We recommend installing pyDeltaRCM in a virtual environment. That said, pyDeltaRCM depends on a small number of packages (list of dependencies), many of which are likely already in a Python user/developer’s regular use, so it’s probably safe to install it in your base environment, too.
We describe installation flavors for both users and developers below.
If you are looking to make any modifications to the code base, you should follow the developer instructions.
We suggest using the Anaconda Python distribution, which you can obtain via the project website.
Before proceeding, you may wish to create a virtual environment for the pyDeltaRCM project. With Anaconda:
$ conda create -n deltarcm
See this helpful guide for creating virtual environments with venv if you do not use Anaconda.
For a user installation, simply install from the pypi package repository:
$ pip install pyDeltaRCM
For a developer installation, you should first fork the repository on Github. This will allow you to submit suggestions and contribute to pyDeltaRCM.
You do not need to create a fork if your are just testing, but it may save you time and headache down the road. If you choose not to, just use the main repository url below (https://github.com/DeltaRCM/pyDeltaRCM.git).
First download or clone your fork of the project:
$ git clone https://github.com/<your-username>/pyDeltaRCM.git
Then, with current working directory as the root of the repository (e.g.,
cd pyDeltaRCM), run the following commands:
$ pip install -r requirements.txt $ pip install -r requirements-docs.txt $ pip install -r requirements-test.txt $ pip install -e .
To check installation, run the complete test suite with:
$ pytest --mpl --mpl-baseline-path=tests/imgs_baseline
Finally, add the upstream repository to your remote repository list:
$ git remote add upstream https://github.com/DeltaRCM/pyDeltaRCM.git
You can build a local copy of the documentation with:
$ (cd docs && make html)
1numpy 2matplotlib 3scipy>=1.5 4netCDF4 5pyyaml>=5.1 6numba