Source: joblib
Maintainer: Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
Uploaders:
 Yaroslav Halchenko <debian@onerussian.com>,
Section: python
Testsuite: autopkgtest-pkg-python
Priority: optional
Build-Depends:
 debhelper-compat (= 13),
 dh-sequence-python3,
 cython3,
 procps,
 pybuild-plugin-pyproject,
 python3-all,
 python3-lz4,
 python3-numpy,
 python3-psutil,
 python3-pytest <!nocheck>,
 python3-setuptools,
 python3-threadpoolctl <!nocheck>,
Build-Depends-Indep:
 dh-sequence-sphinxdoc,
 python-distributed-doc,
 python-numpy-doc,
 python-scipy-doc,
 python3-doc,
 python3-numpydoc,
 python3-pandas,
 python3-sphinx,
 python3-sphinx-autodoc-typehints,
 python3-sphinx-gallery,
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
X-Style: black

Package: python3-joblib
Architecture: all
Depends:
 procps,
 ${misc:Depends},
 ${python3:Depends},
Recommends:
 python3-numpy,
 python3-psutil,
 python3-pytest,
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:
 python-numpy-doc,
 python-scipy-doc,
 python3-doc,
 python3-joblib,
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.