Bump version

[MRG] Add support to read from url

.coveragerc

@@ -1,6 +1,2 @@
 [run]
-branch = True
+branch = True
-source = camelot
-include = */camelot/*
-omit = 
-    */setup.py

.editorconfig

@@ -0,0 +1,10 @@
+root = true
+
+[*]
+end_of_line = lf
+insert_final_newline = true
+
+[*.py]
+charset = utf-8
+indent_style = space
+indent_size = 4

.gitignore

@@ -11,3 +11,6 @@ coverage.xml
 
 .pytest_cache/
 _build/
+
+# vscode
+.vscode

.travis.yml

@@ -1,12 +1,32 @@
-language: python
+sudo: true
-python:
+language: python
-  - "2.7"
+cache: pip
-  - "3.6"
+addons:
-before_install:
+  apt:
-  - sudo apt-get install python-tk python3-tk ghostscript
+    update: true
-install:
+install:
-  - pip install ".[dev]"
+  - make install
-script:
+jobs:
-  - pytest
+  include:
-after_success:
+    - stage: test
-  - codecov
+      script:
+        - make test
+      python: '2.7'
+    - stage: test
+      script:
+        - make test
+      python: '3.5'
+    - stage: test
+      script:
+        - make test
+      python: '3.6'
+    - stage: test
+      script:
+        - make test
+      python: '3.7'
+      dist: xenial
+    - stage: coverage
+      python: '3.6'
+      script:
+        - make test
+        - codecov --verbose

CONTRIBUTING.md

@@ -14,9 +14,9 @@ Kenneth Reitz has also written an [essay](https://www.kennethreitz.org/essays/be
 
 As the [Requests Code Of Conduct](http://docs.python-requests.org/en/master/dev/contributing/#be-cordial) states, **all contributions are welcome**, as long as everyone involved is treated with respect.
 
-## Your First Contribution
+## Your first contribution
 
-A great way to start contributing to Camelot is to pick an issue tagged with the [Contributor Friendly](https://github.com/socialcopsdev/camelot/labels/Contributor%20Friendly) tag or the [Level: Easy](https://github.com/socialcopsdev/camelot/labels/Level%3A%20Easy) tag. If you're unable to find a good first issue, feel free to contact the maintainer.
+A great way to start contributing to Camelot is to pick an issue tagged with the [help wanted](https://github.com/socialcopsdev/camelot/labels/help%20wanted) tag or the [good first issue](https://github.com/socialcopsdev/camelot/labels/good%20first%20issue) tag. If you're unable to find a good first issue, feel free to contact the maintainer.
 
 ## Setting up a development environment
 
@@ -26,19 +26,17 @@ To install the dependencies needed for development, you can use pip:
 $ pip install camelot-py[dev]
 </pre>
 
-### Alternatively
+Alternatively, you can clone the project repository, and install using pip:
-
-You can clone the project repository, and install using pip:
 
 <pre>
-$ pip install .[dev]
+$ pip install ".[dev]"
 </pre>
 
 ## Pull Requests
 
-### Submit a Pull Request
+### Submit a pull request
 
-The preferred workflow for contributing to Camelot is to fork the [project repository](https://github.com/socialcopsdev/camelot) on GitHub, clone, develop on a branch and then finally submit a pull request. Steps:
+The preferred workflow for contributing to Camelot is to fork the [project repository](https://github.com/socialcopsdev/camelot) on GitHub, clone, develop on a branch and then finally submit a pull request. Here are the steps:
 
 1. Fork the project repository. Click on the ‘Fork’ button near the top of the page. This creates a copy of the code under your account on the GitHub.
 
@@ -73,7 +71,7 @@ $ git push -u origin my-feature
 
 Now it's time to go to the your fork of Camelot and create a pull request! You can [follow these instructions](https://help.github.com/articles/creating-a-pull-request-from-a-fork/) to do this.
 
-### Work on your Pull Request
+### Work on your pull request
 
 We recommend that your pull request complies with the following rules:
 
@@ -81,7 +79,7 @@ We recommend that your pull request complies with the following rules:
 
 - In case your pull request contains function docstrings, make sure you follow the [numpydoc](https://numpydoc.readthedocs.io/en/latest/format.html) format. All function docstrings in Camelot follow this format. Moreover, following the format will make sure that the API documentation is generated flawlessly.
 
-- Make sure your commit messages follow [the seven rules of a great git commit message](https://chris.beams.io/posts/git-commit/).
+- Make sure your commit messages follow [the seven rules of a great git commit message](https://chris.beams.io/posts/git-commit/):
     - Separate subject from body with a blank line
     - Limit the subject line to 50 characters
     - Capitalize the subject line
@@ -104,15 +102,15 @@ Writing documentation, function docstrings, examples and tutorials is a great wa
 
 It is written in [reStructuredText](https://en.wikipedia.org/wiki/ReStructuredText), with [Sphinx](http://www.sphinx-doc.org/en/master/) used to generate these lovely HTML files that you're currently reading (unless you're reading this on GitHub). You can edit the documentation using any text editor and then generate the HTML output by running `make html` in the `docs/` directory.
 
-The function docstrings are written using the [numpydoc](https://numpydoc.readthedocs.io/en/latest/format.html) extension for Sphinx. Make sure you check out its format guidelines, before you start writing one.
+The function docstrings are written using the [numpydoc](https://numpydoc.readthedocs.io/en/latest/format.html) extension for Sphinx. Make sure you check out its format guidelines before you start writing one.
 
 ## Filing Issues
 
-We use [GitHub issues](https://docs.pytest.org/en/latest/) to keep track of all issues and pull requests. Before opening an issue (which asks a question or reports a bug), it is advisable to use GitHub search to look for existing issues (both open and closed) that may be similar.
+We use [GitHub issues](https://github.com/socialcopsdev/camelot/issues) to keep track of all issues and pull requests. Before opening an issue (which asks a question or reports a bug), please use GitHub search to look for existing issues (both open and closed) that may be similar.
 
 ### Questions
 
-Please don't use GitHub issues for support questions, a better place for them would be [Stack Overflow](http://stackoverflow.com). Make sure you tag them using the `python-camelot` tag.
+Please don't use GitHub issues for support questions. A better place for them would be [Stack Overflow](http://stackoverflow.com). Make sure you tag them using the `python-camelot` tag.
 
 ### Bug Reports
 

HISTORY.md

@@ -0,0 +1,161 @@
+Release History
+===============
+
+master
+------
+
+0.6.0 (2018-12-24)
+------------------
+
+**Improvements**
+
+* [#91](https://github.com/socialcopsdev/camelot/issues/91) Add support to read from url. [#236](https://github.com/socialcopsdev/camelot/pull/236) by Vinayak Mehta.
+* [#229](https://github.com/socialcopsdev/camelot/issues/229), [#230](https://github.com/socialcopsdev/camelot/issues/230) and [#233](https://github.com/socialcopsdev/camelot/issues/233) New configuration parameters. [#234](https://github.com/socialcopsdev/camelot/pull/234) by Vinayak Mehta.
+    * `strip_text`: To define characters that should be stripped from each string.
+    * `edge_tol`: Tolerance parameter for extending textedges vertically.
+    * `resolution`: Resolution used for PDF to PNG conversion.
+    * Check out the [advanced docs](https://camelot-py.readthedocs.io/en/master/user/advanced.html#strip-characters-from-text) for usage details.
+* [#170](https://github.com/socialcopsdev/camelot/issues/170) Add option to pass pdfminer layout kwargs. [#232](https://github.com/socialcopsdev/camelot/pull/232) by Vinayak Mehta.
+    * Keyword arguments for [pdfminer.layout.LAParams](https://github.com/euske/pdfminer/blob/master/pdfminer/layout.py#L33) can now be passed using `layout_kwargs` in `read_pdf()`.
+    * The `margins` keyword argument in `read_pdf()` is now deprecated.
+
+0.5.0 (2018-12-13)
+------------------
+
+**Improvements**
+
+* [#207](https://github.com/socialcopsdev/camelot/issues/207) Add a plot type for Stream text edges and detected table areas. [#224](https://github.com/socialcopsdev/camelot/pull/224) by Vinayak Mehta.
+* [#204](https://github.com/socialcopsdev/camelot/issues/204) `suppress_warnings` is now called `suppress_stdout`. [#225](https://github.com/socialcopsdev/camelot/pull/225) by Vinayak Mehta.
+
+**Bugfixes**
+
+* [#217](https://github.com/socialcopsdev/camelot/issues/217) Fix IndexError when scale is large.
+* [#105](https://github.com/socialcopsdev/camelot/issues/105), [#192](https://github.com/socialcopsdev/camelot/issues/192) and [#215](https://github.com/socialcopsdev/camelot/issues/215) in [#227](https://github.com/socialcopsdev/camelot/pull/227) by Vinayak Mehta.
+
+**Documentation**
+
+* Add pdfplumber comparison and update Tabula (stream) comparison. Check out the [wiki page](https://github.com/socialcopsdev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools).
+
+0.4.1 (2018-12-05)
+------------------
+
+**Bugfixes**
+
+* Add chardet to `install_requires` to fix [#210](https://github.com/socialcopsdev/camelot/issues/210). More details in [pdfminer.six#213](https://github.com/pdfminer/pdfminer.six/issues/213).
+
+0.4.0 (2018-11-23)
+------------------
+
+**Improvements**
+
+* [#102](https://github.com/socialcopsdev/camelot/issues/102) Detect tables automatically when Stream is used. [#206](https://github.com/socialcopsdev/camelot/pull/206) Add implementation of Anssi Nurminen's table detection algorithm by Vinayak Mehta.
+
+0.3.2 (2018-11-04)
+------------------
+
+**Improvements**
+
+* [#186](https://github.com/socialcopsdev/camelot/issues/186) Add `_bbox` attribute to table. [#193](https://github.com/socialcopsdev/camelot/pull/193) by Vinayak Mehta.
+    * You can use `table._bbox` to get coordinates of the detected table.
+
+0.3.1 (2018-11-02)
+------------------
+
+**Improvements**
+
+* Matplotlib is now an optional requirement. [#190](https://github.com/socialcopsdev/camelot/pull/190) by Vinayak Mehta.
+    * You can install it using `$ pip install camelot-py[plot]`.
+* [#127](https://github.com/socialcopsdev/camelot/issues/127) Add tests for plotting. Coverage is now at 87%! [#179](https://github.com/socialcopsdev/camelot/pull/179) by [Suyash Behera](https://github.com/Suyash458).
+
+0.3.0 (2018-10-28)
+------------------
+
+**Improvements**
+
+* [#162](https://github.com/socialcopsdev/camelot/issues/162) Add password keyword argument. [#180](https://github.com/socialcopsdev/camelot/pull/180) by [rbares](https://github.com/rbares).
+    * An encrypted PDF can now be decrypted by passing `password='<PASSWORD>'` to `read_pdf` or `--password <PASSWORD>` to the command-line interface. (Limited encryption algorithm support from PyPDF2.)
+* [#139](https://github.com/socialcopsdev/camelot/issues/139) Add suppress_warnings keyword argument. [#155](https://github.com/socialcopsdev/camelot/pull/155) by [Jonathan Lloyd](https://github.com/jonathanlloyd).
+    * Warnings raised by Camelot can now be suppressed by passing `suppress_warnings=True` to `read_pdf` or `--quiet` to the command-line interface.
+* [#154](https://github.com/socialcopsdev/camelot/issues/154) The CLI can now be run using `python -m`. Try `python -m camelot --help`. [#159](https://github.com/socialcopsdev/camelot/pull/159) by [Parth P Panchal](https://github.com/pqrth).
+* [#165](https://github.com/socialcopsdev/camelot/issues/165) Rename `table_area` to `table_areas`. [#171](https://github.com/socialcopsdev/camelot/pull/171) by [Parth P Panchal](https://github.com/pqrth).
+
+**Bugfixes**
+
+* Raise error if the ghostscript executable is not on the PATH variable. [#166](https://github.com/socialcopsdev/camelot/pull/166) by Vinayak Mehta.
+* Convert filename to lowercase to check for PDF extension. [#169](https://github.com/socialcopsdev/camelot/pull/169) by [Vinicius Mesel](https://github.com/vmesel).
+
+**Files**
+
+* [#114](https://github.com/socialcopsdev/camelot/issues/114) Add Makefile and make codecov run only once. [#132](https://github.com/socialcopsdev/camelot/pull/132) by [Vaibhav Mule](https://github.com/vaibhavmule).
+* Add .editorconfig. [#151](https://github.com/socialcopsdev/camelot/pull/151) by [KOLANICH](https://github.com/KOLANICH).
+* Downgrade numpy version from 1.15.2 to 1.13.3.
+* Add requirements.txt for readthedocs.
+
+**Documentation**
+
+* Add "Using conda" section to installation instructions.
+* Add readthedocs badge.
+
+0.2.3 (2018-10-08)
+------------------
+
+* Remove hard dependencies on requirements versions.
+
+0.2.2 (2018-10-08)
+------------------
+
+**Bugfixes**
+
+* Move opencv-python to extra\_requires. [#134](https://github.com/socialcopsdev/camelot/pull/134) by Vinayak Mehta.
+
+0.2.1 (2018-10-05)
+------------------
+
+**Bugfixes**
+
+* [#121](https://github.com/socialcopsdev/camelot/issues/121) Fix ghostscript subprocess call for Windows. [#124](https://github.com/socialcopsdev/camelot/pull/124) by Vinayak Mehta.
+
+**Improvements**
+
+* [#123](https://github.com/socialcopsdev/camelot/issues/123) Make PEP8 compatible. [#125](https://github.com/socialcopsdev/camelot/pull/125) by [Oshawk](https://github.com/Oshawk).
+* [#110](https://github.com/socialcopsdev/camelot/issues/110) Add more tests. Coverage is now at 84%!
+    * Add tests for `__repr__`. [#128](https://github.com/socialcopsdev/camelot/pull/128) by [Vaibhav Mule](https://github.com/vaibhavmule).
+    * Add tests for CLI. [#122](https://github.com/socialcopsdev/camelot/pull/122) by [Vaibhav Mule](https://github.com/vaibhavmule) and [#117](https://github.com/socialcopsdev/camelot/pull/117) by Vinayak Mehta.
+    * Add tests for errors/warnings. [#113](https://github.com/socialcopsdev/camelot/pull/113) by Vinayak Mehta.
+    * Add tests for output formats and parser kwargs. [#126](https://github.com/socialcopsdev/camelot/pull/126) by Vinayak Mehta.
+* Add Python 3.5 and 3.7 support. [#119](https://github.com/socialcopsdev/camelot/pull/119) by Vinayak Mehta.
+* Add logging and warnings.
+
+**Documentation**
+
+* Copyedit all documentation. [#112](https://github.com/socialcopsdev/camelot/pull/112) by [Christine Garcia](https://github.com/christinegarcia).
+* [#115](https://github.com/socialcopsdev/camelot/issues/115) Update issue labels in contributor's guide. [#116](https://github.com/socialcopsdev/camelot/pull/116) by [Johnny Metz](https://github.com/johnnymetz).
+* Update installation instructions for Windows. [#124](https://github.com/socialcopsdev/camelot/pull/124) by Vinayak Mehta.
+
+**Note**: This release also bumps the version for numpy from 1.13.3 to 1.15.2 and adds a MANIFEST.in. Also, openpyxl==2.5.8 is a new requirement and pytest-cov==2.6.0 is a new dev requirement.
+
+0.2.0 (2018-09-28)
+------------------
+
+**Improvements**
+
+* [#81](https://github.com/socialcopsdev/camelot/issues/81) Add Python 3.6 support. [#109](https://github.com/socialcopsdev/camelot/pull/109) by Vinayak Mehta.
+
+0.1.2 (2018-09-25)
+------------------
+
+**Improvements**
+
+* [#85](https://github.com/socialcopsdev/camelot/issues/85) Add Travis and Codecov.
+
+0.1.1 (2018-09-24)
+------------------
+
+**Documentation**
+
+* Add documentation fixes.
+
+0.1.0 (2018-09-24)
+------------------
+
+* Rebirth!

MANIFEST.in

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

Makefile

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

README.md

@@ -4,14 +4,17 @@
 
 # Camelot: PDF Table Extraction for Humans
 
-[![Build Status](https://travis-ci.org/socialcopsdev/camelot.svg?branch=master)](https://travis-ci.org/socialcopsdev/camelot) [![codecov.io](https://codecov.io/github/socialcopsdev/camelot/badge.svg?branch=master&service=github)](https://codecov.io/github/socialcopsdev/camelot?branch=master)
+[![Build Status](https://travis-ci.org/socialcopsdev/camelot.svg?branch=master)](https://travis-ci.org/socialcopsdev/camelot) [![Documentation Status](https://readthedocs.org/projects/camelot-py/badge/?version=master)](https://camelot-py.readthedocs.io/en/master/)
- [![image](https://img.shields.io/pypi/v/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![image](https://img.shields.io/pypi/l/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![image](https://img.shields.io/pypi/pyversions/camelot-py.svg)](https://pypi.org/project/camelot-py/)
+ [![codecov.io](https://codecov.io/github/socialcopsdev/camelot/badge.svg?branch=master&service=github)](https://codecov.io/github/socialcopsdev/camelot?branch=master)
+ [![image](https://img.shields.io/pypi/v/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![image](https://img.shields.io/pypi/l/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![image](https://img.shields.io/pypi/pyversions/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![Gitter chat](https://badges.gitter.im/camelot-dev/Lobby.png)](https://gitter.im/camelot-dev/Lobby)
 
-**Camelot** is a Python library which makes it easy for *anyone* to extract tables from PDF files!
+**Camelot** is a Python library that makes it easy for *anyone* to extract tables from PDF files!
+
+**Note:** You can also check out [Excalibur](https://github.com/camelot-dev/excalibur), which is a web interface for Camelot!
 
 ---
 
-**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).
+**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).
 
 <pre>
 >>> import camelot
@@ -41,30 +44,40 @@
 | 2032_2     | 0.17      | 57.8          | 21.7%                | 0.3%            | 2.7%            | 1.2%           |
 | 4171_1     | 0.07      | 173.9         | 58.1%                | 1.6%            | 2.1%            | 0.5%           |
 
-There's a [command-line interface](https://camelot-py.readthedocs.io/en/latest/user/cli.html) too!
+There's a [command-line interface](https://camelot-py.readthedocs.io/en/master/user/cli.html) too!
 
-**Note:** Camelot only works with text-based PDFs and not scanned documents. If you can click-and-drag to select text in your table in a PDF viewer, then your PDF is text-based.
+**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".)
 
 ## Why Camelot?
 
-- **You are in control**: Unlike other libraries and tools which either give a nice output or fail miserably (with no in-between), Camelot gives you the power to tweak table extraction. (Since everything in the real world, including PDF table extraction, is fuzzy.)
+- **You are in control.**: Unlike other libraries and tools which either give a nice output or fail miserably (with no in-between), Camelot gives you the power to tweak table extraction. (This is important since everything in the real world, including PDF table extraction, is fuzzy.)
-- **Metrics**: *Bad* tables can be discarded based on metrics like accuracy and whitespace, without ever having to manually look at each table.
+- *Bad* tables can be discarded based on **metrics** like accuracy and whitespace, without ever having to manually look at each table.
-- Each table is a **pandas DataFrame**, which enables seamless integration into [ETL and data analysis workflows](https://gist.github.com/vinayak-mehta/e5949f7c2410a0e12f25d3682dc9e873).
+- Each table is a **pandas DataFrame**, which seamlessly integrates into [ETL and data analysis workflows](https://gist.github.com/vinayak-mehta/e5949f7c2410a0e12f25d3682dc9e873).
-- **Export** to multiple formats, including json, excel and html.
+- **Export** to multiple formats, including JSON, Excel and HTML.
 
 See [comparison with other PDF table extraction libraries and tools](https://github.com/socialcopsdev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools).
 
 ## Installation
 
-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:
+### Using conda
+
+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.
 
 <pre>
-$ pip install camelot-py
+$ conda install -c conda-forge camelot-py
 </pre>
 
-### Alternatively
+### Using pip
 
-After [installing the dependencies](https://camelot-py.readthedocs.io/en/latest/user/install.html), clone the repo using:
+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:
+
+<pre>
+$ pip install camelot-py[cv]
+</pre>
+
+### From the source code
+
+After [installing the dependencies](https://camelot-py.readthedocs.io/en/master/user/install.html#using-pip), clone the repo using:
 
 <pre>
 $ git clone https://www.github.com/socialcopsdev/camelot
@@ -74,18 +87,16 @@ and install Camelot using pip:
 
 <pre>
 $ cd camelot
-$ pip install .
+$ pip install ".[cv]"
 </pre>
 
-**Note:** Use a [virtualenv](https://virtualenv.pypa.io/en/stable/) if you don't want to affect your global Python installation.
-
 ## Documentation
 
 Great documentation is available at [http://camelot-py.readthedocs.io/](http://camelot-py.readthedocs.io/).
 
 ## Development
 
-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.
 
 ### Source code
 
@@ -113,8 +124,8 @@ $ python setup.py test
 
 ## Versioning
 
-Camelot uses [Semantic Versioning](https://semver.org/). For the available versions, see the tags on this repository.
+Camelot uses [Semantic Versioning](https://semver.org/). For the available versions, see the tags on this repository. For the changelog, you can check out [HISTORY.md](https://github.com/socialcopsdev/camelot/blob/master/HISTORY.md).
 
