1. Getting started#

1.1. Requirements#

julearn is compatible with Python >= 3.8 and requires the following packages:

numpy>=1.24,<1.27
pandas>=1.5.0,<2.2
scikit-learn>=1.2.0,<1.5.0
statsmodels>=0.13,<0.15

Running the examples require:

seaborn>=0.12.2,<0.13
bokeh>=3.0.0
panel>=1.3.0
param>=2.0.0

Depending on the installation method (e.g. the pip install option below), these packages might be installed automatically. It is nevertheless good to be aware of these dependencies as installing julearn might lead to changes in these packages.

2. Setup suggestion#

Although not required, we strongly recommend using virtual environments and installing julearn into a virtual environment. This helps to keep the setup clean. The most prominent options are:

pip: venv
conda: conda env

3. Installing#

Note

julearn keeps on being updated and improved. The latest stable release and the developer version therefore often differ quite a bit. If you want the newest updates, it might make more sense for you to use the developer version until we release the next stable julearn version.

Depending on your aimed usage of julearn you have different options how to install julearn:

Install the latest release: Likely most suitable for most end users. This is done by installing the latest stable release from PyPI:
```
pip install -U julearn
```
or via conda like so:
```
conda install -c conda-forge julearn
```
Install the latest pre-relase: This version will have the latest updates. However, it is still under development and not yet officially released. Some features might still change before the next stable release.
```
pip install -U julearn --pre
```

4. Optional Dependencies#

Some functionality of julearn requires additional packages. These are not installed by default. If you want to use these features, you need to specify them during installation. For example, if you want to use the viz module, you need to install the viz optional dependencies as follows:

pip install -U julearn[viz]

The following optional dependencies are available:

viz: Visualization tools for julearn. This includes the viz module.
deslib: The dynamic module requires the deslib package. This module is not compatible with newer Python versions and it is unmaintained.
skopt: Using the "bayes" searcher (BayesSearchCV) requires the scikit-optimize package.
optuna: Using the "optuna" searcher (OptunaSearchCV) requires the Optuna and optuna_integration packages.
all: Install all optional functional dependencies (except deslib).