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jhermann
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Description

:clapper: :mortar_board: An opinionated list of awesome videos related to Python, with a focus on training and gaining hands-on experience.

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logo Awesome Python Talks

An opinionated list of awesome videos related to Python, with a focus on training and gaining hands-on experience.

CC0 licensed

Contents

Being Pythonic

Writing pythonic code in good style, and for humans…

❑ ❑ ❑ ❑

The New Era

Python 3 and other ‘modern’ and/or exciting stuff…

❑

Architecture & Software Design

❑

  • The Clean Architecture in Python [50 min, PyOhio 2014, slides] – Applying Clean Architecture (a/k/a Hexagonal Architecture) to your Python code, making it more functional, for easier testing and comprehension.

Documentation

Testing

❑

Build Tools & Automation

  • TODO Paver, doit, buildout, …

Releasing & Packaging

❑ ❑

  • devpi: driving packaging and testing needs [55 min, PyCon DE 2013] – Introduction to devpi (shortly before the 1.2 release), which is a private PyPI server, a self-updating
    pypi.python.org
    package cache, and a work-flow for uploading, testing and installing packages backed by tools.
  • Grug make fire! Grug make wheel! [27 min, PyCon AU 2014] – A look back at the confusing history of packaging in Python, how things got better and lead to today's formats and tools for releasing Python code.
  • Python Packaging — A Zeitgeist [16 + 4 min, PyCon 2014] — A look at the current state of PyPI and related tooling (still applicable in 2016), and what's to come (PyPI 2.0 and metadata 2.0).
  • Shipping Software To Users With Python [41 + 4 min, PyCon 2016] — glyph talks about building Python code into something a user can use.
  • Reliably Distributing Compiled Modules [26 + 5 min, PyCon 2016] — Sort-of continues glyph's talk: what happens when you mix in CPython extensions.

DevOps with Python

  • TODO fabric, Salt, Ansible, …

Scientific Python

All about data science with Python…

  • TODO IPython + other basics
  • TODO Pandas, bokeh, Anaconda, …

  • IPython Notebook best practices for data science [35 min, oscon Portland 2015] – How to work with Jupyter in a team, and some opinionated tips on workflows and document organization.

Visualization

Related Resources

Contributing

Contributions are welcome, please open a PR or an issue. Processing these will take a while though, since I'll at least take a peek into new submissions. In this early stage, proposals for adding missing categories are also useful. In your submissons, please stick to the established format of existing entries, and always include a duration and date.

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