An experimental framework that democratizes access to distributed serverless compute.
Planet-scale distributed computing in Python.
!!! RESEARCH PREVIEW !!!
Pythagoras is a super-scalable, easy-to-use, and
low-maintenance framework for (1) massive algorithm parallelization and
(2) hardware usage optimization in Python. It simplifies and speeds up
data science, machine learning, and AI workflows.
Pythagoras excels at complex, long-running, resource-demanding computations.
It’s not recommended for real-time, latency-sensitive workflows.
Pythagoras elevates two popular techniques — memoization and parallelization —
to a global scale and then fuses them, unlocking performance and scalability
that were previously out of reach.
Drawing from many years of functional-programming practice,
Pythagoras extends these proven ideas to the next level.
In a Pythagoras environment, you can seamlessly employ your
preferred functional patterns, augmented by new capabilities.
!!! BOOKMARK THIS PAGE AND COME BACK LATER, WE WILL PUBLISH MORE TUTORIALS SOON !!!
The source code is hosted on GitHub at: https://github.com/pythagoras-dev/pythagoras
Installers for the latest released version are available
at the Python package index at: https://pypi.org/project/pythagoras
Using uv :
uv add pythagoras
Using pip (legacy alternative to uv):
pip install pythagoras
Pythagoras of Samos was a famous ancient Greek thinker and scientist
who was the first man to call himself a philosopher (“lover of wisdom”).
He is most recognised for his many mathematical findings,
including the Pythagorean theorem.
Not everyone knows that in antiquity, Pythagoras was also credited with
major astronomical discoveries, such as sphericity of the Earth
and the identity of the morning and evening stars as the planet Venus.