97 lines
3.6 KiB
Markdown
97 lines
3.6 KiB
Markdown
# Camelot: PDF Table Parsing for Humans
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**Camelot** is a Python library which makes it easy for *anyone* to extract tables from PDF files!
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---
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**Here's how you can extract tables from PDF files.** Check out the PDF used in this example, [here](docs/_static/pdf/foo.pdf).
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<pre>
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>>> import camelot
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>>> tables = camelot.read_pdf('foo.pdf', mesh=True)
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>>> tables
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<TableList tables=1>
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>>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html
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>>> tables[0]
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<Table shape=(7, 7)>
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>>> tables[0].parsing_report
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{
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'accuracy': 99.02,
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'whitespace': 12.24,
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'order': 1,
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'page': 1
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}
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>>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html
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>>> tables[0].df # get a pandas DataFrame!
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</pre>
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| Cycle Name | KI (1/km) | Distance (mi) | Percent Fuel Savings | | | |
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|------------|-----------|---------------|----------------------|-----------------|-----------------|----------------|
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| | | | Improved Speed | Decreased Accel | Eliminate Stops | Decreased Idle |
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| 2012_2 | 3.30 | 1.3 | 5.9% | 9.5% | 29.2% | 17.4% |
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| 2145_1 | 0.68 | 11.2 | 2.4% | 0.1% | 9.5% | 2.7% |
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| 4234_1 | 0.59 | 58.7 | 8.5% | 1.3% | 8.5% | 3.3% |
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| 2032_2 | 0.17 | 57.8 | 21.7% | 0.3% | 2.7% | 1.2% |
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| 4171_1 | 0.07 | 173.9 | 58.1% | 1.6% | 2.1% | 0.5% |
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There's a [command-line interface]() too!
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## Why Camelot?
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- **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.)
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- **Metrics**: *Bad* tables can be discarded based on metrics like accuracy and whitespace, without ever having to manually look at each table.
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- Each table is a **pandas DataFrame**, which enables seamless integration into data analysis workflows.
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- **Export** to multiple formats, including json, excel and html.
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- Simple and Elegant API, written in **Python**!
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See [comparison with other PDF parsing libraries and tools](https://github.com/socialcopsdev/camelot/wiki/Comparison-with-other-PDF-Table-Parsing-libraries-and-tools).
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## Installation
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After [installing the dependencies](), you can simply use pip to install Camelot:
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<pre>
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$ pip install camelot-py
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</pre>
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## Documentation
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Great documentation is available at [link]().
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## Development
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The [Contributor's Guide](CONTRIBUTING.md) has detailed information about contributing code, documentation, tests and more. We've included some basic information in this README.
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### Source code
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You can check the latest sources with:
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<pre>
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$ git clone https://www.github.com/socialcopsdev/camelot
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</pre>
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### Setting up a development environment
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You can install the development dependencies easily, using pip:
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<pre>
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$ pip install camelot-py[dev]
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</pre>
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### Testing
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After installation, you can run tests using:
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<pre>
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$ python setup.py test
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</pre>
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## Versioning
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Camelot uses [Semantic Versioning](https://semver.org/). For the available versions, see the tags on this repository.
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## License
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This project is licensed under the MIT License, see the [LICENSE](LICENSE) file for details. |