Yambopy via conda: Difference between revisions

Revision as of 12:57, 2 April 2022

For the installation of Yambopy we suggest to use conda in order to be sure to have all the Yambopy features available.

If you need only Yambopy because you are able (or you prefer) to install Yambo and Quantum-ESPRESSO by yourself (from source or Spack) or using the Docker container, you can stay with the basic conda channel:

first install the prerequisites (needed only for Miniconda)

conda install numpy scipy netcdf4 matplotlib pyyaml lxml pandas
pip install pymatgen
pip install abipy

then install Yambopy

git clone https://github.com/yambo-code/yambopy.git
cd yambopy
python setup.py install

It is possible to install also Yambo and Quantum-ESPRESSIO via conda-forge (a conda channel/repository):

first we suggest to create a conda environment and activate it:

conda create --name yambopy -c conda-forge
conda activate yambopy

then you can install the prerequisites and the two codes:

conda install numpy scipy netcdf4 matplotlib pyyaml lxml pandas
conda install yambo qe
pip install pymatgen
pip install abipy

finaly install Yambopy

git clone https://github.com/yambo-code/yambopy.git
cd yambopy
python setup.py install

@@ Line 3: / Line 3: @@
 * Start installing [https://www.anaconda.com/products/distribution#Downloads Anaconda] or [https://docs.conda.io/en/latest/miniconda.html Miniconda].
-* If you need only Yambopy because you are able (or you prefer) to install Yambo and Quantum-ESPRESSO by yourself (from source or [https://github.com/nicspalla/my-repo Spack]) or [[Yambo via Docker|using the Docker container]], you can stay with the basic conda channel:
+* If you need only Yambopy because you are able (or you prefer) to install Yambo and Quantum-ESPRESSO by yourself (from [[Installation|source]] or [https://github.com/nicspalla/my-repo Spack]) or [[Yambo via Docker|using the Docker container]], you can stay with the basic conda channel:
 first install the prerequisites (needed only for Miniconda)
   conda install numpy scipy netcdf4 matplotlib pyyaml lxml pandas