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Installation

pyDatalog can be easily installed from the Python Package Index (PyPI).

Quick Installation

Using pip

You can install pyDatalog and its optional dependencies (like SQLAlchemy) using standard pip:

pip install pyDatalog SQLAlchemy

Using uv

If you manage your project using uv, you can run:

uv add pyDatalog SQLAlchemy

To run a script in an isolated environment directly: 

uv run python your_script.py

Installation on PyPy

pyDatalog fully supports PyPy for accelerated JIT performance. You can install it using PyPy's pip tool:

pypy -m pip install pyDatalog SQLAlchemy

Installation in WebAssembly (Pyodide)

Since pyDatalog is distributed with a pure Python wheel, it can be run out of the box in WebAssembly-based Python environments (like Pyodide or JupyterLite).

To load and use pyDatalog inside Pyodide, install it using micropip:

import micropip
await micropip.install("pyDatalog")

After installation, you can import and use the library: 

from pyDatalog import pyDatalog

Installation from Source

You can build and install pyDatalog directly from the source code. This is useful if you want to modify the source code or use development builds.

1. Download the Source

Clone the repository: 

git clone https://github.com/pcarbonn/pyDatalog.git
cd pyDatalog

2. Install the Package

Run pip to install it in editable mode or from the local directory: 

pip install -e .

[!NOTE] During installation from source (instead of from pre-built wheels), the build system will attempt to compile the Cython speed-up extension. If compilation fails (e.g., due to a missing C compiler or missing Python header files), the installation will automatically and gracefully fall back to installing the pure Python implementation of the execution engine.

Verifying the Installation

To verify that pyDatalog has been installed correctly, open a Python interactive shell and run:

>>> import pyDatalog
>>> print(pyDatalog.__version__)

If it executes without errors and prints the version number, the installation was successful!

Checking if the C extension is used

If you installed pyDatalog from source and want to verify whether the compiled C speed-up extension is active (instead of the pure Python fallback), import pyEngine and check its file path:

>>> from pyDatalog import pyEngine
>>> print(pyEngine.__file__)
  • Compiled C extension is active: The file path will end in a compiled extension extension like .so (on Linux/macOS) or .pyd (on Windows).
  • Pure Python fallback is active: The file path is pyEngine.py.