FastWARC 1.0.7

The world's fastest WARC parsing library written in Rust with bindings for Python.

FastWARC (Python)

FastWARC is a high-performance WARC parsing library written in Rust with bindings for Python. FastWARC supports compressed and uncompressed WARC/1.0 and WARC/1.1 streams. Supported compression algorithms are Gzip, Zstd, and LZ4.

This package contains the Python bindings for FastWARC.

FastWARC belongs to the ChatNoir Resiliparse toolkit for fast and robust web data processing.

Installing FastWARC

Pre-built FastWARC binaries for Python can be installed from PyPi:

pip install fastwarc

Building Python Bindings From Source

To be able to build FastWARC, you need the Rust toolchain installed (see above). Then to build directly from the GitHub repository, follow these steps:

# Clone repository

git clone https://github.com/chatnoir-eu/chatnoir-resiliparse.git
cd chatnoir-resiliparse

# Install Rust toolchain (if not already installed)

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

# Create a fresh venv first (recommended)

python3 -m venv venv && source venv/bin/activate

# Option 1: Build and install in editable mode (best for development)

python3 -m pip install -e ./fastwarc-py

# Option 2 (alternative): Build and install wheels in separate steps (best for redistribution)

python3 -m pip wheel -w build ./fastwarc-py
ls ./build/*.whl | xargs python3 -m pip install

Usage Instructions

For detailed usage instructions, please consult the FastWARC User Manual.

Cite Us

If you use FastWARC, please consider citing our OSSYM 2021 abstract paper:

@InProceedings{bevendorff:2021,
  author =                {Janek Bevendorff and Martin Potthast and Benno Stein},
  booktitle =             {3rd International Symposium on Open Search Technology (OSSYM 2021)},
  editor =                {Andreas Wagner and Christian Guetl and Michael Granitzer and Stefan Voigt},
  month =                 oct,
  publisher =             {International Open Search Symposium},
  site =                  {CERN, Geneva, Switzerland},
  title =                 {{FastWARC: Optimizing Large-Scale Web Archive Analytics}},
  year =                  2021
}

You can also cite our ECIR 2018 demo paper:

@InProceedings{bevendorff:2018,
  address =             {Berlin Heidelberg New York},
  author =              {Janek Bevendorff and Benno Stein and Matthias Hagen and Martin Potthast},
  booktitle =           {Advances in Information Retrieval. 40th European Conference on IR Research (ECIR 2018)},
  editor =              {Leif Azzopardi and Allan Hanbury and Gabriella Pasi and Benjamin Piwowarski},
  month =               mar,
  publisher =           {Springer},
  series =              {Lecture Notes in Computer Science},
  site =                {Grenoble, France},
  title =               {{Elastic ChatNoir: Search Engine for the ClueWeb and the Common Crawl}},
  year =                2018
}