Source: joblib Maintainer: Debian Science Maintainers Uploaders: Yaroslav Halchenko Section: python Testsuite: autopkgtest-pkg-python Priority: optional Build-Depends: debhelper-compat (= 13), dh-sequence-python3, python3-all, python3-setuptools, pybuild-plugin-pyproject, python3-pytest , python3-numpy, python3-psutil, python3-lz4, python3-threadpoolctl , cython3, procps Build-Depends-Indep: python3-doc, python3-sphinx, dh-sequence-sphinxdoc, python3-sphinx-autodoc-typehints, python-numpy-doc, python-scipy-doc, python3-numpydoc, python3-pandas, python3-sphinx-gallery, python-distributed-doc Standards-Version: 4.7.0 Vcs-Browser: https://salsa.debian.org/science-team/joblib Vcs-Git: https://salsa.debian.org/science-team/joblib.git Homepage: https://github.com/joblib/joblib Rules-Requires-Root: no Package: python3-joblib Architecture: all Depends: ${python3:Depends}, ${misc:Depends}, procps, Recommends: python3-numpy, python3-pytest, python3-psutil Suggests: python-joblib-doc Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: . - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. . This package contains the Python 3 version. Package: python-joblib-doc Section: doc Architecture: all Multi-Arch: foreign Depends: ${misc:Depends}, ${sphinxdoc:Depends}, Suggests: python3-joblib, python3-doc, python-numpy-doc, python-scipy-doc Description: tools to provide lightweight pipelining in Python -- docs Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: . - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. . This package contains the documentation for joblib.