Parallel execution

• ipyparallel Interactive Parallel Computing in Python http://ipyparallel.readthedocs.org/

Interactive Python

• IPython provides a rich architecture for interactive computing with:

  • A kernel for Jupyter.
  • A powerful interactive shell.
  • Support for interactive data visualization and use of GUI toolkits.
  • Flexible, embeddable interpreters to load into your own projects.
  • Easy to use, high performance tools for parallel computing.

• jupyter/qtconsole Jupyter Qt Console http://jupyter.org/qtconsole/stable/

• The Jupyter Notebook

Web frameworks

• falconry/falcon Falcon is a high-performance Python framework for building cloud APIs, smart proxies, and app backends. [http://falconframework.org]. Documentation: http://falcon.readthedocs.org/en/stable/

Testing

• svanoort/pyresttest, Python Rest Testing

  • A simple but powerful REST testing and benchmarking framework
  • Minimal dependencies, designed to slot into automated configuration management/orchestration tools
  • Tests are defined in basic YAML or JSON config files, no code needed
  • Logic is written and extensible in Python

• Testing your REST client in Python

• chitamoor/Rester allows you to test your APIs using a non-programatic or non-GUI based approach (which are some of the more conventional ways of testing RESTFul APIs). Rester is inspired by various unit testing frameworks like JUnit, 'unittest' (python) etc and is conceptually organized like those frameworks but is geared towards testing RESTful API endpoints. With Rester, all tests are specified in YAML or JSON, so it can also be used by non-programmers as well.
• Testing Flask Applications

• Django Testing Docs’s documentation

• nose extends unittest to make testing easier.

• Mock - Mocking and Testing Library

Documentation

• Python Module of the Week