Get Started¶
It is highly recommended to install in a virtual environment to keep your system in order.
Installing with pip
(recommended)¶
The following command installs the latest version of the library:
pip install coola
To make the package as slim as possible, only the packages required to use coola
are installed.
It is possible to install all the optional dependencies by running the following command:
pip install 'coola[all]'
This command also installed NumPy and PyTorch. It is also possible to install the optional packages manually or to select the packages to install. In the following example, only NumPy is installed:
pip install coola numpy
Installing from source¶
To install coola
from source, you can follow the steps below. First, you will need to
install poetry
. poetry
is used to manage and install
the dependencies.
If poetry
is already installed on your machine, you can skip this step. There are several ways to
install poetry
so you can use the one that you prefer. You can check the poetry
installation by
running the following command:
poetry --version
Then, you can clone the git repository:
git clone git@github.com:durandtibo/coola.git
It is recommended to create a Python 3.9+ virtual environment. This step is optional so you can skip it. To create a virtual environment, you can use the following command:
make conda
It automatically creates a conda virtual environment. When the virtual environment is created, you can activate it with the following command:
conda activate coola
This example uses conda
to create a virtual environment, but you can use other tools or
configurations. Then, you should install the required package to use coola
with the following
command:
make install
This command will install all the required packages. You can also use this command to update the required packages. This command will check if there is a more recent package available and will install it. Finally, you can test the installation with the following command:
make unit-test-cov
Testing¶
The last version of coola
is tested for the following package versions:
package | tested versions |
---|---|
jax |
>=0.4,<0.5 |
numpy |
>=1.21,<1.27 |
pandas |
>=1.3,<2.3 |
polars |
>=0.18.3,<0.21 |
torch |
>=1.10,<2.3 |
xarray |
>=2023.2,<2024.3 |
- More information can be found in the CI workflow configuration.
coola
relies on the semantic versioning (SemVer) of the packages to test the range of versions.xarray
uses calendar versioning (CalVer) andcoola
is tested on the versions for the last year.