 ## License
 
-This project is licensed under the MIT License, see the [LICENSE](https://github.com/socialcopsdev/camelot/blob/master/LICENSE) file for details.
+This project is licensed under the MIT License, see the [LICENSE](https://github.com/socialcopsdev/camelot/blob/master/LICENSE) file for details.

camelot/__init__.py

@@ -1,5 +1,31 @@
 # -*- coding: utf-8 -*-
 
-from .__version__ import __version__
+import logging
 
-from .io import read_pdf
+from click import HelpFormatter
+
+from .__version__ import __version__
+from .io import read_pdf
+from .plotting import PlotMethods
+
+
+def _write_usage(self, prog, args='', prefix='Usage: '):
+    return self._write_usage('camelot', args, prefix=prefix)
+
+
+# monkey patch click.HelpFormatter
+HelpFormatter._write_usage = HelpFormatter.write_usage
+HelpFormatter.write_usage = _write_usage
+
+# set up logging
+logger = logging.getLogger('camelot')
+
+format_string = '%(asctime)s - %(levelname)s - %(message)s'
+formatter = logging.Formatter(format_string, datefmt='%Y-%m-%dT%H:%M:%S')
+handler = logging.StreamHandler()
+handler.setFormatter(formatter)
+
+logger.addHandler(handler)
+
+# instantiate plot method
+plot = PlotMethods()

camelot/__main__.py

@@ -0,0 +1,16 @@
+# -*- coding: utf-8 -*-
+
+from __future__ import absolute_import
+
+
+__all__ = ('main',)
+
+
+def main():
+    from camelot.cli import cli
+
+    cli()
+
+
+if __name__ == "__main__":
+    main()

camelot/__version__.py

@@ -1,11 +1,23 @@
 # -*- coding: utf-8 -*-
 
-VERSION = (0, 2, 0)
+VERSION = (0, 6, 0)
+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'
+__license__ = 'MIT License'

camelot/cli.py

@@ -1,15 +1,24 @@
 # -*- coding: utf-8 -*-
 
-from pprint import pprint
+import logging
 
 import click
+try:
+    import matplotlib.pyplot as plt
+except ImportError:
+    _HAS_MPL = False
+else:
+    _HAS_MPL = True
 
-from . import __version__
+from . import __version__, read_pdf, plot
-from .io import read_pdf
+
+
+logger = logging.getLogger('camelot')
+logger.setLevel(logging.INFO)
 
 
 class Config(object):
-    def  __init__(self):
+    def __init__(self):
         self.config = {}
 
     def set_config(self, key, value):
@@ -21,8 +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.')
 @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']),
@@ -32,18 +43,20 @@ pass_config = click.make_pass_decorator(Config)
               help='Split text that spans across multiple cells.')
 @click.option('-flag', '--flag_size', is_flag=True, help='Flag text based on'
               ' font size. Useful to detect super/subscripts.')
+@click.option('-strip', '--strip_text', help='Characters that should be stripped from a string before'
+              ' assigning it to a cell.')
 @click.option('-M', '--margins', nargs=3, default=(1.0, 0.5, 0.1),
               help='PDFMiner char_margin, line_margin and word_margin.')
 @click.pass_context
 def cli(ctx, *args, **kwargs):
     """Camelot: PDF Table Extraction for Humans"""
     ctx.obj = Config()
-    for key, value in kwargs.iteritems():
+    for key, value in kwargs.items():
         ctx.obj.set_config(key, value)
 
 
 @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,
@@ -57,10 +70,10 @@ def cli(ctx, *args, **kwargs):
 @click.option('-shift', '--shift_text', default=['l', 't'],
               type=click.Choice(['', 'l', 'r', 't', 'b']), multiple=True,
               help='Direction in which text in a spanning cell will flow.')
-@click.option('-l', '--line_close_tol', default=2,
+@click.option('-l', '--line_tol', default=2,
               help='Tolerance parameter used to merge close vertical'
               ' and horizontal lines.')
-@click.option('-j', '--joint_close_tol', default=2,
+@click.option('-j', '--joint_tol', default=2,
               help='Tolerance parameter used to decide whether'
               ' the detected lines and points lie close to each other.')
 @click.option('-block', '--threshold_blocksize', default=15,
@@ -73,9 +86,11 @@ def cli(ctx, *args, **kwargs):
               ' may be zero or negative as well.')
 @click.option('-I', '--iterations', default=0,
               help='Number of times for erosion/dilation will be applied.')
+@click.option('-res', '--resolution', default=300,
+              help='Resolution used for PDF to PNG conversion.')
 @click.option('-plot', '--plot_type',
-              type=click.Choice(['text', 'table', 'contour', 'joint', 'line']),
+              type=click.Choice(['text', 'grid', 'contour', 'joint', 'line']),
-              help='Plot geometry found on PDF page, for debugging.')
+              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):
@@ -85,42 +100,52 @@ 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'])
+    table_areas = list(kwargs['table_areas'])
-    kwargs['table_area'] = None if not table_area else table_area
+    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:
+        if not _HAS_MPL:
-            table.plot(plot_type)
+            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,
               help='X coordinates of column separators.')
-@click.option('-r', '--row_close_tol', default=2, help='Tolerance parameter'
+@click.option('-e', '--edge_tol', default=50, help='Tolerance parameter'
+              ' for extending textedges vertically.')
+@click.option('-r', '--row_tol', default=2, help='Tolerance parameter'
               ' used to combine text vertically, to generate rows.')
-@click.option('-c', '--col_close_tol', default=0, help='Tolerance parameter'
+@click.option('-c', '--column_tol', default=0, help='Tolerance parameter'
               ' used to combine text horizontally, to generate columns.')
 @click.option('-plot', '--plot_type',
-              type=click.Choice(['text', 'table']),
+              type=click.Choice(['text', 'grid', 'contour', 'textedge']),
-              help='Plot geometry found on PDF page for debugging.')
+              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):
@@ -130,23 +155,31 @@ 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'])
+    table_areas = list(kwargs['table_areas'])
-    kwargs['table_area'] = None if not table_area else table_area
+    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:
+        if not _HAS_MPL:
-            table.plot(plot_type)
+            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.export(output, f=f, compress=compress)
+
+    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)

camelot/core.py

@@ -1,14 +1,210 @@
 # -*- coding: utf-8 -*-
 
 import os
-import json
 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
+# 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, edge_tol=50):
+        """Updates the text edge's x and bottom y coordinates and sets
+        the is_valid attribute.
+        """
+        if np.isclose(self.y0, y0, atol=edge_tol):
+            self.x = (self.intersections * self.x + x) / float(self.intersections + 1)
+            self.y0 = y0
+            self.intersections += 1
+            # a textedge is valid only if it extends uninterrupted
+            # over a required number of textlines
+            if self.intersections > TEXTEDGE_REQUIRED_ELEMENTS:
+                self.is_valid = True
+
+
+class TextEdges(object):
+    """Defines a dict of left, right and middle text edges found on
+    the PDF page. The dict has three keys based on the alignments,
+    and each key's value is a list of camelot.core.TextEdge objects.
+    """
+    def __init__(self, edge_tol=50):
+        self.edge_tol = edge_tol
+        self._textedges = {'left': [], 'right': [], 'middle': []}
+
+    @staticmethod
+    def get_x_coord(textline, align):
+        """Returns the x coordinate of a text row based on the
+        specified alignment.
+        """
+        x_left = textline.x0
+        x_right = textline.x1
+        x_middle = x_left + (x_right - x_left) / 2.0
+        x_coord = {'left': x_left, 'middle': x_middle, 'right': x_right}
+        return x_coord[align]
+
+    def find(self, x_coord, align):
+        """Returns the index of an existing text edge using
+        the specified x coordinate and alignment.
+        """
+        for i, te in enumerate(self._textedges[align]):
+            if np.isclose(te.x, x_coord, atol=0.5):
+                return i
+        return None
+
+    def add(self, textline, align):
+        """Adds a new text edge to the current dict.
+        """
+        x = self.get_x_coord(textline, align)
+        y0 = textline.y0
+        y1 = textline.y1
+        te = TextEdge(x, y0, y1, align=align)
+        self._textedges[align].append(te)
+
+    def update(self, textline):
+        """Updates an existing text edge in the current dict.
+        """
+        for align in ['left', 'right', 'middle']:
+            x_coord = self.get_x_coord(textline, align)
+            idx = self.find(x_coord, align)
+            if idx is None:
+                self.add(textline, align)
+            else:
+                self._textedges[align][idx].update_coords(
+                    x_coord, textline.y0, edge_tol=self.edge_tol)
+
+    def generate(self, textlines):
+        """Generates the text edges dict based on horizontal text
+        rows.
+        """
+        for tl in textlines:
+            if len(tl.get_text().strip()) > 1: # TODO: hacky
+                self.update(tl)
+
+    def get_relevant(self):
+        """Returns the list of relevant text edges (all share the same
+        alignment) based on which list intersects horizontal text rows
+        the most.
+        """
+        intersections_sum = {
+            'left': sum(te.intersections for te in self._textedges['left'] if te.is_valid),
+            'right': sum(te.intersections for te in self._textedges['right'] if te.is_valid),
+            'middle': sum(te.intersections for te in self._textedges['middle'] if te.is_valid)
+        }
+
+        # TODO: naive
+        # get vertical textedges that intersect maximum number of
+        # times with horizontal textlines
+        relevant_align = max(intersections_sum.items(), key=itemgetter(1))[0]
+        return self._textedges[relevant_align]
+
+    def get_table_areas(self, textlines, relevant_textedges):
+        """Returns a dict of interesting table areas on the PDF page
+        calculated using relevant text edges.
+        """
+        def pad(area, average_row_height):
+            x0 = area[0] - TABLE_AREA_PADDING
+            y0 = area[1] - TABLE_AREA_PADDING
+            x1 = area[2] + TABLE_AREA_PADDING
+            # add a constant since table headers can be relatively up
+            y1 = area[3] + average_row_height * 5
+            return (x0, y0, x1, y1)
+
+        # sort relevant textedges in reading order
+        relevant_textedges.sort(key=lambda te: (-te.y0, te.x))
+
+        table_areas = {}
+        for te in relevant_textedges:
+            if te.is_valid:
+                if not table_areas:
+                    table_areas[(te.x, te.y0, te.x, te.y1)] = None
+                else:
+                    found = None
+                    for area in table_areas:
+                        # check for overlap
+                        if te.y1 >= area[1] and te.y0 <= area[3]:
+                            found = area
+                            break
+                    if found is None:
+                        table_areas[(te.x, te.y0, te.x, te.y1)] = None
+                    else:
+                        table_areas.pop(found)
+                        updated_area = (
+                            found[0], min(te.y0, found[1]), max(found[2], te.x), max(found[3], te.y1))
+                        table_areas[updated_area] = None
+
+        # extend table areas based on textlines that overlap
+        # vertically. it's possible that these textlines were
+        # eliminated during textedges generation since numbers and
+        # chars/words/sentences are often aligned differently.
+        # drawback: table areas that have paragraphs on their sides
+        # will include the paragraphs too.
+        sum_textline_height = 0
+        for tl in textlines:
+            sum_textline_height += tl.y1 - tl.y0
+            found = None
+            for area in table_areas:
+                # check for overlap
+                if tl.y0 >= area[1] and tl.y1 <= area[3]:
+                    found = area
+                    break
+            if found is not None:
+                table_areas.pop(found)
+                updated_area = (
+                    min(tl.x0, found[0]), min(tl.y0, found[1]), max(found[2], tl.x1), max(found[3], tl.y1))
+                table_areas[updated_area] = None
+        average_textline_height = sum_textline_height / float(len(textlines))
+
+        # add some padding to table areas
+        table_areas_padded = {}
+        for area in table_areas:
+            table_areas_padded[pad(area, average_textline_height)] = None
+
+        return table_areas_padded
 
 
 class Cell(object):
@@ -72,7 +268,7 @@ class Cell(object):
 
     def __repr__(self):
         return '<Cell x1={} y1={} x2={} y2={}>'.format(
-            self.x1, self.y1, self.x2, self.y2)
+            round(self.x1, 2), round(self.y1, 2), round(self.x2, 2), round(self.y2, 2))
 
     @property
     def text(self):
@@ -163,7 +359,7 @@ class Table(object):
                 cell.left = cell.right = cell.top = cell.bottom = True
         return self
 
-    def set_edges(self, vertical, horizontal, joint_close_tol=2):
+    def set_edges(self, vertical, horizontal, joint_tol=2):
         """Sets a cell's edges to True depending on whether the cell's
         coordinates overlap with the line's coordinates within a
         tolerance.
@@ -180,11 +376,11 @@ class Table(object):
             # find closest x coord
             # iterate over y coords and find closest start and end points
             i = [i for i, t in enumerate(self.cols)
-                 if np.isclose(v[0], t[0], atol=joint_close_tol)]
+                 if np.isclose(v[0], t[0], atol=joint_tol)]
             j = [j for j, t in enumerate(self.rows)
-                 if np.isclose(v[3], t[0], atol=joint_close_tol)]
+                 if np.isclose(v[3], t[0], atol=joint_tol)]
             k = [k for k, t in enumerate(self.rows)
-                 if np.isclose(v[1], t[0], atol=joint_close_tol)]
+                 if np.isclose(v[1], t[0], atol=joint_tol)]
             if not j:
                 continue
             J = j[0]
@@ -231,11 +427,11 @@ class Table(object):
             # find closest y coord
             # iterate over x coords and find closest start and end points
             i = [i for i, t in enumerate(self.rows)
-                 if np.isclose(h[1], t[0], atol=joint_close_tol)]
+                 if np.isclose(h[1], t[0], atol=joint_tol)]
             j = [j for j, t in enumerate(self.cols)
-                 if np.isclose(h[0], t[0], atol=joint_close_tol)]
+                 if np.isclose(h[0], t[0], atol=joint_tol)]
             k = [k for k, t in enumerate(self.cols)
-                 if np.isclose(h[2], t[0], atol=joint_close_tol)]
+                 if np.isclose(h[2], t[0], atol=joint_tol)]
             if not j:
                 continue
             J = j[0]
@@ -252,7 +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:
@@ -322,33 +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.
 
@@ -447,18 +616,6 @@ class TableList(object):
     def __getitem__(self, idx):
         return self._tables[idx]
 
-    def __iter__(self):
-        self._n = 0
-        return self
-
-    def next(self):
-        if self._n < len(self):
-            r = self._tables[self._n]
-            self._n += 1
-            return r
-        else:
-            raise StopIteration
-
     @staticmethod
     def _format_func(table, f):
         return getattr(table, 'to_{}'.format(f))
@@ -531,4 +688,4 @@ class TableList(object):
             if compress:
                 zipname = os.path.join(os.path.dirname(path), root) + '.zip'
                 with zipfile.ZipFile(zipname, 'w', allowZip64=True) as z:
-                    z.write(filepath, os.path.basename(filepath))
+                    z.write(filepath, os.path.basename(filepath))

camelot/handlers.py

@@ -1,13 +1,14 @@
 # -*- coding: utf-8 -*-
 
 import os
+import sys
 
 from PyPDF2 import PdfFileReader, PdfFileWriter
 
 from .core import TableList
 from .parsers import Stream, Lattice
 from .utils import (TemporaryDirectory, get_page_layout, get_text_objects,
-                    get_rotation)
+                    get_rotation, is_url, download_url)
 
 
 class PDFHandler(object):
@@ -17,26 +18,36 @@ class PDFHandler(object):
 
     Parameters
     ----------
-    filename : str
+    filepath : str
-        Path to PDF file.
+        Filepath or URL of the 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, filepath, pages='1', password=None):
-        self.filename = filename
+        if is_url(filepath):
-        if not self.filename.endswith('.pdf'):
+            filepath = download_url(filepath)
-            raise TypeError("File format not supported.")
+        self.filepath = filepath
-        self.pages = self._get_pages(self.filename, pages)
+        if not filepath.lower().endswith('.pdf'):
+            raise NotImplementedError("File format not supported")
+        self.pages = self._get_pages(self.filepath, 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):
+    def _get_pages(self, filepath, pages):
         """Converts pages string to list of ints.
 
         Parameters
         ----------
-        filename : str
+        filepath : str
-            Path to PDF file.
+            Filepath or URL of the PDF file.
         pages : str, optional (default: '1')
             Comma-separated page numbers.
             Example: 1,3,4 or 1,4-end.
@@ -51,7 +62,9 @@ class PDFHandler(object):
         if pages == '1':
             page_numbers.append({'start': 1, 'end': 1})
         else:
-            infile = PdfFileReader(open(filename, 'rb'), strict=False)
+            infile = PdfFileReader(open(filepath, 'rb'), strict=False)
+            if infile.isEncrypted:
+                infile.decrypt(self.password)
             if pages == 'all':
                 page_numbers.append({'start': 1, 'end': infile.getNumPages()})
             else:
@@ -68,23 +81,23 @@ class PDFHandler(object):
             P.extend(range(p['start'], p['end'] + 1))
         return sorted(set(P))
 
-    def _save_page(self, filename, page, temp):
+    def _save_page(self, filepath, page, temp):
         """Saves specified page from PDF into a temporary directory.
 
         Parameters
         ----------
-        filename : str
+        filepath : str
-            Path to PDF file.
+            Filepath or URL of the PDF file.
         page : int
             Page number.
         temp : str
             Tmp directory.
 
         """
-        with open(filename, 'rb') as fileobj:
+        with open(filepath, '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 +116,7 @@ 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 +127,7 @@ 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, layout_kwargs={}, **kwargs):
         """Extracts tables by calling parser.get_tables on all single
         page PDFs.
 
@@ -123,6 +136,10 @@ 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.
+        layout_kwargs : dict, optional (default: {})
+            A dict of `pdfminer.layout.LAParams <https://github.com/euske/pdfminer/blob/master/pdfminer/layout.py#L33>`_ kwargs.
         kwargs : dict
             See camelot.read_pdf kwargs.
 
@@ -130,19 +147,17 @@ 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 = []
         with TemporaryDirectory() as tempdir:
             for p in self.pages:
-                self._save_page(self.filename, p, tempdir)
+                self._save_page(self.filepath, p, tempdir)
             pages = [os.path.join(tempdir, 'page-{0}.pdf'.format(p))
                      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,
+                                          layout_kwargs=layout_kwargs)
                 tables.extend(t)
-        return TableList(tables)
+        return TableList(tables)

camelot/image_processing.py

@@ -1,14 +1,10 @@
 # -*- coding: utf-8 -*-
 
 from __future__ import division
-from itertools import groupby
-from operator import itemgetter
 
 import cv2
 import numpy as np
 
-from .utils import merge_tuples
-
 
 def adaptive_threshold(imagename, process_background=False, blocksize=15, c=-2):
     """Thresholds an image using OpenCV's adaptiveThreshold.
@@ -42,10 +38,12 @@ def adaptive_threshold(imagename, process_background=False, blocksize=15, c=-2):
     gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
 
     if process_background:
-        threshold = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
+        threshold = cv2.adaptiveThreshold(
+            gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
             cv2.THRESH_BINARY, blocksize, c)
     else:
-        threshold = cv2.adaptiveThreshold(np.invert(gray), 255,
+        threshold = cv2.adaptiveThreshold(
+            np.invert(gray), 255,
             cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, blocksize, c)
     return img, threshold
 
@@ -102,6 +100,7 @@ def find_lines(threshold, direction='horizontal', line_size_scaling=15, iteratio
         _, contours, _ = cv2.findContours(
             threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
     except ValueError:
+        # for opencv backward compatibility
         contours, _ = cv2.findContours(
             threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
 
@@ -141,6 +140,7 @@ def find_table_contours(vertical, horizontal):
         __, contours, __ = cv2.findContours(
             mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
     except ValueError:
+        # for opencv backward compatibility
         contours, __ = cv2.findContours(
             mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
     contours = sorted(contours, key=cv2.contourArea, reverse=True)[:10]
@@ -185,6 +185,7 @@ def find_table_joints(contours, vertical, horizontal):
             __, jc, __ = cv2.findContours(
                 roi, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
         except ValueError:
+            # for opencv backward compatibility
             jc, __ = cv2.findContours(
                 roi, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
         if len(jc) <= 4:  # remove contours with less than 4 joints
@@ -197,79 +198,3 @@ def find_table_joints(contours, vertical, horizontal):
         tables[(x, y + h, x + w, y)] = joint_coords
 
     return tables
-
-
-def remove_lines(threshold, line_size_scaling=15):
-    """Removes lines from a thresholded image.
-
-    Parameters
-    ----------
-    threshold : object
-        numpy.ndarray representing the thresholded image.
-    line_size_scaling : int, optional (default: 15)
-        Factor by which the page dimensions will be divided to get
-        smallest length of lines that should be detected.
-
-        The larger this value, smaller the detected lines. Making it
-        too large will lead to text being detected as lines.
-
-    Returns
-    -------
-    threshold : object
-        numpy.ndarray representing the thresholded image
-        with horizontal and vertical lines removed.
-
-    """
-    size = threshold.shape[0] // line_size_scaling
-    vertical_erode_el = cv2.getStructuringElement(cv2.MORPH_RECT, (1, size))
-    horizontal_erode_el = cv2.getStructuringElement(cv2.MORPH_RECT, (size, 1))
-    dilate_el = cv2.getStructuringElement(cv2.MORPH_RECT, (10, 10))
-
-    vertical = cv2.erode(threshold, vertical_erode_el)
-    vertical = cv2.dilate(vertical, dilate_el)
-
-    horizontal = cv2.erode(threshold, horizontal_erode_el)
-    horizontal = cv2.dilate(horizontal, dilate_el)
-
-    threshold = np.bitwise_and(threshold, np.invert(vertical))
-    threshold = np.bitwise_and(threshold, np.invert(horizontal))
-    return threshold
-
-
-def find_cuts(threshold, char_size_scaling=200):
-    """Finds cuts made by text projections on y-axis.
-
-    Parameters
-    ----------
-    threshold : object
-        numpy.ndarray representing the thresholded image.
-    line_size_scaling : int, optional (default: 200)
-        Factor by which the page dimensions will be divided to get
-        smallest length of lines that should be detected.
-
-        The larger this value, smaller the detected lines. Making it
-        too large will lead to text being detected as lines.
-
-    Returns
-    -------
-    y_cuts : list
-        List of cuts on y-axis.
-    """
-    size = threshold.shape[0] // char_size_scaling
-    char_el = cv2.getStructuringElement(cv2.MORPH_RECT, (1, size))
-
-    threshold = cv2.erode(threshold, char_el)
-    threshold = cv2.dilate(threshold, char_el)
-
-    try:
-        __, contours, __ = cv2.findContours(threshold, cv2.RETR_EXTERNAL,
-            cv2.CHAIN_APPROX_SIMPLE)
-    except ValueError:
-        contours, __ = cv2.findContours(threshold, cv2.RETR_EXTERNAL,
-            cv2.CHAIN_APPROX_SIMPLE)
-
-    contours = [cv2.boundingRect(c) for c in contours]
-    y_cuts = [(c[1], c[1] + c[3]) for c in contours]
-    y_cuts = list(merge_tuples(sorted(y_cuts)))
-    y_cuts = [(y_cuts[i][0] + y_cuts[i - 1][1]) // 2 for i in range(1, len(y_cuts))]
-    return sorted(y_cuts, reverse=True)

camelot/io.py

@@ -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, layout_kwargs={}, **kwargs):
     """Read PDF and return extracted tables.
 
