Installation#

Using PyPI#

Install the latest stable release from PyPI:

python -m pip install tanat

Using the latest GitHub-hosted version#

To get TanaT’s latest development version directly from GitHub:

python -m pip install git+https://github.com/TanaT-Lab/TanaT.git

Dependencies#

TanaT relies on several foundational libraries from the data science Python ecosystem, including:

  • pandas for convenient tabular data handling

  • polars and pyarrow for high-performance columnar data processing

  • numpy and scipy for numerical and scientific computing (transitive dependencies)

  • matplotlib for basic visualization

  • scikit-learn for machine learning utilities

  • numba for performance optimization through JIT compilation

In addition, TanaT makes use of:

  • tanat_utils for shared internal utilities

  • tqdm for progress tracking in processing pipelines (transitive dependency)

Optional dependencies#

SQL support (requires connectorx):

python -m pip install tanat[sql]