Installation¶
tffpy requires the following packages, which will be automatically
installed with tffpy using pip:
Make sure your Python environment is properly configured. It is recommended to
install tffpy in a virtual environment.
Release version¶
First, make sure you have the latest version of pip (the Python package
manager) installed. If you do not, refer to the Pip documentation and install pip first.
Install the current release with pip:
pip install tffpy
To upgrade to a newer release use the --upgrade flag:
pip install --upgrade tffpy
If you do not have permission to install software systemwide, you can install
into your user directory using the --user flag:
pip install --user tffpy
Alternatively, you can manually download tffpy from its GitLab project or PyPI. To install one of these versions,
unpack it and run the following from the top-level source directory using the
Terminal:
pip install .
Dataset installation¶
Download the data from this link.
Then run function tffpy.utils.generate_config() in order to create
a configuration file and modify it to specify the path to your data folder.
The location of the configuration file is given by function
tffpy.utils.get_config_file().
Development version¶
If you have Git installed on your system, it is also
possible to install the development version of tffpy.
Before installing the development version, you may need to uninstall the
standard version of tffpy using pip:
pip uninstall tffpy
Clone the Git repository:
git clone git@gitlab.lis-lab.fr:skmad-suite/tff2020.git
cd python
You may also need to install required packages:
pip install -r requirements/defaults.txt
Then execute pip with flag -e to follow the development branch:
pip install -e .
To update tffpy at any time, in the same directory do:
git pull
To run unitary tests, first install required packages:
pip install -r requirements/dev.txt
and execute pytest:
pytest