
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## Development
|
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The [Contributor's Guide](https://camelot-py.readthedocs.io/en/latest/dev/contributing.html) has detailed information about contributing code, documentation, tests and more. We've included some basic information in this README.
|
||||
The [Contributor's Guide](https://camelot-py.readthedocs.io/en/master/dev/contributing.html) has detailed information about contributing code, documentation, tests and more. We've included some basic information in this README.
|
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|
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### Source code
|
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|
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@ -117,4 +128,4 @@ Camelot uses [Semantic Versioning](https://semver.org/). For the available versi
|
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|
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## License
|
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|
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This project is licensed under the MIT License, see the [LICENSE](https://github.com/socialcopsdev/camelot/blob/master/LICENSE) file for details.
|
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This project is licensed under the MIT License, see the [LICENSE](https://github.com/socialcopsdev/camelot/blob/master/LICENSE) file for details.
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|
|
|
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@ -2,10 +2,21 @@
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import logging
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from click import HelpFormatter
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|
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from .__version__ import __version__
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from .io import read_pdf
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from .plotting import PlotMethods
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def _write_usage(self, prog, args='', prefix='Usage: '):
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return self._write_usage('camelot', args, prefix=prefix)
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# monkey patch click.HelpFormatter
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HelpFormatter._write_usage = HelpFormatter.write_usage
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HelpFormatter.write_usage = _write_usage
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# set up logging
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logger = logging.getLogger('camelot')
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|
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@ -15,3 +26,6 @@ handler = logging.StreamHandler()
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handler.setFormatter(formatter)
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logger.addHandler(handler)
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# instantiate plot method
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plot = PlotMethods()
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|
|
|
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|
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@ -0,0 +1,16 @@
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# -*- coding: utf-8 -*-
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|
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from __future__ import absolute_import
|
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|
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|
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__all__ = ('main',)
|
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|
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|
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def main():
|
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from camelot.cli import cli
|
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|
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cli()
|
||||
|
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|
||||
if __name__ == "__main__":
|
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main()
|
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|
|
@ -1,11 +1,23 @@
|
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# -*- coding: utf-8 -*-
|
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|
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VERSION = (0, 2, 1)
|
||||
VERSION = (0, 5, 0)
|
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PRERELEASE = None # alpha, beta or rc
|
||||
REVISION = None
|
||||
|
||||
|
||||
def generate_version(version, prerelease=None, revision=None):
|
||||
version_parts = ['.'.join(map(str, version))]
|
||||
if prerelease is not None:
|
||||
version_parts.append('-{}'.format(prerelease))
|
||||
if revision is not None:
|
||||
version_parts.append('.{}'.format(revision))
|
||||
return ''.join(version_parts)
|
||||
|
||||
|
||||
__title__ = 'camelot-py'
|
||||
__description__ = 'PDF Table Extraction for Humans.'
|
||||
__url__ = 'http://camelot-py.readthedocs.io/'
|
||||
__version__ = '.'.join(map(str, VERSION))
|
||||
__version__ = generate_version(VERSION, prerelease=PRERELEASE, revision=REVISION)
|
||||
__author__ = 'Vinayak Mehta'
|
||||
__author_email__ = 'vmehta94@gmail.com'
|
||||
__license__ = 'MIT License'
|
||||
|
|
|
|||
|
|
@ -3,9 +3,14 @@
|
|||
import logging
|
||||
|
||||
import click
|
||||
try:
|
||||
import matplotlib.pyplot as plt
|
||||
except ImportError:
|
||||
_HAS_MPL = False
|
||||
else:
|
||||
_HAS_MPL = True
|
||||
|
||||
from . import __version__
|
||||
from .io import read_pdf
|
||||
from . import __version__, read_pdf, plot
|
||||
|
||||
|
||||
logger = logging.getLogger('camelot')
|
||||
|
|
@ -25,8 +30,10 @@ pass_config = click.make_pass_decorator(Config)
|
|||
|
||||
@click.group()
|
||||
@click.version_option(version=__version__)
|
||||
@click.option('-q', '--quiet', is_flag=False, help='Suppress logs and warnings.')
|
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@click.option('-p', '--pages', default='1', help='Comma-separated page numbers.'
|
||||
' Example: 1,3,4 or 1,4-end.')
|
||||
@click.option('-pw', '--password', help='Password for decryption.')
|
||||
@click.option('-o', '--output', help='Output file path.')
|
||||
@click.option('-f', '--format',
|
||||
type=click.Choice(['csv', 'json', 'excel', 'html']),
|
||||
|
|
@ -47,7 +54,7 @@ def cli(ctx, *args, **kwargs):
|
|||
|
||||
|
||||
@cli.command('lattice')
|
||||
@click.option('-T', '--table_area', default=[], multiple=True,
|
||||
@click.option('-T', '--table_areas', default=[], multiple=True,
|
||||
help='Table areas to process. Example: x1,y1,x2,y2'
|
||||
' where x1, y1 -> left-top and x2, y2 -> right-bottom.')
|
||||
@click.option('-back', '--process_background', is_flag=True,
|
||||
|
|
@ -78,8 +85,8 @@ def cli(ctx, *args, **kwargs):
|
|||
@click.option('-I', '--iterations', default=0,
|
||||
help='Number of times for erosion/dilation will be applied.')
|
||||
@click.option('-plot', '--plot_type',
|
||||
type=click.Choice(['text', 'table', 'contour', 'joint', 'line']),
|
||||
help='Plot geometry found on PDF page, for debugging.')
|
||||
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
|
||||
def lattice(c, *args, **kwargs):
|
||||
|
|
@ -89,31 +96,39 @@ def lattice(c, *args, **kwargs):
|
|||
output = conf.pop('output')
|
||||
f = conf.pop('format')
|
||||
compress = conf.pop('zip')
|
||||
quiet = conf.pop('quiet')
|
||||
plot_type = kwargs.pop('plot_type')
|
||||
filepath = kwargs.pop('filepath')
|
||||
kwargs.update(conf)
|
||||
|
||||
table_area = list(kwargs['table_area'])
|
||||
kwargs['table_area'] = None if not table_area else table_area
|
||||
table_areas = list(kwargs['table_areas'])
|
||||
kwargs['table_areas'] = None if not table_areas else table_areas
|
||||
copy_text = list(kwargs['copy_text'])
|
||||
kwargs['copy_text'] = None if not copy_text else copy_text
|
||||
kwargs['shift_text'] = list(kwargs['shift_text'])
|
||||
|
||||
tables = read_pdf(filepath, pages=pages, flavor='lattice', **kwargs)
|
||||
click.echo('Found {} tables'.format(tables.n))
|
||||
if plot_type is not None:
|
||||
for table in tables:
|
||||
table.plot(plot_type)
|
||||
if not _HAS_MPL:
|
||||
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('Found {} tables'.format(tables.n))
|
||||
if plot_type is not None:
|
||||
for table in tables:
|
||||
plot(table, kind=plot_type)
|
||||
plt.show()
|
||||
else:
|
||||
tables.export(output, f=f, compress=compress)
|
||||
|
||||
|
||||
@cli.command('stream')
|
||||
@click.option('-T', '--table_area', default=[], multiple=True,
|
||||
@click.option('-T', '--table_areas', default=[], multiple=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,
|
||||
|
|
@ -123,8 +138,8 @@ def lattice(c, *args, **kwargs):
|
|||
@click.option('-c', '--col_close_tol', default=0, help='Tolerance parameter'
|
||||
' used to combine text horizontally, to generate columns.')
|
||||
@click.option('-plot', '--plot_type',
|
||||
type=click.Choice(['text', 'table']),
|
||||
help='Plot geometry found on PDF page for debugging.')
|
||||
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
|
||||
def stream(c, *args, **kwargs):
|
||||
|
|
@ -134,23 +149,31 @@ def stream(c, *args, **kwargs):
|
|||
output = conf.pop('output')
|
||||
f = conf.pop('format')
|
||||
compress = conf.pop('zip')
|
||||
quiet = conf.pop('quiet')
|
||||
plot_type = kwargs.pop('plot_type')
|
||||
filepath = kwargs.pop('filepath')
|
||||
kwargs.update(conf)
|
||||
|
||||
table_area = list(kwargs['table_area'])
|
||||
kwargs['table_area'] = None if not table_area else table_area
|
||||
table_areas = list(kwargs['table_areas'])
|
||||
kwargs['table_areas'] = None if not table_areas else table_areas
|
||||
columns = list(kwargs['columns'])
|
||||
kwargs['columns'] = None if not columns else columns
|
||||
|
||||
tables = read_pdf(filepath, pages=pages, flavor='stream', **kwargs)
|
||||
click.echo('Found {} tables'.format(tables.n))
|
||||
if plot_type is not None:
|
||||
for table in tables:
|
||||
table.plot(plot_type)
|
||||
if not _HAS_MPL:
|
||||
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('Found {} tables'.format(tables.n))
|
||||
if plot_type is not None:
|
||||
for table in tables:
|
||||
plot(table, kind=plot_type)
|
||||
plt.show()
|
||||
else:
|
||||
tables.export(output, f=f, compress=compress)
|
||||
|
|
|
|||
228
camelot/core.py
228
camelot/core.py
|
|
@ -3,11 +3,208 @@
|
|||
import os
|
||||
import zipfile
|
||||
import tempfile
|
||||
from itertools import chain
|
||||
from operator import itemgetter
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
|
||||
from .plotting import *
|
||||
|
||||
# minimum number of vertical textline intersections for a textedge
|
||||
# to be considered valid
|
||||
TEXTEDGE_REQUIRED_ELEMENTS = 4
|
||||
# y coordinate tolerance for extending textedge
|
||||
TEXTEDGE_EXTEND_TOLERANCE = 50
|
||||
# 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):
|
||||
return '<TextEdge x={} y0={} y1={} align={} valid={}>'.format(
|
||||
round(self.x, 2), round(self.y0, 2), round(self.y1, 2), self.align, self.is_valid)
|
||||
|
||||
def update_coords(self, x, y0):
|
||||
"""Updates the text edge's x and bottom y coordinates and sets
|
||||
the is_valid attribute.
|
||||
"""
|
||||
if np.isclose(self.y0, y0, atol=TEXTEDGE_EXTEND_TOLERANCE):
|
||||
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):
|
||||
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)
|
||||
|
||||
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):
|
||||
|
|
@ -251,7 +448,7 @@ class Table(object):
|
|||
self.cells[L][J].top = True
|
||||
J += 1
|
||||
elif i == []: # only bottom edge
|
||||
I = len(self.rows) - 1
|
||||
L = len(self.rows) - 1
|
||||
if k:
|
||||
K = k[0]
|
||||
while J < K:
|
||||
|
|
@ -321,33 +518,6 @@ class Table(object):
|
|||
cell.hspan = True
|
||||
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):
|
||||
"""Writes Table to a comma-separated values (csv) file.
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
|
||||
import os
|
||||
import sys
|
||||
|
||||
from PyPDF2 import PdfFileReader, PdfFileWriter
|
||||
|
||||
|
|
@ -21,14 +22,22 @@ class PDFHandler(object):
|
|||
Path to PDF file.
|
||||
pages : str, optional (default: '1')
|
||||
Comma-separated page numbers.
|
||||
Example: 1,3,4 or 1,4-end.
|
||||
Example: '1,3,4' or '1,4-end'.
|
||||
password : str, optional (default: None)
|
||||
Password for decryption.
|
||||
|
||||
"""
|
||||
def __init__(self, filename, pages='1'):
|
||||
def __init__(self, filename, pages='1', password=None):
|
||||
self.filename = filename
|
||||
if not self.filename.endswith('.pdf'):
|
||||
if not filename.lower().endswith('.pdf'):
|
||||
raise NotImplementedError("File format not supported")
|
||||
self.pages = self._get_pages(self.filename, pages)
|
||||
if password is None:
|
||||
self.password = ''
|
||||
else:
|
||||
self.password = password
|
||||
if sys.version_info[0] < 3:
|
||||
self.password = self.password.encode('ascii')
|
||||
|
||||
def _get_pages(self, filename, pages):
|
||||
"""Converts pages string to list of ints.
|
||||
|
|
@ -52,6 +61,8 @@ class PDFHandler(object):
|
|||
page_numbers.append({'start': 1, 'end': 1})
|
||||
else:
|
||||
infile = PdfFileReader(open(filename, 'rb'), strict=False)
|
||||
if infile.isEncrypted:
|
||||
infile.decrypt(self.password)
|
||||
if pages == 'all':
|
||||
page_numbers.append({'start': 1, 'end': infile.getNumPages()})
|
||||
else:
|
||||
|
|
@ -84,7 +95,7 @@ class PDFHandler(object):
|
|||
with open(filename, 'rb') as fileobj:
|
||||
infile = PdfFileReader(fileobj, strict=False)
|
||||
if infile.isEncrypted:
|
||||
infile.decrypt('')
|
||||
infile.decrypt(self.password)
|
||||
fpath = os.path.join(temp, 'page-{0}.pdf'.format(page))
|
||||
froot, fext = os.path.splitext(fpath)
|
||||
p = infile.getPage(page - 1)
|
||||
|
|
@ -103,7 +114,7 @@ class PDFHandler(object):
|
|||
os.rename(fpath, fpath_new)
|
||||
infile = PdfFileReader(open(fpath_new, 'rb'), strict=False)
|
||||
if infile.isEncrypted:
|
||||
infile.decrypt('')
|
||||
infile.decrypt(self.password)
|
||||
outfile = PdfFileWriter()
|
||||
p = infile.getPage(0)
|
||||
if rotation == 'anticlockwise':
|
||||
|
|
@ -114,7 +125,7 @@ class PDFHandler(object):
|
|||
with open(fpath, 'wb') as f:
|
||||
outfile.write(f)
|
||||
|
||||
def parse(self, flavor='lattice', **kwargs):
|
||||
def parse(self, flavor='lattice', suppress_stdout=False, **kwargs):
|
||||
"""Extracts tables by calling parser.get_tables on all single
|
||||
page PDFs.
|
||||
|
||||
|
|
@ -123,6 +134,8 @@ class PDFHandler(object):
|
|||
flavor : str (default: 'lattice')
|
||||
The parsing method to use ('lattice' or 'stream').
|
||||
Lattice is used by default.
|
||||
suppress_stdout : str (default: False)
|
||||
Suppress logs and warnings.
|
||||
kwargs : dict
|
||||
See camelot.read_pdf kwargs.
|
||||
|
||||
|
|
@ -130,9 +143,6 @@ class PDFHandler(object):
|
|||
-------
|
||||
tables : camelot.core.TableList
|
||||
List of tables found in PDF.
|
||||
geometry : camelot.core.GeometryList
|
||||
List of geometry objects (contours, lines, joints) found
|
||||
in PDF.
|
||||
|
||||
"""
|
||||
tables = []
|
||||
|
|
@ -143,6 +153,6 @@ class PDFHandler(object):
|
|||
for p in self.pages]
|
||||
parser = Lattice(**kwargs) if flavor == 'lattice' else Stream(**kwargs)
|
||||
for p in pages:
|
||||
t = parser.extract_tables(p)
|
||||
t = parser.extract_tables(p, suppress_stdout=suppress_stdout)
|
||||
tables.extend(t)
|
||||
return TableList(tables)
|
||||
|
|
|
|||
|
|
@ -1,10 +1,12 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
import warnings
|
||||
|
||||
from .handlers import PDFHandler
|
||||
from .utils import validate_input, remove_extra
|
||||
|
||||
|
||||
def read_pdf(filepath, pages='1', flavor='lattice', **kwargs):
|
||||
def read_pdf(filepath, pages='1', password=None, flavor='lattice',
|
||||
suppress_stdout=False, **kwargs):
|
||||
"""Read PDF and return extracted tables.
|
||||
|
||||
Note: kwargs annotated with ^ can only be used with flavor='stream'
|
||||
|
|
@ -16,11 +18,15 @@ def read_pdf(filepath, pages='1', flavor='lattice', **kwargs):
|
|||
Path to PDF file.
|
||||
pages : str, optional (default: '1')
|
||||
Comma-separated page numbers.
|
||||
Example: 1,3,4 or 1,4-end.
|
||||
Example: '1,3,4' or '1,4-end'.
|
||||
password : str, optional (default: None)
|
||||
Password for decryption.
|
||||
flavor : str (default: 'lattice')
|
||||
The parsing method to use ('lattice' or 'stream').
|
||||
Lattice is used by default.
|
||||
table_area : list, optional (default: None)
|
||||
suppress_stdout : bool, optional (default: True)
|
||||
Print all logs and warnings.
|
||||
table_areas : list, optional (default: None)
|
||||
List of table area strings of the form x1,y1,x2,y2
|
||||
where (x1, y1) -> left-top and (x2, y2) -> right-bottom
|
||||
in PDF coordinate space.
|
||||
|
|
@ -85,8 +91,12 @@ def read_pdf(filepath, pages='1', flavor='lattice', **kwargs):
|
|||
raise NotImplementedError("Unknown flavor specified."
|
||||
" Use either 'lattice' or 'stream'")
|
||||
|
||||
validate_input(kwargs, flavor=flavor)
|
||||
p = PDFHandler(filepath, pages)
|
||||
kwargs = remove_extra(kwargs, flavor=flavor)
|
||||
tables = p.parse(flavor=flavor, **kwargs)
|
||||
return tables
|
||||
with warnings.catch_warnings():
|
||||
if suppress_stdout:
|
||||
warnings.simplefilter("ignore")
|
||||
|
||||
validate_input(kwargs, flavor=flavor)
|
||||
p = PDFHandler(filepath, pages=pages, password=password)
|
||||
kwargs = remove_extra(kwargs, flavor=flavor)
|
||||
tables = p.parse(flavor=flavor, suppress_stdout=suppress_stdout, **kwargs)
|
||||
return tables
|
||||
|
|
|
|||
|
|
@ -31,7 +31,7 @@ class Lattice(BaseParser):
|
|||
|
||||
Parameters
|
||||
----------
|
||||
table_area : list, optional (default: None)
|
||||
table_areas : list, optional (default: None)
|
||||
List of table area strings of the form x1,y1,x2,y2
|
||||
where (x1, y1) -> left-top and (x2, y2) -> right-bottom
|
||||
in PDF coordinate space.
|
||||
|
|
@ -79,12 +79,12 @@ class Lattice(BaseParser):
|
|||
For more information, refer `PDFMiner docs <https://euske.github.io/pdfminer/>`_.
|
||||
|
||||
"""
|
||||
def __init__(self, table_area=None, process_background=False,
|
||||
def __init__(self, table_areas=None, process_background=False,
|
||||
line_size_scaling=15, copy_text=None, shift_text=['l', 't'],
|
||||
split_text=False, flag_size=False, line_close_tol=2,
|
||||
joint_close_tol=2, threshold_blocksize=15, threshold_constant=-2,
|
||||
iterations=0, margins=(1.0, 0.5, 0.1), **kwargs):
|
||||
self.table_area = table_area
|
||||
self.table_areas = table_areas
|
||||
self.process_background = process_background
|
||||
self.line_size_scaling = line_size_scaling
|
||||
self.copy_text = copy_text
|
||||
|
|
@ -210,9 +210,9 @@ class Lattice(BaseParser):
|
|||
self.threshold, direction='horizontal',
|
||||
line_size_scaling=self.line_size_scaling, iterations=self.iterations)
|
||||
|
||||
if self.table_area is not None:
|
||||
if self.table_areas is not None:
|
||||
areas = []
|
||||
for area in self.table_area:
|
||||
for area in self.table_areas:
|
||||
x1, y1, x2, y2 = area.split(",")
|
||||
x1 = float(x1)
|
||||
y1 = float(y1)
|
||||
|
|
@ -237,10 +237,11 @@ class Lattice(BaseParser):
|
|||
tk, self.vertical_segments, self.horizontal_segments)
|
||||
t_bbox['horizontal'] = text_in_bbox(tk, self.horizontal_text)
|
||||
t_bbox['vertical'] = text_in_bbox(tk, self.vertical_text)
|
||||
self.t_bbox = t_bbox
|
||||
|
||||
for direction in t_bbox:
|
||||
t_bbox[direction].sort(key=lambda x: (-x.y0, x.x0))
|
||||
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
|
||||
|
||||
cols, rows = zip(*self.table_bbox[tk])
|
||||
cols, rows = list(cols), list(rows)
|
||||
|
|
@ -274,7 +275,9 @@ class Lattice(BaseParser):
|
|||
table = table.set_span()
|
||||
|
||||
pos_errors = []
|
||||
for direction in self.t_bbox:
|
||||
# TODO: have a single list in place of two directional ones?
|
||||
# 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]:
|
||||
indices, error = get_table_index(
|
||||
table, t, direction, split_text=self.split_text,
|
||||
|
|
@ -307,12 +310,14 @@ class Lattice(BaseParser):
|
|||
table._text = _text
|
||||
table._image = (self.image, self.table_bbox_unscaled)
|
||||
table._segments = (self.vertical_segments, self.horizontal_segments)
|
||||
table._textedges = None
|
||||
|
||||
return table
|
||||
|
||||
def extract_tables(self, filename):
|
||||
def extract_tables(self, filename, suppress_stdout=False):
|
||||
self._generate_layout(filename)
|
||||
logger.info('Processing {}'.format(os.path.basename(self.rootname)))
|
||||
if not suppress_stdout:
|
||||
logger.info('Processing {}'.format(os.path.basename(self.rootname)))
|
||||
|
||||
if not self.horizontal_text:
|
||||
warnings.warn("No tables found on {}".format(
|
||||
|
|
@ -328,6 +333,7 @@ class Lattice(BaseParser):
|
|||
self.table_bbox.keys(), key=lambda x: x[1], reverse=True)):
|
||||
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._bbox = tk
|
||||
_tables.append(table)
|
||||
|
||||
return _tables
|
||||
|
|
|
|||
|
|
@ -9,7 +9,7 @@ import numpy as np
|
|||
import pandas as pd
|
||||
|
||||
from .base import BaseParser
|
||||
from ..core import Table
|
||||
from ..core import TextEdges, Table
|
||||
from ..utils import (text_in_bbox, get_table_index, compute_accuracy,
|
||||
compute_whitespace)
|
||||
|
||||
|
|
@ -26,7 +26,7 @@ class Stream(BaseParser):
|
|||
|
||||
Parameters
|
||||
----------
|
||||
table_area : list, optional (default: None)
|
||||
table_areas : list, optional (default: None)
|
||||
List of table area strings of the form x1,y1,x2,y2
|
||||
where (x1, y1) -> left-top and (x2, y2) -> right-bottom
|
||||
in PDF coordinate space.
|
||||
|
|
@ -50,10 +50,10 @@ class Stream(BaseParser):
|
|||
For more information, refer `PDFMiner docs <https://euske.github.io/pdfminer/>`_.
|
||||
|
||||
"""
|
||||
def __init__(self, table_area=None, columns=None, split_text=False,
|
||||
def __init__(self, table_areas=None, columns=None, split_text=False,
|
||||
flag_size=False, row_close_tol=2, col_close_tol=0,
|
||||
margins=(1.0, 0.5, 0.1), **kwargs):
|
||||
self.table_area = table_area
|
||||
self.table_areas = table_areas
|
||||
self.columns = columns
|
||||
self._validate_columns()
|
||||
self.split_text = split_text
|
||||
|
|
@ -116,7 +116,7 @@ class Stream(BaseParser):
|
|||
row_y = t.y0
|
||||
temp.append(t)
|
||||
rows.append(sorted(temp, key=lambda t: t.x0))
|
||||
__ = rows.pop(0) # hacky
|
||||
__ = rows.pop(0) # TODO: hacky
|
||||
return rows
|
||||
|
||||
@staticmethod
|
||||
|
|
@ -241,15 +241,42 @@ class Stream(BaseParser):
|
|||
return cols
|
||||
|
||||
def _validate_columns(self):
|
||||
if self.table_area is not None and self.columns is not None:
|
||||
if len(self.table_area) != len(self.columns):
|
||||
raise ValueError("Length of table_area and columns"
|
||||
if self.table_areas is not None and self.columns is not None:
|
||||
if len(self.table_areas) != len(self.columns):
|
||||
raise ValueError("Length of table_areas 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()
|
||||
# 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):
|
||||
if self.table_area is not None:
|
||||
self.textedges = []
|
||||
if self.table_areas is not None:
|
||||
table_bbox = {}
|
||||
for area in self.table_area:
|
||||
for area in self.table_areas:
|
||||
x1, y1, x2, y2 = area.split(",")
|
||||
x1 = float(x1)
|
||||
y1 = float(y1)
|
||||
|
|
@ -257,7 +284,8 @@ class Stream(BaseParser):
|
|||
y2 = float(y2)
|
||||
table_bbox[(x1, y2, x2, y1)] = None
|
||||
else:
|
||||
table_bbox = {(0, 0, self.pdf_width, self.pdf_height): None}
|
||||
# find tables based on nurminen's detection algorithm
|
||||
table_bbox = self._nurminen_table_detection(self.horizontal_text)
|
||||
self.table_bbox = table_bbox
|
||||
|
||||
def _generate_columns_and_rows(self, table_idx, tk):
|
||||
|
|
@ -265,10 +293,11 @@ class Stream(BaseParser):
|
|||
t_bbox = {}
|
||||
t_bbox['horizontal'] = text_in_bbox(tk, self.horizontal_text)
|
||||
t_bbox['vertical'] = text_in_bbox(tk, self.vertical_text)
|
||||
self.t_bbox = t_bbox
|
||||
|
||||
for direction in self.t_bbox:
|
||||
self.t_bbox[direction].sort(key=lambda x: (-x.y0, x.x0))
|
||||
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
|
||||
|
||||
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_close_tol=self.row_close_tol)
|
||||
|
|
@ -286,10 +315,21 @@ class Stream(BaseParser):
|
|||
cols.append(text_x_max)
|
||||
cols = [(cols[i], cols[i + 1]) for i in range(0, len(cols) - 1)]
|
||||
else:
|
||||
# calculate mode of the list of number of elements in
|
||||
# each row to guess the number of columns
|
||||
ncols = max(set(elements), key=elements.count)
|
||||
if ncols == 1:
|
||||
warnings.warn("No tables found on {}".format(
|
||||
os.path.basename(self.rootname)))
|
||||
# if mode is 1, the page usually contains not tables
|
||||
# but there can be cases where the list can be skewed,
|
||||
# try to remove all 1s from list in this case and
|
||||
# see if the list contains elements, if yes, then use
|
||||
# the mode after removing 1s
|
||||
elements = list(filter(lambda x: x != 1, elements))
|
||||
if len(elements):
|
||||
ncols = max(set(elements), key=elements.count)
|
||||
else:
|
||||
warnings.warn("No tables found in table area {}".format(
|
||||
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), col_close_tol=self.col_close_tol)
|
||||
inner_text = []
|
||||
|
|
@ -311,8 +351,11 @@ class Stream(BaseParser):
|
|||
def _generate_table(self, table_idx, cols, rows, **kwargs):
|
||||
table = Table(cols, rows)
|
||||
table = table.set_all_edges()
|
||||
|
||||
pos_errors = []
|
||||
for direction in self.t_bbox:
|
||||
# TODO: have a single list in place of two directional ones?
|
||||
# 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]:
|
||||
indices, error = get_table_index(
|
||||
table, t, direction, split_text=self.split_text,
|
||||
|
|
@ -341,12 +384,14 @@ class Stream(BaseParser):
|
|||
table._text = _text
|
||||
table._image = None
|
||||
table._segments = None
|
||||
table._textedges = self.textedges
|
||||
|
||||
return table
|
||||
|
||||
def extract_tables(self, filename):
|
||||
def extract_tables(self, filename, suppress_stdout=False):
|
||||
self._generate_layout(filename)
|
||||
logger.info('Processing {}'.format(os.path.basename(self.rootname)))
|
||||
if not suppress_stdout:
|
||||
logger.info('Processing {}'.format(os.path.basename(self.rootname)))
|
||||
|
||||
if not self.horizontal_text:
|
||||
warnings.warn("No tables found on {}".format(
|
||||
|
|
@ -361,6 +406,7 @@ class Stream(BaseParser):
|
|||
self.table_bbox.keys(), key=lambda x: x[1], reverse=True)):
|
||||
cols, rows = self._generate_columns_and_rows(table_idx, tk)
|
||||
table = self._generate_table(table_idx, cols, rows)
|
||||
table._bbox = tk
|
||||
_tables.append(table)
|
||||
|
||||
return _tables
|
||||
|
|
|
|||
|
|
@ -1,108 +1,244 @@
|
|||
import cv2
|
||||
import matplotlib.pyplot as plt
|
||||
import matplotlib.patches as patches
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
try:
|
||||
import matplotlib.pyplot as plt
|
||||
import matplotlib.patches as patches
|
||||
except ImportError:
|
||||
_HAS_MPL = False
|
||||
else:
|
||||
_HAS_MPL = True
|
||||
|
||||
|
||||
def plot_text(text):
|
||||
"""Generates a plot for all text present on the PDF page.
|
||||
class PlotMethods(object):
|
||||
def __call__(self, table, kind='text', filename=None):
|
||||
"""Plot elements found on PDF page based on kind
|
||||
specified, useful for debugging and playing with different
|
||||
parameters to get the best output.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
text : list
|
||||
Parameters
|
||||
----------
|
||||
table: camelot.core.Table
|
||||
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.
|
||||
|
||||
"""
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, aspect='equal')
|
||||
xs, ys = [], []
|
||||
for t in 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]
|
||||
Returns
|
||||
-------
|
||||
fig : matplotlib.fig.Figure
|
||||
|
||||
"""
|
||||
if not _HAS_MPL:
|
||||
raise ImportError('matplotlib is required for plotting.')
|
||||
|
||||
if table.flavor == 'lattice' and kind in ['textedge']:
|
||||
raise NotImplementedError("Lattice flavor does not support kind='{}'".format(
|
||||
kind))
|
||||
elif table.flavor == 'stream' and kind in ['joint', 'line']:
|
||||
raise NotImplementedError("Stream flavor does not support kind='{}'".format(
|
||||
kind))
|
||||
|
||||
plot_method = getattr(self, kind)
|
||||
return plot_method(table)
|
||||
|
||||
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)
|
||||
plt.show()
|
||||
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.
|
||||
|
||||
def plot_table(table):
|
||||
"""Generates a plot for the table.
|
||||
Parameters
|
||||
----------
|
||||
table : camelot.core.Table
|
||||
|
||||
Parameters
|
||||
----------
|
||||
table : camelot.core.Table
|
||||
Returns
|
||||
-------
|
||||
fig : matplotlib.fig.Figure
|
||||
|
||||
"""
|
||||
for row in table.cells:
|
||||
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')
|
||||
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.
|
||||
|
||||
def plot_contour(image):
|
||||
"""Generates a plot for all table boundaries present on the
|
||||
PDF page.
|
||||
Parameters
|
||||
----------
|
||||
table : camelot.core.Table
|
||||
|
||||
Parameters
|
||||
----------
|
||||
image : tuple
|
||||
Returns
|
||||
-------
|
||||
fig : matplotlib.fig.Figure
|
||||
|
||||
"""
|
||||
img, table_bbox = image
|
||||
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()
|
||||
"""
|
||||
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'
|
||||
)
|
||||
)
|
||||
|
||||
def plot_joint(image):
|
||||
"""Generates a plot for all line intersections present on the
|
||||
PDF page.
|
||||
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]])
|
||||
ys.extend([t[1], t[3]])
|
||||
ax.set_xlim(min(xs) - 10, max(xs) + 10)
|
||||
ax.set_ylim(min(ys) - 10, max(ys) + 10)
|
||||
|
||||
Parameters
|
||||
----------
|
||||
image : tuple
|
||||
if _FOR_LATTICE:
|
||||
ax.imshow(img)
|
||||
return fig
|
||||
|
||||
"""
|
||||
img, table_bbox = image
|
||||
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()
|
||||
def textedge(self, table):
|
||||
"""Generates a plot for relevant textedges.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
table : camelot.core.Table
|
||||
|
||||
def plot_line(segments):
|
||||
"""Generates a plot for all line segments present on the PDF page.
|
||||
Returns
|
||||
-------
|
||||
fig : matplotlib.fig.Figure
|
||||
|
||||
Parameters
|
||||
----------
|
||||
segments : tuple
|
||||
"""
|
||||
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)
|
||||
|
||||
"""
|
||||
vertical, horizontal = segments
|
||||
for v in vertical:
|
||||
plt.plot([v[0], v[2]], [v[1], v[3]])
|
||||
for h in horizontal:
|
||||
plt.plot([h[0], h[2]], [h[1], h[3]])
|
||||
plt.show()
|
||||
for te in table._textedges:
|
||||
ax.plot([te.x, te.x],
|
||||
[te.y0, te.y1])
|
||||
|
||||
return fig
|
||||
|
||||
def joint(self, table):
|
||||
"""Generates a plot for all line intersections present
|
||||
on the PDF page.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
table : camelot.core.Table
|
||||
|
||||
Returns
|
||||
-------
|
||||
fig : matplotlib.fig.Figure
|
||||
|
||||
"""
|
||||
img, table_bbox = table._image
|
||||
fig = plt.figure()
|
||||
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
|
||||
on the PDF page.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
table : camelot.core.Table
|
||||
|
||||
Returns
|
||||
-------
|
||||
fig : matplotlib.fig.Figure
|
||||
|
||||
"""
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, aspect='equal')
|
||||
vertical, horizontal = table._segments
|
||||
for v in vertical:
|
||||
ax.plot([v[0], v[2]], [v[1], v[3]])
|
||||
for h in horizontal:
|
||||
ax.plot([h[0], h[2]], [h[1], h[3]])
|
||||
return fig
|
||||
|
|
|
|||
|
|
@ -344,9 +344,9 @@ def flag_font_size(textline, direction):
|
|||
fchars = [t[0] for t in chars]
|
||||
if ''.join(fchars).strip():
|
||||
flist.append(''.join(fchars))
|
||||
fstring = ''.join(flist).strip('\n')
|
||||
fstring = ''.join(flist)
|
||||
else:
|
||||
fstring = ''.join([t.get_text() for t in textline]).strip('\n')
|
||||
fstring = ''.join([t.get_text() for t in textline])
|
||||
return fstring
|
||||
|
||||
|
||||
|
|
@ -419,7 +419,7 @@ def split_textline(table, textline, direction, flag_size=False):
|
|||
grouped_chars.append((key[0], key[1], flag_font_size([t[2] for t in chars], direction)))
|
||||
else:
|
||||
gchars = [t[2].get_text() for t in chars]
|
||||
grouped_chars.append((key[0], key[1], ''.join(gchars).strip('\n')))
|
||||
grouped_chars.append((key[0], key[1], ''.join(gchars)))
|
||||
return grouped_chars
|
||||
|
||||
|
||||
|
|
@ -500,7 +500,7 @@ def get_table_index(table, t, direction, split_text=False, flag_size=False):
|
|||
if flag_size:
|
||||
return [(r_idx, c_idx, flag_font_size(t._objs, direction))], error
|
||||
else:
|
||||
return [(r_idx, c_idx, t.get_text().strip('\n'))], error
|
||||
return [(r_idx, c_idx, t.get_text())], error
|
||||
|
||||
|
||||
def compute_accuracy(error_weights):
|
||||
|
|
|
|||
|
Before Width: | Height: | Size: 20 KiB After Width: | Height: | Size: 20 KiB |
|
Before Width: | Height: | Size: 24 KiB After Width: | Height: | Size: 24 KiB |
|
Before Width: | Height: | Size: 8.1 KiB After Width: | Height: | Size: 8.1 KiB |
|
Before Width: | Height: | Size: 8.8 KiB After Width: | Height: | Size: 8.8 KiB |
|
Before Width: | Height: | Size: 64 KiB After Width: | Height: | Size: 64 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 68 KiB |
|
|
@ -0,0 +1,96 @@
|
|||
"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"
|
||||
|
|
|
@ -0,0 +1,56 @@
|
|||
"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"
|
||||
|
|
|
@ -0,0 +1,18 @@
|
|||
"0","1","2"
|
||||
"","e
|
||||
bl
|
||||
a
|
||||
ail
|
||||
v
|
||||
a
|
||||
|
||||
t
|
||||
o
|
||||
n
|
||||
|
||||
a
|
||||
t
|
||||
a
|
||||
D
|
||||
|
||||
*",""
|
||||
|
|
|
@ -0,0 +1,3 @@
|
|||
"0"
|
||||
"Sl."
|
||||
"No."
|
||||
|
|
|
@ -0,0 +1,3 @@
|
|||
"0"
|
||||
"Table 6 : DISTRIBUTION (%) OF HOUSEHOLDS BY LITERACY STATUS OF"
|
||||
"MALE HEAD OF THE HOUSEHOLD"
|
||||
|
|
|
@ -1,3 +1,7 @@
|
|||
"[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",""
|
||||
"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"
|
||||
|
|
@ -36,3 +40,4 @@
|
|||
"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)"
|
||||
"","– 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.","","","","","","","",""
|
||||
|
|
|
|||
|
|
|
@ -1,3 +1,7 @@
|
|||
"","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",""
|
||||
"Offense charged","","","","Indian/Alaskan","Asian Pacific"
|
||||
"","Total","White","Black","Native","Islander"
|
||||
|
|
@ -34,3 +38,4 @@
|
|||
"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"
|
||||
"1 Except forcible rape and prostitution.","","","","",""
|
||||
"","Source: U.S. Department of Justice, Federal Bureau of Investigation, “Crime in the United States, Arrests,” September 2010,","","","",""
|
||||
|
|
|
|||
|
|
|
@ -1,35 +1,43 @@
|
|||
"","","","","","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"
|
||||
"","2012 BETTER VARIETIES Harvest Report for Minnesota Central [ MNCE ]2012 BETTER VARIETIES Harvest Report for Minnesota Central [ MNCE ]","","","","","","","","","","","","ALL SEASON TESTALL SEASON TEST",""
|
||||
"","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",""
|
||||
"PREVPREV. CROP/HERB:","CROP/HERB","C/ S","Corn / Surpass, RoundupR","d","","","","","","","","","","S2MNCE01S2MNCE01"
|
||||
"SOIL DESCRIPTION:","","C","Canisteo clay loam, mod. well drained, non-irrigated","","","","","","","","","","",""
|
||||
"SOIL CONDITIONS:","","","High P, high K, 6.7 pH, 3.9% OM, Low SCN","","","","","","","","","","","30"" ROW SPACING"
|
||||
"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"
|
||||
|
|
|
|||
|
|
|
@ -0,0 +1,39 @@
|
|||
"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"
|
||||
|
|
|
@ -0,0 +1,66 @@
|
|||
"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","","","",""
|
||||
|
|
|
@ -0,0 +1,44 @@
|
|||
"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",""
|
||||
"","","","","","","","","","","","","","","","","","","","","","","",""
|
||||
|
|
|
@ -0,0 +1,71 @@
|
|||
"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","","","",""
|
||||
|
|
|
@ -63,7 +63,7 @@ master_doc = 'index'
|
|||
|
||||
# General information about the project.
|
||||
project = u'Camelot'
|
||||
copyright = u'2018, Peeply Private Ltd (Singapore)'
|
||||
copyright = u'2018, <a href="https://socialcops.com" target="_blank">SocialCops</a>'
|
||||
author = u'Vinayak Mehta'
|
||||
|
||||
# The version info for the project you're documenting, acts as replacement for
|
||||
|
|
|
|||
|
|
@ -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.
|
||||
|
||||
.. _Vinayak Mehta: https://vinayak-mehta.github.io
|
||||
.. _Vinayak Mehta: https://www.vinayakmehta.com
|
||||
|
||||
Code Of Conduct
|
||||
---------------
|
||||
|
|
|
|||
|
|
@ -11,6 +11,10 @@ Release v\ |version|. (:ref:`Installation <install>`)
|
|||
.. image:: https://travis-ci.org/socialcopsdev/camelot.svg?branch=master
|
||||
:target: https://travis-ci.org/socialcopsdev/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/socialcopsdev/camelot/badge.svg?branch=master&service=github
|
||||
:target: https://codecov.io/github/socialcopsdev/camelot?branch=master
|
||||
|
||||
|
|
@ -23,8 +27,15 @@ Release v\ |version|. (:ref:`Installation <install>`)
|
|||
.. image:: https://img.shields.io/pypi/pyversions/camelot-py.svg
|
||||
:target: https://pypi.org/project/camelot-py/
|
||||
|
||||
.. image:: https://badges.gitter.im/camelot-dev/Lobby.png
|
||||
:target: https://gitter.im/camelot-dev/Lobby
|
||||
|
||||
**Camelot** is a Python library that makes it easy for *anyone* to extract tables from PDF files!
|
||||
|
||||
.. note:: You can also check out `Excalibur`_, which is a web interface for Camelot!
|
||||
|
||||
.. _Excalibur: https://github.com/camelot-dev/excalibur
|
||||
|
||||
----
|
||||
|
||||
**Here's how you can extract tables from PDF files.** Check out the PDF used in this example `here`_.
|
||||
|
|
@ -81,6 +92,7 @@ This part of the documentation begins with some background information about why
|
|||
:maxdepth: 2
|
||||
|
||||
user/intro
|
||||
user/install-deps
|
||||
user/install
|
||||
user/how-it-works
|
||||
user/quickstart
|
||||
|
|
@ -107,4 +119,4 @@ you.
|
|||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
dev/contributing
|
||||
dev/contributing
|
||||
|
|
|
|||
|
|
@ -24,25 +24,34 @@ To process background lines, you can pass ``process_background=True``.
|
|||
>>> tables = camelot.read_pdf('background_lines.pdf', process_background=True)
|
||||
>>> 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::
|
||||
:file: ../_static/csv/background_lines.csv
|
||||
|
||||
Plot geometry
|
||||
-------------
|
||||
Visual debugging
|
||||
----------------
|
||||
|
||||
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.
|
||||
.. 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]``.
|
||||
|
||||
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 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.
|
||||
|
||||
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'
|
||||
- 'table'
|
||||
- 'grid'
|
||||
- 'contour'
|
||||
- 'line'
|
||||
- 'joint'
|
||||
- 'textedge'
|
||||
|
||||
.. note:: The last three geometries can only be used with :ref:`Lattice <lattice>`, i.e. when ``flavor='lattice'``.
|
||||
.. note:: 'line' and 'joint' can only be used with :ref:`Lattice <lattice>` and 'textedge' can only be used with :ref:`Stream <stream>`.
|
||||
|
||||
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.
|
||||
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.
|
||||
|
||||
::
|
||||
|
||||
|
|
@ -50,8 +59,6 @@ Let's generate a plot for each geometry using this `PDF <../_static/pdf/foo.pdf>
|
|||
>>> tables
|
||||
<TableList n=1>
|
||||
|
||||
.. _geometry_text:
|
||||
|
||||
text
|
||||
^^^^
|
||||
|
||||
|
|
@ -59,9 +66,16 @@ Let's plot all the text present on the table's PDF page.
|
|||
|
||||
::
|
||||
|
||||
>>> tables[0].plot('text')
|
||||
>>> camelot.plot(tables[0], kind='text')
|
||||
>>> plt.show()
|
||||
|
||||
.. figure:: ../_static/png/geometry_text.png
|
||||
.. tip::
|
||||
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
|
||||
:width: 1366
|
||||
:scale: 50%
|
||||
|
|
@ -72,18 +86,23 @@ This, as we shall later see, is very helpful with :ref:`Stream <stream>` for not
|
|||
|
||||
.. note:: The *x-y* coordinates shown above change as you move your mouse cursor on the image, which can help you note coordinates.
|
||||
|
||||
.. _geometry_table:
|
||||
|
||||
table
|
||||
^^^^^
|
||||
|
||||
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.)
|
||||
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.)
|
||||
|
||||
::
|
||||
|
||||
>>> tables[0].plot('table')
|
||||
>>> camelot.plot(tables[0], kind='grid')
|
||||
>>> plt.show()
|
||||
|
||||
.. figure:: ../_static/png/geometry_table.png
|
||||
.. tip::
|
||||
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
|
||||
:width: 1366
|
||||
:scale: 50%
|
||||
|
|
@ -92,8 +111,6 @@ Let's plot the table (to see if it was detected correctly or not). This geometry
|
|||
|
||||
The table is perfect!
|
||||
|
||||
.. _geometry_contour:
|
||||
|
||||
contour
|
||||
^^^^^^^
|
||||
|
||||
|
|
@ -101,17 +118,22 @@ Now, let's plot all table boundaries present on the table's PDF page.
|
|||
|
||||
::
|
||||
|
||||
>>> tables[0].plot('contour')
|
||||
>>> camelot.plot(tables[0], kind='contour')
|
||||
>>> plt.show()
|
||||
|
||||
.. figure:: ../_static/png/geometry_contour.png
|
||||
.. tip::
|
||||
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
|
||||
:width: 1366
|
||||
:scale: 50%
|
||||
:alt: A plot of all contours on a PDF page
|
||||
:align: left
|
||||
|
||||
.. _geometry_line:
|
||||
|
||||
line
|
||||
^^^^
|
||||
|
||||
|
|
@ -119,17 +141,22 @@ Cool, let's plot all line segments present on the table's PDF page.
|
|||
|
||||
::
|
||||
|
||||
>>> tables[0].plot('line')
|
||||
>>> camelot.plot(tables[0], kind='line')
|
||||
>>> plt.show()
|
||||
|
||||
.. figure:: ../_static/png/geometry_line.png
|
||||
.. tip::
|
||||
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
|
||||
:width: 1366
|
||||
:scale: 50%
|
||||
:alt: A plot of all lines on a PDF page
|
||||
:align: left
|
||||
|
||||
.. _geometry_joint:
|
||||
|
||||
joint
|
||||
^^^^^
|
||||
|
||||
|
|
@ -137,19 +164,49 @@ Finally, let's plot all line intersections present on the table's PDF page.
|
|||
|
||||
::
|
||||
|
||||
>>> tables[0].plot('joint')
|
||||
>>> camelot.plot(tables[0], kind='joint')
|
||||
>>> plt.show()
|
||||
|
||||
.. figure:: ../_static/png/geometry_joint.png
|
||||
.. tip::
|
||||
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
|
||||
:width: 1366
|
||||
:scale: 50%
|
||||
:alt: A plot of all line intersections on a PDF page
|
||||
: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')
|
||||
>>> plt.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
|
||||
-------------------
|
||||
|
||||
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.
|
||||
In cases such as `these <../_static/pdf/table_areas.pdf>`__, it can be useful to specify table boundaries. You can plot the text on this page and note the top left and bottom right 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.
|
||||
|
||||
|
|
@ -160,27 +217,39 @@ Table areas that you want Camelot to analyze can be passed as a list of comma-se
|
|||
>>> tables = camelot.read_pdf('table_areas.pdf', flavor='stream', table_areas=['316,499,566,337'])
|
||||
>>> 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::
|
||||
:file: ../_static/csv/table_areas.csv
|
||||
|
||||
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 :ref:`plotting the text <geometry_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 plotting the 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.
|
||||
|
||||
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.
|
||||
|
||||
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', '']``.
|
||||
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', '']``.
|
||||
|
||||
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!
|
||||
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!
|
||||
|
||||
::
|
||||
|
||||
>>> tables = camelot.read_pdf('column_separators.pdf', flavor='stream', columns=['72,95,209,327,442,529,566,606,683'])
|
||||
>>> 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::
|
||||
|
||||
"...","...","...","...","...","...","...","...","...","..."
|
||||
|
|
@ -200,6 +269,12 @@ To deal with cases like the output from the previous section, you can pass ``spl
|
|||
>>> 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
|
||||
|
||||
.. 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::
|
||||
|
||||
"...","...","...","...","...","...","...","...","...","..."
|
||||
|
|
@ -227,6 +302,12 @@ You can solve this by passing ``flag_size=True``, which will enclose the supersc
|
|||
>>> tables = camelot.read_pdf('superscript.pdf', flavor='stream', flag_size=True)
|
||||
>>> 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::
|
||||
|
||||
"...","...","...","...","...","...","...","...","...","...","..."
|
||||
|
|
@ -259,6 +340,12 @@ You can pass ``row_close_tol=<+int>`` to group the rows closer together, as show
|
|||
>>> tables = camelot.read_pdf('group_rows.pdf', flavor='stream', row_close_tol=10)
|
||||
>>> 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::
|
||||
|
||||
"Clave","Nombre Entidad","Clave","","Nombre Municipio","Clave","Nombre Localidad"
|
||||
|
|
@ -282,23 +369,31 @@ Here's a `PDF <../_static/pdf/short_lines.pdf>`__ where small lines separating t
|
|||
:alt: A PDF table with short lines
|
||||
:align: left
|
||||
|
||||
Let's :ref:`plot the table <geometry_table>` for this PDF.
|
||||
Let's plot the table for this PDF.
|
||||
|
||||
::
|
||||
|
||||
>>> tables = camelot.read_pdf('short_lines.pdf')
|
||||
>>> tables[0].plot('table')
|
||||
>>> camelot.plot(tables[0], kind='grid')
|
||||
>>> plt.show()
|
||||
|
||||
.. figure:: ../_static/png/short_lines_1.png
|
||||
:alt: A plot of the PDF table with short lines
|
||||
:align: left
|
||||
|
||||
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.
|
||||
Clearly, the smaller lines separating the headers, couldn't be detected. Let's try with ``line_size_scaling=40``, and plot the table again.
|
||||
|
||||
::
|
||||
|
||||
>>> tables = camelot.read_pdf('short_lines.pdf', line_size_scaling=40)
|
||||
>>> tables[0].plot('table')
|
||||
>>> camelot.plot(tables[0], kind='grid')
|
||||
>>> plt.show()
|
||||
|
||||
.. 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
|
||||
:alt: An improved plot of the PDF table with short lines
|
||||
|
|
@ -363,6 +458,12 @@ No surprises there — it did remain in place (observe the strings "2400" and "A
|
|||
>>> tables = camelot.read_pdf('short_lines.pdf', line_size_scaling=40, shift_text=['r', 'b'])
|
||||
>>> 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::
|
||||
|
||||
"Investigations","No. ofHHs","Age/Sex/Physiological Group","Preva-lence","C.I*","RelativePrecision","Sample sizeper State"
|
||||
|
|
@ -408,6 +509,12 @@ 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[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::
|
||||
|
||||
"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","..."
|
||||
|
|
@ -416,4 +523,4 @@ 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","..."
|
||||
"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","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","..."
|
||||
|
|
|
|||
|
|
@ -11,12 +11,14 @@ You can print the help for the interface by typing ``camelot --help`` in your fa
|
|||
|
||||
Usage: camelot [OPTIONS] COMMAND [ARGS]...
|
||||
|
||||
Camelot: PDF Table Extraction for Humans
|
||||
Camelot: PDF Table Extraction for Humans
|
||||
|
||||
Options:
|
||||
--version Show the version and exit.
|
||||
-q, --quiet TEXT Suppress logs and warnings.
|
||||
-p, --pages TEXT Comma-separated page numbers. Example: 1,3,4
|
||||
or 1,4-end.
|
||||
-pw, --password TEXT Password for decryption.
|
||||
-o, --output TEXT Output file path.
|
||||
-f, --format [csv|json|excel|html]
|
||||
Output file format.
|
||||
|
|
@ -31,4 +33,4 @@ You can print the help for the interface by typing ``camelot --help`` in your fa
|
|||
|
||||
Commands:
|
||||
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.
|
||||
|
|
|
|||
|
|
@ -5,24 +5,24 @@ How It Works
|
|||
|
||||
This part of the documentation includes 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`_.
|
||||
|
||||
.. _Tabula: https://github.com/tabulapdf/tabula
|
||||
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>`_.
|
||||
|
||||
.. _stream:
|
||||
|
||||
Stream
|
||||
------
|
||||
|
||||
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.
|
||||
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>`_.
|
||||
|
||||
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 on a page, it groups them into rows based on their *y* coordinates. It then 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.
|
||||
1. Words on the PDF page are grouped into text rows based on their *y* axis overlaps.
|
||||
|
||||
.. _margins: https://euske.github.io/pdfminer/#tools
|
||||
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 <http://dspace.cc.tut.fi/dpub/bitstream/handle/123456789/21520/Nurminen.pdf?sequence=3>`_ to know more about this table detection technique. [See pages 20, 35 and 40]
|
||||
|
||||
.. 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`_.
|
||||
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.
|
||||
|
||||
.. _in the works: https://github.com/socialcopsdev/camelot/issues/102
|
||||
4. Words that lie inside/outside the current column *x* ranges are then used to extend extend the current list of columns.
|
||||
|
||||
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:
|
||||
|
||||
|
|
@ -39,7 +39,7 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
|
|||
|
||||
1. Line segments are detected.
|
||||
|
||||
.. image:: ../_static/png/geometry_line.png
|
||||
.. image:: ../_static/png/plot_line.png
|
||||
:height: 674
|
||||
:width: 1366
|
||||
:scale: 50%
|
||||
|
|
@ -49,7 +49,7 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
|
|||
|
||||
.. _and: https://en.wikipedia.org/wiki/Logical_conjunction
|
||||
|
||||
.. image:: ../_static/png/geometry_joint.png
|
||||
.. image:: ../_static/png/plot_joint.png
|
||||
:height: 674
|
||||
:width: 1366
|
||||
:scale: 50%
|
||||
|
|
@ -59,7 +59,7 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
|
|||
|
||||
.. _or: https://en.wikipedia.org/wiki/Logical_disjunction
|
||||
|
||||
.. image:: ../_static/png/geometry_contour.png
|
||||
.. image:: ../_static/png/plot_contour.png
|
||||
:height: 674
|
||||
:width: 1366
|
||||
:scale: 50%
|
||||
|
|
@ -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.
|
||||
|
||||
.. image:: ../_static/png/geometry_table.png
|
||||
.. image:: ../_static/png/plot_table.png
|
||||
:height: 674
|
||||
:width: 1366
|
||||
:scale: 50%
|
||||
: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.
|
||||
|
|
|
|||
|
|
@ -0,0 +1,76 @@
|
|||
.. _install_deps:
|
||||
|
||||
Installation of dependencies
|
||||
============================
|
||||
|
||||
The dependencies `Tkinter`_ and `ghostscript`_ can be installed using your system's package manager. You can run one of the following, based on your OS.
|
||||
|
||||
.. _Tkinter: https://wiki.python.org/moin/TkInter
|
||||
.. _ghostscript: https://www.ghostscript.com
|
||||
|
||||
OS-specific instructions
|
||||
------------------------
|
||||
|
||||
For Ubuntu
|
||||
^^^^^^^^^^
|
||||
::
|
||||
|
||||
$ apt install python-tk ghostscript
|
||||
|
||||
Or for Python 3::
|
||||
|
||||
$ apt install python3-tk ghostscript
|
||||
|
||||
For macOS
|
||||
^^^^^^^^^
|
||||
::
|
||||
|
||||
$ brew install tcl-tk ghostscript
|
||||
|
||||
For Windows
|
||||
^^^^^^^^^^^
|
||||
|
||||
For Tkinter, you can download the `ActiveTcl Community Edition`_ from ActiveState. For ghostscript, you can get the installer at the `ghostscript downloads page`_.
|
||||
|
||||
After installing ghostscript, you'll need to reboot your system to make sure that the ghostscript executable's path is in the windows PATH environment variable. In case you don't want to reboot, you can manually add the ghostscript executable's path to the PATH variable, `as shown here`_.
|
||||
|
||||
.. _ActiveTcl Community Edition: https://www.activestate.com/activetcl/downloads
|
||||
.. _ghostscript downloads page: https://www.ghostscript.com/download/gsdnld.html
|
||||
.. _as shown here: https://java.com/en/download/help/path.xml
|
||||
|
||||
Checks to see if dependencies were installed correctly
|
||||
------------------------------------------------------
|
||||
|
||||
You can do the following checks to see if the dependencies were installed correctly.
|
||||
|
||||
For Tkinter
|
||||
^^^^^^^^^^^
|
||||
|
||||
Launch Python, and then at the prompt, type::
|
||||
|
||||
>>> import Tkinter
|
||||
|
||||
Or in Python 3::
|
||||
|
||||
>>> import tkinter
|
||||
|
||||
If you have Tkinter, Python will not print an error message, and if not, you will see an ``ImportError``.
|
||||
|
||||
For ghostscript
|
||||
^^^^^^^^^^^^^^^
|
||||
|
||||
Run the following to check the ghostscript version.
|
||||
|
||||
For Ubuntu/macOS::
|
||||
|
||||
$ gs -version
|
||||
|
||||
For Windows::
|
||||
|
||||
C:\> gswin64c.exe -version
|
||||
|
||||
Or for Windows 32-bit::
|
||||
|
||||
C:\> gswin32c.exe -version
|
||||
|
||||
If you have ghostscript, you should see the ghostscript version and copyright information.
|
||||
|
|
@ -3,90 +3,37 @@
|
|||
Installation of Camelot
|
||||
=======================
|
||||
|
||||
This part of the documentation covers how to install Camelot. First, you'll need to install the dependencies, which include `Tkinter`_ and `ghostscript`_.
|
||||
This part of the documentation covers the steps to install Camelot.
|
||||
|
||||
Using conda
|
||||
-----------
|
||||
|
||||
The easiest way to install Camelot is to install it with `conda`_, which is a package manager and environment management system for the `Anaconda`_ distribution.
|
||||
::
|
||||
|
||||
$ conda install -c conda-forge camelot-py
|
||||
|
||||
.. note:: Camelot is available for Python 2.7, 3.5 and 3.6 on Linux, macOS and Windows. For Windows, you will need to install ghostscript which you can get from their `downloads page`_.
|
||||
|
||||
.. _conda: https://conda.io/docs/
|
||||
.. _Anaconda: http://docs.continuum.io/anaconda/
|
||||
.. _downloads page: https://www.ghostscript.com/download/gsdnld.html
|
||||
.. _conda-forge: https://conda-forge.org/
|
||||
|
||||
Using pip
|
||||
---------
|
||||
|
||||
After :ref:`installing the dependencies <install_deps>`, which include `Tkinter`_ and `ghostscript`_, you can simply use pip to install Camelot::
|
||||
|
||||
$ pip install camelot-py[cv]
|
||||
|
||||
.. _Tkinter: https://wiki.python.org/moin/TkInter
|
||||
.. _ghostscript: https://www.ghostscript.com
|
||||
|
||||
Install the dependencies
|
||||
------------------------
|
||||
From the source code
|
||||
--------------------
|
||||
|
||||
These can be installed using your system's package manager. You can run one of the following, based on your OS.
|
||||
|
||||
For Ubuntu
|
||||
^^^^^^^^^^
|
||||
::
|
||||
|
||||
$ apt install python-tk ghostscript
|
||||
|
||||
Or for Python 3::
|
||||
|
||||
$ apt install python3-tk ghostscript
|
||||
|
||||
For macOS
|
||||
^^^^^^^^^
|
||||
::
|
||||
|
||||
$ brew install tcl-tk ghostscript
|
||||
|
||||
For Windows
|
||||
^^^^^^^^^^^
|
||||
|
||||
For Tkinter, you can download the `ActiveTcl Community Edition`_ from ActiveState. For ghostscript, you can get the installer at the `ghostscript downloads page`_.
|
||||
|
||||
After installing ghostscript, you'll need to reboot your system to make sure that the ghostscript executable's path is in the windows PATH environment variable. In case you don't want to reboot, you can manually add the ghostscript executable's path to the PATH variable, `as shown here`_.
|
||||
|
||||
.. _ActiveTcl Community Edition: https://www.activestate.com/activetcl/downloads
|
||||
.. _ghostscript downloads page: https://www.ghostscript.com/download/gsdnld.html
|
||||
.. _as shown here: https://java.com/en/download/help/path.xml
|
||||
|
||||
----
|
||||
|
||||
You can do the following checks to see if the dependencies were installed correctly.
|
||||
|
||||
For Tkinter
|
||||
^^^^^^^^^^^
|
||||
|
||||
Launch Python, and then at the prompt, type::
|
||||
|
||||
>>> import Tkinter
|
||||
|
||||
Or in Python 3::
|
||||
|
||||
>>> import tkinter
|
||||
|
||||
If you have Tkinter, Python will not print an error message, and if not, you will see an ``ImportError``.
|
||||
|
||||
For ghostscript
|
||||
^^^^^^^^^^^^^^^
|
||||
|
||||
Run the following to check the ghostscript version.
|
||||
|
||||
For Ubuntu/macOS::
|
||||
|
||||
$ gs -version
|
||||
|
||||
For Windows::
|
||||
|
||||
C:\> gswin64c.exe -version
|
||||
|
||||
Or for Windows 32-bit::
|
||||
|
||||
C:\> gswin32c.exe -version
|
||||
|
||||
If you have ghostscript, you should see the ghostscript version and copyright information.
|
||||
|
||||
$ pip install camelot-py
|
||||
------------------------
|
||||
|
||||
After installing the dependencies, you can simply use pip to install Camelot::
|
||||
|
||||
$ pip install camelot-py
|
||||
|
||||
Get the source code
|
||||
-------------------
|
||||
|
||||
Alternatively, you can install from the source by:
|
||||
After :ref:`installing the dependencies <install_deps>`, you can install from the source by:
|
||||
|
||||
1. Cloning the GitHub repository.
|
||||
::
|
||||
|
|
@ -97,4 +44,4 @@ Alternatively, you can install from the source by:
|
|||
::
|
||||
|
||||
$ cd camelot
|
||||
$ pip install .
|
||||
$ pip install ".[cv]"
|
||||
|
|
|
|||
|
|
@ -70,6 +70,12 @@ You can also export all tables at once, using the :class:`tables <camelot.core.T
|
|||
|
||||
>>> tables.export('foo.csv', f='csv')
|
||||
|
||||
.. tip::
|
||||
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'`` or ``f='html'``.
|
||||
|
||||
.. 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.
|
||||
|
|
@ -85,8 +91,42 @@ 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')
|
||||
|
||||
.. tip::
|
||||
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``.
|
||||
|
||||
------------------------
|
||||
Reading encrypted PDFs
|
||||
----------------------
|
||||
|
||||
Ready for more? Check out the :ref:`advanced <advanced>` section.
|
||||
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.
|
||||
|
|
|
|||
|
|
@ -1,5 +0,0 @@
|
|||
codecov==2.0.15
|
||||
pytest==3.8.0
|
||||
pytest-cov==2.6.0
|
||||
pytest-runner==4.2
|
||||
Sphinx==1.7.9
|
||||
|
|
@ -1,9 +1,9 @@
|
|||
click==6.7
|
||||
ghostscript==0.6
|
||||
matplotlib==2.2.3
|
||||
numpy==1.15.2
|
||||
opencv-python==3.4.2.17
|
||||
openpyxl==2.5.8
|
||||
pandas==0.23.4
|
||||
pdfminer.six==20170720
|
||||
PyPDF2==1.26.0
|
||||
click>=6.7
|
||||
ghostscript>=0.6
|
||||
matplotlib>=2.2.3
|
||||
numpy>=1.13.3
|
||||
opencv-python>=3.4.2.17
|
||||
openpyxl>=2.5.8
|
||||
pandas>=0.23.4
|
||||
pdfminer.six>=20170720
|
||||
PyPDF2>=1.26.0
|
||||
|
|
|
|||
|
|
@ -2,5 +2,5 @@
|
|||
test=pytest
|
||||
|
||||
[tool:pytest]
|
||||
addopts = --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot tests
|
||||
python_files = tests/test_*.py
|
||||
addopts = --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot --mpl
|
||||
python_files = tests/test_*.py
|
||||
|
|
|
|||
48
setup.py
48
setup.py
|
|
@ -13,17 +13,38 @@ with open('README.md', 'r') as f:
|
|||
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>=20170720',
|
||||
'PyPDF2>=1.26.0'
|
||||
]
|
||||
|
||||
cv_requires = [
|
||||
'opencv-python>=3.4.2.17'
|
||||
]
|
||||
|
||||
plot_requires = [
|
||||
'matplotlib>=2.2.3',
|
||||
]
|
||||
|
||||
dev_requires = [
|
||||
'codecov>=2.0.15',
|
||||
'pytest>=3.8.0',
|
||||
'pytest-cov>=2.6.0',
|
||||
'pytest-mpl>=0.10',
|
||||
'pytest-runner>=4.2',
|
||||
'Sphinx>=1.7.9'
|
||||
]
|
||||
|
||||
all_requires = cv_requires + plot_requires
|
||||
dev_requires = dev_requires + all_requires
|
||||
|
||||
|
||||
def setup_package():
|
||||
reqs = []
|
||||
with open('requirements.txt', 'r') as f:
|
||||
for line in f:
|
||||
reqs.append(line.strip())
|
||||
|
||||
dev_reqs = []
|
||||
with open('requirements-dev.txt', 'r') as f:
|
||||
for line in f:
|
||||
dev_reqs.append(line.strip())
|
||||
|
||||
metadata = dict(name=about['__title__'],
|
||||
version=about['__version__'],
|
||||
description=about['__description__'],
|
||||
|
|
@ -34,9 +55,12 @@ def setup_package():
|
|||
author_email=about['__author_email__'],
|
||||
license=about['__license__'],
|
||||
packages=find_packages(exclude=('tests',)),
|
||||
install_requires=reqs,
|
||||
install_requires=requires,
|
||||
extras_require={
|
||||
'dev': dev_reqs
|
||||
'all': all_requires,
|
||||
'cv': cv_requires,
|
||||
'dev': dev_requires,
|
||||
'plot': plot_requires
|
||||
},
|
||||
entry_points={
|
||||
'console_scripts': [
|
||||
|
|
|
|||
|
|
@ -0,0 +1,2 @@
|
|||
import matplotlib
|
||||
matplotlib.use('agg')
|
||||
255
tests/data.py
255
tests/data.py
|
|
@ -33,58 +33,141 @@ data_stream = [
|
|||
["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"],
|
||||
["", "Health Sector Financing by Centre and States/UTs in India [2009-10 to 2012-13](Revised) P a g e |23", "", "", "", "", "", ""]
|
||||
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|
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||||
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|
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|
||||
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|
||||
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||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
["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"],
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||||
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|
||||
["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"],
|
||||
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||||
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|
||||
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|
||||
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|
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|
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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["Violent crime . . . . . . . .\n . .\n . .\n . .\n . .\n . .", "467 .9", "69 .1", "398 .8", "380 .2", "56 .5", "323 .7", "87 .7", "12 .6", "75 .2"],
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|
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["Forcible rape . . . . . . . .\n. .\n. .\n. .\n. .\n. .", "17.5", "2.6", "14.9", "17.2", "2.5", "14.7", "–", "–", "–"],
|
||||
["Robbery . . . .\n. .\n. . .\n. . .\n.\n. . .\n.\n. . .\n.\n.", "102.1", "25.5", "76.6", "90.0", "22.9", "67.1", "12.1", "2.5", "9.5"],
|
||||
["Aggravated assault . . . . . . . .\n. .\n. .\n.", "338.4", "40.1", "298.3", "264.0", "30.2", "233.8", "74.4", "9.9", "64.5"],
|
||||
["Property crime . . . .\n . .\n . . .\n . . .\n .\n . . . .", "1,396 .4", "338 .7", "1,057 .7", "875 .9", "210 .8", "665 .1", "608 .2", "127 .9", "392 .6"],
|
||||
["Burglary . .\n. . . . . .\n. .\n.\n. .\n.\n.\n. .\n.\n.\n. .\n.", "240.9", "60.3", "180.6", "205.0", "53.4", "151.7", "35.9", "6.9", "29.0"],
|
||||
["Larceny-theft . . . . . . . .\n. .\n. .\n. .\n. .\n. .", "1,080.1", "258.1", "822.0", "608.8", "140.5", "468.3", "471.3", "117.6", "353.6"],
|
||||
["Motor vehicle theft . . . . .\n. .\n. . .\n.\n.\n. .", "65.6", "16.0", "49.6", "53.9", "13.3", "40.7", "11.7", "2.7", "8.9"],
|
||||
["Arson .\n. . . . .\n. . .\n.\n. .\n.\n.\n. .\n.\n.\n. .\n.\n.\n. .", "9.8", "4.3", "5.5", "8.1", "3.7", "4.4", "1.7", "0.6", "1.1"],
|
||||
["Other assaults .\n. . . . . .\n. . .\n.\n. . .\n.\n. .\n.", "1,061.3", "175.3", "886.1", "785.4", "115.4", "670.0", "276.0", "59.9", "216.1"],
|
||||
["Forgery and counterfeiting .\n. . . . . . .\n.", "68.9", "1.7", "67.2", "42.9", "1.2", "41.7", "26.0", "0.5", "25.5"],
|
||||
["Fraud .\n.\n.\n. .\n. . . .\n. .\n.\n. .\n.\n.\n. .\n.\n.\n. .\n.\n.\n.", "173.7", "5.1", "168.5", "98.4", "3.3", "95.0", "75.3", "1.8", "73.5"],
|
||||
["Embezzlement . . .\n. . . . .\n. . .\n.\n. . .\n.\n.\n.", "14.6", "–", "14.1", "7.2", "–", "6.9", "7.4", "–", "7.2"],
|
||||
["Stolen property 1 . . . . . . .\n. . .\n. .\n. .\n.\n.", "84.3", "15.1", "69.2", "66.7", "12.2", "54.5", "17.6", "2.8", "14.7"],
|
||||
["Vandalism . . . . . . . .\n. .\n. .\n. .\n. .\n. .\n.\n.\n.", "217.4", "72.7", "144.7", "178.1", "62.8", "115.3", "39.3", "9.9", "29.4"],
|
||||
["Weapons; carrying, possessing, etc. .", "132.9", "27.1", "105.8", "122.1", "24.3", "97.8", "10.8", "2.8", "8.0"],
|
||||
["Prostitution and commercialized vice", "56.9", "1.1", "55.8", "17.3", "–", "17.1", "39.6", "0.8", "38.7"],
|
||||
["Sex offenses 2 . . . . .\n. . . . .\n. .\n. .\n. . .\n.", "61.5", "10.7", "50.7", "56.1", "9.6", "46.5", "5.4", "1.1", "4.3"],
|
||||
["Drug abuse violations . . . . . . . .\n. .\n.\n.", "1,333.0", "136.6", "1,196.4", "1,084.3", "115.2", "969.1", "248.7", "21.4", "227.3"],
|
||||
["Gambling .\n. . . . . .\n. .\n.\n. . .\n.\n. . .\n.\n. .\n.\n.", "8.2", "1.4", "6.8", "7.2", "1.4", "5.9", "0.9", "–", "0.9"],
|
||||
["Offenses against the family and", "", "", "", "", "", "", "", "", ""],
|
||||
["children . . . .\n. . . .\n. .\n. .\n. .\n. .\n. .\n. . .\n.", "92.4", "3.7", "88.7", "68.9", "2.4", "66.6", "23.4", "1.3", "22.1"],
|
||||
["Driving under the influence . . . . . .\n. .", "1,158.5", "109.2", "1,147.5", "895.8", "8.2", "887.6", "262.7", "2.7", "260.0"],
|
||||
["Liquor laws . . . . . . . .\n. .\n. .\n. .\n. .\n. .\n. .", "48.2", "90.2", "368.0", "326.8", "55.4", "271.4", "131.4", "34.7", "96.6"],
|
||||
["Drunkenness . . .\n. . . . .\n. . .\n.\n. . .\n.\n. .\n.", "488.1", "11.4", "476.8", "406.8", "8.5", "398.3", "81.3", "2.9", "78.4"],
|
||||
["Disorderly conduct . .\n. . . . . . .\n. .\n. .\n. .", "529.5", "136.1", "393.3", "387.1", "90.8", "296.2", "142.4", "45.3", "97.1"],
|
||||
["Vagrancy . . . .\n. . . . .\n.\n. .\n.\n.\n. .\n.\n.\n. .\n.\n.", "26.6", "2.2", "24.4", "20.9", "1.6", "19.3", "5.7", "0.6", "5.1"],
|
||||
["All other offenses (except traffic) . . .\n.", "306.1", "263.4", "2,800.8", "2,337.1", "194.2", "2,142.9", "727.0", "69.2", "657.9"],
|
||||
["Suspicion . . . .\n. . . .\n. .\n. .\n. .\n. .\n. .\n. . .\n.", "1.6", "–", "1.4", "1.2", "–", "1.0", "–", "–", "–"],
|
||||
["Curfew and loitering law violations .\n.", "91.0", "91.0", "(X)", "63.1", "63.1", "(X)", "28.0", "28.0", "(X)"],
|
||||
["Runaways . . . . . . . .\n. .\n. .\n. .\n. .\n. .\n.\n.\n.", "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.", "", "", "", "", "", "", "", ""],
|
||||
["", "Source: U.S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports, Arrests Master Files.", "", "", "", "", "", "", "", ""]
|
||||
]
|
||||
|
||||
data_stream_two_tables_2 = [
|
||||
["", "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", ""],
|
||||
["Offense charged", "", "", "", "Indian/Alaskan", "Asian Pacific"],
|
||||
["", "Total", "White", "Black", "Native", "Islander"],
|
||||
["Total .\n .\n .\n .\n . .\n . . .\n . . .\n .\n . . .\n .\n . . .\n . .\n .\n . . .\n .\n .\n .\n . .\n . .\n . .", "10,690,561", "7,389,208", "3,027,153", "150,544", "123,656"],
|
||||
["Violent crime . . . . . . . .\n . .\n . .\n . .\n . .\n .\n .\n . .\n . .\n .\n .\n .\n .\n . .", "456,965", "268,346", "177,766", "5,608", "5,245"],
|
||||
["Murder and nonnegligent manslaughter . .\n. .\n.\n. .", "9,739", "4,741", "4,801", "100", "97"],
|
||||
["Forcible rape . . . . . . . .\n. .\n. .\n. .\n. .\n.\n.\n. .\n. .\n.\n.\n.\n.\n. .", "16,362", "10,644", "5,319", "169", "230"],
|
||||
["Robbery . . . . .\n. . . . .\n.\n. . .\n.\n. . .\n.\n.\n. .\n.\n.\n. .\n.\n.\n. . . .", "100,496", "43,039", "55,742", "726", "989"],
|
||||
["Aggravated assault . . . . . . . .\n. .\n. .\n.\n.\n.\n.\n. .\n. .\n.\n.\n.", "330,368", "209,922", "111,904", "4,613", "3,929"],
|
||||
["Property crime . . . . .\n . . . . .\n .\n . . .\n .\n . .\n .\n .\n .\n . .\n .\n . .\n .\n .", "1,364,409", "922,139", "406,382", "17,599", "18,289"],
|
||||
["Burglary . . .\n. . . . .\n. . .\n.\n.\n. .\n.\n.\n. .\n.\n.\n. .\n.\n.\n. .\n.\n. . . .", "234,551", "155,994", "74,419", "2,021", "2,117"],
|
||||
["Larceny-theft . . . . . . . .\n. .\n. .\n. .\n. .\n.\n.\n. .\n. .\n.\n.\n.\n.\n. .", "1,056,473", "719,983", "306,625", "14,646", "15,219"],
|
||||
["Motor vehicle theft . . . . . .\n. .\n.\n. . .\n.\n. .\n.\n.\n.\n. .\n.\n. .\n.", "63,919", "39,077", "23,184", "817", "841"],
|
||||
["Arson .\n. . . .\n. .\n. .\n. .\n.\n. .\n.\n.\n. .\n.\n.\n. .\n.\n.\n. .\n.\n.\n. . . . . .", "9,466", "7,085", "2,154", "115", "112"],
|
||||
["Other assaults .\n. . . . . . .\n.\n. . .\n.\n. . .\n.\n. .\n.\n.\n.\n. .\n.\n. .\n.", "1,032,502", "672,865", "332,435", "15,127", "12,075"],
|
||||
["Forgery and counterfeiting .\n. . . . . . .\n.\n. .\n.\n.\n.\n. .\n. .\n.", "67,054", "44,730", "21,251", "345", "728"],
|
||||
["Fraud .\n.\n. . . . . .\n. .\n. .\n. .\n. .\n. .\n. .\n. .\n. .\n. .\n.\n.\n. . . . . . .", "161,233", "108,032", "50,367", "1,315", "1,519"],
|
||||
["Embezzlement . . . .\n. . . . .\n.\n. . .\n.\n. . .\n.\n.\n. .\n.\n. .\n.\n.\n.\n.", "13,960", "9,208", "4,429", "75", "248"],
|
||||
["Stolen property; buying, receiving, possessing .\n. .", "82,714", "51,953", "29,357", "662", "742"],
|
||||
["Vandalism . . . . . . . .\n. .\n. .\n. .\n. .\n. .\n. .\n.\n.\n. .\n. .\n.\n.\n.\n. .", "212,173", "157,723", "48,746", "3,352", "2,352"],
|
||||
["Weapons—carrying, possessing, etc. .\n. .\n. .\n.\n. .\n. .", "130,503", "74,942", "53,441", "951", "1,169"],
|
||||
["Prostitution and commercialized vice . .\n.\n. .\n. .\n. .\n.", "56,560", "31,699", "23,021", "427", "1,413"],
|
||||
["Sex offenses 1 . . . . . . . .\n. .\n. .\n. .\n. .\n.\n.\n. .\n. .\n.\n.\n.\n.\n. .", "60,175", "44,240", "14,347", "715", "873"],
|
||||
["Drug abuse violations . . . . . . . .\n. . .\n.\n.\n.\n. .\n. .\n.\n.\n.\n.", "1,301,629", "845,974", "437,623", "8,588", "9,444"],
|
||||
["Gambling . . . . .\n. . . . .\n.\n. . .\n.\n. . .\n. .\n.\n. . .\n.\n.\n.\n.\n. .\n. .", "8,046", "2,290", "5,518", "27", "211"],
|
||||
["Offenses against the family and children .\n.\n. .\n. .\n. .", "87,232", "58,068", "26,850", "1,690", "624"],
|
||||
["Driving under the influence . . . . . . .\n. .\n.\n. .\n.\n.\n.\n.\n. .", "1,105,401", "954,444", "121,594", "14,903", "14,460"],
|
||||
["Liquor laws . . . . . . . .\n. .\n. .\n. .\n. .\n. . .\n.\n.\n.\n. .\n. .\n.\n.\n.\n.", "444,087", "373,189", "50,431", "14,876", "5,591"],
|
||||
["Drunkenness . .\n. . . . . . .\n.\n. . .\n.\n. . .\n.\n.\n.\n. . .\n.\n.\n.\n.\n.\n.", "469,958", "387,542", "71,020", "8,552", "2,844"],
|
||||
["Disorderly conduct . . .\n. . . . . .\n. .\n. . .\n.\n.\n.\n. .\n. .\n.\n.\n.\n.", "515,689", "326,563", "176,169", "8,783", "4,174"],
|
||||
["Vagrancy . . .\n. .\n. . . .\n. .\n.\n. .\n.\n.\n. .\n.\n.\n. .\n.\n.\n. .\n.\n.\n. . . .", "26,347", "14,581", "11,031", "543", "192"],
|
||||
["All other offenses (except traffic) . .\n. .\n. .\n. .\n.\n.\n.\n. .\n.", "2,929,217", "1,937,221", "911,670", "43,880", "36,446"],
|
||||
["Suspicion . . .\n. . . . .\n. .\n. .\n. .\n. .\n. .\n. .\n. .\n.\n.\n.\n.\n. .\n. . . .", "1,513", "677", "828", "1", "7"],
|
||||
["Curfew and loitering law violations . .\n. .\n.\n. .\n. .\n.\n.\n.", "89,578", "54,439", "33,207", "872", "1,060"],
|
||||
["Runaways . . . . . . . .\n. .\n. .\n. .\n. .\n. .\n. .\n.\n.\n. .\n. .\n.\n.\n.\n. .", "73,616", "48,343", "19,670", "1,653", "3,950"],
|
||||
["1 Except forcible rape and prostitution.", "", "", "", "", ""],
|
||||
["", "Source: U.S. Department of Justice, Federal Bureau of Investigation, “Crime in the United States, Arrests,” September 2010,", "", "", "", ""]
|
||||
]
|
||||
|
||||
data_stream_table_areas = [
|
||||
["", "One Withholding"],
|
||||
["Payroll Period", "Allowance"],
|
||||
["Weekly", "$71.15"],
|
||||
["Weekly", "$\n71.15"],
|
||||
["Biweekly", "142.31"],
|
||||
["Semimonthly", "154.17"],
|
||||
["Monthly", "308.33"],
|
||||
|
|
@ -187,14 +270,10 @@ data_stream_split_text = [
|
|||
["", "", "", "", "1522 WEST LINDSEY", "", "", "", "", ""],
|
||||
["632575", "BAW", "BASHU LEGENDS", "HYH HE CHUANG LLC", "STREET", "NORMAN", "OK", "73069", "-", "2014/07/21"],
|
||||
["", "", "", "DEEP FORK HOLDINGS", "", "", "", "", "", ""],
|
||||
["543149", "BAW", "BEDLAM BAR-B-Q", "LLC", "610 NORTHEAST 50TH", "OKLAHOMA CITY", "OK", "73105", "(405) 528-7427", "2015/02/23"],
|
||||
["", "", "", "", "Page 1 of 151", "", "", "", "", ""]
|
||||
