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Including conda and pytest in README
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README.md
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README.md
@ -34,7 +34,7 @@ TREX library for efficient I/O.
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- python3 (>= 3.6)
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- python3 (>= 3.6)
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- Emacs (>= 26.0)
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- Emacs (>= 26.0)
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- SWIG (>= 4.0)
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- SWIG (>= 4.0) [required for the Python API]
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## Installation procedure from the GitHub repo clone (for developers):
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## Installation procedure from the GitHub repo clone (for developers):
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@ -61,6 +61,18 @@ The aforementioned instructions rely on [Autotools](https://www.gnu.org/software
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**Note: when linking against an MPI-enabled HDF5 library one usually has to specify the MPI wrapper for the C compiler by adding, e.g., `-DCMAKE_C_COMPILER=mpicc` to the `cmake` command.**
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**Note: when linking against an MPI-enabled HDF5 library one usually has to specify the MPI wrapper for the C compiler by adding, e.g., `-DCMAKE_C_COMPILER=mpicc` to the `cmake` command.**
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## Installation procedure for conda users
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The official releases (tarballs) of TREXIO `>2.0.0` are also available via the `conda-forge` channel.
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The pre-compiled stable binaries of `trexio` can be installed as follows:
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```
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conda install trexio -c conda-forge
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```
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More details can be found in the corresponding [trexio-feedstock](https://github.com/conda-forge/trexio-feedstock).
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Note that both parallel (see `mpi_openmpi` prefix) and serial (`nompi`) variants are provided.
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## Compilation without the HDF5 library
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## Compilation without the HDF5 library
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By default, the configuration step proceeds to search for the [HDF5 library](https://portal.hdfgroup.org/display/HDF5/HDF5).
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By default, the configuration step proceeds to search for the [HDF5 library](https://portal.hdfgroup.org/display/HDF5/HDF5).
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@ -130,6 +142,12 @@ make python-install
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**Note: this implies that both HDF5 and SWIG are installed and available.
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**Note: this implies that both HDF5 and SWIG are installed and available.
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At the moment, it is not possible to configure the Python API without HDF5 library.**
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At the moment, it is not possible to configure the Python API without HDF5 library.**
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We rely on the `pytest` package for unit testing. It can be installed via `pip install pytest`. To test the installation, run
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```
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make python-test
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```
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We highly recommend to use virtual environments to avoid compatibility issues and to improve reproducibility.
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We highly recommend to use virtual environments to avoid compatibility issues and to improve reproducibility.
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