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The PEP Talk - Episode 37

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Summary

The Python language is built by and for its community. In order to add a new feature, change the specification, or create a new policy the first step is to submit a proposal for consideration. Those proposals are called PEPs, or Python Enhancement Proposals. In this episode we had the great pleasure of speaking with three of the people who act as stewards for this process to learn more about how it got started, how it works, and what impacts it has had.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • Subscribe on iTunes, Stitcher, TuneIn or RSS
  • Follow us on Twitter or Google+
  • Give us feedback! Leave a review on iTunes, Tweet to us, send us an email or leave us a message on Google+
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable. For details on how to support the show you can visit our site at pythonpodcast.com
  • This episode is sponsored by Zato – Microservices, ESB, SOA, REST, API, and Cloud Integrations in Python. Visitzato.io to learn more about how to integrate smarter in the modern world.
  • I would also like to thank Hired, a job marketplace for developers, for sponsoring this episode of Podcast.__init__. Use the link hired.com/podcastinit to double your signing bonus.
  • Searching for Pythonistas with Disabilities
  • We are recording today on December 7th, 2015 and your hosts as usual are Tobias Macey and Chris Patti
  • Today we are interviewing some of the PEP editors

Interview with PEP editors

  • Introductions
  • How did you get introduced to Python? – Chris
  • For anyone who isn’t familiar with them, can you explain what a PEP is and how they influence the Python language? – Tobias
  • What are the requirements for a PEP to be considered for approval and what does the overall process look like to get it finalized? – Tobias
  • How has the PEP process evolved to meet challenges posed by changes in the Python community? – Chris
  • How many reviewers are there and how did each of you end up in that role? Is there a set number of editors that must be maintained and if so how did you arrive at that number? – Tobias
  • What mistakes have other communities made when creating similar processes, and how has PEP learned from those mistakes? – Chris
  • There are different categories for PEPs. Can you describe what those are and how you arrived at that ontology? – Tobias
  • Is there any significance to the numbering system used for identifying different PEPs? – Tobias
  • How does the PEP process maintain its sense of humor (e.g. PEP 20) while being sure to be taken seriously where it really counts? – Chris
  • Along the lines of humorous PEPs, can you share the story of PEP 401? – Tobias
  • How does the PEP process strive to prevent an undesirable level of control by any one company or other special interest group? – Chris
  • How much control does Guido have over the PEP process? Has a PEP ever directly countered Guido’s wishes? How did it turn out? – Chris
  • What is your favorite PEP and why? – Tobias
  • What, in your opinion, has been the most important or far-reaching PEP, whether it was approved or not? – Tobias
  • What was the strangest / most extreme PEP proposal you’ve ever seen? – Chris

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Maneesha Sane on Software and Data Carpentry - Episode 33

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Summary

The Software and Data Carpentry organizations have a mission of making it easier for scientists and data analysts in academia to replicate and review each others work. In order to achieve this goal they conduct training and workshops that teach modern best practices in software and data engineering, including version control and proper data management. In this episode we had the opportunity to speak with Maneesha Sane, the program coordinator for both organizations, so that we could learn more about how these projects are related and how they approach their mission.

Brief Introduction

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • Subscribe on iTunes, Stitcher, TuneIn or RSS
  • Follow us on Twitter or Google+
  • Give us feedback! Leave a review on iTunes, Tweet to us, send us an email or leave us a message on Google+
  • I would like to thank everyone who has donated to the show. Your contributions help us make the show sustainable. For details on how to support the show you can visit our site at pythonpodcast.com
  • This episode is sponsored by Zato – Microservices, ESB, SOA, REST, API, and Cloud Integrations in Python. Visit zato.io to learn more about how to integrate smarter in the modern world.
  • I would also like to thank Hired, a job marketplace for developers, for sponsoring this episode of Podcast.__init__. Use the link hired.com/podcastinit to double your signing bonus.
  • Linode is sponsoring us this week. Check them out at linode.com/podcastinit and get a $10 credit to try out their fast and reliable Linux virtual servers for your next project
  • We are recording today on November 10th, 2015 and your hosts as usual are Tobias Macey and Chris Patti
  • Today we are interviewing Maneesha Sane about Software Carpentry and Data Carpentry

Interview with Maneesha Sane

  • Introductions
  • How did you get introduced to Python?
  • Can you explain what the Software and Data Carpentry organizations are and what their respective goals are?
  • What is the history of these organizations and how are they related?
  • What does a typical Software Carpentry or Data Carpentry workshop look like?
  • What is the background of your instructors?
  • Can you explain why Python was chosen as the language for your workshops and why it is such a good language to use for teaching proper software engineering practices to scientists?
  • In what ways do the lessons taught by both groups differ and what parts are common between the two organizations?
  • What are some of the most important tools and lessons that you teach to scientists in academia?
  • Do you tend to focus mostly on procedural development or do you also teach object oriented programming in Software Carpentry?
  • What is the target audience for Data Carpentry and what are some of the most important lessons and tools taught to them?
  • Do you teach any particular method of pre-coding design like flowcharting, pseudocode, or top down decomposition in software carpentry?
  • What scientific domains are most commonly represented among your workshop participants for Software Carpentry?
  • What are some specific things the Python community and the Python core team could do to make it easier to adopt for your students?
  • What are the most common concepts students have trouble with in software & data carpentry?
  • How can our audience help support the goals of these organizations?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA