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Get Started

It is highly recommended to install in a virtual environment to keep your system in order.

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

Note: coola requires Python 3.10 or higher.

It is recommended to create a virtual environment (this step is optional). 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

coola is continuously tested with the following package versions:

package tested versions
jax >=0.5.0,<1.0
numpy >=1.24,<3.0
packaging >=22.0,<26.0
pandas >=2.0,<3.0
polars >=1.0,<2.0
pyarrow >=11.0,<23.0
torch >=2.0,<3.0
xarray >=2023.1

For the most up-to-date compatibility information, see:

Note:

  • coola relies on semantic versioning (SemVer) for most packages.
  • xarray uses calendar versioning (CalVer).
  • Version constraints are designed to be flexible while ensuring compatibility.