>>> import camelot
>>> tables = camelot.read_pdf('foo.pdf')
>>> tables
<TableList tables=1>
>>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html
>>> tables[0]
<Table shape=(7, 7)>
>>> tables[0].parsing_report
{
'accuracy': 99.02,
'whitespace': 12.24,
'order': 1,
'page': 1
}
>>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html
>>> tables[0].df # get a pandas DataFrame!
| 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% |
There's a [command-line interface](https://camelot-py.readthedocs.io/en/latest/user/cli.html) too!
## 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.)
- **Metrics**: *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).
- **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:
$ pip install camelot-py### Alternatively After [installing the dependencies](https://camelot-py.readthedocs.io/en/latest/user/install.html), clone the repo using:
$ git clone https://www.github.com/socialcopsdev/camelotand install Camelot using pip:
$ cd camelot $ pip install .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. ### Source code You can check the latest sources with:
$ git clone https://www.github.com/socialcopsdev/camelot### Setting up a development environment You can install the development dependencies easily, using pip:
$ pip install camelot-py[dev]### Testing After installation, you can run tests using:
$ python setup.py test## Versioning Camelot uses [Semantic Versioning](https://semver.org/). For the available versions, see the tags on this repository. ## License This project is licensed under the MIT License, see the [LICENSE](https://github.com/socialcopsdev/camelot/blob/master/LICENSE) file for details.