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|
%global _empty_manifest_terminate_build 0
Name: python-tfs-pandas
Version: 3.7.0
Release: 1
Summary: Read and write tfs files.
License: MIT
URL: https://github.com/pylhc/tfs
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/25/58/31e92bed9554d146e658f88e4b27257f5bc2dd4954bf5aaa1f52a352258a/tfs-pandas-3.7.0.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-pandas
Requires: python3-pytest
Requires: python3-pytest-cov
Requires: python3-cpymad
Requires: python3-zstandard
Requires: python3-h5py
Requires: python3-tables
Requires: python3-sphinx
Requires: python3-sphinx-rtd-theme
Requires: python3-sphinx-copybutton
Requires: python3-sphinx-prompt
Requires: python3-sphinx-codeautolink
Requires: python3-sphinx
Requires: python3-sphinx-rtd-theme
Requires: python3-sphinx-copybutton
Requires: python3-sphinx-prompt
Requires: python3-sphinx-codeautolink
Requires: python3-h5py
Requires: python3-tables
Requires: python3-pytest
Requires: python3-pytest-cov
Requires: python3-cpymad
Requires: python3-zstandard
Requires: python3-h5py
Requires: python3-tables
%description
# TFS-Pandas
[](https://github.com/pylhc/tfs/actions?query=workflow%3A%22Cron+Testing%22)
[](https://codeclimate.com/github/pylhc/tfs)
[](https://codeclimate.com/github/pylhc/tfs)
<!-- [](https://github.com/pylhc/tfs/) -->
[](https://pypi.org/project/tfs-pandas/)
[](https://github.com/pylhc/tfs/)
[](https://anaconda.org/conda-forge/tfs-pandas)
[](https://doi.org/10.5281/zenodo.5070986)
This package provides reading and writing functionality for [**Table Format System (TFS)** files](http://mad.web.cern.ch/mad/madx.old/Introduction/tfs.html).
Files are read into a `TfsDataFrame`, a class built on top of the famous `pandas.DataFrame`, which in addition to the normal behavior attaches an `OrderedDict` of headers to the `DataFrame`.
See the [API documentation](https://pylhc.github.io/tfs/) for details.
## Installing
Installation is easily done via `pip`:
```bash
python -m pip install tfs-pandas
```
One can also install in a `conda`/`mamba` environment via the `conda-forge` channel with:
```bash
conda install -c conda-forge tfs-pandas
```
## Example Usage
The package is imported as `tfs`, and exports top-level functions for reading and writing:
```python
import tfs
# Loading a TFS file is simple
data_frame = tfs.read("path_to_input.tfs", index="index_column")
# You can access and modify the headers with the .headers attribute
useful_variable = data_frame.headers["SOME_KEY"]
data_frame.headers["NEW_KEY"] = some_variable
# Manipulate data as you do with pandas DataFrames
data_frame["NEWCOL"] = data_frame.COL_A * data_frame.COL_B
# You can check the validity of a TfsDataFrame, and choose the behavior in case of errors
tfs.frame.validate(data_frame, non_unique_behavior="raise") # or choose "warn"
# Writing out to disk is simple too
tfs.write("path_to_output.tfs", data_frame, save_index="index_column")
```
Reading and writing compressed files is also supported, and done automatically based on the provided file extension:
```python
import tfs
# Reading a compressed file is simple, compression format is inferred
df = tfs.read("path_to_input.tfs.gz")
# When writing choose the compression format by providing the appropriate file extension
tfs.write("path_to_output.tfs.bz2", df)
tfs.write("path_to_output.tfs.zip", df)
```
## License
This project is licensed under the `MIT License` - see the [LICENSE](LICENSE) file for details.
%package -n python3-tfs-pandas
Summary: Read and write tfs files.
Provides: python-tfs-pandas
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-tfs-pandas
# TFS-Pandas
[](https://github.com/pylhc/tfs/actions?query=workflow%3A%22Cron+Testing%22)
[](https://codeclimate.com/github/pylhc/tfs)
[](https://codeclimate.com/github/pylhc/tfs)
<!-- [](https://github.com/pylhc/tfs/) -->
[](https://pypi.org/project/tfs-pandas/)
[](https://github.com/pylhc/tfs/)
[](https://anaconda.org/conda-forge/tfs-pandas)
[](https://doi.org/10.5281/zenodo.5070986)
This package provides reading and writing functionality for [**Table Format System (TFS)** files](http://mad.web.cern.ch/mad/madx.old/Introduction/tfs.html).
