Resiliparse 1.0.7

A collection of robust and fast processing tools for parsing and analyzing (not only) web archive data.

ChatNoir Resiliparse

A collection of robust and fast processing tools for parsing and analyzing web archive data written in Rust and Cython/C++ with bindings for Python.

Resiliparse is a part of the ChatNoir web analytics toolkit.

Installing Resiliparse

Pre-built Resiliparse binaries can be installed from PyPi:

pip install resiliparse

Building Resiliparse From Source

To build Resiliparse from sources, you need to install all required build-time dependencies listed in vcpkg.json. It's possible to install them globally via your package manager, but the easiest and most consistent way is to use vcpkg:

# Install vcpkg itself (skip if you have a working vcpkg installation already)
git clone https://github.com/Microsoft/vcpkg
./vcpkg/bootstrap-vcpkg.sh

# Install dependencies to vcpkg_installed (must be run from sources root)
./vcpkg/vcpkg install --triplet=x64-linux

Replace the triplet value with one suitable for your platform. Valid values are: x64-windows, x64-osx, arm64-osx, aarch64-linux (or any of the vcpkg default triplets).

After installing the dependencies, you can build the actual Python packages:

# 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 ./resiliparse-py

# Option 2 (alternative): Build and install wheels in separate steps (best for redistribution)
python3 -m pip wheel -w build ./resiliparse-py
ls ./build/*.whl | xargs python3 -m pip install

In most cases, the build routine should be smart enough to detect the location of the installed vcpkg dependencies. However, in some cases you may be getting errors about missing header files or undefined symbols. This can happen if you don't build from the source repository, use Python's new build module, or run pip wheel with --isolated. To work around that, set the RESILIPARSE_VCPKG_PATH environment variable to the absolute path of the vcpkg installation directory:

export RESILIPARSE_VCPKG_PATH="$(pwd)/vcpkg_installed"

NOTE: Unless you fix up the wheels to embed the linked shared libraries ( via auditwheel on Linux, delocate-wheel on macOS, or delvewheel on Windows), you will have to add the vcpkg library directory ( vcpkg_installed/TRIPLET/lib) to your library search path to use them. On Linux, add the directory path to the LD_LIBRARY_PATH environment variable, on macOS to DYLD_LIBRARY_PATH. On Windows, you have to add the directory to the Path environment variable.

Here's an example of how to use auditwheel on Linux to fix up the build wheels:

LD_LIBRARY_PATH=$(pwd)/vcpkg_installed/x64-linux/lib \
  auditwheel repair --plat linux_x86_64 build/Resiliparse*.whl

(Please note that linux_x86_64 platform wheels are not suitable for general redistribution.)

Usage Instructions

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

Cite Us

If you use ChatNoir or Resiliparse, please consider citing 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
}

If you use FastWARC, you can also cite 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
}