     Note: kwargs annotated with ^ can only be used with flavor='stream'
@@ -13,14 +15,20 @@ def read_pdf(filepath, pages='1', flavor='lattice', **kwargs):
     Parameters
     ----------
     filepath : str
-        Path to PDF file.
+        Filepath or URL of the 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.
+    layout_kwargs : dict, optional (default: {})
+        A dict of `pdfminer.layout.LAParams <https://github.com/euske/pdfminer/blob/master/pdfminer/layout.py#L33>`_ kwargs.
+    table_areas : list, optional (default: None)
         List of table area strings of the form x1,y1,x2,y2
         where (x1, y1) -> left-top and (x2, y2) -> right-bottom
         in PDF coordinate space.
@@ -32,10 +40,13 @@ def read_pdf(filepath, pages='1', flavor='lattice', **kwargs):
     flag_size : bool, optional (default: False)
         Flag text based on font size. Useful to detect
         super/subscripts. Adds <s></s> around flagged text.
-    row_close_tol^ : int, optional (default: 2)
+    strip_text : str, optional (default: '')
+        Characters that should be stripped from a string before
+        assigning it to a cell.
+    row_tol^ : int, optional (default: 2)
         Tolerance parameter used to combine text vertically,
         to generate rows.
-    col_close_tol^ : int, optional (default: 0)
+    column_tol^ : int, optional (default: 0)
         Tolerance parameter used to combine text horizontally,
         to generate columns.
     process_background* : bool, optional (default: False)
@@ -51,10 +62,10 @@ def read_pdf(filepath, pages='1', flavor='lattice', **kwargs):
     shift_text* : list, optional (default: ['l', 't'])
         {'l', 'r', 't', 'b'}
         Direction in which text in a spanning cell will flow.
-    line_close_tol* : int, optional (default: 2)
+    line_tol* : int, optional (default: 2)
         Tolerance parameter used to merge close vertical and horizontal
         lines.
-    joint_close_tol* : int, optional (default: 2)
+    joint_tol* : int, optional (default: 2)
         Tolerance parameter used to decide whether the detected lines
         and points lie close to each other.
     threshold_blocksize* : int, optional (default: 15)
@@ -71,10 +82,8 @@ def read_pdf(filepath, pages='1', flavor='lattice', **kwargs):
         Number of times for erosion/dilation is applied.
 
         For more information, refer `OpenCV's dilate <https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html#dilate>`_.
-    margins : tuple
+    resolution* : int, optional (default: 300)
-        PDFMiner char_margin, line_margin and word_margin.
+        Resolution used for PDF to PNG conversion.
-
-        For more information, refer `PDFMiner docs <https://euske.github.io/pdfminer/>`_.
 
     Returns
     -------
@@ -85,8 +94,13 @@ def read_pdf(filepath, pages='1', flavor='lattice', **kwargs):
         raise NotImplementedError("Unknown flavor specified."
                                   " Use either 'lattice' or 'stream'")
 
-    validate_input(kwargs, flavor=flavor)
+    with warnings.catch_warnings():
-    p = PDFHandler(filepath, pages)
+        if suppress_stdout:
-    kwargs = remove_extra(kwargs, flavor=flavor)
+            warnings.simplefilter("ignore")
-    tables = p.parse(flavor=flavor, **kwargs)
+
-    return tables
+        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,
+                         layout_kwargs=layout_kwargs, **kwargs)
+        return tables

camelot/parsers/__init__.py

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

camelot/parsers/base.py

@@ -8,14 +8,12 @@ from ..utils import get_page_layout, get_text_objects
 class BaseParser(object):
     """Defines a base parser.
     """
-    def _generate_layout(self, filename):
+    def _generate_layout(self, filename, layout_kwargs):
         self.filename = filename
+        self.layout_kwargs = layout_kwargs
         self.layout, self.dimensions = get_page_layout(
-            self.filename,
+            filename, **layout_kwargs)
-            char_margin=self.char_margin,
-            line_margin=self.line_margin,
-            word_margin=self.word_margin)
         self.horizontal_text = get_text_objects(self.layout, ltype="lh")
         self.vertical_text = get_text_objects(self.layout, ltype="lv")
         self.pdf_width, self.pdf_height = self.dimensions
-        self.rootname, __ = os.path.splitext(self.filename)
+        self.rootname, __ = os.path.splitext(self.filename)

camelot/parsers/lattice.py

@@ -4,6 +4,7 @@ from __future__ import division
 import os
 import copy
 import logging
+import warnings
 import subprocess
 
 import numpy as np
@@ -13,12 +14,12 @@ from .base import BaseParser
 from ..core import Table
 from ..utils import (scale_image, scale_pdf, segments_in_bbox, text_in_bbox,
                      merge_close_lines, get_table_index, compute_accuracy,
-                     compute_whitespace, setup_logging)
+                     compute_whitespace)
 from ..image_processing import (adaptive_threshold, find_lines,
                                 find_table_contours, find_table_joints)
 
 
-logger = setup_logging(__name__)
+logger = logging.getLogger('camelot')
 
 
 class Lattice(BaseParser):
@@ -27,7 +28,7 @@ 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.
@@ -49,10 +50,13 @@ class Lattice(BaseParser):
     flag_size : bool, optional (default: False)
         Flag text based on font size. Useful to detect
         super/subscripts. Adds <s></s> around flagged text.
-    line_close_tol : int, optional (default: 2)
+    strip_text : str, optional (default: '')
+        Characters that should be stripped from a string before
+        assigning it to a cell.
+    line_tol : int, optional (default: 2)
         Tolerance parameter used to merge close vertical and horizontal
         lines.
-    joint_close_tol : int, optional (default: 2)
+    joint_tol : int, optional (default: 2)
         Tolerance parameter used to decide whether the detected lines
         and points lie close to each other.
     threshold_blocksize : int, optional (default: 15)
@@ -69,30 +73,29 @@ class Lattice(BaseParser):
         Number of times for erosion/dilation is applied.
 
         For more information, refer `OpenCV's dilate <https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html#dilate>`_.
-    margins : tuple
+    resolution : int, optional (default: 300)
-        PDFMiner char_margin, line_margin and word_margin.
+        Resolution used for PDF to PNG conversion.
-
-        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,
+                 split_text=False, flag_size=False, strip_text='', line_tol=2,
-                 joint_close_tol=2, threshold_blocksize=15, threshold_constant=-2,
+                 joint_tol=2, threshold_blocksize=15, threshold_constant=-2,
-                 iterations=0, margins=(1.0, 0.5, 0.1), **kwargs):
+                 iterations=0, resolution=300, **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
         self.shift_text = shift_text
         self.split_text = split_text
         self.flag_size = flag_size
-        self.line_close_tol = line_close_tol
+        self.strip_text = strip_text
-        self.joint_close_tol = joint_close_tol
+        self.line_tol = line_tol
+        self.joint_tol = joint_tol
         self.threshold_blocksize = threshold_blocksize
         self.threshold_constant = threshold_constant
         self.iterations = iterations
-        self.char_margin, self.line_margin, self.word_margin = margins
+        self.resolution = resolution
 
     @staticmethod
     def _reduce_index(t, idx, shift_text):
@@ -173,15 +176,54 @@ class Lattice(BaseParser):
         return t
 
     def _generate_image(self):
+        # TODO: get rid of ghostscript #96
+        def get_executable():
+            import platform
+            from distutils.spawn import find_executable
+
+            class GhostscriptNotFound(Exception): pass
+
+            gs = None
+            system = platform.system().lower()
+            try:
+                if system == 'windows':
+                    if find_executable('gswin32c.exe'):
+                        gs = 'gswin32c.exe'
+                    elif find_executable('gswin64c.exe'):
+                        gs = 'gswin64c.exe'
+                    else:
+                        raise ValueError
+                else:
+                    if find_executable('gs'):
+                        gs = 'gs'
+                    elif find_executable('gsc'):
+                        gs = 'gsc'
+                    else:
+                        raise ValueError
+                if 'ghostscript' not in subprocess.check_output(
+                        [gs, '-version']).decode('utf-8').lower():
+                    raise ValueError
+            except ValueError:
+                raise GhostscriptNotFound(
+                    'Please make sure that Ghostscript is installed'
+                    ' and available on the PATH environment variable')
+
+            return gs
+
         self.imagename = ''.join([self.rootname, '.png'])
         gs_call = [
-            "-q", "-sDEVICE=png16m", "-o", self.imagename, "-r600", self.filename
+            '-q',
+            '-sDEVICE=png16m',
+            '-o',
+            self.imagename,
+            '-r{}'.format(self.resolution),
+            self.filename
         ]
-        if "ghostscript" in subprocess.check_output(["gs", "-version"]).decode('utf-8').lower():
+        gs = get_executable()
-            gs_call.insert(0, "gs")
+        gs_call.insert(0, gs)
-        else:
+
-            gs_call.insert(0, "gsc")
+        subprocess.call(
-        subprocess.call(gs_call, stdout=open(os.devnull, 'w'),
+            gs_call, stdout=open(os.devnull, 'w'),
             stderr=subprocess.STDOUT)
 
     def _generate_table_bbox(self):
@@ -204,9 +246,9 @@ 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)
@@ -231,10 +273,11 @@ 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['horizontal'].sort(key=lambda x: (-x.y0, x.x0))
-            t_bbox[direction].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)
@@ -242,9 +285,9 @@ class Lattice(BaseParser):
         rows.extend([tk[1], tk[3]])
         # sort horizontal and vertical segments
         cols = merge_close_lines(
-            sorted(cols), line_close_tol=self.line_close_tol)
+            sorted(cols), line_tol=self.line_tol)
         rows = merge_close_lines(
-            sorted(rows, reverse=True), line_close_tol=self.line_close_tol)
+            sorted(rows, reverse=True), line_tol=self.line_tol)
         # make grid using x and y coord of shortlisted rows and cols
         cols = [(cols[i], cols[i + 1])
                 for i in range(0, len(cols) - 1)]
@@ -261,18 +304,20 @@ class Lattice(BaseParser):
 
         table = Table(cols, rows)
         # set table edges to True using ver+hor lines
-        table = table.set_edges(v_s, h_s, joint_close_tol=self.joint_close_tol)
+        table = table.set_edges(v_s, h_s, joint_tol=self.joint_tol)
         # set table border edges to True
         table = table.set_border()
         # set spanning cells to True
         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,
-                    flag_size=self.flag_size)
+                    flag_size=self.flag_size, strip_text=self.strip_text)
                 if indices[:2] != (-1, -1):
                     pos_errors.append(error)
                     indices = Lattice._reduce_index(table, indices, shift_text=self.shift_text)
@@ -301,15 +346,17 @@ 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, layout_kwargs={}):
-        logger.info('Processing {}'.format(os.path.basename(filename)))
+        self._generate_layout(filename, layout_kwargs)
-        self._generate_layout(filename)
+        if not suppress_stdout:
+            logger.info('Processing {}'.format(os.path.basename(self.rootname)))
 
         if not self.horizontal_text:
-            logger.info("No tables found on {}".format(
+            warnings.warn("No tables found on {}".format(
                 os.path.basename(self.rootname)))
             return []
 
@@ -318,10 +365,11 @@ class Lattice(BaseParser):
 
         _tables = []
         # sort tables based on y-coord
-        for table_idx, tk in enumerate(sorted(self.table_bbox.keys(),
+        for table_idx, tk in enumerate(sorted(
-                key=lambda x: x[1], reverse=True)):
+                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
+        return _tables

camelot/parsers/stream.py

@@ -3,17 +3,18 @@
 from __future__ import division
 import os
 import logging
+import warnings
 
 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, setup_logging)
+                     compute_whitespace)
 
 
-logger = setup_logging(__name__)
+logger = logging.getLogger('camelot')
 
 
 class Stream(BaseParser):
@@ -25,7 +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.
@@ -37,29 +38,31 @@ class Stream(BaseParser):
     flag_size : bool, optional (default: False)
         Flag text based on font size. Useful to detect
         super/subscripts. Adds <s></s> around flagged text.
-    row_close_tol : int, optional (default: 2)
+    strip_text : str, optional (default: '')
+        Characters that should be stripped from a string before
+        assigning it to a cell.
+    edge_tol : int, optional (default: 50)
+        Tolerance parameter for extending textedges vertically.
+    row_tol : int, optional (default: 2)
         Tolerance parameter used to combine text vertically,
         to generate rows.
-    col_close_tol : int, optional (default: 0)
+    column_tol : int, optional (default: 0)
         Tolerance parameter used to combine text horizontally,
         to generate columns.
-    margins : tuple, optional (default: (1.0, 0.5, 0.1))
-        PDFMiner char_margin, line_margin and word_margin.
-
-        For more information, refer `PDFMiner docs <https://euske.github.io/pdfminer/>`_.
 
     """
-    def __init__(self, table_area=None, columns=None, split_text=False,
+    def __init__(self, table_areas=None, columns=None, split_text=False,
-                 flag_size=False, row_close_tol=2, col_close_tol=0,
+                 flag_size=False, strip_text='', edge_tol=50, row_tol=2,
-                 margins=(1.0, 0.5, 0.1), **kwargs):
+                 column_tol=0, **kwargs):
-        self.table_area = table_area
+        self.table_areas = table_areas
         self.columns = columns
         self._validate_columns()
         self.split_text = split_text
         self.flag_size = flag_size
-        self.row_close_tol = row_close_tol
+        self.strip_text = strip_text
-        self.col_close_tol = col_close_tol
+        self.edge_tol = edge_tol
-        self.char_margin, self.line_margin, self.word_margin = margins
+        self.row_tol = row_tol
+        self.column_tol = column_tol
 
     @staticmethod
     def _text_bbox(t_bbox):
@@ -85,7 +88,7 @@ class Stream(BaseParser):
         return text_bbox
 
     @staticmethod
-    def _group_rows(text, row_close_tol=2):
+    def _group_rows(text, row_tol=2):
         """Groups PDFMiner text objects into rows vertically
         within a tolerance.
 
@@ -93,7 +96,7 @@ class Stream(BaseParser):
         ----------
         text : list
             List of PDFMiner text objects.
-        row_close_tol : int, optional (default: 2)
+        row_tol : int, optional (default: 2)
 
         Returns
         -------
@@ -109,17 +112,17 @@ class Stream(BaseParser):
             # if t.get_text().strip() and all([obj.upright for obj in t._objs if
             # type(obj) is LTChar]):
             if t.get_text().strip():
-                if not np.isclose(row_y, t.y0, atol=row_close_tol):
+                if not np.isclose(row_y, t.y0, atol=row_tol):
                     rows.append(sorted(temp, key=lambda t: t.x0))
                     temp = []
                     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
-    def _merge_columns(l, col_close_tol=0):
+    def _merge_columns(l, column_tol=0):
         """Merges column boundaries horizontally if they overlap
         or lie within a tolerance.
 
@@ -127,7 +130,7 @@ class Stream(BaseParser):
         ----------
         l : list
             List of column x-coordinate tuples.
-        col_close_tol : int, optional (default: 0)
+        column_tol : int, optional (default: 0)
 
         Returns
         -------
@@ -141,17 +144,17 @@ class Stream(BaseParser):
                 merged.append(higher)
             else:
                 lower = merged[-1]
-                if col_close_tol >= 0:
+                if column_tol >= 0:
                     if (higher[0] <= lower[1] or
-                            np.isclose(higher[0], lower[1], atol=col_close_tol)):
+                            np.isclose(higher[0], lower[1], atol=column_tol)):
                         upper_bound = max(lower[1], higher[1])
                         lower_bound = min(lower[0], higher[0])
                         merged[-1] = (lower_bound, upper_bound)
                     else:
                         merged.append(higher)
-                elif col_close_tol < 0:
+                elif column_tol < 0:
                     if higher[0] <= lower[1]:
-                        if np.isclose(higher[0], lower[1], atol=abs(col_close_tol)):
+                        if np.isclose(higher[0], lower[1], atol=abs(column_tol)):
                             merged.append(higher)
                         else:
                             upper_bound = max(lower[1], higher[1])
@@ -188,7 +191,7 @@ class Stream(BaseParser):
         return rows
 
     @staticmethod
-    def _add_columns(cols, text, row_close_tol):
+    def _add_columns(cols, text, row_tol):
         """Adds columns to existing list by taking into account
         the text that lies outside the current column x-coordinates.
 
@@ -207,10 +210,10 @@ class Stream(BaseParser):
 
         """
         if text:
-            text = Stream._group_rows(text, row_close_tol=row_close_tol)
+            text = Stream._group_rows(text, row_tol=row_tol)
             elements = [len(r) for r in text]
             new_cols = [(t.x0, t.x1)
-                for r in text if len(r) == max(elements) for t in r]
+                        for r in text if len(r) == max(elements) for t in r]
             cols.extend(Stream._merge_columns(sorted(new_cols)))
         return cols
 
@@ -240,15 +243,41 @@ class Stream(BaseParser):
         return cols
 
     def _validate_columns(self):
-        if self.table_area is not None and self.columns is not None:
+        if self.table_areas is not None and self.columns is not None:
-            if len(self.table_area) != len(self.columns):
+            if len(self.table_areas) != len(self.columns):
-                raise ValueError("Length of table_area and 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(edge_tol=self.edge_tol)
+        # generate left, middle and right textedges
+        textedges.generate(textlines)
+        # select relevant edges
+        relevant_textedges = textedges.get_relevant()
+        self.textedges.extend(relevant_textedges)
+        # guess table areas using textlines and relevant edges
+        table_bbox = textedges.get_table_areas(textlines, relevant_textedges)
+        # treat whole page as table area if no table areas found
+        if not len(table_bbox):
+            table_bbox = {(0, 0, self.pdf_width, self.pdf_height): None}
+
+        return table_bbox
+
     def _generate_table_bbox(self):
-        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)
@@ -256,7 +285,8 @@ 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):
@@ -264,13 +294,14 @@ 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)
+
+        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
 
-        for direction in self.t_bbox:
-            self.t_bbox[direction].sort(key=lambda x: (-x.y0, x.x0))
-
         text_x_min, text_y_min, text_x_max, text_y_max = self._text_bbox(self.t_bbox)
-        rows_grouped = self._group_rows(self.t_bbox['horizontal'], row_close_tol=self.row_close_tol)
+        rows_grouped = self._group_rows(self.t_bbox['horizontal'], row_tol=self.row_tol)
         rows = self._join_rows(rows_grouped, text_y_max, text_y_min)
         elements = [len(r) for r in rows_grouped]
 
@@ -285,12 +316,23 @@ 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:
-                logger.info("No tables found on {}".format(
+                # if mode is 1, the page usually contains not tables
-                    os.path.basename(self.rootname)))
+                # 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)
+            cols = self._merge_columns(sorted(cols), column_tol=self.column_tol)
             inner_text = []
             for i in range(1, len(cols)):
                 left = cols[i - 1][1]
@@ -302,7 +344,7 @@ class Stream(BaseParser):
                             for t in self.t_bbox[direction]
                             if t.x0 > cols[-1][1] or t.x1 < cols[0][0]]
             inner_text.extend(outer_text)
-            cols = self._add_columns(cols, inner_text, self.row_close_tol)
+            cols = self._add_columns(cols, inner_text, self.row_tol)
             cols = self._join_columns(cols, text_x_min, text_x_max)
 
         return cols, rows
@@ -310,12 +352,15 @@ 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,
-                    flag_size=self.flag_size)
+                    flag_size=self.flag_size, strip_text=self.strip_text)
                 if indices[:2] != (-1, -1):
                     pos_errors.append(error)
                     for r_idx, c_idx, text in indices:
@@ -340,15 +385,17 @@ 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, layout_kwargs={}):
-        logger.info('Processing {}'.format(os.path.basename(filename)))
+        self._generate_layout(filename, layout_kwargs)
-        self._generate_layout(filename)
+        if not suppress_stdout:
+            logger.info('Processing {}'.format(os.path.basename(self.rootname)))
 
         if not self.horizontal_text:
-            logger.info("No tables found on {}".format(
+            warnings.warn("No tables found on {}".format(
                 os.path.basename(self.rootname)))
             return []
 
@@ -356,10 +403,11 @@ class Stream(BaseParser):
 
         _tables = []
         # sort tables based on y-coord
-        for table_idx, tk in enumerate(sorted(self.table_bbox.keys(),
+        for table_idx, tk in enumerate(sorted(
-                key=lambda x: x[1], reverse=True)):
+                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
+        return _tables

camelot/plotting.py

@@ -1,108 +1,244 @@
-import cv2
+# -*- coding: utf-8 -*-
-import matplotlib.pyplot as plt
+
-import matplotlib.patches as patches
+try:
+    import matplotlib.pyplot as plt
+    import matplotlib.patches as patches
+except ImportError:
+    _HAS_MPL = False
+else:
+    _HAS_MPL = True
 
 
-def plot_text(text):
+class PlotMethods(object):
-    """Generates a plot for all text present on the PDF page.
+    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
+        Parameters
-    ----------
+        ----------
-    text : list
+        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.
 
-    """
+        Returns
-    fig = plt.figure()
+        -------
-    ax = fig.add_subplot(111, aspect='equal')
+        fig : matplotlib.fig.Figure
-    xs, ys = [], []
+
-    for t in text:
+        """
-        xs.extend([t[0], t[2]])
+        if not _HAS_MPL:
-        ys.extend([t[1], t[3]])
+            raise ImportError('matplotlib is required for plotting.')
-        ax.add_patch(
+
-            patches.Rectangle(
+        if table.flavor == 'lattice' and kind in ['textedge']:
-                (t[0], t[1]),
+            raise NotImplementedError("Lattice flavor does not support kind='{}'".format(
-                t[2] - t[0],
+                                      kind))
-                t[3] - t[1]
+        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_xlim(min(xs) - 10, max(xs) + 10)
+        ax.set_ylim(min(ys) - 10, max(ys) + 10)
-    ax.set_ylim(min(ys) - 10, max(ys) + 10)
+        return fig
-    plt.show()
 
+    def grid(self, table):
+        """Generates a plot for the detected table grids
+        on the PDF page.
 
-def plot_table(table):
+        Parameters
-    """Generates a plot for the table.
+        ----------
+        table : camelot.core.Table
 
-    Parameters
+        Returns
-    ----------
+        -------
-    table : camelot.core.Table
+        fig : matplotlib.fig.Figure
 
-    """
+        """
-    for row in table.cells:
+        fig = plt.figure()
-        for cell in row:
+        ax = fig.add_subplot(111, aspect='equal')
-            if cell.left:
+        for row in table.cells:
-                plt.plot([cell.lb[0], cell.lt[0]],
+            for cell in row:
+                if cell.left:
+                    ax.plot([cell.lb[0], cell.lt[0]],
                             [cell.lb[1], cell.lt[1]])
-            if cell.right:
+                if cell.right:
-                plt.plot([cell.rb[0], cell.rt[0]],
+                    ax.plot([cell.rb[0], cell.rt[0]],
                             [cell.rb[1], cell.rt[1]])
-            if cell.top:
+                if cell.top:
-                plt.plot([cell.lt[0], cell.rt[0]],
+                    ax.plot([cell.lt[0], cell.rt[0]],
                             [cell.lt[1], cell.rt[1]])
-            if cell.bottom:
+                if cell.bottom:
-                plt.plot([cell.lb[0], cell.rb[0]],
+                    ax.plot([cell.lb[0], cell.rb[0]],
                             [cell.lb[1], cell.rb[1]])
-    plt.show()
+        return fig
 
+    def contour(self, table):
+        """Generates a plot for all table boundaries present
+        on the PDF page.
 
