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Source: python-pyomop
Section: python
Priority: optional
Maintainer: Debian Python Team <team+python@tracker.debian.org>
Uploaders:
Michael Fladischer <fladi@debian.org>,
Build-Depends:
debhelper-compat (= 13),
dh-sequence-python3,
help2man,
pybuild-plugin-pyproject,
python-pandas-doc,
python-scipy-doc,
python-sklearn-doc,
python3-aiosqlite,
python3-all,
python3-click,
python3-doc,
python3-pandas,
python3-pytest,
python3-recommonmark,
python3-scipy,
python3-setuptools,
python3-setuptools-scm,
python3-sphinx,
python3-sqlalchemy,
sphinx-doc,
Standards-Version: 4.7.0
Homepage: https://github.com/dermatologist/pyomop
Vcs-Browser: https://salsa.debian.org/python-team/packages/python-pyomop
Vcs-Git: https://salsa.debian.org/python-team/packages/python-pyomop.git
Rules-Requires-Root: no
Package: pyomop
Section: science
Architecture: all
Depends:
python3-pyomop (= ${binary:Version}),
${misc:Depends},
${python3:Depends},
Description: OHSDI OMOP Common Data Model tools
The OHSDI OMOP Common Data Model allows for the systematic analysis of
healthcare observational databases. This is a Python library to use the CDM v6
compliant databases using SQLAlchemy as the ORM. pyomop also supports
converting query results to a pandas dataframe (see below) for use in machine
learning pipelines.
Package: python-pyomop-doc
Section: doc
Architecture: all
Depends:
${misc:Depends},
${sphinxdoc:Depends},
Description: OHSDI OMOP Common Data Model tools (Documentation)
The OHSDI OMOP Common Data Model allows for the systematic analysis of
healthcare observational databases. This is a Python library to use the CDM v6
compliant databases using SQLAlchemy as the ORM. pyomop also supports
converting query results to a pandas dataframe (see below) for use in machine
learning pipelines.
.
This package contains the documentation.
Package: python3-pyomop
Architecture: all
Depends:
${misc:Depends},
${python3:Depends},
Suggests:
python-pyomop-doc,
Description: OHSDI OMOP Common Data Model tools (Python3 version)
The OHSDI OMOP Common Data Model allows for the systematic analysis of
healthcare observational databases. This is a Python library to use the CDM v6
compliant databases using SQLAlchemy as the ORM. pyomop also supports
converting query results to a pandas dataframe (see below) for use in machine
learning pipelines.
.
This package contains the Python 3 version of the library.
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