index.rst

Welcome to Scaler's documentation!

Scaler is a lightweight distributed computing Python framework that lets you easily distribute tasks across multiple machines or parallelize on a single machine.

Scaler is designed to be a drop-in replacement for Dask requiring minimal code changes. Scaler's design focuses on performance, simplicity, reduced overhead, debuggable errors.

Key features include:

• Python's multiprocessing module like API - e.g. client.map() and client.submit()
• Graph Tasks - submit DAG tasks with complex interdependence
• Monitoring Dashboard - monitor utilization of workers and task completion in real time
• Task Profiling - profile and trace execution of tasks

Content

.. toctree::
   :maxdepth: 2

   tutorials/quickstart
   tutorials/features
   tutorials/scaling
   tutorials/worker_adapters/index
   tutorials/worker_adapters/native
   tutorials/worker_adapters/fixed_native
   tutorials/worker_adapters/orb
   tutorials/worker_adapters/aws_hpc/index
   tutorials/worker_adapters/common_parameters
   tutorials/compatibility/ray
   tutorials/configuration
   tutorials/examples
   tutorials/development/devcontainer
   tutorials/development/guidelines