-def plot_contour(image):
+        Parameters
-    """Generates a plot for all table boundaries present on the
+        ----------
-    PDF page.
+        table : camelot.core.Table
 
-    Parameters
+        Returns
-    ----------
+        -------
-    image : tuple
+        fig : matplotlib.fig.Figure
 
-    """
+        """
-    img, table_bbox = image
+        try:
-    for t in table_bbox.keys():
+            img, table_bbox = table._image
-        cv2.rectangle(img, (t[0], t[1]),
+            _FOR_LATTICE = True
-                      (t[2], t[3]), (255, 0, 0), 20)
+        except TypeError:
-    plt.imshow(img)
+            img, table_bbox = (None, {table._bbox: None})
-    plt.show()
+            _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):
+        for t in table_bbox.keys():
-    """Generates a plot for all line intersections present on the
+            ax.add_patch(
-    PDF page.
+                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
+        if _FOR_LATTICE:
-    ----------
+            ax.imshow(img)
-    image : tuple
+        return fig
 
-    """
+    def textedge(self, table):
-    img, table_bbox = image
+        """Generates a plot for relevant textedges.
-    x_coord = []
-    y_coord = []
-    for k in table_bbox.keys():
-        for coord in table_bbox[k]:
-            x_coord.append(coord[0])
-            y_coord.append(coord[1])
-    plt.plot(x_coord, y_coord, 'ro')
-    plt.imshow(img)
-    plt.show()
 
+        Parameters
+        ----------
+        table : camelot.core.Table
 
-def plot_line(segments):
+        Returns
-    """Generates a plot for all line segments present on the PDF page.
+        -------
+        fig : matplotlib.fig.Figure
 
-    Parameters
+        """
-    ----------
+        fig = plt.figure()
-    segments : tuple
+        ax = fig.add_subplot(111, aspect='equal')
+        xs, ys = [], []
+        for t in table._text:
+            xs.extend([t[0], t[2]])
+            ys.extend([t[1], t[3]])
+            ax.add_patch(
+                patches.Rectangle(
+                    (t[0], t[1]),
+                    t[2] - t[0],
+                    t[3] - t[1],
+                    color='blue'
+                )
+            )
+        ax.set_xlim(min(xs) - 10, max(xs) + 10)
+        ax.set_ylim(min(ys) - 10, max(ys) + 10)
 
-    """
+        for te in table._textedges:
-    vertical, horizontal = segments
+            ax.plot([te.x, te.x],
-    for v in vertical:
+                    [te.y0, te.y1])
-        plt.plot([v[0], v[2]], [v[1], v[3]])
+
-    for h in horizontal:
+        return fig
-        plt.plot([h[0], h[2]], [h[1], h[3]])
+
-    plt.show()
+    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

camelot/utils.py

@@ -1,44 +1,118 @@
+# -*- coding: utf-8 -*-
 from __future__ import division
+
 import os
+import sys
+import random
 import shutil
-import logging
+import string
 import tempfile
+import warnings
 from itertools import groupby
 from operator import itemgetter
 
 import numpy as np
-
 from pdfminer.pdfparser import PDFParser
 from pdfminer.pdfdocument import PDFDocument
 from pdfminer.pdfpage import PDFPage
 from pdfminer.pdfpage import PDFTextExtractionNotAllowed
 from pdfminer.pdfinterp import PDFResourceManager
 from pdfminer.pdfinterp import PDFPageInterpreter
-from pdfminer.pdfdevice import PDFDevice
 from pdfminer.converter import PDFPageAggregator
 from pdfminer.layout import (LAParams, LTAnno, LTChar, LTTextLineHorizontal,
                              LTTextLineVertical)
 
 
+PY3 = sys.version_info[0] >= 3
+if PY3:
+    from urllib.request import urlopen
+    from urllib.parse import urlparse as parse_url
+    from urllib.parse import uses_relative, uses_netloc, uses_params
+else:
+    from urllib2 import urlopen
+    from urlparse import urlparse as parse_url
+    from urlparse import uses_relative, uses_netloc, uses_params
+
+
+_VALID_URLS = set(uses_relative + uses_netloc + uses_params)
+_VALID_URLS.discard('')
+
+
+# https://github.com/pandas-dev/pandas/blob/master/pandas/io/common.py
+def is_url(url):
+    """Check to see if a URL has a valid protocol.
+
+    Parameters
+    ----------
+    url : str or unicode
+
+    Returns
+    -------
+    isurl : bool
+        If url has a valid protocol return True otherwise False.
+
+    """
+    try:
+        return parse_url(url).scheme in _VALID_URLS
+    except Exception:
+        return False
+
+
+def random_string(length):
+    ret = ''
+    while length:
+        ret += random.choice(string.digits + string.ascii_lowercase + string.ascii_uppercase)
+        length -= 1
+    return ret
+
+
+def download_url(url):
+    """Download file from specified URL.
+
+    Parameters
+    ----------
+    url : str or unicode
+
+    Returns
+    -------
+    filepath : str or unicode
+        Temporary filepath.
+
+    """
+    filename = '{}.pdf'.format(random_string(6))
+    with tempfile.NamedTemporaryFile('wb', delete=False) as f:
+        obj = urlopen(url)
+        if PY3:
+            content_type = obj.info().get_content_type()
+        else:
+            content_type = obj.info().getheader('Content-Type')
+        if content_type != 'application/pdf':
+            raise NotImplementedError("File format not supported")
+        f.write(obj.read())
+    filepath = os.path.join(os.path.dirname(f.name), filename)
+    shutil.move(f.name, filepath)
+    return filepath
+
+
 stream_kwargs = [
     'columns',
-    'row_close_tol',
+    'row_tol',
-    'col_close_tol'
+    'column_tol'
 ]
 lattice_kwargs = [
     'process_background',
     'line_size_scaling',
     'copy_text',
     'shift_text',
-    'line_close_tol',
+    'line_tol',
-    'joint_close_tol',
+    'joint_tol',
     'threshold_blocksize',
     'threshold_constant',
     'iterations'
 ]
 
 
-def validate_input(kwargs, flavor='lattice', geometry_type=False):
+def validate_input(kwargs, flavor='lattice'):
     def check_intersection(parser_kwargs, input_kwargs):
         isec = set(parser_kwargs).intersection(set(input_kwargs.keys()))
         if isec:
@@ -49,10 +123,6 @@ def validate_input(kwargs, flavor='lattice', geometry_type=False):
         check_intersection(stream_kwargs, kwargs)
     else:
         check_intersection(lattice_kwargs, kwargs)
-    if geometry_type:
-        if flavor != 'lattice' and geometry_type in ['contour', 'joint', 'line']:
-            raise ValueError("Use geometry_type='{}' with flavor='lattice'".format(
-                             geometry_type))
 
 
 def remove_extra(kwargs, flavor='lattice'):
@@ -77,35 +147,6 @@ class TemporaryDirectory(object):
         shutil.rmtree(self.name)
 
 
-def setup_logging(name):
-    """Sets up a logger with StreamHandler.
-
-    Parameters
-    ----------
-    name : str
-
-    Returns
-    -------
-    logger : logging.Logger
-
-    """
-    logger = logging.getLogger(name)
-
-    format_string = '%(asctime)s - %(levelname)s - %(funcName)s - %(message)s'
-    formatter = logging.Formatter(format_string, datefmt='%Y-%m-%dT%H:%M:%S')
-
-    handler = logging.StreamHandler()
-    handler.setLevel(logging.INFO)
-    handler.setFormatter(formatter)
-
-    logger.addHandler(handler)
-
-    return logger
-
-
-logger = setup_logging(__name__)
-
-
 def translate(x1, x2):
     """Translates x2 by x1.
 
@@ -140,35 +181,6 @@ def scale(x, s):
     return x
 
 
-def rotate(x1, y1, x2, y2, angle):
-    """Rotates point x2, y2 about point x1, y1 by angle.
-
-    Parameters
-    ----------
-    x1 : float
-    y1 : float
-    x2 : float
-    y2 : float
-    angle : float
-        Angle in radians.
-
-    Returns
-    -------
-    xnew : float
-    ynew : float
-
-    """
-    s = np.sin(angle)
-    c = np.cos(angle)
-    x2 = translate(-x1, x2)
-    y2 = translate(-y1, y2)
-    xnew = c * x2 - s * y2
-    ynew = s * x2 + c * y2
-    xnew = translate(x1, xnew)
-    ynew = translate(y1, ynew)
-    return xnew, ynew
-
-
 def scale_pdf(k, factors):
     """Translates and scales pdf coordinate space to image
     coordinate space.
@@ -340,46 +352,19 @@ def text_in_bbox(bbox, text):
     lb = (bbox[0], bbox[1])
     rt = (bbox[2], bbox[3])
     t_bbox = [t for t in text if lb[0] - 2 <= (t.x0 + t.x1) / 2.0
-                <= rt[0] + 2 and lb[1] - 2 <= (t.y0 + t.y1) / 2.0
+              <= rt[0] + 2 and lb[1] - 2 <= (t.y0 + t.y1) / 2.0
-                <= rt[1] + 2]
+              <= rt[1] + 2]
     return t_bbox
 
 
-def remove_close_lines(ar, line_close_tol=2):
+def merge_close_lines(ar, line_tol=2):
-    """Removes lines which are within a tolerance, based on their x or
-    y axis projections.
-
-    Parameters
-    ----------
-    ar : list
-    line_close_tol : int, optional (default: 2)
-
-    Returns
-    -------
-    ret : list
-
-    """
-    ret = []
-    for a in ar:
-        if not ret:
-            ret.append(a)
-        else:
-            temp = ret[-1]
-            if np.isclose(temp, a, atol=line_close_tol):
-                pass
-            else:
-                ret.append(a)
-    return ret
-
-
-def merge_close_lines(ar, line_close_tol=2):
     """Merges lines which are within a tolerance by calculating a
     moving mean, based on their x or y axis projections.
 
     Parameters
     ----------
     ar : list
-    line_close_tol : int, optional (default: 2)
+    line_tol : int, optional (default: 2)
 
     Returns
     -------
@@ -392,7 +377,7 @@ def merge_close_lines(ar, line_close_tol=2):
             ret.append(a)
         else:
             temp = ret[-1]
-            if np.isclose(temp, a, atol=line_close_tol):
+            if np.isclose(temp, a, atol=line_tol):
                 temp = (temp + a) / 2.0
                 ret[-1] = temp
             else:
@@ -400,7 +385,12 @@ def merge_close_lines(ar, line_close_tol=2):
     return ret
 
 
-def flag_font_size(textline, direction):
+# TODO: combine the following functions into a TextProcessor class which
+# applies corresponding transformations sequentially
+# (inspired from sklearn.pipeline.Pipeline)
+
+
+def flag_font_size(textline, direction, strip_text=''):
     """Flags super/subscripts in text by enclosing them with <s></s>.
     May give false positives.
 
@@ -410,6 +400,9 @@ def flag_font_size(textline, direction):
         List of PDFMiner LTChar objects.
     direction : string
         Direction of the PDFMiner LTTextLine object.
+    strip_text : str, optional (default: '')
+        Characters that should be stripped from a string before
+        assigning it to a cell.
 
     Returns
     -------
@@ -435,13 +428,13 @@ 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).strip(strip_text)
     else:
-        fstring = ''.join([t.get_text() for t in textline]).strip('\n')
+        fstring = ''.join([t.get_text() for t in textline]).strip(strip_text)
     return fstring
 
 
-def split_textline(table, textline, direction, flag_size=False):
+def split_textline(table, textline, direction, flag_size=False, strip_text=''):
     """Splits PDFMiner LTTextLine into substrings if it spans across
     multiple rows/columns.
 
@@ -456,6 +449,9 @@ def split_textline(table, textline, direction, flag_size=False):
         Whether or not to highlight a substring using <s></s>
         if its size is different from rest of the string. (Useful for
         super and subscripts.)
+    strip_text : str, optional (default: '')
+        Characters that should be stripped from a string before
+        assigning it to a cell.
 
     Returns
     -------
@@ -507,14 +503,15 @@ def split_textline(table, textline, direction, flag_size=False):
     grouped_chars = []
     for key, chars in groupby(cut_text, itemgetter(0, 1)):
         if flag_size:
-            grouped_chars.append((key[0], key[1], flag_font_size([t[2] for t in chars], direction)))
+            grouped_chars.append((key[0], key[1],
+                flag_font_size([t[2] for t in chars], direction, strip_text=strip_text)))
         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).strip(strip_text)))
     return grouped_chars
 
 
-def get_table_index(table, t, direction, split_text=False, flag_size=False):
+def get_table_index(table, t, direction, split_text=False, flag_size=False, strip_text='',):
     """Gets indices of the table cell where given text object lies by
     comparing their y and x-coordinates.
 
@@ -532,6 +529,9 @@ def get_table_index(table, t, direction, split_text=False, flag_size=False):
         Whether or not to highlight a substring using <s></s>
         if its size is different from rest of the string. (Useful for
         super and subscripts)
+    strip_text : str, optional (default: '')
+        Characters that should be stripped from a string before
+        assigning it to a cell.
 
     Returns
     -------
@@ -564,7 +564,7 @@ def get_table_index(table, t, direction, split_text=False, flag_size=False):
                 text = t.get_text().strip('\n')
                 text_range = (t.x0, t.x1)
                 col_range = (table.cols[0][0], table.cols[-1][1])
-                logger.info("{} {} does not lie in column range {}".format(
+                warnings.warn("{} {} does not lie in column range {}".format(
                     text, text_range, col_range))
             r_idx = r
             c_idx = lt_col_overlap.index(max(lt_col_overlap))
@@ -586,12 +586,12 @@ def get_table_index(table, t, direction, split_text=False, flag_size=False):
     error = ((X * (y0_offset + y1_offset)) + (Y * (x0_offset + x1_offset))) / charea
 
     if split_text:
-        return split_textline(table, t, direction, flag_size=flag_size), error
+        return split_textline(table, t, direction, flag_size=flag_size, strip_text=strip_text), error
     else:
         if flag_size:
-            return [(r_idx, c_idx, flag_font_size(t._objs, direction))], error
+            return [(r_idx, c_idx, flag_font_size(t._objs, direction, strip_text=strip_text))], error
         else:
-            return [(r_idx, c_idx, t.get_text().strip('\n'))], error
+            return [(r_idx, c_idx, t.get_text().strip(strip_text))], error
 
 
 def compute_accuracy(error_weights):
@@ -648,29 +648,8 @@ def compute_whitespace(d):
     return whitespace
 
 
-def remove_empty(d):
-    """Removes empty rows and columns from a two-dimensional list.
-
-    Parameters
-    ----------
-    d : list
-
-    Returns
-    -------
-    d : list
-
-    """
-    for i, row in enumerate(d):
-        if row == [''] * len(row):
-            d.pop(i)
-    d = zip(*d)
-    d = [list(row) for row in d if any(row)]
-    d = zip(*d)
-    return d
-
-
 def get_page_layout(filename, char_margin=1.0, line_margin=0.5, word_margin=0.1,
-               detect_vertical=True, all_texts=True):
+                    detect_vertical=True, all_texts=True):
     """Returns a PDFMiner LTPage object and page dimension of a single
     page pdf. See https://euske.github.io/pdfminer/ to get definitions
     of kwargs.
@@ -751,27 +730,3 @@ def get_text_objects(layout, ltype="char", t=None):
     except AttributeError:
         pass
     return t
-
-
-def merge_tuples(tuples):
-    """Merges a list of overlapping tuples.
-
-    Parameters
-    ----------
-    tuples : list
-        List of tuples where a tuple is a single axis coordinate pair.
-
-    Yields
-    ------
-    tuple
-
-    """
-    merged = list(tuples[0])
-    for s, e in tuples:
-        if s <= merged[1]:
-            merged[1] = max(merged[1], e)
-        else:
-            yield tuple(merged)
-            merged[0] = s
-            merged[1] = e
-    yield tuple(merged)

docs/_themes/flask_theme_support.py

@@ -10,21 +10,21 @@ class FlaskyStyle(Style):
 
     styles = {
         # No corresponding class for the following:
-        #Text:                     "", # class:  ''
+        # Text:                    "", # class:  ''
-        Whitespace:                "underline #f8f8f8",      # class: 'w'
+        Whitespace:                "underline #f8f8f8",       # class: 'w'
-        Error:                     "#a40000 border:#ef2929", # class: 'err'
+        Error:                     "#a40000 border:#ef2929",  # class: 'err'
-        Other:                     "#000000",                # class 'x'
+        Other:                     "#000000",                 # class 'x'
 
-        Comment:                   "italic #8f5902", # class: 'c'
+        Comment:                   "italic #8f5902",  # class: 'c'
-        Comment.Preproc:           "noitalic",       # class: 'cp'
+        Comment.Preproc:           "noitalic",        # class: 'cp'
 
-        Keyword:                   "bold #004461",   # class: 'k'
+        Keyword:                   "bold #004461",    # class: 'k'
-        Keyword.Constant:          "bold #004461",   # class: 'kc'
+        Keyword.Constant:          "bold #004461",    # class: 'kc'
-        Keyword.Declaration:       "bold #004461",   # class: 'kd'
+        Keyword.Declaration:       "bold #004461",    # class: 'kd'
-        Keyword.Namespace:         "bold #004461",   # class: 'kn'
+        Keyword.Namespace:         "bold #004461",    # class: 'kn'
-        Keyword.Pseudo:            "bold #004461",   # class: 'kp'
+        Keyword.Pseudo:            "bold #004461",    # class: 'kp'
-        Keyword.Reserved:          "bold #004461",   # class: 'kr'
+        Keyword.Reserved:          "bold #004461",    # class: 'kr'
-        Keyword.Type:              "bold #004461",   # class: 'kt'
+        Keyword.Type:              "bold #004461",    # class: 'kt'
 
         Operator:                  "#582800",   # class: 'o'
         Operator.Word:             "bold #004461",   # class: 'ow' - like keywords
@@ -34,53 +34,53 @@ class FlaskyStyle(Style):
         # because special names such as Name.Class, Name.Function, etc.
         # are not recognized as such later in the parsing, we choose them
         # to look the same as ordinary variables.
-        Name:                      "#000000",        # class: 'n'
+        Name:                      "#000000",         # class: 'n'
-        Name.Attribute:            "#c4a000",        # class: 'na' - to be revised
+        Name.Attribute:            "#c4a000",         # class: 'na' - to be revised
-        Name.Builtin:              "#004461",        # class: 'nb'
+        Name.Builtin:              "#004461",         # class: 'nb'
-        Name.Builtin.Pseudo:       "#3465a4",        # class: 'bp'
+        Name.Builtin.Pseudo:       "#3465a4",         # class: 'bp'
-        Name.Class:                "#000000",        # class: 'nc' - to be revised
+        Name.Class:                "#000000",         # class: 'nc' - to be revised
-        Name.Constant:             "#000000",        # class: 'no' - to be revised
+        Name.Constant:             "#000000",         # class: 'no' - to be revised
-        Name.Decorator:            "#888",           # class: 'nd' - to be revised
+        Name.Decorator:            "#888",            # class: 'nd' - to be revised
-        Name.Entity:               "#ce5c00",        # class: 'ni'
+        Name.Entity:               "#ce5c00",         # class: 'ni'
-        Name.Exception:            "bold #cc0000",   # class: 'ne'
+        Name.Exception:            "bold #cc0000",    # class: 'ne'
-        Name.Function:             "#000000",        # class: 'nf'
+        Name.Function:             "#000000",         # class: 'nf'
-        Name.Property:             "#000000",        # class: 'py'
+        Name.Property:             "#000000",         # class: 'py'
-        Name.Label:                "#f57900",        # class: 'nl'
+        Name.Label:                "#f57900",         # class: 'nl'
-        Name.Namespace:            "#000000",        # class: 'nn' - to be revised
+        Name.Namespace:            "#000000",         # class: 'nn' - to be revised
-        Name.Other:                "#000000",        # class: 'nx'
+        Name.Other:                "#000000",         # class: 'nx'
-        Name.Tag:                  "bold #004461",   # class: 'nt' - like a keyword
+        Name.Tag:                  "bold #004461",    # class: 'nt' - like a keyword
-        Name.Variable:             "#000000",        # class: 'nv' - to be revised
+        Name.Variable:             "#000000",         # class: 'nv' - to be revised
-        Name.Variable.Class:       "#000000",        # class: 'vc' - to be revised
+        Name.Variable.Class:       "#000000",         # class: 'vc' - to be revised
-        Name.Variable.Global:      "#000000",        # class: 'vg' - to be revised
+        Name.Variable.Global:      "#000000",         # class: 'vg' - to be revised
-        Name.Variable.Instance:    "#000000",        # class: 'vi' - to be revised
+        Name.Variable.Instance:    "#000000",         # class: 'vi' - to be revised
 
-        Number:                    "#990000",        # class: 'm'
+        Number:                    "#990000",         # class: 'm'
 
-        Literal:                   "#000000",        # class: 'l'
+        Literal:                   "#000000",         # class: 'l'
-        Literal.Date:              "#000000",        # class: 'ld'
+        Literal.Date:              "#000000",         # class: 'ld'
 
-        String:                    "#4e9a06",        # class: 's'
+        String:                    "#4e9a06",         # class: 's'
-        String.Backtick:           "#4e9a06",        # class: 'sb'
+        String.Backtick:           "#4e9a06",         # class: 'sb'
-        String.Char:               "#4e9a06",        # class: 'sc'
+        String.Char:               "#4e9a06",         # class: 'sc'
-        String.Doc:                "italic #8f5902", # class: 'sd' - like a comment
+        String.Doc:                "italic #8f5902",  # class: 'sd' - like a comment
-        String.Double:             "#4e9a06",        # class: 's2'
+        String.Double:             "#4e9a06",         # class: 's2'
-        String.Escape:             "#4e9a06",        # class: 'se'
+        String.Escape:             "#4e9a06",         # class: 'se'
-        String.Heredoc:            "#4e9a06",        # class: 'sh'
+        String.Heredoc:            "#4e9a06",         # class: 'sh'
-        String.Interpol:           "#4e9a06",        # class: 'si'
+        String.Interpol:           "#4e9a06",         # class: 'si'
-        String.Other:              "#4e9a06",        # class: 'sx'
+        String.Other:              "#4e9a06",         # class: 'sx'
-        String.Regex:              "#4e9a06",        # class: 'sr'
+        String.Regex:              "#4e9a06",         # class: 'sr'
-        String.Single:             "#4e9a06",        # class: 's1'
+        String.Single:             "#4e9a06",         # class: 's1'
-        String.Symbol:             "#4e9a06",        # class: 'ss'
+        String.Symbol:             "#4e9a06",         # class: 'ss'
 
