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@@ -0,0 +1 @@ +/pycausalmatch-0.0.4.tar.gz diff --git a/python-pycausalmatch.spec b/python-pycausalmatch.spec new file mode 100644 index 0000000..5384907 --- /dev/null +++ b/python-pycausalmatch.spec @@ -0,0 +1,202 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pycausalmatch +Version: 0.0.4 +Release: 1 +Summary: Causal Impact of an intervention integrated with control group selection +License: MIT License +URL: https://github.com/unbiasedmodeler/pycausalmatch +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/d3/53/f92a3af9e3cf629832792704266531720c8ac8e925732d51f10a9ae5c8f6/pycausalmatch-0.0.4.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-pandas +Requires: python3-dtw-python +Requires: python3-tfcausalimpact + +%description + ├── LICENSE + ├── Makefile <- Makefile with commands like `make data` or `make train` + ├── README.md <- The top-level README for developers using this project. + ├── data + │ ├── external <- Data from third party sources. + │ ├── interim <- Intermediate data that has been transformed. + │ ├── processed <- The final, canonical data sets for modeling. + │ └── raw <- The original, immutable data dump. + │ + ├── docs <- A default Sphinx project; see sphinx-doc.org for details + │ + ├── models <- Trained and serialized models, model predictions, or model summaries + │ + ├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering), + │ the creator's initials, and a short `-` delimited description, e.g. + │ `1.0-jqp-initial-data-exploration`. + │ + ├── references <- Data dictionaries, manuals, and all other explanatory materials. + │ + ├── reports <- Generated analysis as HTML, PDF, LaTeX, etc. + │ └── figures <- Generated graphics and figures to be used in reporting + │ + ├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g. + │ generated with `pip freeze > requirements.txt` + │ + ├── setup.py <- makes project pip installable (pip install -e .) so src can be imported + ├── src <- Source code for use in this project. + │ ├── __init__.py <- Makes src a Python module + │ │ + │ ├── data <- Scripts to download or generate data + │ │ └── make_dataset.py + │ │ + │ ├── features <- Scripts to turn raw data into features for modeling + │ │ └── build_features.py + │ │ + │ ├── models <- Scripts to train models and then use trained models to make + │ │ │ predictions + │ │ ├── predict_model.py + │ │ └── train_model.py + │ │ + │ └── visualization <- Scripts to create exploratory and results oriented visualizations + │ └── visualize.py + │ + +%package -n python3-pycausalmatch +Summary: Causal Impact of an intervention integrated with control group selection +Provides: python-pycausalmatch +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-pycausalmatch + ├── LICENSE + ├── Makefile <- Makefile with commands like `make data` or `make train` + ├── README.md <- The top-level README for developers using this project. + ├── data + │ ├── external <- Data from third party sources. + │ ├── interim <- Intermediate data that has been transformed. + │ ├── processed <- The final, canonical data sets for modeling. + │ └── raw <- The original, immutable data dump. + │ + ├── docs <- A default Sphinx project; see sphinx-doc.org for details + │ + ├── models <- Trained and serialized models, model predictions, or model summaries + │ + ├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering), + │ the creator's initials, and a short `-` delimited description, e.g. + │ `1.0-jqp-initial-data-exploration`. + │ + ├── references <- Data dictionaries, manuals, and all other explanatory materials. + │ + ├── reports <- Generated analysis as HTML, PDF, LaTeX, etc. + │ └── figures <- Generated graphics and figures to be used in reporting + │ + ├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g. + │ generated with `pip freeze > requirements.txt` + │ + ├── setup.py <- makes project pip installable (pip install -e .) so src can be imported + ├── src <- Source code for use in this project. + │ ├── __init__.py <- Makes src a Python module + │ │ + │ ├── data <- Scripts to download or generate data + │ │ └── make_dataset.py + │ │ + │ ├── features <- Scripts to turn raw data into features for modeling + │ │ └── build_features.py + │ │ + │ ├── models <- Scripts to train models and then use trained models to make + │ │ │ predictions + │ │ ├── predict_model.py + │ │ └── train_model.py + │ │ + │ └── visualization <- Scripts to create exploratory and results oriented visualizations + │ └── visualize.py + │ + +%package help +Summary: Development documents and examples for pycausalmatch +Provides: python3-pycausalmatch-doc +%description help + ├── LICENSE + ├── Makefile <- Makefile with commands like `make data` or `make train` + ├── README.md <- The top-level README for developers using this project. + ├── data + │ ├── external <- Data from third party sources. + │ ├── interim <- Intermediate data that has been transformed. + │ ├── processed <- The final, canonical data sets for modeling. + │ └── raw <- The original, immutable data dump. + │ + ├── docs <- A default Sphinx project; see sphinx-doc.org for details + │ + ├── models <- Trained and serialized models, model predictions, or model summaries + │ + ├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering), + │ the creator's initials, and a short `-` delimited description, e.g. + │ `1.0-jqp-initial-data-exploration`. + │ + ├── references <- Data dictionaries, manuals, and all other explanatory materials. + │ + ├── reports <- Generated analysis as HTML, PDF, LaTeX, etc. + │ └── figures <- Generated graphics and figures to be used in reporting + │ + ├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g. + │ generated with `pip freeze > requirements.txt` + │ + ├── setup.py <- makes project pip installable (pip install -e .) so src can be imported + ├── src <- Source code for use in this project. + │ ├── __init__.py <- Makes src a Python module + │ │ + │ ├── data <- Scripts to download or generate data + │ │ └── make_dataset.py + │ │ + │ ├── features <- Scripts to turn raw data into features for modeling + │ │ └── build_features.py + │ │ + │ ├── models <- Scripts to train models and then use trained models to make + │ │ │ predictions + │ │ ├── predict_model.py + │ │ └── train_model.py + │ │ + │ └── visualization <- Scripts to create exploratory and results oriented visualizations + │ └── visualize.py + │ + +%prep +%autosetup -n pycausalmatch-0.0.4 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-pycausalmatch -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.4-1 +- Package Spec generated @@ -0,0 +1 @@ +c38badf6482bf080898b272cedb987f2 pycausalmatch-0.0.4.tar.gz |