["543149", "BAW", "BEDLAM BAR-B-Q", "LLC", "610 NORTHEAST 50TH", "OKLAHOMA CITY", "OK", "73105", "(405) 528-7427", "2015/02/23"]
|
||||
]
|
||||
|
||||
data_stream_flag_size = [
|
||||
["", "TABLE 125: STATE-WISE COMPOSITION OF OUTSTANDING LIABILITIES - 1997 <s>(Contd.)</s>", "", "", "", "", "", "", "", "", ""],
|
||||
["", "", "", "", "(As at end-March)", "", "", "", "", "", ""],
|
||||
["", "", "", "", "", "", "", "", "", "", "(<s>`</s> Billion)"],
|
||||
["States", "Total", "Market", "NSSF", "WMA", "Loans", "Loans", "Loans", "Loans", "Loans", "Loans"],
|
||||
["", "Internal", "Loans", "", "from", "from", "from", "from", "from", "from SBI", "from"],
|
||||
["", "Debt", "", "", "RBI", "Banks", "LIC", "GIC", "NABARD", "& Other", "NCDC"],
|
||||
|
|
@ -230,14 +309,12 @@ data_stream_flag_size = [
|
|||
["Uttar Pradesh", "80.62", "74.89", "-", "4.34", "1.34", "0.6", "-", "-0.21", "0.18", "0.03"],
|
||||
["West Bengal", "34.23", "32.19", "-", "-", "2.04", "0.77", "-", "0.06", "-", "0.51"],
|
||||
["NCT Delhi", "-", "-", "-", "-", "-", "-", "-", "-", "-", "-"],
|
||||
["ALL STATES", "513.38", "436.02", "-", "25.57", "51.06", "14.18", "-", "8.21", "11.83", "11.08"],
|
||||
["<s>2</s> Includes `2.45 crore outstanding under “Market Loan Suspense”.", "", "", "", "", "", "", "", "", "", ""],
|
||||
["", "", "", "", "445", "", "", "", "", "", ""]
|
||||
["ALL STATES", "513.38", "436.02", "-", "25.57", "51.06", "14.18", "-", "8.21", "11.83", "11.08"]
|
||||
]
|
||||
|
||||
data_lattice = [
|
||||
["Cycle Name", "KI (1/km)", "Distance (mi)", "Percent Fuel Savings", "", "", ""],
|
||||
["", "", "", "Improved Speed", "Decreased Accel", "Eliminate Stops", "Decreased Idle"],
|
||||
["Cycle \nName", "KI \n(1/km)", "Distance \n(mi)", "Percent Fuel Savings", "", "", ""],
|
||||
["", "", "", "Improved \nSpeed", "Decreased \nAccel", "Eliminate \nStops", "Decreased \nIdle"],
|
||||
["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%"],
|
||||
|
|
@ -246,7 +323,7 @@ data_lattice = [
|
|||
]
|
||||
|
||||
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)", ""],
|
||||
["State", "Nutritional Assessment \n(No. of individuals)", "", "", "", "IYCF Practices \n(No. of mothers: \n2011-12)", "Blood Pressure \n(No. of adults: \n2011-12)", "", "Fasting Blood Sugar \n(No. of adults:\n2011-12)", ""],
|
||||
["", "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"],
|
||||
|
|
@ -261,10 +338,42 @@ data_lattice_table_rotated = [
|
|||
["Pooled", "38742", "53618", "60601", "86898", "4459", "21918", "27041", "14312", "18519"]
|
||||
]
|
||||
|
||||
data_lattice_table_area = [
|
||||
data_lattice_two_tables_1 = [
|
||||
["State", "n", "Literacy Status", "", "", "", "", ""],
|
||||
["", "", "Illiterate", "Read & \nWrite", "1-4 std.", "5-8 std.", "9-12 std.", "College"],
|
||||
["Kerala", "2400", "7.2", "0.5", "25.3", "20.1", "41.5", "5.5"],
|
||||
["Tamil Nadu", "2400", "21.4", "2.3", "8.8", "35.5", "25.8", "6.2"],
|
||||
["Karnataka", "2399", "37.4", "2.8", "12.5", "18.3", "23.1", "5.8"],
|
||||
["Andhra Pradesh", "2400", "54.0", "1.7", "8.4", "13.2", "18.8", "3.9"],
|
||||
["Maharashtra", "2400", "22.0", "0.9", "17.3", "20.3", "32.6", "7.0"],
|
||||
["Gujarat", "2390", "28.6", "0.1", "14.4", "23.1", "26.9", "6.8"],
|
||||
["Madhya Pradesh", "2402", "29.1", "3.4", "8.5", "35.1", "13.3", "10.6"],
|
||||
["Orissa", "2405", "33.2", "1.0", "10.4", "25.7", "21.2", "8.5"],
|
||||
["West Bengal", "2293", "41.7", "4.4", "13.2", "17.1", "21.2", "2.4"],
|
||||
["Uttar Pradesh", "2400", "35.3", "2.1", "4.5", "23.3", "27.1", "7.6"],
|
||||
["Pooled", "23889", "30.9", "1.9", "12.3", "23.2", "25.2", "6.4"]
|
||||
]
|
||||
|
||||
data_lattice_two_tables_2 = [
|
||||
["State", "n", "Literacy Status", "", "", "", "", ""],
|
||||
["", "", "Illiterate", "Read & \nWrite", "1-4 std.", "5-8 std.", "9-12 std.", "College"],
|
||||
["Kerala", "2400", "8.8", "0.3", "20.1", "17.0", "45.6", "8.2"],
|
||||
["Tamil Nadu", "2400", "29.9", "1.5", "8.5", "33.1", "22.3", "4.8"],
|
||||
["Karnataka", "2399", "47.9", "2.5", "10.2", "18.8", "18.4", "2.3"],
|
||||
["Andhra Pradesh", "2400", "66.4", "0.7", "6.8", "12.9", "11.4", "1.8"],
|
||||
["Maharashtra", "2400", "41.3", "0.6", "14.1", "20.1", "21.6", "2.2"],
|
||||
["Gujarat", "2390", "57.6", "0.1", "10.3", "16.5", "12.9", "2.7"],
|
||||
["Madhya Pradesh", "2402", "58.7", "2.2", "6.6", "24.1", "5.3", "3.0"],
|
||||
["Orissa", "2405", "50.0", "0.9", "8.1", "21.9", "15.1", "4.0"],
|
||||
["West Bengal", "2293", "49.1", "4.8", "11.2", "16.8", "17.1", "1.1"],
|
||||
["Uttar Pradesh", "2400", "67.3", "2.0", "3.1", "17.2", "7.7", "2.7"],
|
||||
["Pooled", "23889", "47.7", "1.5", "9.9", "19.9", "17.8", "3.3"]
|
||||
]
|
||||
|
||||
data_lattice_table_areas = [
|
||||
["", "", "", "", "", "", "", "", ""],
|
||||
["State", "n", "Literacy Status", "", "", "", "", "", ""],
|
||||
["", "", "Illiterate", "Read & Write", "1-4 std.", "5-8 std.", "9-12 std.", "College", ""],
|
||||
["", "", "Illiterate", "Read & \nWrite", "1-4 std.", "5-8 std.", "9-12 std.", "College", ""],
|
||||
["Kerala", "2400", "7.2", "0.5", "25.3", "20.1", "41.5", "5.5", ""],
|
||||
["Tamil Nadu", "2400", "21.4", "2.3", "8.8", "35.5", "25.8", "6.2", ""],
|
||||
["Karnataka", "2399", "37.4", "2.8", "12.5", "18.3", "23.1", "5.8", ""],
|
||||
|
|
@ -280,13 +389,13 @@ data_lattice_table_area = [
|
|||
]
|
||||
|
||||
data_lattice_process_background = [
|
||||
["State", "Date", "Halt stations", "Halt days", "Persons directly reached(in lakh)", "Persons trained", "Persons counseled" ,"Persons testedfor HIV"],
|
||||
["State", "Date", "Halt \nstations", "Halt \ndays", "Persons \ndirectly \nreached\n(in lakh)", "Persons \ntrained", "Persons \ncounseled", "Persons \ntested\nfor 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"],
|
||||
["Rajasthan", "2.12.2009 to \n19.12.2009", "", "", "", "", "", ""],
|
||||
["Gujarat", "20.12.2009 to \n3.1.2010", "6", "13", "6.03", "3,810", "2,317", "1,453"],
|
||||
["Maharashtra", "4.01.2010 to \n1.2.2010", "13", "26", "1.27", "5,680", "9,027", "4,153"],
|
||||
["Karnataka", "2.2.2010 to \n22.2.2010", "11", "19", "1.80", "5,741", "3,658", "3,183"],
|
||||
["Kerala", "23.2.2010 to \n11.3.2010", "9", "17", "1.42", "3,559", "2,173", "855"],
|
||||
["Total", "", "47", "92", "11.81", "22,455", "19,584", "10,644"]
|
||||
]
|
||||
|
||||
|
|
@ -330,11 +439,11 @@ data_lattice_copy_text = [
|
|||
["PCCM", "San Francisco", "Family Mosaic", "25"],
|
||||
["PCCM", "Total PHP Enrollment", "", "853"],
|
||||
["All Models Total Enrollments", "", "", "10,132,875"],
|
||||
["Source: Data Warehouse 12/14/15", "", "", ""]
|
||||
["Source: Data Warehouse \n12/14/15", "", "", ""]
|
||||
]
|
||||
|
||||
data_lattice_shift_text_left_top = [
|
||||
["Investigations", "No. ofHHs", "Age/Sex/Physiological Group", "Preva-lence", "C.I*", "RelativePrecision", "Sample sizeper State"],
|
||||
["Investigations", "No. of\nHHs", "Age/Sex/\nPhysiological Group", "Preva-\nlence", "C.I*", "Relative\nPrecision", "Sample size\nper State"],
|
||||
["Anthropometry", "2400", "All the available individuals", "", "", "", ""],
|
||||
["Clinical Examination", "", "", "", "", "", ""],
|
||||
["History of morbidity", "", "", "", "", "", ""],
|
||||
|
|
@ -343,12 +452,12 @@ data_lattice_shift_text_left_top = [
|
|||
["", "", "Women (≥ 18 yrs)", "", "", "", "1728"],
|
||||
["Fasting blood glucose", "2400", "Men (≥ 18 yrs)", "5%", "95%", "20%", "1825"],
|
||||
["", "", "Women (≥ 18 yrs)", "", "", "", "1825"],
|
||||
["Knowledge &Practices on HTN &DM", "2400", "Men (≥ 18 yrs)", "-", "-", "-", "1728"],
|
||||
["Knowledge &\nPractices on HTN &\nDM", "2400", "Men (≥ 18 yrs)", "-", "-", "-", "1728"],
|
||||
["", "2400", "Women (≥ 18 yrs)", "-", "-", "-", "1728"]
|
||||
]
|
||||
|
||||
data_lattice_shift_text_disable = [
|
||||
["Investigations", "No. ofHHs", "Age/Sex/Physiological Group", "Preva-lence", "C.I*", "RelativePrecision", "Sample sizeper State"],
|
||||
["Investigations", "No. of\nHHs", "Age/Sex/\nPhysiological Group", "Preva-\nlence", "C.I*", "Relative\nPrecision", "Sample size\nper State"],
|
||||
["Anthropometry", "", "", "", "", "", ""],
|
||||
["Clinical Examination", "2400", "", "All the available individuals", "", "", ""],
|
||||
["History of morbidity", "", "", "", "", "", ""],
|
||||
|
|
@ -357,12 +466,12 @@ data_lattice_shift_text_disable = [
|
|||
["Blood Pressure #", "2400", "Women (≥ 18 yrs)", "10%", "95%", "20%", "1728"],
|
||||
["", "", "Men (≥ 18 yrs)", "", "", "", "1825"],
|
||||
["Fasting blood glucose", "2400", "Women (≥ 18 yrs)", "5%", "95%", "20%", "1825"],
|
||||
["Knowledge &Practices on HTN &", "2400", "Men (≥ 18 yrs)", "-", "-", "-", "1728"],
|
||||
["Knowledge &\nPractices on HTN &", "2400", "Men (≥ 18 yrs)", "-", "-", "-", "1728"],
|
||||
["DM", "2400", "Women (≥ 18 yrs)", "-", "-", "-", "1728"]
|
||||
]
|
||||
|
||||
data_lattice_shift_text_right_bottom = [
|
||||
["Investigations", "No. ofHHs", "Age/Sex/Physiological Group", "Preva-lence", "C.I*", "RelativePrecision", "Sample sizeper State"],
|
||||
["Investigations", "No. of\nHHs", "Age/Sex/\nPhysiological Group", "Preva-\nlence", "C.I*", "Relative\nPrecision", "Sample size\nper State"],
|
||||
["Anthropometry", "", "", "", "", "", ""],
|
||||
["Clinical Examination", "", "", "", "", "", ""],
|
||||
["History of morbidity", "2400", "", "", "", "", "All the available individuals"],
|
||||
|
|
@ -372,5 +481,13 @@ data_lattice_shift_text_right_bottom = [
|
|||
["", "", "Men (≥ 18 yrs)", "", "", "", "1825"],
|
||||
["Fasting blood glucose", "2400", "Women (≥ 18 yrs)", "5%", "95%", "20%", "1825"],
|
||||
["", "2400", "Men (≥ 18 yrs)", "-", "-", "-", "1728"],
|
||||
["Knowledge &Practices on HTN &DM", "2400", "Women (≥ 18 yrs)", "-", "-", "-", "1728"]
|
||||
["Knowledge &\nPractices on HTN &\nDM", "2400", "Women (≥ 18 yrs)", "-", "-", "-", "1728"]
|
||||
]
|
||||
|
||||
data_arabic = [
|
||||
['ً\n\xa0\nﺎﺒﺣﺮﻣ', 'ﻥﺎﻄﻠﺳ\xa0ﻲﻤﺳﺍ'],
|
||||
['ﻝﺎﻤﺸﻟﺍ\xa0ﺎﻨﻴﻟﻭﺭﺎﻛ\xa0ﺔﻳﻻﻭ\xa0ﻦﻣ\xa0ﺎﻧﺍ', '؟ﺖﻧﺍ\xa0ﻦﻳﺍ\xa0ﻦﻣ'],
|
||||
['1234', 'ﻂﻄﻗ\xa047\xa0ﻱﺪﻨﻋ'],
|
||||
['؟ﻙﺎﺒﺷ\xa0ﺖﻧﺍ\xa0ﻞﻫ', 'ﺔﻳﺰﻴﻠﺠﻧﻻﺍ\xa0ﻲﻓ\xa0Jeremy\xa0ﻲﻤﺳﺍ'],
|
||||
['Jeremy\xa0is\xa0ﻲﻣﺮﺟ\xa0in\xa0Arabic', '']
|
||||
]
|
||||
|
|
|
|||
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|
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|
|
@ -1,79 +1,117 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
|
||||
import os
|
||||
|
||||
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')
|
||||
|
||||
|
||||
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 result.output == 'Found 1 tables\n'
|
||||
|
||||
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_output_format():
|
||||
with TemporaryDirectory() as tempdir:
|
||||
infile = os.path.join(testdir, 'health.pdf')
|
||||
outfile = os.path.join(tempdir, 'health.{}')
|
||||