-        Generic:                   "#000000",        # class: 'g'
+        Generic:                   "#000000",         # class: 'g'
-        Generic.Deleted:           "#a40000",        # class: 'gd'
+        Generic.Deleted:           "#a40000",         # class: 'gd'
-        Generic.Emph:              "italic #000000", # class: 'ge'
+        Generic.Emph:              "italic #000000",  # class: 'ge'
-        Generic.Error:             "#ef2929",        # class: 'gr'
+        Generic.Error:             "#ef2929",         # class: 'gr'
-        Generic.Heading:           "bold #000080",   # class: 'gh'
+        Generic.Heading:           "bold #000080",    # class: 'gh'
-        Generic.Inserted:          "#00A000",        # class: 'gi'
+        Generic.Inserted:          "#00A000",         # class: 'gi'
-        Generic.Output:            "#888",           # class: 'go'
+        Generic.Output:            "#888",            # class: 'go'
-        Generic.Prompt:            "#745334",        # class: 'gp'
+        Generic.Prompt:            "#745334",         # class: 'gp'
-        Generic.Strong:            "bold #000000",   # class: 'gs'
+        Generic.Strong:            "bold #000000",    # class: 'gs'
-        Generic.Subheading:        "bold #800080",   # class: 'gu'
+        Generic.Subheading:        "bold #800080",    # class: 'gu'
-        Generic.Traceback:         "bold #a40000",   # class: 'gt'
+        Generic.Traceback:         "bold #a40000",    # class: 'gt'
-    }
+    }

docs/benchmark/lattice/agstat/agstat-data-pdfplumber.csv

@@ -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
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+"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"

docs/benchmark/lattice/column_span_1/column_span_1-data-pdfplumber.csv

@@ -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"

docs/benchmark/lattice/rotated/rotated-data-pdfplumber.csv

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

docs/benchmark/lattice/twotables_1/twotables_1-data-pdfplumber.csv

@@ -0,0 +1,3 @@
+"0"
+"Sl."
+"No."

docs/benchmark/lattice/twotables_2/twotables_2-data-pdfplumber.csv

@@ -0,0 +1,3 @@
+"0"
+"Table 6 : DISTRIBUTION (%) OF HOUSEHOLDS BY LITERACY STATUS OF"
+"MALE HEAD OF THE HOUSEHOLD"

docs/benchmark/stream/12s0324/12s0324-data-camelot-page-1-table-1.csv

@@ -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.","","","","","","","",""

docs/benchmark/stream/12s0324/12s0324-data-camelot-page-1-table-2.csv

@@ -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,","","","",""

docs/benchmark/stream/birdisland/birdisland-data-camelot-page-1-table-1.csv

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

docs/benchmark/stream/birdisland/birdisland-data-camelot-page-1-table-2.csv

@@ -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"

docs/benchmark/stream/district_health/district_health-data-pdfplumber.csv

@@ -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","","","",""

docs/benchmark/stream/health/health-data-pdfplumber.csv

@@ -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",""
+"","","","","","","","","","","","","","","","","","","","","","","",""

docs/benchmark/stream/missing_values/missing_values-data-pdfplumber.csv

@@ -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","","","",""

docs/conf.py

@@ -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
@@ -358,4 +358,4 @@ texinfo_documents = [
 intersphinx_mapping = {
     'https://docs.python.org/2': None,
     'http://pandas.pydata.org/pandas-docs/stable': None
-}
+}

docs/dev/contributing.rst

@@ -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
 ---------------
@@ -24,13 +24,13 @@ As the `Requests Code Of Conduct`_ states, **all contributions are welcome**, as
 
 .. _Requests Code Of Conduct: http://docs.python-requests.org/en/master/dev/contributing/#be-cordial
 
-Your First Contribution
+Your first contribution
 -----------------------
 
-A great way to start contributing to Camelot is to pick an issue tagged with the `Contributor Friendly`_ or the `Easy`_ tags. If you're unable to find a good first issue, feel free to contact the maintainer.
+A great way to start contributing to Camelot is to pick an issue tagged with the `help wanted`_ or the `good first issue`_ tags. If you're unable to find a good first issue, feel free to contact the maintainer.
 
-.. _Contributor Friendly: https://github.com/socialcopsdev/camelot/labels/Contributor%20Friendly
+.. _help wanted: https://github.com/socialcopsdev/camelot/labels/help%20wanted
-.. _Easy: https://github.com/socialcopsdev/camelot/labels/Level%3A%20Easy
+.. _good first issue: https://github.com/socialcopsdev/camelot/labels/good%20first%20issue
 
 Setting up a development environment
 ------------------------------------
@@ -39,13 +39,17 @@ To install the dependencies needed for development, you can use pip::
 
     $ pip install camelot-py[dev]
 
+Alternatively, you can clone the project repository, and install using pip::
+
+    $ pip install ".[dev]"
+
 Pull Requests
 -------------
 
-Submit a Pull Request
+Submit a pull request
 ^^^^^^^^^^^^^^^^^^^^^
 
-The preferred workflow for contributing to Camelot is to fork the `project repository`_ on GitHub, clone, develop on a branch and then finally submit a pull request. Steps:
+The preferred workflow for contributing to Camelot is to fork the `project repository`_ on GitHub, clone, develop on a branch and then finally submit a pull request. Here are the steps:
 
 .. _project repository: https://github.com/socialcopsdev/camelot
 
@@ -76,7 +80,7 @@ Now it's time to go to the your fork of Camelot and create a pull request! You c
 
 .. _follow these instructions: https://help.github.com/articles/creating-a-pull-request-from-a-fork/
 
-Work on your Pull Request
+Work on your pull request
 ^^^^^^^^^^^^^^^^^^^^^^^^^
 
 We recommend that your pull request complies with the following guidelines:
@@ -89,7 +93,7 @@ We recommend that your pull request complies with the following guidelines:
 
 .. _numpydoc: https://numpydoc.readthedocs.io/en/latest/format.html
 
-- Make sure your commit messages follow `the seven rules of a great git commit message`_.
+- Make sure your commit messages follow `the seven rules of a great git commit message`_:
     - Separate subject from body with a blank line
     - Limit the subject line to 50 characters
     - Capitalize the subject line
@@ -119,7 +123,7 @@ Writing documentation, function docstrings, examples and tutorials is a great wa
 
 The documentation is written in `reStructuredText`_, with `Sphinx`_ used to generate these lovely HTML files that you're currently reading (unless you're reading this on GitHub). You can edit the documentation using any text editor and then generate the HTML output by running `make html` in the ``docs/`` directory.
 
-The function docstrings are written using the `numpydoc`_ extension for Sphinx. Make sure you check out how its format guidelines, before you start writing one.
+The function docstrings are written using the `numpydoc`_ extension for Sphinx. Make sure you check out how its format guidelines before you start writing one.
 
 .. _reStructuredText: https://en.wikipedia.org/wiki/ReStructuredText
 .. _Sphinx: http://www.sphinx-doc.org/en/master/
@@ -128,14 +132,14 @@ The function docstrings are written using the `numpydoc`_ extension for Sphinx.
 Filing Issues
 -------------
 
-We use `GitHub issues`_ to keep track of all issues and pull requests. Before opening an issue (which asks a question or reports a bug), it is advisable to use GitHub search to look for existing issues (both open and closed) that may be similar.
+We use `GitHub issues`_ to keep track of all issues and pull requests. Before opening an issue (which asks a question or reports a bug), please use GitHub search to look for existing issues (both open and closed) that may be similar.
 
-.. _GitHub issues: https://docs.pytest.org/en/latest/
+.. _GitHub issues: https://github.com/socialcopsdev/camelot/issues
 
 Questions
 ^^^^^^^^^
 
-Please don't use GitHub issues for support questions, a better place for them would be `Stack Overflow`_. Make sure you tag them using the ``python-camelot`` tag.
+Please don't use GitHub issues for support questions. A better place for them would be `Stack Overflow`_. Make sure you tag them using the ``python-camelot`` tag.
 
 .. _Stack Overflow: http://stackoverflow.com
 

docs/index.rst

@@ -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
 
@@ -23,11 +27,18 @@ Release v\ |version|. (:ref:`Installation <install>`)
 .. image:: https://img.shields.io/pypi/pyversions/camelot-py.svg
     :target: https://pypi.org/project/camelot-py/
 
-**Camelot** is a Python library which makes it easy for *anyone* to extract tables from PDF files!
+.. 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`_.
+**Here's how you can extract tables from PDF files.** Check out the PDF used in this example `here`_.
 
 .. _here: _static/pdf/foo.pdf
 
@@ -55,15 +66,17 @@ Release v\ |version|. (:ref:`Installation <install>`)
 
 There's a :ref:`command-line interface <cli>` too!
 
-.. note:: Camelot only works with text-based PDFs and not scanned documents. If you can click-and-drag to select text in your table in a PDF viewer, then your PDF is text-based.
+.. note:: Camelot only works with text-based PDFs and not scanned documents. (As Tabula `explains`_, "If you can click and drag to select text in your table in a PDF viewer, then your PDF is text-based".)
+
+.. _explains: https://github.com/tabulapdf/tabula#why-tabula
 
 Why Camelot?
 ------------
 
-- **You are in control**: Unlike other libraries and tools which either give a nice output or fail miserably (with no in-between), Camelot gives you the power to tweak table extraction. (Since everything in the real world, including PDF table extraction, is fuzzy.)
+- **You are in control.** Unlike other libraries and tools which either give a nice output or fail miserably (with no in-between), Camelot gives you the power to tweak table extraction. (This is important since everything in the real world, including PDF table extraction, is fuzzy.)
-- **Metrics**: *Bad* tables can be discarded based on metrics like accuracy and whitespace, without ever having to manually look at each table.
+- *Bad* tables can be discarded based on **metrics** like accuracy and whitespace, without ever having to manually look at each table.
-- Each table is a **pandas DataFrame**, which enables seamless integration into `ETL and data analysis workflows`_.
+- Each table is a **pandas DataFrame**, which seamlessly integrates into `ETL and data analysis workflows`_.
-- **Export** to multiple formats, including json, excel and html.
+- **Export** to multiple formats, including JSON, Excel and HTML.
 
 See `comparison with other PDF table extraction libraries and tools`_.
 
@@ -73,20 +86,21 @@ See `comparison with other PDF table extraction libraries and tools`_.
 The User Guide
 --------------
 
-This part of the documentation, begins with some background information about why Camelot was created, takes a small dip into the implementation details and then focuses on step-by-step instructions for getting the most out of Camelot.
+This part of the documentation begins with some background information about why Camelot was created, takes a small dip into the implementation details and then focuses on step-by-step instructions for getting the most out of Camelot.
 
 .. toctree::
    :maxdepth: 2
 
    user/intro
+   user/install-deps
    user/install
    user/how-it-works
    user/quickstart
    user/advanced
    user/cli
 
-The API Documentation / Guide
+The API Documentation/Guide
------------------------------
+---------------------------
 
 If you are looking for information on a specific function, class, or method,
 this part of the documentation is for you.
@@ -105,4 +119,4 @@ you.
 .. toctree::
    :maxdepth: 2
 
-   dev/contributing
+   dev/contributing

docs/user/advanced.rst

@@ -8,7 +8,7 @@ This page covers some of the more advanced configurations for :ref:`Lattice <lat
 Process background lines
 ------------------------
 
-To detect line segments, :ref:`Lattice <lattice>` needs the lines that make the table, to be in foreground. Here's an example of a table with lines in background.
+To detect line segments, :ref:`Lattice <lattice>` needs the lines that make the table to be in the foreground. Here's an example of a table with lines in the background:
 
 .. figure:: ../_static/png/background_lines.png
     :scale: 50%
@@ -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
 ^^^^
 
@@ -59,31 +66,43 @@ 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%
     :alt: A plot of all text on a PDF page
     :align: left
 
-This, as we shall later see, is very helpful with :ref:`Stream <stream>`, for noting table areas and column separators, in case Stream does not guess them correctly.
+This, as we shall later see, is very helpful with :ref:`Stream <stream>` for noting table areas and column separators, in case Stream does not guess them correctly.
 
-.. note:: The *x-y* coordinates shown aboe change as you move your mouse cursor on the image, which can help you note coordinates.
+.. 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 there is a need to specify column separators as well, **the length of both lists should be equal**. Each table area will be mapped to each column separators' string using their indices.
+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::
 
     "...","...","...","...","...","...","...","...","...","..."
@@ -188,18 +257,24 @@ Let's get back to the *x* coordinates we got from :ref:`plotting text <geometry_
     "NUMBER TYPE DBA NAME","","","LICENSEE NAME","ADDRESS","CITY","ST","ZIP","PHONE NUMBER","EXPIRES"
     "...","...","...","...","...","...","...","...","...","..."
 
-Ah! Since `PDFMiner <https://euske.github.io/pdfminer/>`_ merged the strings, "NUMBER", "TYPE" and "DBA NAME"; all of them were assigned to the same cell. Let's see how we can fix this in the next section.
+Ah! Since `PDFMiner <https://euske.github.io/pdfminer/>`_ merged the strings, "NUMBER", "TYPE" and "DBA NAME", all of them were assigned to the same cell. Let's see how we can fix this in the next section.
 
 Split text along separators
 ---------------------------
 
-To deal with cases like the output from the previous section, you can pass ``split_text=True`` to :meth:`read_pdf() <camelot.read_pdf>`, which will split any strings that lie in different cells but have been assigned to the a single cell (as a result of being merged together by `PDFMiner <https://euske.github.io/pdfminer/>`_).
+To deal with cases like the output from the previous section, you can pass ``split_text=True`` to :meth:`read_pdf() <camelot.read_pdf>`, which will split any strings that lie in different cells but have been assigned to a single cell (as a result of being merged together by `PDFMiner <https://euske.github.io/pdfminer/>`_).
 
 ::
 
     >>> 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::
 
     "...","...","...","...","...","...","...","...","...","..."
@@ -210,13 +285,13 @@ To deal with cases like the output from the previous section, you can pass ``spl
 Flag superscripts and subscripts
 --------------------------------
 
-There might be cases where you want to differentiate between the text, and superscripts or subscripts, like this `PDF <../_static/pdf/superscript.pdf>`_.
+There might be cases where you want to differentiate between the text and superscripts or subscripts, like this `PDF <../_static/pdf/superscript.pdf>`_.
 
 .. figure:: ../_static/png/superscript.png
     :alt: A PDF with superscripts
     :align: left
 
-In this case, the text that `other tools`_ return, will be ``24.912``. This is harmless as long as there is that decimal point involved. But when it isn't there, you'll be left wondering why the results of your data analysis were 10x bigger!
+In this case, the text that `other tools`_ return, will be ``24.912``. This is relatively harmless when that decimal point is involved. But when it isn't there, you'll be left wondering why the results of your data analysis are 10x bigger!
 
 You can solve this by passing ``flag_size=True``, which will enclose the superscripts and subscripts with ``<s></s>``, based on font size, as shown below.
 
@@ -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::
 
     "...","...","...","...","...","...","...","...","...","...","..."
@@ -235,10 +316,87 @@ You can solve this by passing ``flag_size=True``, which will enclose the supersc
     "Madhya Pradesh","27.13","23.57","-","-","3.56","0.38","-","1.86","-","1.28"
     "...","...","...","...","...","...","...","...","...","...","..."
 
-Control how text is grouped into rows
+Strip characters from text
--------------------------------------
+--------------------------
 
-You can pass ``row_close_tol=<+int>`` to group the rows closer together, as shown below.
+You can strip unwanted characters like spaces, dots and newlines from a string using the ``strip_text`` keyword argument. Take a look at `this PDF <https://github.com/socialcopsdev/camelot/blob/master/tests/files/tabula/12s0324.pdf>`_ as an example, the text at the start of each row contains a lot of unwanted spaces, dots and newlines.
+
+::
+
+    >>> tables = camelot.read_pdf('12s0324.pdf', flavor='stream', strip_text=' .\n')
+    >>> tables[0].df
+
+.. tip::
+    Here's how you can do the same with the :ref:`command-line interface <cli>`.
+    ::
+
+        $ camelot -strip ' .\n' stream 12s0324.pdf
+
+.. csv-table::
+
+    "...","...","...","...","...","...","...","...","...","..."
+    "Forcible rape","17.5","2.6","14.9","17.2","2.5","14.7","–","–","–"
+    "Robbery","102.1","25.5","76.6","90.0","22.9","67.1","12.1","2.5","9.5"
+    "Aggravated assault","338.4","40.1","298.3","264.0","30.2","233.8","74.4","9.9","64.5"
+    "Property crime","1,396 .4","338 .7","1,057 .7","875 .9","210 .8","665 .1","608 .2","127 .9","392 .6"
+    "Burglary","240.9","60.3","180.6","205.0","53.4","151.7","35.9","6.9","29.0"
+    "...","...","...","...","...","...","...","...","...","..."
+
+Improve guessed table areas
+---------------------------
+
+While using :ref:`Stream <stream>`, automatic table detection can fail for PDFs like `this one <https://github.com/socialcopsdev/camelot/blob/master/tests/files/edge_tol.pdf>`_. That's because the text is relatively far apart vertically, which can lead to shorter textedges being calculated.
+
+.. note:: To know more about how textedges are calculated to guess table areas, you can see pages 20, 35 and 40 of `Anssi Nurminen's master's thesis <http://dspace.cc.tut.fi/dpub/bitstream/handle/123456789/21520/Nurminen.pdf?sequence=3>`_.
+
+Let's see the table area that is detected by default.
+
+::
+
+    >>> tables = camelot.read_pdf('edge_tol.pdf', flavor='stream')
+    >>> camelot.plot(tables[0], kind='contour')
+    >>> plt.show()
+
+.. tip::
+    Here's how you can do the same with the :ref:`command-line interface <cli>`.
+    ::
+
+        $ camelot stream -plot contour edge.pdf
+
+.. figure:: ../_static/png/edge_tol_1.png
+    :height: 674
+    :width: 1366
+    :scale: 50%
+    :alt: Table area with default edge_tol
+    :align: left
+
+To improve the detected area, you can increase the ``edge_tol`` (default: 50) value to counter the effect of text being placed relatively far apart vertically. Larger ``edge_tol`` will lead to longer textedges being detected, leading to an improved guess of the table area. Let's use a value of 500.
+
+::
+
+    >>> tables = camelot.read_pdf('edge_tol.pdf', flavor='stream', edge_tol=500)
+    >>> camelot.plot(tables[0], kind='contour')
+    >>> plt.show()
+
+.. tip::
+    Here's how you can do the same with the :ref:`command-line interface <cli>`.
+    ::
+
+        $ camelot stream -e 500 -plot contour edge.pdf
+
+.. figure:: ../_static/png/edge_tol_2.png
+    :height: 674
+    :width: 1366
+    :scale: 50%
+    :alt: Table area with default edge_tol
+    :align: left
+
+As you can see, the guessed table area has improved!
+
+Improve guessed table rows
+--------------------------
+
+You can pass ``row_tol=<+int>`` to group the rows closer together, as shown below.
 
 ::
 
@@ -256,9 +414,15 @@ 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 = camelot.read_pdf('group_rows.pdf', flavor='stream', row_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 +446,31 @@ 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
@@ -327,7 +499,7 @@ Voila! Camelot can now see those lines. Let's get our table.
 Shift text in spanning cells
 ----------------------------
 
-By default, the :ref:`Lattice <lattice>` method shifts text in spanning cells, first to the left and then to the top, as you can observe in the output table above. However, this behavior can be changed using the ``shift_text`` keyword argument. Think of it as setting the *gravity* for a table, it decides the direction in which the text will move and finally come to rest.
+By default, the :ref:`Lattice <lattice>` method shifts text in spanning cells, first to the left and then to the top, as you can observe in the output table above. However, this behavior can be changed using the ``shift_text`` keyword argument. Think of it as setting the *gravity* for a table — it decides the direction in which the text will move and finally come to rest.
 
 ``shift_text`` expects a list with one or more characters from the following set: ``('', l', 'r', 't', 'b')``, which are then applied *in order*. The default, as we discussed above, is ``['l', 't']``.
 
@@ -356,13 +528,19 @@ We'll use the `PDF <../_static/pdf/short_lines.pdf>`__ from the previous example
     "Knowledge &Practices on HTN &","2400","Men (≥ 18 yrs)","-","-","-","1728"
     "DM","2400","Women (≥ 18 yrs)","-","-","-","1728"
 
-No surprises there, it did remain in place (observe the strings "2400" and "All the available individuals"). Let's pass ``shift_text=['r', 'b']``, to set the *gravity* to right-bottom, and move the text in that direction.
+No surprises there — it did remain in place (observe the strings "2400" and "All the available individuals"). Let's pass ``shift_text=['r', 'b']`` to set the *gravity* to right-bottom and move the text in that direction.
 
 ::
 
     >>> tables = camelot.read_pdf('short_lines.pdf', line_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"
@@ -380,7 +558,7 @@ No surprises there, it did remain in place (observe the strings "2400" and "All
 Copy text in spanning cells
 ---------------------------
 
-You can copy text in spanning cells when using :ref:`Lattice <lattice>`, in either horizontal or vertical direction, or both. This behavior is disabled by default.
+You can copy text in spanning cells when using :ref:`Lattice <lattice>`, in either the horizontal or vertical direction, or both. This behavior is disabled by default.
 
 ``copy_text`` expects a list with one or more characters from the following set: ``('v', 'h')``, which are then applied *in order*.
 
@@ -408,6 +586,12 @@ 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 +600,15 @@ 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","..."
+
+Tweak layout generation
+-----------------------
+
+Camelot is built on top of PDFMiner's functionality of grouping characters on a page into words and sentences. In some cases (such as `#170 <https://github.com/socialcopsdev/camelot/issues/170>`_ and `#215 <https://github.com/socialcopsdev/camelot/issues/215>`_), PDFMiner can group characters that should belong to the same sentence into separate sentences.
+
+To deal with such cases, you can tweak PDFMiner's `LAParams kwargs <https://github.com/euske/pdfminer/blob/master/pdfminer/layout.py#L33>`_ to improve layout generation, by passing the keyword arguments as a dict using ``layout_kwargs`` in :meth:`read_pdf() <camelot.read_pdf>`. To know more about the parameters you can tweak, you can check out `PDFMiner docs <https://euske.github.io/pdfminer/>`_.
+
+::
+
+    >>> tables = camelot.read_pdf('foo.pdf', layout_kwargs={'detect_vertical': False})

docs/user/cli.rst

@@ -1,22 +1,24 @@
 .. _cli:
 
-Command-line interface
+Command-Line Interface
 ======================
 
 Camelot comes with a command-line interface.
 
-You can print the help for the interface, by typing ``camelot --help`` in your favorite terminal program, as shown below. Furthermore, you can print the help for each command, by typing ``camelot <command> --help``, try it out!
+You can print the help for the interface by typing ``camelot --help`` in your favorite terminal program, as shown below. Furthermore, you can print the help for each command by typing ``camelot <command> --help``. Try it out!
 
 ::
 
   Usage: camelot [OPTIONS] COMMAND [ARGS]...
 
