Installation

You do not need anything special to install the package . Just run the following (with python >= 3.10) to get the latest version and all basic dependencies:

pip install qsprpred

You can also get tags and development snapshots by varying the @main part (i.e. @1.0.0). After that you can start building models (see Command Line Interface Usage).

Note that this will install the basic dependencies, but not the optional dependencies. If you want to use the optional dependencies, you can install the package with an option:

pip install qsprpred[<option>]

The following options are available:

• extra : include extra dependencies for PCM models and extra descriptor sets from packages other than RDKit

• deep : include deep learning models (torch and chemprop)

• pyboost : include pyboost model (requires cupy, pip install cupy-cudaX, replace X with your cuda version, you can obtain cude toolkit from Anaconda as well: conda install cudatoolkit)

• full : include all optional dependecies (requires cupy, pip install cupy-cudaX, replace X with your cuda version)

You can test the installation by running the unit test suite:

python -m unittest discover qsprpred

Note that this can potentially take a long time and some tests may require you to have additional dependencies installed. However, you can also test each module separately:

python -m unittest qsprpred.data.tables.tests