Skip to main content

PDF Table Extraction for Humans.

Project description

Camelot: PDF Table Extraction for Humans

tests Documentation Status codecov.io image image image Gitter chat image

Camelot is a Python library that can help you extract tables from PDFs!

Note: You can also check out Excalibur, the web interface to Camelot!


Here's how you can extract tables from PDFs. You can check out the PDF used in this example here.

>>> import camelot
>>> tables = camelot.read_pdf('foo.pdf')
>>> tables
<TableList n=1>
>>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html, markdown, sqlite
>>> 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, to_markdown, to_sqlite
>>> 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%

Camelot also comes packaged with a command-line interface!

Note: Camelot only works with text-based PDFs and not scanned documents. (As Tabula explains, "If you can click and drag to select text in your table in a PDF viewer, then your PDF is text-based".)

You can check out some frequently asked questions here.

Why Camelot?

  • Configurability: Camelot gives you control over the table extraction process with tweakable settings.
  • Metrics: You can discard bad tables based on metrics like accuracy and whitespace, without having to manually look at each table.
  • Output: Each table is extracted into a pandas DataFrame, which seamlessly integrates into ETL and data analysis workflows. You can also export tables to multiple formats, which include CSV, JSON, Excel, HTML, Markdown, and Sqlite.

See comparison with similar libraries and tools.

Support the development

If Camelot has helped you, please consider supporting its development with a one-time or monthly donation on OpenCollective.

Installation

Using conda

The easiest way to install Camelot is with conda, which is a package manager and environment management system for the Anaconda distribution.

$ conda install -c conda-forge camelot-py

Using pip

After installing the dependencies (tk and ghostscript), you can also just use pip to install Camelot:

$ pip install "camelot-py[cv]"

From the source code

After installing the dependencies, clone the repo using:

$ git clone https://www.github.com/camelot-dev/camelot

and install Camelot using pip:

$ cd camelot
$ pip install ".[cv]"

Documentation

The documentation is available at http://camelot-py.readthedocs.io/.

Wrappers

Contributing

The Contributor's Guide has detailed information about contributing issues, documentation, code, and tests.

Versioning

Camelot uses Semantic Versioning. For the available versions, see the tags on this repository. For the changelog, you can check out HISTORY.md.

License

This project is licensed under the MIT License, see the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

camelot-py-0.10.0.tar.gz (40.0 kB view details)

Uploaded Source

Built Distribution

camelot_py-0.10.0-py3-none-any.whl (41.0 kB view details)

Uploaded Python 3

File details

Details for the file camelot-py-0.10.0.tar.gz.

File metadata

  • Download URL: camelot-py-0.10.0.tar.gz
  • Upload date:
  • Size: 40.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.8.10

File hashes

Hashes for camelot-py-0.10.0.tar.gz
Algorithm Hash digest
SHA256 2dc3131b0679b8a6cfe6caed9e2d1f6a5bb532e3584eea269ec2816402ea8eb2
MD5 c855925f55768f701f2edb8b0ed876b4
BLAKE2b-256 9fe8f890f901b7420aeb56cb948ea5e328f7126dd483d954b00dc99bc6f1a450

See more details on using hashes here.

File details

Details for the file camelot_py-0.10.0-py3-none-any.whl.

File metadata

  • Download URL: camelot_py-0.10.0-py3-none-any.whl
  • Upload date:
  • Size: 41.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.8.10

File hashes

Hashes for camelot_py-0.10.0-py3-none-any.whl
Algorithm Hash digest
SHA256 b0f587de5d8d25b86e0baf0d9f08b0cd9292b327a998e33b44916015033ba2cd
MD5 75e9cb00b2f122cb2bce336373ffc8db
BLAKE2b-256 00191574b26ed2c76834f6e3ea716b56a48ca41acca3651da84d11cc2e74384e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page