Installing ODL from source¶
This installation method is intended for developers who want to make changes to the code and users that need the cutting edge.
TL;DR¶
Instructions for the impatient:
Clone ODL from git:
$ git clone https://github.com/odlgroup/odl
Install ODL
$ cd odl $ pip install [--user] --editable .
Don’t use the
--user
option together withconda
.Install the extensions you want.
Introduction¶
This guide assumes that the Git version control system is available on your system; for up-to-date instructions, consult the Git installation instructions. You also need pip to perform the installation.
Note
You should consider performing all described steps in a conda environment – it gives you the same encapsulation benefits as developer that you would enjoy also as a user (no conflicting packages, free to choose Python version, …). See the Installing Anaconda section for setup instructions.
To get ODL, navigate to a folder where you want the ODL repository to be stored and clone the repository with the command
$ git clone https://github.com/odlgroup/odl
No GitHub account is required for this step.
In a conda environment¶
This part assumes that you have activated a conda environment before (see Installing Anaconda).
You can choose to install dependencies first:
On Linux/MacOS:
$ conda install nomkl numpy scipy future matplotlib
On Windows:
$ conda install numpy scipy future matplotlib
After that, enter the top-level directory of the cloned repository and run
$ pip install --editable .
Optional dependencies:
You may also want to install optional dependencies:
$ conda install matplotlib pytest pytest-pep8
Using only pip
¶
Enter the top-level directory of the cloned repository and run
$ pip install --user --editable .
Note
Don’t forget the “.” (dot) at the end - it refers to the current directory, the location from where pip
is supposed to install ODL.
Note
We recommend the --editable
option (can be shortened to -e
) since it installs a link instead of copying the files to your Python packages location.
This way, local changes to the code (e.g. after a git pull
) take immediate effect after reloading the package, without requiring re-installation.
Optional dependencies:
You may also want to install optional dependencies:
$ pip install --user .[testing, show]
Running the tests¶
Unit tests in ODL are based on pytest.
They can be run either from within odl
or by invoking pytest
directly.
First, you need to install the testing dependencies using your favorite method below.
Using conda:
$ conda install pytest
Using pip:
$ pip install --user odl[testing]
Now you can check that everything was installed properly by running
$ python -c "import odl; odl.test()"
Note
If you have several versions of ODL and run this command in the top-level directory of an ODL clone, the tests in the repository will be run, not the ones in the installed package.
You can also use pytest
directly in the root of your ODL clone:
$ pytest
For more information on the tests, see Testing in ODL.
Further developer information¶
See Contributing to ODL for more information.