Files are read into a `TfsDataFrame`, a class built on top of the famous `pandas.DataFrame`, which in addition to the normal behavior attaches an `OrderedDict` of headers to the `DataFrame`.
See the [API documentation](https://pylhc.github.io/tfs/) for details.
## Installing
Installation is easily done via `pip`:
```bash
python -m pip install tfs-pandas
```
One can also install in a `conda`/`mamba` environment via the `conda-forge` channel with:
```bash
conda install -c conda-forge tfs-pandas
```
## Example Usage
The package is imported as `tfs`, and exports top-level functions for reading and writing:
```python
import tfs
# Loading a TFS file is simple
data_frame = tfs.read("path_to_input.tfs", index="index_column")
# You can access and modify the headers with the .headers attribute
useful_variable = data_frame.headers["SOME_KEY"]
data_frame.headers["NEW_KEY"] = some_variable
# Manipulate data as you do with pandas DataFrames
data_frame["NEWCOL"] = data_frame.COL_A * data_frame.COL_B
# You can check the validity of a TfsDataFrame, and choose the behavior in case of errors
tfs.frame.validate(data_frame, non_unique_behavior="raise") # or choose "warn"
# Writing out to disk is simple too
tfs.write("path_to_output.tfs", data_frame, save_index="index_column")
```
Reading and writing compressed files is also supported, and done automatically based on the provided file extension:
```python
import tfs
# Reading a compressed file is simple, compression format is inferred
df = tfs.read("path_to_input.tfs.gz")
# When writing choose the compression format by providing the appropriate file extension
tfs.write("path_to_output.tfs.bz2", df)
tfs.write("path_to_output.tfs.zip", df)
```
## License
This project is licensed under the `MIT License` - see the [LICENSE](LICENSE) file for details.
%package help
Summary: Development documents and examples for tfs-pandas
Provides: python3-tfs-pandas-doc
%description help
# TFS-Pandas
[](https://github.com/pylhc/tfs/actions?query=workflow%3A%22Cron+Testing%22)
[](https://codeclimate.com/github/pylhc/tfs)
[](https://codeclimate.com/github/pylhc/tfs)
<!-- [](https://github.com/pylhc/tfs/) -->
[](https://pypi.org/project/tfs-pandas/)
[](https://github.com/pylhc/tfs/)
[](https://anaconda.org/conda-forge/tfs-pandas)
[](https://doi.org/10.5281/zenodo.5070986)
This package provides reading and writing functionality for [**Table Format System (TFS)** files](http://mad.web.cern.ch/mad/madx.old/Introduction/tfs.html).
Files are read into a `TfsDataFrame`, a class built on top of the famous `pandas.DataFrame`, which in addition to the normal behavior attaches an `OrderedDict` of headers to the `DataFrame`.
See the [API documentation](https://pylhc.github.io/tfs/) for details.
## Installing
Installation is easily done via `pip`:
```bash
python -m pip install tfs-pandas
```
One can also install in a `conda`/`mamba` environment via the `conda-forge` channel with:
```bash
conda install -c conda-forge tfs-pandas
```
## Example Usage
The package is imported as `tfs`, and exports top-level functions for reading and writing:
```python
import tfs
# Loading a TFS file is simple
data_frame = tfs.read("path_to_input.tfs", index="index_column")
# You can access and modify the headers with the .headers attribute
useful_variable = data_frame.headers["SOME_KEY"]
data_frame.headers["NEW_KEY"] = some_variable
# Manipulate data as you do with pandas DataFrames
data_frame["NEWCOL"] = data_frame.COL_A * data_frame.COL_B
# You can check the validity of a TfsDataFrame, and choose the behavior in case of errors
tfs.frame.validate(data_frame, non_unique_behavior="raise") # or choose "warn"
# Writing out to disk is simple too
tfs.write("path_to_output.tfs", data_frame, save_index="index_column")
```
Reading and writing compressed files is also supported, and done automatically based on the provided file extension:
```python
import tfs
# Reading a compressed file is simple, compression format is inferred
df = tfs.read("path_to_input.tfs.gz")
# When writing choose the compression format by providing the appropriate file extension
tfs.write("path_to_output.tfs.bz2", df)
tfs.write("path_to_output.tfs.zip", df)
```
## License
This project is licensed under the `MIT License` - see the [LICENSE](LICENSE) file for details.
%prep
%autosetup -n tfs-pandas-3.7.0
%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-tfs-pandas -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue May 30 2023 Python_Bot <Python_Bot@openeuler.org> - 3.7.0-1
- Package Spec generated
|