-  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 f
 
   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.

docs/user/how-it-works.rst

@@ -3,35 +3,35 @@
 How It Works
 ============
 
-This part of the documentation details a high-level explanation of how Camelot extracts tables from PDF files.
+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*. The naming for parsing methods inside Camelot (i.e. Stream and Lattice) was inspired from `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>`_.
-
-.. _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 given on a page, it groups them into rows based on their *y* coordinates and tries to guess the number of columns the table might have by calculating the mode of the number of words in each row. This mode is used to calculate *x* ranges for the table's columns. It then adds columns to this column range list based on any words that may lie outside or inside the current column *x* ranges.
+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:
 
 Lattice
 -------
 
-Lattice is more deterministic in nature, and does not rely on guesses. It can be used to parse tables that have demarcated lines between cells, and can automatically parse multiple tables present on a page.
+Lattice is more deterministic in nature, and it does not rely on guesses. It can be used to parse tables that have demarcated lines between cells, and it can automatically parse multiple tables present on a page.
 
-It starts by converting the PDF page to an image using ghostscript and then processing it to get horizontal and vertical line segments by applying a set of morphological transformations (erosion and dilation) using OpenCV.
+It starts by converting the PDF page to an image using ghostscript, and then processes it to get horizontal and vertical line segments by applying a set of morphological transformations (erosion and dilation) using OpenCV.
 
 Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
 
@@ -39,7 +39,7 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
 
 1. Line segments are detected.
 
-.. image:: ../_static/png/geometry_line.png
+.. image:: ../_static/png/plot_line.png
     :height: 674
     :width: 1366
     :scale: 50%
@@ -49,23 +49,23 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
 
 .. _and: https://en.wikipedia.org/wiki/Logical_conjunction
 
-.. image:: ../_static/png/geometry_joint.png
+.. image:: ../_static/png/plot_joint.png
     :height: 674
     :width: 1366
     :scale: 50%
     :align: left
 
-3. Table boundaries are computed, by overlapping the detected line segments again, this time by "`or`_"ing their pixel intensities.
+3. Table boundaries are computed by overlapping the detected line segments again, this time by "`or`_"ing their pixel intensities.
 
 .. _or: https://en.wikipedia.org/wiki/Logical_disjunction
 
-.. image:: ../_static/png/geometry_contour.png
+.. image:: ../_static/png/plot_contour.png
     :height: 674
     :width: 1366
     :scale: 50%
     :align: left
 
-4. Since dimensions of the PDF page and its image vary; the detected table boundaries, line intersections and line segments are scaled and translated to the PDF page's coordinate space, and a representation of the table is created.
+4. Since dimensions of the PDF page and its image vary, the detected table boundaries, line intersections, and line segments are scaled and translated to the PDF page's coordinate space, and a representation of the table is created.
 
 .. image:: ../_static/png/table.png
     :height: 674
@@ -75,10 +75,10 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
 
 5. Spanning cells are detected using the line segments and line intersections.
 
-.. 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.

docs/user/install-deps.rst

@@ -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.

docs/user/install.rst

@@ -3,42 +3,45 @@
 Installation of Camelot
 =======================
 
-This part of the documentation covers the installation of Camelot. First, you'll need to install the dependencies, which include `tk`_ and `ghostscript`_.
+This part of the documentation covers the steps to install Camelot.
 
-.. _tk: https://packages.ubuntu.com/trusty/python-tk
+Using conda
-.. _ghostscript: https://www.ghostscript.com/
+-----------
 
-These can be installed using your system's package manager. You can run the following based on your OS.
+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.
+::
 
-For Ubuntu::
+    $ conda install -c conda-forge camelot-py
 
-    $ apt install python-tk ghostscript
+.. 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`_.
 
-.. note:: For Python 3, install python3-tk.
+.. _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/
 
-For macOS::
+Using pip
+---------
 
-    $ brew install tcl-tk ghostscript
+After :ref:`installing the dependencies <install_deps>`, which include `Tkinter`_ and `ghostscript`_, you can simply use pip to install Camelot::
 
-$ pip install camelot-py
+    $ pip install camelot-py[cv]
-------------------------
 
-After installing the dependencies, you can simply use pip to install Camelot::
+.. _Tkinter: https://wiki.python.org/moin/TkInter
+.. _ghostscript: https://www.ghostscript.com
 
-    $ pip install camelot-py
+From the source code
+--------------------
 
-Get the Source Code
+After :ref:`installing the dependencies <install_deps>`, you can install from the source by:
--------------------
-
-Alternatively, you can install from source by:
 
 1. Cloning the GitHub repository.
 ::
 
     $ git clone https://www.github.com/socialcopsdev/camelot
 
-2. And then simply using pip again.
+2. Then simply using pip again.
 ::
 
     $ cd camelot
-    $ pip install .
+    $ pip install ".[cv]"

docs/user/intro.rst

@@ -6,20 +6,20 @@ Introduction
 The Camelot Project
 -------------------
 
-The Portable Document Format (PDF) was born out of `The Camelot Project`_ when a need was felt for "a universal to communicate documents across a wide variety of machine configurations, operating systems and communication networks". The goal was to make these documents viewable on any display and printable on any modern printers. The invention of the `PostScript`_ page description language, which enabled the creation of *fixed-layout* flat documents (with text, fonts, graphics, images encapsulated), solved the problem.
+The PDF (Portable Document Format) was born out of `The Camelot Project`_ to create "a universal way to communicate documents across a wide variety of machine configurations, operating systems and communication networks". The goal was to make these documents viewable on any display and printable on any modern printers. The invention of the `PostScript`_ page description language, which enabled the creation of *fixed-layout* flat documents (with text, fonts, graphics, images encapsulated), solved this problem.
 
-At a very high level, PostScript defines instructions, such as, "place this character at this x,y coordinate on a plane". Spaces can be *simulated* by placing characters relatively far apart. Extending from that, tables can be *simulated* by placing characters (which constitute words) in two-dimensional grids. A PDF viewer just takes these instructions and draws everything for the user to view. Since it's just characters on a plane, there is no table data structure which can be extracted and used for analysis!
+At a high level, PostScript defines instructions, such as "place this character at this *x,y* coordinate on a plane". Spaces can be *simulated* by placing characters relatively far apart. Extending from that, tables can be *simulated* by placing characters (which constitute words) in two-dimensional grids. A PDF viewer just takes these instructions and draws everything for the user to view. Since a PDF is just characters on a plane, there is no table data structure that can be extracted and used for analysis!
 
-Sadly, a lot of open data is given out as tables which are trapped inside PDF files.
+Sadly, a lot of today's open data is trapped in PDF tables.
 
 .. _PostScript: http://www.planetpdf.com/planetpdf/pdfs/warnock_camelot.pdf
 
-Why another PDF Table Extraction library?
+Why another PDF table extraction library?
 -----------------------------------------
 
-There are both open (`Tabula`_, `pdf-table-extract`_) and closed-source (`smallpdf`_, `PDFTables`_) tools that are widely used, to extract tables from PDF files. They either give a nice output, or fail miserably. There is no in-between. This is not helpful, since everything in the real world, including PDF table extraction, is fuzzy, leading to creation of adhoc table extraction scripts for each different type of PDF that the user wants to parse.
+There are both open (`Tabula`_, `pdf-table-extract`_) and closed-source (`smallpdf`_, `PDFTables`_) tools that are widely used to extract tables from PDF files. They either give a nice output or fail miserably. There is no in between. This is not helpful since everything in the real world, including PDF table extraction, is fuzzy. This leads to the creation of ad-hoc table extraction scripts for each type of PDF table.
 
-Camelot was created with the goal of offering its users complete control over table extraction. If the users are not able to get the desired output with the default configuration, they should be able to tweak it and get the job done!
+Camelot was created to offer users complete control over table extraction. If you can't get your desired output with the default settings, you can tweak them and get the job done!
 
 Here is a `comparison`_ of Camelot's output with outputs from other open-source PDF parsing libraries and tools.
 
@@ -34,7 +34,7 @@ What's in a name?
 
 As you can already guess, this library is named after `The Camelot Project`_.
 
-Fun fact: "Camelot" is the name of the castle in the British comedy film `Monty Python and the Holy Grail`_ (and in the `Arthurian legend`_, which the film depicts), where Arthur leads his men, the Knights of the Round Table, and then sets off elsewhere after deciding that it is "a silly place". Interestingly, the language in which this library is written (Python) was named after Monty Python.
+Fun fact: In the British comedy film `Monty Python and the Holy Grail`_ (and in the `Arthurian legend`_ depicted in the film), "Camelot" is the name of the castle where Arthur leads his men, the Knights of the Round Table, and then sets off elsewhere after deciding that it is "a silly place". Interestingly, the language in which this library is written (Python) was named after Monty Python.
 
 .. _The Camelot Project: http://www.planetpdf.com/planetpdf/pdfs/warnock_camelot.pdf
 .. _Monty Python and the Holy Grail: https://en.wikipedia.org/wiki/Monty_Python_and_the_Holy_Grail

docs/user/quickstart.rst

@@ -3,7 +3,7 @@
 Quickstart
 ==========
 
-In a hurry to extract tables from PDFs? This document gives a good introduction to help you get started with using Camelot.
+In a hurry to extract tables from PDFs? This document gives a good introduction to help you get started with Camelot.
 
 Read the PDF
 ------------
@@ -14,7 +14,7 @@ Begin by importing the Camelot module::
 
     >>> import camelot
 
-Now, let's try to read a PDF. You can check out the PDF used in this example, `here`_. Since the PDF has a table with clearly demarcated lines, we will use the :ref:`Lattice <lattice>` method here. To do that we will set the ``mesh`` keyword argument to ``True``.
+Now, let's try to read a PDF. (You can check out the PDF used in this example `here`_.) Since the PDF has a table with clearly demarcated lines, we will use the :ref:`Lattice <lattice>` method here. To do that, we will set the ``mesh`` keyword argument to ``True``.
 
 .. note:: :ref:`Lattice <lattice>` is used by default. You can use :ref:`Stream <stream>` with ``flavor='stream'``.
 
@@ -47,7 +47,7 @@ Let's print the parsing report.
         'page': 1
     }
 
-Woah! The accuracy is top-notch and whitespace is less, that means the table was extracted correctly (most probably). You can access the table as a pandas DataFrame by using the :class:`table <camelot.core.Table>` object's ``df`` property.
+Woah! The accuracy is top-notch and there is less whitespace, which means the table was most likely extracted correctly. You can access the table as a pandas DataFrame by using the :class:`table <camelot.core.Table>` object's ``df`` property.
 
 ::
 
@@ -56,7 +56,7 @@ Woah! The accuracy is top-notch and whitespace is less, that means the table was
 .. csv-table::
   :file: ../_static/csv/foo.csv
 
-Looks good! You can be export the table as a CSV file using its :meth:`to_csv() <camelot.core.Table.to_csv>` method. Alternatively you can use :meth:`to_json() <camelot.core.Table.to_json>`, :meth:`to_excel() <camelot.core.Table.to_excel>` or :meth:`to_html() <camelot.core.Table.to_html>` methods to export the table as JSON, Excel and HTML files respectively.
+Looks good! You can now export the table as a CSV file using its :meth:`to_csv() <camelot.core.Table.to_csv>` method. Alternatively you can use :meth:`to_json() <camelot.core.Table.to_json>`, :meth:`to_excel() <camelot.core.Table.to_excel>` or :meth:`to_html() <camelot.core.Table.to_html>` methods to export the table as JSON, Excel and HTML files respectively.
 
 ::
 
@@ -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')
 
-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``.
+.. tip::
+    Here's how you can do the same with the :ref:`command-line interface <cli>`.
+    ::
 
-------------------------
+        $ camelot --pages 1,2,3 lattice your.pdf
 
-Ready for more? Check out the :ref:`advanced <advanced>` section.
+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
+----------------------
+
+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.

requirements-dev.txt

@@ -1,4 +0,0 @@
-codecov==2.0.15
-pytest==3.8.0
-pytest-runner==4.2
-Sphinx==1.7.9

requirements.txt

@@ -1,7 +1,8 @@
-click==6.7
+click>=6.7
-matplotlib==2.2.3
+matplotlib>=2.2.3
-numpy==1.13.3
+numpy>=1.13.3
-opencv-python==3.4.2.17
+opencv-python>=3.4.2.17
-pandas==0.23.4
+openpyxl>=2.5.8
-pdfminer.six==20170720
+pandas>=0.23.4
-PyPDF2==1.26.0
+pdfminer.six>=20170720
+PyPDF2>=1.26.0

setup.cfg

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

setup.py

@@ -2,7 +2,6 @@
 
 import os
 from setuptools import find_packages
-from pkg_resources import parse_version
 
 
 here = os.path.abspath(os.path.dirname(__file__))
@@ -14,17 +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__'],
@@ -35,9 +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': [
@@ -49,16 +72,18 @@ def setup_package():
                         # Full list: https://pypi.python.org/pypi?%3Aaction=list_classifiers
                         'License :: OSI Approved :: MIT License',
                         'Programming Language :: Python :: 2.7',
-                        'Programming Language :: Python :: 3.6'
+                        'Programming Language :: Python :: 3.5',
+                        'Programming Language :: Python :: 3.6',
+                        'Programming Language :: Python :: 3.7'
                     ])
 
     try:
         from setuptools import setup
-    except:
+    except ImportError:
         from distutils.core import setup
 
     setup(**metadata)
 
 
 if __name__ == '__main__':
-    setup_package()
+    setup_package()

tests/__init__.py

@@ -0,0 +1,2 @@
+import matplotlib
+matplotlib.use('agg')

