Install¶
Rian requires Python 3.7 or later. If you do not already have a Python environment configured on your computer, please see the instructions for installing the full scientific Python stack.
Note
If you are using the Windows platform and want to install optional packages (e.g., scipy), then it may be useful to install a Python distribution such as: Anaconda, Enthought Canopy, Python(x,y), WinPython, or Pyzo. If you already use one of these Python distributions, please refer to their online documentation.
Below it is assumed, that you have the default Python environment configured on your computer and you intend to install Rian inside of it. If you want to create and work with Python virtual environments, please follow instructions on venv and virtual environments.
Install the latest distributed package¶
You can install the latest distributed package of Rian by using pip:
$ pip install rian
Install the development branch¶
The installation requires that you have Git installed on your system. Under this prerequisite the first step is to clone the GitHub repository of Rian:
$ git clone https://github.com/frootlab/rian.git
Thereupon the development branch can locally be installed by using pip:
$ cd rian
$ pip install -e .
The pip install
command allows you to follow the development branch as
it changes by creating links in the right places and installing the command
line scripts to the appropriate locations.
Update the development branch¶
Once you have cloned the Rian GitHub repository onto a local directory, you
can update it anytime by running a git pull
in this directory:
$ git pull
Testing the development branch¶
Rian uses the Python builtin package unittest for testing. Since the tests are not included in the distributed package you are required to install the Rian development branch. Thereupon you have to switch to the repository directory and run:
$ python3 tests
Required packages¶
Note
Some required packages (e.g., numpy) may require compiling C or C++ code. If you have difficulty installing these packages with pip, it is highly recommended to review the instructions for installing the full scientific Python stack.
By using the pip install
the required packages should by installed
automatically. These packages include:
- `numpy <https://www.numpy.org/>`_ (>= 1.15.0)
- `NetworkX <https://networkx.github.io/>`_ (>= 2.1)
- `Matplotlib <https://matplotlib.org/>`_ (>= 2.2.2)
- `AppDirs <https://github.com/ActiveState/appdirs>`_ (>= 1.1.0)