runner = CliRunner()
|
||||
|
||||
# json
|
||||
result = runner.invoke(cli, ['--format', 'json', '--output', outfile.format('json'),
|
||||
'stream', infile])
|
||||
assert result.exit_code == 0
|
||||
|
||||
# excel
|
||||
result = runner.invoke(cli, ['--format', 'excel', '--output', outfile.format('xlsx'),
|
||||
'stream', infile])
|
||||
assert result.exit_code == 0
|
||||
|
||||
# html
|
||||
result = runner.invoke(cli, ['--format', 'html', '--output', outfile.format('html'),
|
||||
'stream', infile])
|
||||
assert result.exit_code == 0
|
||||
|
||||
# zip
|
||||
result = runner.invoke(cli, ['--zip', '--format', 'csv', '--output', outfile.format('csv'),
|
||||
'stream', infile])
|
||||
assert result.exit_code == 0
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import os
|
||||
|
||||
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')
|
||||
|
||||
|
||||
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 result.output == 'Found 1 tables\n'
|
||||
|
||||
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')
|
||||
outfile = os.path.join(tempdir, 'health.{}')
|
||||
runner = CliRunner()
|
||||
|
||||
# json
|
||||
result = runner.invoke(cli, ['--format', 'json', '--output', outfile.format('json'),
|
||||
'stream', infile])
|
||||
assert result.exit_code == 0
|
||||
|
||||
# excel
|
||||
result = runner.invoke(cli, ['--format', 'excel', '--output', outfile.format('xlsx'),
|
||||
'stream', infile])
|
||||
assert result.exit_code == 0
|
||||
|
||||
# html
|
||||
result = runner.invoke(cli, ['--format', 'html', '--output', outfile.format('html'),
|
||||
'stream', infile])
|
||||
assert result.exit_code == 0
|
||||
|
||||
# zip
|
||||
result = runner.invoke(cli, ['--zip', '--format', 'csv', '--output', outfile.format('csv'),
|
||||
'stream', infile])
|
||||
assert result.exit_code == 0
|
||||
|
||||
def test_cli_quiet():
|
||||
with TemporaryDirectory() as tempdir:
|
||||
infile = os.path.join(testdir, 'blank.pdf')
|
||||
outfile = os.path.join(tempdir, 'blank.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
|
||||
|
|
|
|||
|
|
@ -25,6 +25,17 @@ def test_parsing_report():
|
|||
assert tables[0].parsing_report == parsing_report
|
||||
|
||||
|
||||
def test_password():
|
||||
df = pd.DataFrame(data_stream)
|
||||
|
||||
filename = os.path.join(testdir, "health_protected.pdf")
|
||||
tables = camelot.read_pdf(filename, password="ownerpass", flavor="stream")
|
||||
assert df.equals(tables[0].df)
|
||||
|
||||
tables = camelot.read_pdf(filename, password="userpass", flavor="stream")
|
||||
assert df.equals(tables[0].df)
|
||||
|
||||
|
||||
def test_stream():
|
||||
df = pd.DataFrame(data_stream)
|
||||
|
||||
|
|
@ -45,11 +56,23 @@ def test_stream_table_rotated():
|
|||
assert df.equals(tables[0].df)
|
||||
|
||||
|
||||
def test_stream_table_area():
|
||||
df = pd.DataFrame(data_stream_table_area)
|
||||
def test_stream_two_tables():
|
||||
df1 = pd.DataFrame(data_stream_two_tables_1)
|
||||
df2 = pd.DataFrame(data_stream_two_tables_2)
|
||||
|
||||
filename = os.path.join(testdir, "tabula/12s0324.pdf")
|
||||
tables = camelot.read_pdf(filename, flavor='stream')
|
||||
|
||||
assert len(tables) == 2
|
||||
assert df1.equals(tables[0].df)
|
||||
assert df2.equals(tables[1].df)
|
||||
|
||||
|
||||
def test_stream_table_areas():
|
||||
df = pd.DataFrame(data_stream_table_areas)
|
||||
|
||||
filename = os.path.join(testdir, "tabula/us-007.pdf")
|
||||
tables = camelot.read_pdf(filename, flavor="stream", table_area=["320,500,573,335"])
|
||||
tables = camelot.read_pdf(filename, flavor="stream", table_areas=["320,500,573,335"])
|
||||
assert df.equals(tables[0].df)
|
||||
|
||||
|
||||
|
|
@ -100,11 +123,22 @@ def test_lattice_table_rotated():
|
|||
assert df.equals(tables[0].df)
|
||||
|
||||
|
||||
def test_lattice_table_area():
|
||||
df = pd.DataFrame(data_lattice_table_area)
|
||||
def test_lattice_two_tables():
|
||||
df1 = pd.DataFrame(data_lattice_two_tables_1)
|
||||
df2 = pd.DataFrame(data_lattice_two_tables_2)
|
||||
|
||||
filename = os.path.join(testdir, "twotables_2.pdf")
|
||||
tables = camelot.read_pdf(filename, table_area=["80,693,535,448"])
|
||||
tables = camelot.read_pdf(filename)
|
||||
assert len(tables) == 2
|
||||
assert df1.equals(tables[0].df)
|
||||
assert df2.equals(tables[1].df)
|
||||
|
||||
|
||||
def test_lattice_table_areas():
|
||||
df = pd.DataFrame(data_lattice_table_areas)
|
||||
|
||||
filename = os.path.join(testdir, "twotables_2.pdf")
|
||||
tables = camelot.read_pdf(filename, table_areas=["80,693,535,448"])
|
||||
assert df.equals(tables[0].df)
|
||||
|
||||
|
||||
|
|
@ -139,10 +173,18 @@ def test_lattice_shift_text():
|
|||
tables = camelot.read_pdf(filename, line_size_scaling=40, shift_text=['r', 'b'])
|
||||
assert df_rb.equals(tables[0].df)
|
||||
|
||||
|
||||
|
||||
def test_repr():
|
||||
filename = os.path.join(testdir, "foo.pdf")
|
||||
tables = camelot.read_pdf(filename)
|
||||
assert repr(tables) == "<TableList n=1>"
|
||||
assert repr(tables[0]) == "<Table shape=(7, 7)>"
|
||||
assert repr(tables[0].cells[0][0]) == "<Cell x1=120.48 y1=218.42 x2=164.64 y2=233.89>"
|
||||
|
||||
|
||||
def test_arabic():
|
||||
df = pd.DataFrame(data_arabic)
|
||||
|
||||
filename = os.path.join(testdir, "tabula/arabic.pdf")
|
||||
tables = camelot.read_pdf(filename)
|
||||
assert df.equals(tables[0].df)
|
||||
|
|
|
|||
|
|
@ -34,20 +34,70 @@ def test_unsupported_format():
|
|||
|
||||
|
||||
def test_stream_equal_length():
|
||||
message = ("Length of table_area and columns"
|
||||
message = ("Length of table_areas and columns"
|
||||
" should be equal")
|
||||
with pytest.raises(ValueError, message=message):
|
||||
tables = camelot.read_pdf(filename, flavor='stream',
|
||||
table_area=['10,20,30,40'], columns=['10,20,30,40', '10,20,30,40'])
|
||||
table_areas=['10,20,30,40'], columns=['10,20,30,40', '10,20,30,40'])
|
||||
|
||||
|
||||
def test_no_tables_found():
|
||||
filename = os.path.join(testdir, 'blank.pdf')
|
||||
# TODO: use pytest.warns
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter('error')
|
||||
try:
|
||||
with pytest.raises(UserWarning) as e:
|
||||
tables = camelot.read_pdf(filename)
|
||||
except Exception as e:
|
||||
assert type(e).__name__ == 'UserWarning'
|
||||
assert str(e) == 'No tables found on page-1'
|
||||
assert str(e.value) == 'No tables found on page-1'
|
||||
|
||||
|
||||
def test_no_tables_found_logs_suppressed():
|
||||
filename = os.path.join(testdir, 'foo.pdf')
|
||||
with warnings.catch_warnings():
|
||||
# the test should fail if any warning is thrown
|
||||
warnings.simplefilter('error')
|
||||
try:
|
||||
tables = camelot.read_pdf(filename, suppress_stdout=True)
|
||||
except Warning as e:
|
||||
warning_text = str(e)
|
||||
pytest.fail('Unexpected warning: {}'.format(warning_text))
|
||||
|
||||
|
||||
def test_no_tables_found_warnings_suppressed():
|
||||
filename = os.path.join(testdir, 'blank.pdf')
|
||||
with warnings.catch_warnings():
|
||||
# the test should fail if any warning is thrown
|
||||
warnings.simplefilter('error')
|
||||
try:
|
||||
tables = camelot.read_pdf(filename, suppress_stdout=True)
|
||||
except Warning as e:
|
||||
warning_text = str(e)
|
||||
pytest.fail('Unexpected warning: {}'.format(warning_text))
|
||||
|
||||
|
||||
def test_ghostscript_not_found(monkeypatch):
|
||||
import distutils
|
||||
|
||||
def _find_executable_patch(arg):
|
||||
return ''
|
||||
|
||||
monkeypatch.setattr(distutils.spawn, 'find_executable', _find_executable_patch)
|
||||
|
||||
message = ('Please make sure that Ghostscript is installed and available'
|
||||
' on the PATH environment variable')
|
||||
filename = os.path.join(testdir, 'foo.pdf')
|
||||
with pytest.raises(Exception, message=message):
|
||||
tables = camelot.read_pdf(filename)
|
||||
|
||||
|
||||
def test_no_password():
|
||||
filename = os.path.join(testdir, 'health_protected.pdf')
|
||||
message = 'file has not been decrypted'
|
||||
with pytest.raises(Exception, message=message):
|
||||
tables = camelot.read_pdf(filename)
|
||||
|
||||
|
||||
def test_bad_password():
|
||||
filename = os.path.join(testdir, 'health_protected.pdf')
|
||||
message = 'file has not been decrypted'
|
||||
with pytest.raises(Exception, message=message):
|
||||
tables = camelot.read_pdf(filename, password='wrongpass')
|
||||
|
|
|
|||
|
|
@ -0,0 +1,67 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
|
||||
import os
|
||||
|
||||
import pytest
|
||||
|
||||
import camelot
|
||||
|
||||
|
||||
testdir = os.path.dirname(os.path.abspath(__file__))
|
||||
testdir = os.path.join(testdir, "files")
|
||||
|
||||
|
||||
@pytest.mark.mpl_image_compare(
|
||||
baseline_dir="files/baseline_plots", remove_text=True)
|
||||
def test_text_plot():
|
||||
filename = os.path.join(testdir, "foo.pdf")
|
||||
tables = camelot.read_pdf(filename)
|
||||
return camelot.plot(tables[0], kind='text')
|
||||
|
||||
|
||||
@pytest.mark.mpl_image_compare(
|
||||
baseline_dir="files/baseline_plots", remove_text=True)
|
||||
def test_grid_plot():
|
||||
filename = os.path.join(testdir, "foo.pdf")
|
||||
tables = camelot.read_pdf(filename)
|
||||
return camelot.plot(tables[0], kind='grid')
|
||||
|
||||
|
||||
@pytest.mark.mpl_image_compare(
|
||||
baseline_dir="files/baseline_plots", remove_text=True)
|
||||
def test_lattice_contour_plot():
|
||||
filename = os.path.join(testdir, "foo.pdf")
|
||||
tables = camelot.read_pdf(filename)
|
||||
return camelot.plot(tables[0], kind='contour')
|
||||
|
||||
|
||||
@pytest.mark.mpl_image_compare(
|
||||
baseline_dir="files/baseline_plots", remove_text=True)
|
||||
def test_stream_contour_plot():
|
||||
filename = os.path.join(testdir, "tabula/12s0324.pdf")
|
||||
tables = camelot.read_pdf(filename, flavor='stream')
|
||||
return camelot.plot(tables[0], kind='contour')
|
||||
|
||||
|
||||
@pytest.mark.mpl_image_compare(
|
||||
baseline_dir="files/baseline_plots", remove_text=True)
|
||||
def test_line_plot():
|
||||
filename = os.path.join(testdir, "foo.pdf")
|
||||
tables = camelot.read_pdf(filename)
|
||||
return camelot.plot(tables[0], kind='line')
|
||||
|
||||
|
||||
@pytest.mark.mpl_image_compare(
|
||||
baseline_dir="files/baseline_plots", remove_text=True)
|
||||
def test_joint_plot():
|
||||
filename = os.path.join(testdir, "foo.pdf")
|
||||
tables = camelot.read_pdf(filename)
|
||||
return camelot.plot(tables[0], kind='joint')
|
||||
|
||||
|
||||
@pytest.mark.mpl_image_compare(
|
||||
baseline_dir="files/baseline_plots", remove_text=True)
|
||||
def test_textedge_plot():
|
||||
filename = os.path.join(testdir, "tabula/12s0324.pdf")
|
||||
tables = camelot.read_pdf(filename, flavor='stream')
|
||||
return camelot.plot(tables[0], kind='textedge')
|
||||
Loading…
Reference in New Issue