tests/data.py

@@ -0,0 +1,590 @@
+# -*- coding: utf-8 -*-
+
+from __future__ import unicode_literals
+
+
+data_stream = [
+    ["", "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", "", "", ""],
+    ["", "", "", "", "", "Capital", "", ""],
+    ["", "Public", "Welfare", "Public", "Welfare", "", "", ""],
+    ["", "Health", "", "Health", "", "", "", ""],
+    ["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"]
+]
+
+data_stream_table_rotated = [
+    ["Table 21  Current use of contraception by background characteristics\u2014Continued", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+    ["", "", "", "", "", "Modern method", "", "", "", "", "", "", "Traditional method", "", "", "", ""],
+    ["", "", "Any", "", "", "", "", "", "", "Other", "Any", "", "", "", "Not", "", "Number"],
+    ["", "Any", "modern", "Female", "Male", "", "", "", "Condom/", "modern", "traditional", "", "With-", "Folk", "currently", "", "of"],
+    ["Background characteristic", "method", "method", "sterilization", "sterilization", "Pill", "IUD", "Injectables", "Nirodh", "method", "method", "Rhythm", "drawal", "method", "using", "Total", "women"],
+    ["Caste/tribe", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+    ["Scheduled caste", "74.8", "55.8", "42.9", "0.9", "9.7", "0.0", "0.2", "2.2", "0.0", "19.0", "11.2", "7.4", "0.4", "25.2", "100.0", "1,363"],
+    ["Scheduled tribe", "59.3", "39.0", "26.8", "0.6", "6.4", "0.6", "1.2", "3.5", "0.0", "20.3", "10.4", "5.8", "4.1", "40.7", "100.0", "256"],
+    ["Other backward class", "71.4", "51.1", "34.9", "0.0", "8.6", "1.4", "0.0", "6.2", "0.0", "20.4", "12.6", "7.8", "0.0", "28.6", "100.0", "211"],
+    ["Other", "71.1", "48.8", "28.2", "0.8", "13.3", "0.9", "0.3", "5.2", "0.1", "22.3", "12.9", "9.1", "0.3", "28.9", "100.0", "3,319"],
+    ["Wealth index", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+    ["Lowest", "64.5", "48.6", "34.3", "0.5", "10.5", "0.6", "0.7", "2.0", "0.0", "15.9", "9.9", "4.6", "1.4", "35.5", "100.0", "1,258"],
+    ["Second", "68.5", "50.4", "36.2", "1.1", "11.4", "0.5", "0.1", "1.1", "0.0", "18.1", "11.2", "6.7", "0.2", "31.5", "100.0", "1,317"],
+    ["Middle", "75.5", "52.8", "33.6", "0.6", "14.2", "0.4", "0.5", "3.4", "0.1", "22.7", "13.4", "8.9", "0.4", "24.5", "100.0", "1,018"],
+    ["Fourth", "73.9", "52.3", "32.0", "0.5", "12.5", "0.6", "0.2", "6.3", "0.2", "21.6", "11.5", "9.9", "0.2", "26.1", "100.0", "908"],
+    ["Highest", "78.3", "44.4", "19.5", "1.0", "9.7", "1.4", "0.0", "12.7", "0.0", "33.8", "18.2", "15.6", "0.0", "21.7", "100.0", "733"],
+    ["Number of living children", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+    ["No children", "25.1", "7.6", "0.3", "0.5", "2.0", "0.0",
+    "0.0", "4.8", "0.0", "17.5", "9.0", "8.5", "0.0", "74.9", "100.0", "563"],
+    ["1 child", "66.5", "32.1", "3.7", "0.7", "20.1", "0.7", "0.1", "6.9", "0.0", "34.3", "18.9", "15.2", "0.3", "33.5", "100.0", "1,190"],
+    ["1 son", "66.8", "33.2", "4.1", "0.7", "21.1", "0.5", "0.3", "6.6", "0.0", "33.5", "21.2", "12.3", "0.0", "33.2", "100.0", "672"],
+    ["No sons", "66.1", "30.7", "3.1", "0.6", "18.8", "0.8", "0.0", "7.3", "0.0", "35.4", "15.8", "19.0", "0.6", "33.9", "100.0", "517"],
+    ["2 children", "81.6", "60.5", "41.8", "0.9", "11.6", "0.8", "0.3", "4.8", "0.2", "21.1", "12.2", "8.3", "0.6", "18.4", "100.0", "1,576"],
+    ["1 or more sons", "83.7", "64.2", "46.4", "0.9", "10.8", "0.8", "0.4", "4.8", "0.1", "19.5", "11.1", "7.6", "0.7", "16.3", "100.0", "1,268"],
+    ["No sons", "73.2", "45.5", "23.2", "1.0", "15.1", "0.9", "0.0", "4.8", "0.5", "27.7", "16.8", "11.0", "0.0", "26.8", "100.0", "308"],
+    ["3 children", "83.9", "71.2", "57.7", "0.8", "9.8", "0.6", "0.5", "1.8", "0.0", "12.7", "8.7", "3.3", "0.8", "16.1", "100.0", "961"],
+    ["1 or more sons", "85.0", "73.2", "60.3", "0.9", "9.4", "0.5", "0.5", "1.6", "0.0", "11.8", "8.1", "3.0", "0.7", "15.0", "100.0", "860"],
+    ["No sons", "74.7", "53.8", "35.3", "0.0", "13.7", "1.6", "0.0", "3.2", "0.0", "20.9", "13.4", "6.1", "1.5", "25.3", "100.0", "101"],
+    ["4+ children", "74.3", "58.1", "45.1", "0.6", "8.7", "0.6", "0.7", "2.4", "0.0", "16.1", "9.9", "5.4", "0.8", "25.7", "100.0", "944"],
+    ["1 or more sons", "73.9", "58.2", "46.0", "0.7", "8.3", "0.7", "0.7", "1.9", "0.0", "15.7", "9.4", "5.5", "0.8", "26.1", "100.0", "901"],
+    ["No sons", "(82.1)", "(57.3)", "(25.6)", "(0.0)", "(17.8)", "(0.0)", "(0.0)", "(13.9)", "(0.0)", "(24.8)", "(21.3)", "(3.5)", "(0.0)", "(17.9)", "100.0", "43"],
+    ["Total", "71.2", "49.9", "32.2",
+    "0.7", "11.7", "0.6", "0.3", "4.3", "0.1", "21.3", "12.3", "8.4", "0.5", "28.8", "100.0", "5,234"],
+    ["NFHS-2 (1998-99)", "66.6", "47.3", "32.0", "1.8", "9.2", "1.4", "na", "2.9", "na", "na", "8.7", "9.8", "na", "33.4", "100.0", "4,116"],
+    ["NFHS-1 (1992-93)", "57.7", "37.6", "26.5", "4.3", "3.6", "1.3", "0.1", "1.9", "na", "na", "11.3", "8.3", "na", "42.3", "100.0", "3,970"]
+]
+
+data_stream_two_tables_1 = [
+    ["[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"],
+    ["Total   .\n .\n .  .  .  .  .  .\n .  .\n .  .\n .  .\n .  .\n .  .\n .  .\n .  .\n .  .  .", "11,062 .6", "1,540 .0", "9,522 .6", "8,263 .3", "1,071 .6", "7,191 .7", "2,799 .2", "468 .3", "2,330 .9"],
+    ["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"],
+    ["Murder and nonnegligent", "", "", "", "", "", "", "", "", ""],
+    ["manslaughter . . . . . . . .\n. .\n. .\n. .\n. .\n.", "10.0", "0.9", "9.1", "9.0", "0.9", "8.1", "1.1", "–", "1.0"],
+    ["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", "$\n71.15"],
+    ["Biweekly", "142.31"],
+    ["Semimonthly", "154.17"],
+    ["Monthly", "308.33"],
+    ["Quarterly", "925.00"],
+    ["Semiannually", "1,850.00"],
+    ["Annually", "3,700.00"],
+    ["Daily or Miscellaneous", "14.23"],
+    ["(each day of the payroll period)", ""]
+]
+
+data_stream_columns = [
+    ["Clave", "Nombre Entidad", "Clave", "Nombre Municipio", "Clave", "Nombre Localidad"],
+    ["Entidad", "", "Municipio", "", "Localidad", ""],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0094", "Granja Adelita"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0096", "Agua Azul"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0100", "Rancho Alegre"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0102", "Los Arbolitos [Rancho]"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0104", "Ardillas de Abajo (Las Ardillas)"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0106", "Arellano"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0112", "Baj\xedo los V\xe1zquez"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0113", "Baj\xedo de Montoro"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0114", "Residencial San Nicol\xe1s [Ba\xf1os la Cantera]"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0120", "Buenavista de Pe\xf1uelas"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0121", "Cabecita 3 Mar\xedas (Rancho Nuevo)"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0125", "Ca\xf1ada Grande de Cotorina"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0126", "Ca\xf1ada Honda [Estaci\xf3n]"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0127", "Los Ca\xf1os"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0128", "El Cari\xf1\xe1n"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0129", "El Carmen [Granja]"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0135", "El Cedazo (Cedazo de San Antonio)"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0138", "Centro de Arriba (El Taray)"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0139", "Cieneguilla (La Lumbrera)"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0141", "Cobos"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0144", "El Colorado (El Soyatal)"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0146", "El Conejal"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0157", "Cotorina de Abajo"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0162", "Coyotes"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0166", "La Huerta (La Cruz)"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0170", "Cuauht\xe9moc (Las Palomas)"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0171", "Los Cuervos (Los Ojos de Agua)"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0172", "San Jos\xe9 [Granja]"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0176", "La Chiripa"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0182", "Dolores"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0183", "Los Dolores"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0190", "El Duraznillo"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0191", "Los Dur\xf3n"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0197", "La Escondida"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0201", "Brande Vin [Bodegas]"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0207", "Valle Redondo"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0209", "La Fortuna"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0212", "Lomas del Gachup\xedn"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0213", "El Carmen (Gallinas G\xfceras) [Rancho]"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0216", "La Gloria"],
+    ["01", "Aguascalientes", "001", "Aguascalientes", "0226", "Hacienda Nueva"]
+]
+
+data_stream_split_text = [
+    ["FEB", "RUAR", "Y 2014 M27 (BUS)", "", "ALPHABETIC LISTING BY T", "YPE", "", "", "", "ABLPDM27"],
+    ["", "", "", "", "OF ACTIVE LICENSES", "", "", "", "", "3/19/2014"],
+    ["", "", "", "", "OKLAHOMA ABLE COMMIS", "SION", "", "", "", ""],
+    ["LICENSE", "", "", "", "PREMISE", "", "", "", "", ""],
+    ["NUMBER", "TYPE", "DBA NAME", "LICENSEE NAME", "ADDRESS", "CITY", "ST", "ZIP", "PHONE NUMBER", "EXPIRES"],
+    ["648765", "AAA", "ALLEGIANT AIR", "ALLEGIANT AIR LLC", "7100 TERMINAL DRIVE", "OKLAHOMA CITY", "OK", "73159", "-", "2014/12/03"],
+    ["", "", "", "", "7777 EAST APACHE", "", "", "", "", ""],
+    ["648766", "AAA", "ALLEGIANT AIR", "ALLEGIANT AIR LLC", "STREET", "TULSA", "OK", "74115", "-", "2014/12/16"],
+    ["82030", "AAA", "AMERICAN AIRLINES", "AMERICAN AIRLINES INC", "7100 TERMINAL DRIVE", "OKLAHOMA CITY", "OK", "73159", "(405) 680-3701", "2014/09/14"],
+    ["509462", "AAA", "AMERICAN AIRLINES", "AMERICAN AIRLINES INC", "7777 EAST APACHE DRIVE", "TULSA", "OK", "74115", "(918) 831-6302", "2014/08/19"],
+    ["", "", "", "AMERICAN EAGLE", "", "", "", "", "", ""],
+    ["509609", "AAA", "AMERICAN EAGLE", "AIRLINES INC", "7100 TERMINAL DRIVE", "OKLAHOMA CITY", "OK", "73159", "(405) 680-3701", "2014/08/19"],
+    ["", "", "", "AMERICAN EAGLE", "", "", "", "", "", ""],
+    ["402986", "AAA", "AMERICAN EAGLE", "AIRLINES INC", "7777 EAST APACHE DRIVE", "TULSA", "OK", "74115", "(859) 767-3747", "2014/10/22"],
+    ["", "", "", "", "WILL ROGERS AIRPORT", "", "", "", "", ""],
+    ["79145", "AAA", "DELTA AIR LINES", "DELTA AIR LINES INC", "BOX 59975", "OKLAHOMA CITY", "OK", "73159", "(404) 773-9745", "2014/05/11"],
+    ["600941", "AAA", "ENDEAVOR AIR", "ENDEAVOR AIR INC", "7100 TERMINAL DRIVE", "OKLAHOMA CITY", "OK", "73159", "(901) 348-4100", "2015/03/26"],
+    ["", "", "", "", "7100 TERMINAL DRIVE", "", "", "", "", ""],
+    ["478482", "AAA", "EXPRESSJET AIRLINES", "EXPRESSJET AIRLINES INC", "WILL ROGERS AIRPORT", "OKLAHOMA CITY", "OK", "73159", "(832) 353-1201", "2014/05/08"],
+    ["505981", "AAA", "SKYWEST AIRLINES", "SKYWEST INC", "7100 TERMINAL DRIVE", "OKLAHOMA CITY", "OK", "73159", "(405) 634-3000", "2014/05/28"],
+    ["429754", "AAA", "SOUTHWEST AIRLINES", "SOUTHWEST AIRLINES CO", "7100 TERMINAL DRIVE", "OKLAHOMA CITY", "OK", "73159", "(405) 682-4183", "2015/02/15"],
+    ["", "", "TULSA INTERNATIONAL", "", "", "", "", "", "", ""],
+    ["429755", "AAA", "AIRPORT", "SOUTHWEST AIRLINES CO", "7777 EAST APACHE DRIVE", "TULSA", "OK", "74115", "(918) 834-4495", "2015/02/16"],
+    ["415051", "AAA", "UNITED AIRLINES", "UNITED AIRLINES INC", "7777 EAST APACHE DRIVE", "TULSA", "OK", "74115", "(872) 825-8309", "2014/05/12"],
+    ["106719", "AAA", "UNITED AIRLINES", "UNITED AIRLINES INC", "WILL ROGERS AIRPORT", "OKLAHOMA CITY", "OK", "73159", "(872) 825-8309", "2014/04/11"],
+    ["", "", "A SENSU JAPANESE", "", "7123 SOUTH 92ND EAST", "", "", "", "", ""],
+    ["625422", "BAW", "RESTAURANT", "INFORMAL PARTNERSHIP", "AVENUE SUITE J", "TULSA", "OK", "74133", "(918) 252-0333", "2015/02/14"],
+    ["", "", "ADAMO'S ROUTE 66", "", "2132 WEST GARY", "", "", "", "", ""],
+    ["464828", "BAW", "ITALIAN VILLA", "TADJ INC", "BOULEVARD", "CLINTON", "OK", "73601", "(580) 323-5900", "2015/02/11"],
+    ["", "", "", "", "12215 NORTH", "", "", "", "", ""],
+    ["184066", "BAW", "AJANTA", "CABAB N' CURRY INC", "PENNSYLVANIA", "OKLAHOMA CITY", "OK", "73120", "(405) 752-5283", "2014/07/27"],
+    ["", "", "", "SAYRE LODGING", "", "", "", "", "", ""],
+    ["547693", "BAW", "AMERICINN OF SAYRE", "ENTERPRISES LLC", "2405 SOUTH EL CAMINO", "SAYRE", "OK", "73662", "(580) 928-2700", "2014/09/08"],
+    ["", "", "ANDOLINI'S PIZZERIA &", "", "12140 EAST 96TH STREET", "", "", "", "", ""],
+    ["428377", "BAW", "ITALIAN RESTAURANT", "ANDOLINI'S LLC", "NORTH #106", "OWASSO", "OK", "74055", "(918) 272-9325", "2015/02/10"],
+    ["", "", "ASAHI JAPANESE", "", "", "", "", "", "", ""],
+    ["446957", "BAW", "RESTAURANT", "JIN CORPORATION", "7831 EAST 71ST STREET", "TULSA", "OK", "74133", "(918) 307-9151", "2014/12/22"],
+    ["", "", "", "SMOKEHOUSE", "", "", "", "", "", ""],
+    ["632501", "BAW", "BACK DOOR BARBECUE", "ASSOCIATES INC", "315 NORTHWEST 23RD", "OKLAHOMA CITY", "OK", "73103", "-", "2014/08/01"],
+    ["598515", "BAW", "BAMBOO THAI BISTRO", "BAMBOO THAI BISTRO INC", "5079 SOUTH YALE AVENUE", "TULSA", "OK", "74135", "(918) 828-0740", "2015/03/11"],
+    ["", "", "BANDANA RED'S", "", "", "", "", "", "", ""],
+    ["618693", "BAW", "STEAKHOUSE", "BRADSHAW, STEVE_LEN", "37808 OLD HIGHWAY 270", "SHAWNEE", "OK", "74804", "-", "2014/08/20"],
+    ["", "", "", "", "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"]
+]
+
+data_stream_flag_size = [
+    ["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"],
+    ["", "", "", "", "", "& FIs", "", "", "", "Banks", ""],
+    ["1", "2=", "3", "4", "5", "6=", "7", "8", "9", "10", "11"],
+    ["", "(3 to 6)+14", "", "", "", "(7 to13)", "", "", "", "", ""],
+    ["Andhra Pradesh", "48.11", "40.45", "-", "3.26", "4.4", "2.62", "-", "0.91", "-", "0.25"],
+    ["Arunachal Pradesh", "1.23", "1.1", "-", "-", "0.13", "-", "-", "-", "-", "-"],
+    ["Assam", "12.69", "10.02", "-", "2.41", "0.26", "0.08", "-", "-0.06", "0.01", "0.24"],
+    ["Bihar", "40.75", "41.54", "-", "-", "-1.42", "0.19", "-", "-1.01", "-0.36", "0.2"],
+    ["Chhattisgarh", "-", "-", "-", "-", "-", "-", "-", "-", "-", "-"],
+    ["Goa", "1.4", "1.02", "-", "-", "0.38", "0.31", "-", "0.07", "-", "-"],
+    ["Gujarat", "19.75", "17.1", "-", "-", "2.64", "1.17", "-", "1.11", "-", "0.44"],
+    ["Haryana", "11.53", "9.67", "-", "0.06", "1.8", "0.55", "-", "0.64", "-", "0.49"],
+    ["Himachal Pradesh", "8.02", "2.94", "-", "4.55", "0.53", "0.13", "-", "0.05", "-", "0.25"],
+    ["Jammu and Kashmir", "11.72", "4.49", "-", "-", "7.23", "0.66", "-", "0.02", "6.08", "-"],
+    ["Jharkhand", "-", "-", "-", "-", "-", "-", "-", "-", "-", "-"],
+    ["Karnataka", "22.44", "19.59", "-", "-", "2.86", "1.22", "-", "0.89", "-", "0.69"],
+    ["Kerala", "29.03", "24.91<s>2</s>", "-", "-", "4.11", "1.77", "-", "0.48", "-", "1.45"],
+    ["Madhya Pradesh", "27.13", "23.57", "-", "-", "3.56", "0.38", "-", "1.86", "-", "1.28"],
+    ["Maharashtra", "30.47", "26.07", "-", "-", "4.39", "0.21", "-", "-0.12", "0.02", "2.89"],
+    ["Manipur", "2.17", "1.61", "-", "0.26", "0.29", "0.08", "-", "-", "-", "0.09"],
+    ["Meghalaya", "1.36", "1.38", "-", "-", "-0.02", "0.04", "-", "-0.05", "-", "0.03"],
+    ["Mizoram", "1.17", "0.46", "-", "0.27", "0.43", "0.11", "-", "-", "-", "0.03"],
+    ["Nagaland", "2.99", "2.6", "-", "-", "0.39", "0.24", "-", "-", "-", "0.04"],
+    ["Odisha", "34.04", "27.58", "-", "4.4", "2.06", "0.56", "-", "0.66", "-", "0.2"],
+    ["Punjab", "19.18", "10.93", "-", "1.03", "7.23", "0.17", "-", "0.71", "5.9", "0.46"],
+    ["Rajasthan", "36.77", "28.63", "-", "4.99", "3.16", "0.57", "-", "1.64", "-", "0.81"],
+    ["Sikkim", "0.16", "-", "-", "-", "0.16", "0.03", "-", "-", "-", "0.01"],
+    ["Tamil Nadu", "34.11", "31.41", "-", "-", "2.7", "1.3", "-", "0.6", "-", "0.68"],
+    ["Tripura", "2.3", "1.89", "-", "-", "0.41", "0.41", "-", "-0.05", "-", "0.02"],
+    ["Uttaranchal", "-", "-", "-", "-", "-", "-", "-", "-", "-", "-"],
+    ["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"]
+]
+
+data_stream_strip_text = [
+    ["V i n s   a u   Ve r r e", ""],
+    ["Les Blancs", "12.5CL"],
+    ["A.O.P Côtes du Rhône", ""],
+    ["Domaine de la Guicharde «  Autour de la chapelle » 2016", "8 €"],
+    ["A.O.P Vacqueyras", ""],
+    ["Domaine de Montvac  « Melodine » 2016", "10 €"],
+    ["A.O.P Châteauneuf du Pape", ""],
+    ["Domaine de Beaurenard 2017", "13 €"],
+    ["A.O.P Côteaux du Languedoc", ""],
+    ["Villa Tempora « Un temps pour elle » 2014", "9 €"],
+    ["A.O.P Côtes de Provence", ""],
+    ["Château Grand Boise 2017", "9 €"],
+    ["Les Rosés", "12,5 CL"],
+    ["A.O.P Côtes du Rhône", ""],
+    ["Domaine de la Florane « A fleur de Pampre » 2016", "8 €"],
+    ["Famille Coulon (Domaine Beaurenard) Biotifulfox 2017", "8 €"],
+    ["A.O.P Vacqueyras", ""],
+    ["Domaine de Montvac 2017", "9 €"],
+    ["A.O.P Languedoc", ""],
+    ["Domaine de Joncas « Nébla » 2015", "8 €"],
+    ["Villa Tempora « L’arroseur arrosé » 2015", "9 €"],
+    ["A.O.P Côtes de Provence", ""],
+    ["Château Grand Boise « Sainte Victoire » 2017", "9 €"],
+    ["Château Léoube 2016", "10 €"]
+]
+
+data_stream_edge_tol = [
+    ["Key figures", ""],
+    ["", "2016"],
+    ["(all amounts in EUR)", ""],
+    ["C\nlass A", ""],
+    ["N\net Asset Value at 31 December", "5,111,372"],
+    ["N\number of outstanding units at 31 December", "49,136"],
+    ["N\net Asset Value per unit at 31 December", "104.03"],
+    ["C\nlass B", ""],
+    ["N\net Asset Value at 31 December", "49,144,825"],
+    ["N\number of outstanding units at 31 December", "471,555"],
+    ["N\net Asset Value per unit at 31 December", "104.22"],
+    ["T\notal for the Fund", ""],
+    ["N\net Asset Value at 31 December", "54,256,197"],
+    ["N\number of outstanding units at 31 December", "520,691"],
+    ["I\nnvestment result", ""],
+    ["Direct result", "-"],
+    ["Revaluation", "2,076,667"],
+    ["Costs", "(106,870)"],
+    ["T\notal investment result for the period1", "1,969,797"],
+    ["I\nnvestment result per unit2", ""],
+    ["Direct result", "-"],
+    ["Revaluation", "3.99"],
+    ["Costs", "(0.21)"],
+    ["T\notal investment result per unit", "3.78"],
+    ["1 The results cover the period from inception of the Fund at 8 April 2016 through 31 December 2016.", ""],
+    ["2 The result per unit is calculated using the total number of outstanding unit as per the end of the", ""],
+    ["period.", ""]
+]
+
+data_lattice = [
+    ["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%"],
+    ["2032_2", "0.17", "57.8", "21.7%", "0.3%", "2.7%", "1.2%"],
+    ["4171_1", "0.07", "173.9", "58.1%", "1.6%", "2.1%", "0.5%"]
+]
+
+data_lattice_table_rotated = [
+    ["State", "Nutritional Assessment  \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"],
+    ["Karnataka", "6453", "8138", "12606", "8958", "428", "2467", "2894", "1628", "2028"],
+    ["Andhra Pradesh", "5844", "9920", "9545", "8300", "557", "1899", "2493", "1111", "1529"],
+    ["Maharashtra", "5161", "7796", "6883", "9525", "467", "2368", "2648", "1417", "1599"],
+    ["Gujarat", "4403", "5374", "4866", "9645", "477", "2687", "3021", "2122", "2503"],
+    ["Madhya Pradesh", "*", "*", "*", "7942", "470", "1965", "2150", "1579", "1709"],
+    ["Orissa", "3756", "5540", "12024", "8473", "398", "2040", "2624", "1093", "1628"],
+    ["West Bengal", "*", "*", "*", "8047", "423", "2058", "2743", "1413", "2027"],
+    ["Uttar Pradesh", "*", "*", "*", "9860", "581", "2139", "2415", "1185", "1366"],
+    ["Pooled", "38742", "53618", "60601", "86898", "4459", "21918", "27041", "14312", "18519"]
+]
+
+data_lattice_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 & \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_process_background = [
+    ["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 \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"]
+]
+
+data_lattice_copy_text = [
+    ["Plan Type", "County", "Plan Name", "Totals"],
+    ["GMC", "Sacramento", "Anthem Blue Cross", "164,380"],
+    ["GMC", "Sacramento", "Health Net", "126,547"],
+    ["GMC", "Sacramento", "Kaiser Foundation", "74,620"],
+    ["GMC", "Sacramento", "Molina Healthcare", "59,989"],
+    ["GMC", "San Diego", "Care 1st Health Plan", "71,831"],
+    ["GMC", "San Diego", "Community Health Group", "264,639"],
+    ["GMC", "San Diego", "Health Net", "72,404"],
+    ["GMC", "San Diego", "Kaiser", "50,415"],
+    ["GMC", "San Diego", "Molina Healthcare", "206,430"],
+    ["GMC", "Total GMC Enrollment", "", "1,091,255"],
+    ["COHS", "Marin", "Partnership Health Plan of CA", "36,006"],
+    ["COHS", "Mendocino", "Partnership Health Plan of CA", "37,243"],
+    ["COHS", "Napa", "Partnership Health Plan of CA", "28,398"],
+    ["COHS", "Solano", "Partnership Health Plan of CA", "113,220"],
+    ["COHS", "Sonoma", "Partnership Health Plan of CA", "112,271"],
+    ["COHS", "Yolo", "Partnership Health Plan of CA", "52,674"],
+    ["COHS", "Del Norte", "Partnership Health Plan of CA", "11,242"],
+    ["COHS", "Humboldt", "Partnership Health Plan of CA", "49,911"],
+    ["COHS", "Lake", "Partnership Health Plan of CA", "29,149"],
+    ["COHS", "Lassen", "Partnership Health Plan of CA", "7,360"],
+    ["COHS", "Modoc", "Partnership Health Plan of CA", "2,940"],
+    ["COHS", "Shasta", "Partnership Health Plan of CA", "61,763"],
+    ["COHS", "Siskiyou", "Partnership Health Plan of CA", "16,715"],
+    ["COHS", "Trinity", "Partnership Health Plan of CA", "4,542"],
+    ["COHS", "Merced", "Central California Alliance for Health", "123,907"],
+    ["COHS", "Monterey", "Central California Alliance for Health", "147,397"],
+    ["COHS", "Santa Cruz", "Central California Alliance for Health", "69,458"],
+    ["COHS", "Santa Barbara", "CenCal", "117,609"],
+    ["COHS", "San Luis Obispo", "CenCal", "55,761"],
+    ["COHS", "Orange", "CalOptima", "783,079"],
+    ["COHS", "San Mateo", "Health Plan of San Mateo", "113,202"],
+    ["COHS", "Ventura", "Gold Coast Health Plan", "202,217"],
+    ["COHS", "Total COHS Enrollment", "", "2,176,064"],
+    ["Subtotal for Two-Plan, Regional Model, GMC and COHS", "", "", "10,132,022"],
+    ["PCCM", "Los Angeles", "AIDS Healthcare Foundation", "828"],
+    ["PCCM", "San Francisco", "Family Mosaic", "25"],
+    ["PCCM", "Total PHP Enrollment", "", "853"],
+    ["All Models Total Enrollments", "", "", "10,132,875"],
+    ["Source:   Data Warehouse \n12/14/15", "", "", ""]
+]
+
+data_lattice_shift_text_left_top = [
+    ["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", "", "", "", "", "", ""],
+    ["Diet survey", "1200", "All the individuals partaking meals in the HH", "", "", "", ""],
+    ["Blood Pressure #", "2400", "Men (≥ 18yrs)", "10%", "95%", "20%", "1728"],
+    ["", "", "Women (≥ 18 yrs)", "", "", "", "1728"],
+    ["Fasting blood glucose", "2400", "Men (≥ 18 yrs)", "5%", "95%", "20%", "1825"],
+    ["", "", "Women (≥ 18 yrs)", "", "", "", "1825"],
+    ["Knowledge &\nPractices on HTN &\nDM", "2400", "Men (≥ 18 yrs)", "-", "-", "-", "1728"],
+    ["", "2400", "Women (≥ 18 yrs)", "-", "-", "-", "1728"]
+]
+
+data_lattice_shift_text_disable = [
+    ["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", "", "", "", "", "", ""],
+    ["Diet survey", "1200", "", "All the individuals partaking meals in the HH", "", "", ""],
+    ["", "", "Men (≥ 18yrs)", "", "", "", "1728"],
+    ["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 &\nPractices on HTN &", "2400", "Men (≥ 18 yrs)", "-", "-", "-", "1728"],
+    ["DM", "2400", "Women (≥ 18 yrs)", "-", "-", "-", "1728"]
+]
+
+data_lattice_shift_text_right_bottom = [
+    ["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"],
+    ["Diet survey", "1200", "", "", "", "", "All the individuals partaking meals in the HH"],
+    ["", "", "Men (≥ 18yrs)", "", "", "", "1728"],
+    ["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"],
+    ["", "2400", "Men (≥ 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", ""]
+]
+
+data_stream_layout_kwargs = [
+    ["V i n s   a u   Ve r r e", ""],
+    ["Les Blancs", "12.5CL"],
+    ["A.O.P Côtes du Rhône", ""],
+    ["Domaine de la Guicharde «  Autour de la chapelle » 2016", "8 €"],
+    ["A.O.P Vacqueyras", ""],
+    ["Domaine de Montvac  « Melodine » 2016", "10 €"],
+    ["A.O.P Châteauneuf du Pape", ""],
+    ["Domaine de Beaurenard 2017", "13 €"],
+    ["A.O.P Côteaux du Languedoc", ""],
+    ["Villa Tempora « Un temps pour elle » 2014", "9 €"],
+    ["A.O.P Côtes de Provence", ""],
+    ["Château Grand Boise 2017", "9 €"],
+    ["Les Rosés", "12,5 CL"],
+    ["A.O.P Côtes du Rhône", ""],
+    ["Domaine de la Florane « A fleur de Pampre » 2016", "8 €"],
+    ["Famille Coulon (Domaine Beaurenard) Biotifulfox 2017", "8 €"],
+    ["A.O.P Vacqueyras", ""],
+    ["Domaine de Montvac 2017", "9 €"],
+    ["A.O.P Languedoc", ""],
+    ["Domaine de Joncas « Nébla » 2015", "8 €"],
+    ["Villa Tempora « L’arroseur arrosé » 2015", "9 €"],
+    ["A.O.P Côtes de Provence", ""],
+    ["Château Grand Boise « Sainte Victoire » 2017", "9 €"],
+    ["Château Léoube 2016", "10 €"],
+    ["Les Rouges", "12,CL"],
+    ["A.O.P Côtes du Rhône", ""],
+    ["Domaine de Dionysos « La Cigalette »", "8 €"],
+    ["Château Saint Estève d’Uchaux « Grande Réserve » 2014", "9 €"],
+    ["Domaine de la Guicharde « Cuvée Massillan » 2016", "9 €"],
+    ["Domaine de la Florane « Terre Pourpre » 2014", "10 €"],
+    ["L’Oratoire St Martin « Réserve des Seigneurs » 2015", "11 €"],
+    ["A.O.P Saint Joseph", ""],
+    ["Domaine Monier Perréol « Châtelet » 2015", "13 €"],
+    ["A.O.P Châteauneuf du Pape", ""],
+    ["Domaine de Beaurenard 2011", "15 €"],
+    ["A.O.P Cornas", ""],
+    ["Domaine Lionnet « Terre Brûlée » 2012", "15 €"]
+]

tests/files/foo.csv

@@ -0,0 +1,2 @@
+"a","b"
+"1","2"

tests/test_cli.py

@@ -0,0 +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_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

tests/test_common.py

@@ -6,14 +6,42 @@ import pandas as pd
 
 import camelot
 
-from test_data import *
+from .data import *
 
 testdir = os.path.dirname(os.path.abspath(__file__))
 testdir = os.path.join(testdir, "files")
 
