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|
%global _empty_manifest_terminate_build 0
Name: python-trexio
Version: 1.3.2
Release: 1
Summary: Python API of the TREXIO library
License: BSD
URL: https://github.com/TREX-CoE/trexio
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a4/14/0170089577ec974a808106a0589e7bc641ff39bc00e9a34463a9bd2b5d9b/trexio-1.3.2.tar.gz
BuildArch: noarch
Requires: python3-numpy
%description
# TREXIO Python API
[](https://badge.fury.io/py/trexio)
[](https://mybinder.org/v2/gh/TREX-CoE/trexio-tutorials/HEAD)
TREXIO provides a Python API, which enables interactive calls to the library.
It facilitates the development of interfaces between different codes and
can be used to convert data from one input/output file format into another.
## Requirements
- python3 (>= 3.6)
- numpy (>= 1.17.3)
## Installation from PyPI
In short, you can run the following command:
`pip install trexio`
However, it is good practice to first check for updates of the build-system packages. This can be achieved by running
`python -m pip install --upgrade pip setuptools build wheel`
**Note: we highly recommend to use virtual environments to avoid compatibility issues and to improve reproducibility.**
For more details, see the corresponding part of the [Python documentation](https://docs.python.org/3/library/venv.html#creating-virtual-environments).
## Additional requirements (for installation from source)
- C compiler (gcc/icc/clang)
- HDF5 library (>= 1.8)
- pkgconfig (Python package)
- build (Python package)
- pytest (Python package)
## Installation from source
1. Download the `trexio-<version>.tar.gz` file with the latest Python API
2. `gzip -cd trexio-<version>.tar.gz | tar xvf -`
3. `cd trexio-<version>`
4. `pip install -r requirements.txt` (this installs all required python dependencies)
5. Export custom environment variables needed for the installation following the procedure below and replacing `/path/to/hdf5/` with your paths.
The following two steps can be skipped if HDF5 is properly configured for `pkg-config` (i.e. if executing `pkg-config --libs hdf5` returns a list of options).
- `export H5_CFLAGS=-I/path/to/hdf5/include`
- `export H5_LDFLAGS=-L/path/to/hdf5/lib`
6. `pip install .` (this installs `trexio` in your environment)
7. `cd test && python -m pytest -v test_api.py` (this executes several tests that verify the installation)
You are ready to go!
**Note:**
installation based on `pip` compiles its own C extension (shared library) called `pytrexio`.
This extension is built from the TREXIO source files coupled to the wrapper code generated by [SWIG](http://www.swig.org/).
The compiler options during this installation may differ from the ones used to compile the primary TREXIO API in C.
Furthermore, custom compiler flags provided to `./configure` or `make` are not applied to the Python API.
## Examples
An interactive Jupyter notebook called `tutorial_benzene.ipynb` is provided in the `examples` directory.
The notebook can be lauched either locally (see [next section](#Running-the-notebook) for details) or using [pre-built environment on Binder](https://mybinder.org/v2/gh/TREX-CoE/trexio-tutorials/HEAD?filepath=notebooks%2Ftutorial_benzene.ipynb).
Jupyter can be installed using `pip install jupyter`. If you are not familiar with it, feel free to consult the [Jupyter documentation](https://jupyter-notebook.readthedocs.io/en/stable/notebook.html).
### Running the notebook
The example notebook can be launched using the following command:
`jupyter notebook tutorial_benzene.ipynb`
### Additional steps needed to run a custom virtual environment in Jupyter notebooks
In some cases, it may happen that the Jupyter kernels in the activated virtual environment (e.g. `myvenv`) still point to the system-wide python binaries and not to the environment ones.
This will result in `ImportError` when importing `trexio` in the notebook cell. In order to avoid this, the `myvenv` has to be installed as an additional kernel.
This requires `ipykernel` python package, which usually comes together with the Jupyter installation. If this is not the case, run `pip install ipykernel`.
You can install `myvenv` as a kernel by executing the following command:
`python3 -m ipykernel install --user --name=myvenv`
Now you can launch a Jupyter notebook. Once it is open, make sure that your virtual environment is selected as the current kernel.
If this is not the case, try this:
1. Press the `Kernel` button in the navigation panel
2. In the output list of options select `Change kernel`
3. Find the name of your virtual environment (e.g. `myvenv`) in the list and select it
That's it, you have activated the custom virtual environment called `myvenv` in your notebook.
To uninstall the kernel named `myvenv`, execute the following command:
`jupyter kernelspec uninstall myvenv`
%package -n python3-trexio
Summary: Python API of the TREXIO library
Provides: python-trexio
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-trexio
# TREXIO Python API
[](https://badge.fury.io/py/trexio)
[](https://mybinder.org/v2/gh/TREX-CoE/trexio-tutorials/HEAD)
TREXIO provides a Python API, which enables interactive calls to the library.
It facilitates the development of interfaces between different codes and
can be used to convert data from one input/output file format into another.
## Requirements
- python3 (>= 3.6)
- numpy (>= 1.17.3)
## Installation from PyPI
In short, you can run the following command:
`pip install trexio`
However, it is good practice to first check for updates of the build-system packages. This can be achieved by running
`python -m pip install --upgrade pip setuptools build wheel`
**Note: we highly recommend to use virtual environments to avoid compatibility issues and to improve reproducibility.**
For more details, see the corresponding part of the [Python documentation](https://docs.python.org/3/library/venv.html#creating-virtual-environments).
## Additional requirements (for installation from source)
- C compiler (gcc/icc/clang)
- HDF5 library (>= 1.8)
- pkgconfig (Python package)
- build (Python package)
- pytest (Python package)
## Installation from source
1. Download the `trexio-<version>.tar.gz` file with the latest Python API
2. `gzip -cd trexio-<version>.tar.gz | tar xvf -`
3. `cd trexio-<version>`
4. `pip install -r requirements.txt` (this installs all required python dependencies)
5. Export custom environment variables needed for the installation following the procedure below and replacing `/path/to/hdf5/` with your paths.
The following two steps can be skipped if HDF5 is properly configured for `pkg-config` (i.e. if executing `pkg-config --libs hdf5` returns a list of options).
- `export H5_CFLAGS=-I/path/to/hdf5/include`
- `export H5_LDFLAGS=-L/path/to/hdf5/lib`
6. `pip install .` (this installs `trexio` in your environment)
7. `cd test && python -m pytest -v test_api.py` (this executes several tests that verify the installation)
You are ready to go!
**Note:**
installation based on `pip` compiles its own C extension (shared library) called `pytrexio`.
This extension is built from the TREXIO source files coupled to the wrapper code generated by [SWIG](http://www.swig.org/).
The compiler options during this installation may differ from the ones used to compile the primary TREXIO API in C.
Furthermore, custom compiler flags provided to `./configure` or `make` are not applied to the Python API.
## Examples
An interactive Jupyter notebook called `tutorial_benzene.ipynb` is provided in the `examples` directory.
The notebook can be lauched either locally (see [next section](#Running-the-notebook) for details) or using [pre-built environment on Binder](https://mybinder.org/v2/gh/TREX-CoE/trexio-tutorials/HEAD?filepath=notebooks%2Ftutorial_benzene.ipynb).
Jupyter can be installed using `pip install jupyter`. If you are not familiar with it, feel free to consult the [Jupyter documentation](https://jupyter-notebook.readthedocs.io/en/stable/notebook.html).
### Running the notebook
The example notebook can be launched using the following command:
`jupyter notebook tutorial_benzene.ipynb`
### Additional steps needed to run a custom virtual environment in Jupyter notebooks
In some cases, it may happen that the Jupyter kernels in the activated virtual environment (e.g. `myvenv`) still point to the system-wide python binaries and not to the environment ones.
This will result in `ImportError` when importing `trexio` in the notebook cell. In order to avoid this, the `myvenv` has to be installed as an additional kernel.
This requires `ipykernel` python package, which usually comes together with the Jupyter installation. If this is not the case, run `pip install ipykernel`.
You can install `myvenv` as a kernel by executing the following command:
`python3 -m ipykernel install --user --name=myvenv`
Now you can launch a Jupyter notebook. Once it is open, make sure that your virtual environment is selected as the current kernel.
If this is not the case, try this:
1. Press the `Kernel` button in the navigation panel
2. In the output list of options select `Change kernel`
3. Find the name of your virtual environment (e.g. `myvenv`) in the list and select it
That's it, you have activated the custom virtual environment called `myvenv` in your notebook.
To uninstall the kernel named `myvenv`, execute the following command:
`jupyter kernelspec uninstall myvenv`
%package help
Summary: Development documents and examples for trexio
Provides: python3-trexio-doc
%description help
# TREXIO Python API
[](https://badge.fury.io/py/trexio)
[](https://mybinder.org/v2/gh/TREX-CoE/trexio-tutorials/HEAD)
TREXIO provides a Python API, which enables interactive calls to the library.
It facilitates the development of interfaces between different codes and
can be used to convert data from one input/output file format into another.
## Requirements
- python3 (>= 3.6)
- numpy (>= 1.17.3)
## Installation from PyPI
In short, you can run the following command:
`pip install trexio`
However, it is good practice to first check for updates of the build-system packages. This can be achieved by running
`python -m pip install --upgrade pip setuptools build wheel`
**Note: we highly recommend to use virtual environments to avoid compatibility issues and to improve reproducibility.**
For more details, see the corresponding part of the [Python documentation](https://docs.python.org/3/library/venv.html#creating-virtual-environments).
## Additional requirements (for installation from source)
- C compiler (gcc/icc/clang)
- HDF5 library (>= 1.8)
- pkgconfig (Python package)
- build (Python package)
- pytest (Python package)
## Installation from source
1. Download the `trexio-<version>.tar.gz` file with the latest Python API
2. `gzip -cd trexio-<version>.tar.gz | tar xvf -`
3. `cd trexio-<version>`
4. `pip install -r requirements.txt` (this installs all required python dependencies)
5. Export custom environment variables needed for the installation following the procedure below and replacing `/path/to/hdf5/` with your paths.
The following two steps can be skipped if HDF5 is properly configured for `pkg-config` (i.e. if executing `pkg-config --libs hdf5` returns a list of options).
- `export H5_CFLAGS=-I/path/to/hdf5/include`
- `export H5_LDFLAGS=-L/path/to/hdf5/lib`
6. `pip install .` (this installs `trexio` in your environment)
7. `cd test && python -m pytest -v test_api.py` (this executes several tests that verify the installation)
You are ready to go!
**Note:**
installation based on `pip` compiles its own C extension (shared library) called `pytrexio`.
This extension is built from the TREXIO source files coupled to the wrapper code generated by [SWIG](http://www.swig.org/).
The compiler options during this installation may differ from the ones used to compile the primary TREXIO API in C.
Furthermore, custom compiler flags provided to `./configure` or `make` are not applied to the Python API.
## Examples
An interactive Jupyter notebook called `tutorial_benzene.ipynb` is provided in the `examples` directory.
The notebook can be lauched either locally (see [next section](#Running-the-notebook) for details) or using [pre-built environment on Binder](https://mybinder.org/v2/gh/TREX-CoE/trexio-tutorials/HEAD?filepath=notebooks%2Ftutorial_benzene.ipynb).
Jupyter can be installed using `pip install jupyter`. If you are not familiar with it, feel free to consult the [Jupyter documentation](https://jupyter-notebook.readthedocs.io/en/stable/notebook.html).
### Running the notebook
The example notebook can be launched using the following command:
`jupyter notebook tutorial_benzene.ipynb`
### Additional steps needed to run a custom virtual environment in Jupyter notebooks
In some cases, it may happen that the Jupyter kernels in the activated virtual environment (e.g. `myvenv`) still point to the system-wide python binaries and not to the environment ones.
This will result in `ImportError` when importing `trexio` in the notebook cell. In order to avoid this, the `myvenv` has to be installed as an additional kernel.
This requires `ipykernel` python package, which usually comes together with the Jupyter installation. If this is not the case, run `pip install ipykernel`.
You can install `myvenv` as a kernel by executing the following command:
`python3 -m ipykernel install --user --name=myvenv`
Now you can launch a Jupyter notebook. Once it is open, make sure that your virtual environment is selected as the current kernel.
If this is not the case, try this:
1. Press the `Kernel` button in the navigation panel
2. In the output list of options select `Change kernel`
3. Find the name of your virtual environment (e.g. `myvenv`) in the list and select it
That's it, you have activated the custom virtual environment called `myvenv` in your notebook.
To uninstall the kernel named `myvenv`, execute the following command:
`jupyter kernelspec uninstall myvenv`
%prep
%autosetup -n trexio-1.3.2
%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-trexio -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 1.3.2-1
- Package Spec generated
|