 
+def test_parsing_report():
+    parsing_report = {
+        'accuracy': 99.02,
+        'whitespace': 12.24,
+        'order': 1,
+        'page': 1
+    }
+
+    filename = os.path.join(testdir, "foo.pdf")
+    tables = camelot.read_pdf(filename)
+    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():
-    pass
+    df = pd.DataFrame(data_stream)
+
+    filename = os.path.join(testdir, "health.pdf")
+    tables = camelot.read_pdf(filename, flavor="stream")
+    assert df.equals(tables[0].df)
 
 
 def test_stream_table_rotated():
@@ -28,11 +56,23 @@ def test_stream_table_rotated():
     assert df.equals(tables[0].df)
 
 
-def test_stream_table_area():
+def test_stream_two_tables():
-    df = pd.DataFrame(data_stream_table_area_single)
+    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)
 
 
@@ -41,15 +81,57 @@ def test_stream_columns():
 
     filename = os.path.join(testdir, "mexican_towns.pdf")
     tables = camelot.read_pdf(
-        filename, flavor="stream", columns=["67,180,230,425,475"], row_close_tol=10)
+        filename, flavor="stream", columns=["67,180,230,425,475"], row_tol=10)
+    assert df.equals(tables[0].df)
+
+
+def test_stream_split_text():
+    df = pd.DataFrame(data_stream_split_text)
+
+    filename = os.path.join(testdir, "tabula/m27.pdf")
+    tables = camelot.read_pdf(
+        filename, flavor="stream", columns=["72,95,209,327,442,529,566,606,683"], split_text=True)
+    assert df.equals(tables[0].df)
+
+
+def test_stream_flag_size():
+    df = pd.DataFrame(data_stream_flag_size)
+
+    filename = os.path.join(testdir, "superscript.pdf")
+    tables = camelot.read_pdf(filename, flavor="stream", flag_size=True)
+    assert df.equals(tables[0].df)
+
+
+def test_stream_strip_text():
+    df = pd.DataFrame(data_stream_strip_text)
+
+    filename = os.path.join(testdir, "detect_vertical_false.pdf")
+    tables = camelot.read_pdf(filename, flavor="stream", strip_text="\n")
+    assert df.equals(tables[0].df)
+
+
+def test_stream_edge_tol():
+    df = pd.DataFrame(data_stream_edge_tol)
+
+    filename = os.path.join(testdir, "edge_tol.pdf")
+    tables = camelot.read_pdf(filename, flavor="stream", edge_tol=500)
+    assert df.equals(tables[0].df)
+
+
+def test_stream_layout_kwargs():
+    df = pd.DataFrame(data_stream_layout_kwargs)
+
+    filename = os.path.join(testdir, "detect_vertical_false.pdf")
+    tables = camelot.read_pdf(
+        filename, flavor="stream", layout_kwargs={"detect_vertical": False})
     assert df.equals(tables[0].df)
 
 
 def test_lattice():
     df = pd.DataFrame(data_lattice)
 
-    filename = os.path.join(testdir,
+    filename = os.path.join(
-        "tabula/icdar2013-dataset/competition-dataset-us/us-030.pdf")
+        testdir, "tabula/icdar2013-dataset/competition-dataset-us/us-030.pdf")
     tables = camelot.read_pdf(filename, pages="2")
     assert df.equals(tables[0].df)
 
@@ -66,6 +148,25 @@ def test_lattice_table_rotated():
     assert df.equals(tables[0].df)
 
 
+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)
+    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)
+
+
 def test_lattice_process_background():
     df = pd.DataFrame(data_lattice_process_background)
 
@@ -79,4 +180,44 @@ def test_lattice_copy_text():
 
     filename = os.path.join(testdir, "row_span_1.pdf")
     tables = camelot.read_pdf(filename, line_size_scaling=60, copy_text="v")
-    assert df.equals(tables[0].df)
+    assert df.equals(tables[0].df)
+
+
+def test_lattice_shift_text():
+    df_lt = pd.DataFrame(data_lattice_shift_text_left_top)
+    df_disable = pd.DataFrame(data_lattice_shift_text_disable)
+    df_rb = pd.DataFrame(data_lattice_shift_text_right_bottom)
+
+    filename = os.path.join(testdir, "column_span_2.pdf")
+    tables = camelot.read_pdf(filename, line_size_scaling=40)
+    assert df_lt.equals(tables[0].df)
+
+    tables = camelot.read_pdf(filename, line_size_scaling=40, shift_text=[''])
+    assert df_disable.equals(tables[0].df)
+
+    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=218.43 x2=164.64 y2=233.77>"
+
+
+def test_url():
+    url = "https://camelot-py.readthedocs.io/en/master/_static/pdf/foo.pdf"
+    tables = camelot.read_pdf(url)
+    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=218.43 x2=164.64 y2=233.77>"
+
+
+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)

tests/test_data.py

@@ -1,188 +0,0 @@
-# -*- coding: utf-8 -*-
-
-from __future__ import unicode_literals
-
-
-data_stream_table_rotated = [
-    ["", "", "Table 21  Current use of contraception by background characteristics\u2014Continued", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "", "", "", "", "", "Modern method", "", "", "", "", "", "", "Traditional method", "", "", "", ""],
-    ["", "", "", "Any", "", "", "", "", "", "", "Other", "Any","", "", "", "Not", "", "Number"],
-    ["", "", "Any", "modern", "Female", "Male", "", "", "", "Condom/", "modern", "traditional", "", "With-", "Folk", "currently", "", "of"],
-    ["", "Background characteristic", "method", "method", "sterilization", "sterilization", "Pill", "IUD", "Injectables", "Nirodh", "method", "method", "Rhythm", "drawal", "method", "using", "Total", "women"],
-    ["", "Caste/tribe", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "Scheduled caste", "74.8", "55.8", "42.9", "0.9", "9.7", "0.0", "0.2", "2.2", "0.0", "19.0", "11.2", "7.4", "0.4", "25.2", "100.0", "1,363"],
-    ["", "Scheduled tribe", "59.3", "39.0", "26.8", "0.6", "6.4", "0.6", "1.2", "3.5", "0.0", "20.3", "10.4", "5.8", "4.1", "40.7", "100.0", "256"],
-    ["", "Other backward class", "71.4", "51.1", "34.9", "0.0", "8.6", "1.4", "0.0", "6.2", "0.0", "20.4", "12.6", "7.8", "0.0", "28.6", "100.0", "211"],
-    ["", "Other", "71.1","48.8", "28.2", "0.8", "13.3", "0.9", "0.3", "5.2", "0.1", "22.3", "12.9", "9.1", "0.3", "28.9", "100.0", "3,319"],
-    ["", "Wealth index", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "Lowest", "64.5", "48.6", "34.3", "0.5", "10.5", "0.6", "0.7", "2.0", "0.0", "15.9", "9.9", "4.6", "1.4", "35.5", "100.0", "1,258"],
-    ["", "Second", "68.5", "50.4", "36.2", "1.1", "11.4", "0.5", "0.1", "1.1", "0.0", "18.1", "11.2", "6.7", "0.2", "31.5", "100.0", "1,317"],
-    ["", "Middle", "75.5", "52.8", "33.6", "0.6", "14.2", "0.4", "0.5", "3.4", "0.1", "22.7", "13.4", "8.9", "0.4", "24.5", "100.0", "1,018"],
-    ["", "Fourth", "73.9", "52.3", "32.0", "0.5", "12.5", "0.6", "0.2", "6.3", "0.2", "21.6", "11.5", "9.9", "0.2", "26.1", "100.0", "908"],
-    ["", "Highest", "78.3", "44.4", "19.5", "1.0", "9.7", "1.4", "0.0", "12.7", "0.0", "33.8", "18.2", "15.6", "0.0", "21.7", "100.0", "733"],
-    ["", "Number of living children", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "No children", "25.1", "7.6", "0.3", "0.5", "2.0", "0.0",
-    "0.0", "4.8", "0.0", "17.5", "9.0", "8.5", "0.0", "74.9", "100.0", "563"],
-    ["", "1 child", "66.5", "32.1", "3.7", "0.7", "20.1", "0.7", "0.1", "6.9", "0.0", "34.3", "18.9", "15.2", "0.3", "33.5", "100.0", "1,190"],
-    ["\x18\x18", "1 son", "66.8", "33.2", "4.1", "0.7", "21.1", "0.5", "0.3", "6.6", "0.0", "33.5", "21.2", "12.3", "0.0", "33.2", "100.0", "672"],
-    ["", "No sons", "66.1", "30.7", "3.1", "0.6", "18.8", "0.8", "0.0", "7.3", "0.0", "35.4", "15.8", "19.0", "0.6", "33.9", "100.0", "517"],
-    ["", "2 children", "81.6", "60.5", "41.8", "0.9", "11.6", "0.8", "0.3", "4.8", "0.2", "21.1", "12.2", "8.3", "0.6", "18.4", "100.0", "1,576"],
-    ["", "1 or more sons", "83.7", "64.2", "46.4", "0.9", "10.8", "0.8", "0.4", "4.8", "0.1", "19.5", "11.1", "7.6", "0.7", "16.3", "100.0", "1,268"],
-    ["", "No sons", "73.2", "45.5", "23.2", "1.0", "15.1", "0.9", "0.0", "4.8", "0.5", "27.7", "16.8", "11.0", "0.0", "26.8", "100.0", "308"],
-    ["", "3 children", "83.9", "71.2", "57.7", "0.8", "9.8", "0.6", "0.5", "1.8", "0.0", "12.7", "8.7", "3.3", "0.8", "16.1", "100.0", "961"],
-    ["", "1 or more sons", "85.0", "73.2", "60.3", "0.9", "9.4", "0.5", "0.5", "1.6", "0.0", "11.8", "8.1", "3.0", "0.7", "15.0", "100.0", "860"],
-    ["", "No sons", "74.7", "53.8", "35.3", "0.0", "13.7", "1.6", "0.0", "3.2", "0.0", "20.9", "13.4", "6.1", "1.5", "25.3", "100.0", "101"],
-    ["", "4+ children", "74.3", "58.1", "45.1", "0.6", "8.7", "0.6", "0.7", "2.4", "0.0", "16.1", "9.9", "5.4", "0.8", "25.7", "100.0", "944"],
-    ["", "1 or more sons", "73.9", "58.2", "46.0", "0.7", "8.3", "0.7", "0.7", "1.9", "0.0", "15.7", "9.4", "5.5", "0.8", "26.1", "100.0", "901"],
-    ["", "No sons", "(82.1)", "(57.3)", "(25.6)", "(0.0)", "(17.8)", "(0.0)", "(0.0)", "(13.9)", "(0.0)", "(24.8)", "(21.3)", "(3.5)", "(0.0)", "(17.9)", "100.0", "43"],
-    ["", "Total", "71.2", "49.9", "32.2",
-    "0.7", "11.7", "0.6", "0.3", "4.3", "0.1", "21.3", "12.3", "8.4", "0.5", "28.8", "100.0", "5,234"],
-    ["", "NFHS-2 (1998-99)", "66.6", "47.3", "32.0", "1.8", "9.2", "1.4", "na", "2.9", "na", "na", "8.7", "9.8", "na", "33.4", "100.0", "4,116"],
-    ["", "NFHS-1 (1992-93)", "57.7", "37.6", "26.5", "4.3", "3.6", "1.3", "0.1", "1.9", "na", "na", "11.3", "8.3", "na", "42.3", "100.0", "3,970"],
-    ["", "", "Note: If more than one method is used, only the most effective method is considered in this tabulation. Total includes women for whom caste/tribe was not known or is missing, who are", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "not shown separately.", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "na = Not available", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "", "ns = Not shown; see table 2b, footnote 1", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "( ) Based on 25-49 unweighted cases.", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "", "", "", "", "", "", "", "54", "", "", "", "", "", "", "", "", ""]
-]
-
-data_stream_table_area_single = [
-    ["","One Withholding"],
-    ["Payroll Period","Allowance"],
-    ["Weekly","$71.15"],
-    ["Biweekly","142.31"],
-    ["Semimonthly","154.17"],
-    ["Monthly","308.33"],
-    ["Quarterly","925.00"],
-    ["Semiannually","1,850.00"],
-    ["Annually","3,700.00"],
-    ["Daily or Miscellaneous","14.23"],
-    ["(each day of the payroll period)",""]
-]
-
-data_stream_columns = [
-    ["Clave", "Nombre Entidad", "Clave", "Nombre Municipio", "Clave", "Nombre Localidad"],
-    ["Entidad", "", "Municipio", "", "Localidad", ""],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0094", "Granja Adelita"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0096", "Agua Azul"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0100", "Rancho Alegre"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0102", "Los Arbolitos [Rancho]"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0104", "Ardillas de Abajo (Las Ardillas)"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0106", "Arellano"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0112", "Baj\xedo los V\xe1zquez"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0113", "Baj\xedo de Montoro"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0114", "Residencial San Nicol\xe1s [Ba\xf1os la Cantera]"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0120", "Buenavista de Pe\xf1uelas"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0121", "Cabecita 3 Mar\xedas (Rancho Nuevo)"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0125", "Ca\xf1ada Grande de Cotorina"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0126", "Ca\xf1ada Honda [Estaci\xf3n]"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0127", "Los Ca\xf1os"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0128", "El Cari\xf1\xe1n"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0129", "El Carmen [Granja]"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0135", "El Cedazo (Cedazo de San Antonio)"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0138", "Centro de Arriba (El Taray)"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0139", "Cieneguilla (La Lumbrera)"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0141", "Cobos"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0144", "El Colorado (El Soyatal)"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0146", "El Conejal"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0157", "Cotorina de Abajo"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0162", "Coyotes"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0166", "La Huerta (La Cruz)"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0170", "Cuauht\xe9moc (Las Palomas)"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0171", "Los Cuervos (Los Ojos de Agua)"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0172", "San Jos\xe9 [Granja]"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0176", "La Chiripa"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0182", "Dolores"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0183", "Los Dolores"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0190", "El Duraznillo"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0191", "Los Dur\xf3n"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0197", "La Escondida"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0201", "Brande Vin [Bodegas]"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0207", "Valle Redondo"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0209", "La Fortuna"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0212", "Lomas del Gachup\xedn"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0213", "El Carmen (Gallinas G\xfceras) [Rancho]"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0216", "La Gloria"],
-    ["01", "Aguascalientes", "001", "Aguascalientes", "0226", "Hacienda Nueva"]
-]
-
-data_lattice = [
-    ["Cycle Name","KI (1/km)","Distance (mi)","Percent Fuel Savings","","",""],
-    ["","","","Improved Speed","Decreased Accel","Eliminate Stops","Decreased Idle"],
-    ["2012_2","3.30","1.3","5.9%","9.5%","29.2%","17.4%"],
-    ["2145_1","0.68","11.2","2.4%","0.1%","9.5%","2.7%"],
-    ["4234_1","0.59","58.7","8.5%","1.3%","8.5%","3.3%"],
-    ["2032_2","0.17","57.8","21.7%","0.3%","2.7%","1.2%"],
-    ["4171_1","0.07","173.9","58.1%","1.6%","2.1%","0.5%"]
-]
-
-data_lattice_table_rotated = [
-    ["State","Nutritional Assessment  (No. of individuals)","","","","IYCF Practices  (No. of mothers: 2011-12)","Blood Pressure  (No. of adults: 2011-12)","","Fasting  Blood Sugar (No. of adults:2011-12)",""],
-    ["","1975-79","1988-90","1996-97","2011-12","","Men","Women","Men","Women"],
-    ["Kerala","5738","6633","8864","8297","245","2161","3195","1645","2391"],
-    ["Tamil Nadu","7387","10217","5813","7851","413","2134","2858","1119","1739"],
-    ["Karnataka","6453","8138","12606","8958","428","2467","2894","1628","2028"],
-    ["Andhra Pradesh","5844","9920","9545","8300","557","1899","2493","1111","1529"],
-    ["Maharashtra","5161","7796","6883","9525","467","2368","2648","1417","1599"],
-    ["Gujarat","4403","5374","4866","9645","477","2687","3021","2122","2503"],
-    ["Madhya Pradesh","*","*","*","7942","470","1965","2150","1579","1709"],
-    ["Orissa","3756","5540","12024","8473","398","2040","2624","1093","1628"],
-    ["West Bengal","*","*","*","8047","423","2058","2743","1413","2027"],
-    ["Uttar Pradesh","*","*","*","9860","581","2139","2415","1185","1366"],
-    ["Pooled","38742","53618","60601","86898","4459","21918","27041","14312","18519"]
-]
-
-data_lattice_process_background = [
-    ["State","Date","Halt stations","Halt days","Persons directly reached(in lakh)","Persons trained","Persons counseled","Persons testedfor HIV"],
-    ["Delhi","1.12.2009","8","17","1.29","3,665","2,409","1,000"],
-    ["Rajasthan","2.12.2009 to 19.12.2009","","","","","",""],
-    ["Gujarat","20.12.2009 to 3.1.2010","6","13","6.03","3,810","2,317","1,453"],
-    ["Maharashtra","4.01.2010 to 1.2.2010","13","26","1.27","5,680","9,027","4,153"],
-    ["Karnataka","2.2.2010 to 22.2.2010","11","19","1.80","5,741","3,658","3,183"],
-    ["Kerala","23.2.2010 to 11.3.2010","9","17","1.42","3,559","2,173","855"],
-    ["Total","","47","92","11.81","22,455","19,584","10,644"]
-]
-
-data_lattice_copy_text = [
-    ["Plan Type","County","Plan Name","Totals"],
-    ["GMC","Sacramento","Anthem Blue Cross","164,380"],
-    ["GMC","Sacramento","Health Net","126,547"],
-    ["GMC","Sacramento","Kaiser Foundation","74,620"],
-    ["GMC","Sacramento","Molina Healthcare","59,989"],
-    ["GMC","San Diego","Care 1st Health Plan","71,831"],
-    ["GMC","San Diego","Community Health Group","264,639"],
-    ["GMC","San Diego","Health Net","72,404"],
-    ["GMC","San Diego","Kaiser","50,415"],
-    ["GMC","San Diego","Molina Healthcare","206,430"],
-    ["GMC","Total GMC Enrollment","","1,091,255"],
-    ["COHS","Marin","Partnership Health Plan of CA","36,006"],
-    ["COHS","Mendocino","Partnership Health Plan of CA","37,243"],
-    ["COHS","Napa","Partnership Health Plan of CA","28,398"],
-    ["COHS","Solano","Partnership Health Plan of CA","113,220"],
-    ["COHS","Sonoma","Partnership Health Plan of CA","112,271"],
-    ["COHS","Yolo","Partnership Health Plan of CA","52,674"],
-    ["COHS","Del Norte","Partnership Health Plan of CA","11,242"],
-    ["COHS","Humboldt","Partnership Health Plan of CA","49,911"],
-    ["COHS","Lake","Partnership Health Plan of CA","29,149"],
-    ["COHS","Lassen","Partnership Health Plan of CA","7,360"],
-    ["COHS","Modoc","Partnership Health Plan of CA","2,940"],
-    ["COHS","Shasta","Partnership Health Plan of CA","61,763"],
-    ["COHS","Siskiyou","Partnership Health Plan of CA","16,715"],
-    ["COHS","Trinity","Partnership Health Plan of CA","4,542"],
-    ["COHS","Merced","Central California Alliance for Health","123,907"],
-    ["COHS","Monterey","Central California Alliance for Health","147,397"],
-    ["COHS","Santa Cruz","Central California Alliance for Health","69,458"],
-    ["COHS","Santa Barbara","CenCal","117,609"],
-    ["COHS","San Luis Obispo","CenCal","55,761"],
-    ["COHS","Orange","CalOptima","783,079"],
-    ["COHS","San Mateo","Health Plan of San Mateo","113,202"],
-    ["COHS","Ventura","Gold Coast Health Plan","202,217"],
-    ["COHS","Total COHS Enrollment","","2,176,064"],
-    ["Subtotal for Two-Plan, Regional Model, GMC and COHS","","","10,132,022"],
-    ["PCCM","Los Angeles","AIDS Healthcare Foundation","828"],
-    ["PCCM","San Francisco","Family Mosaic","25"],
-    ["PCCM","Total PHP Enrollment","","853"],
-    ["All Models Total Enrollments","","","10,132,875"],
-    ["Source:   Data Warehouse 12/14/15","","",""]
-]

tests/test_errors.py

@@ -0,0 +1,103 @@
+# -*- coding: utf-8 -*-
+
+import os
+import warnings
+
+import pytest
+
+import camelot
+
+
+testdir = os.path.dirname(os.path.abspath(__file__))
+testdir = os.path.join(testdir, "files")
+filename = os.path.join(testdir, 'foo.pdf')
+
+
+def test_unknown_flavor():
+    message = ("Unknown flavor specified."
+               " Use either 'lattice' or 'stream'")
+    with pytest.raises(NotImplementedError, message=message):
+        tables = camelot.read_pdf(filename, flavor='chocolate')
+
+
+def test_input_kwargs():
+    message = "columns cannot be used with flavor='lattice'"
+    with pytest.raises(ValueError, message=message):
+        tables = camelot.read_pdf(filename, columns=['10,20,30,40'])
+
+
+def test_unsupported_format():
+    message = 'File format not supported'
+    filename = os.path.join(testdir, 'foo.csv')
+    with pytest.raises(NotImplementedError, message=message):
+        tables = camelot.read_pdf(filename)
+
+
+def test_stream_equal_length():
+    message = ("Length of table_areas and columns"
+               " should be equal")
+    with pytest.raises(ValueError, message=message):
+        tables = camelot.read_pdf(filename, flavor='stream',
+            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')
+    with warnings.catch_warnings():
+        warnings.simplefilter('error')
+        with pytest.raises(UserWarning) as e:
+            tables = camelot.read_pdf(filename)
+        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')

tests/test_plotting.py

@@ -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')