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Writing about Python

One of the world’s most popular programming languages

A bit beyond 100 days ago I set out to write about artificial intelligence every day for 500 days. In a spur of a moment decision I decided that the next 100 days, that is day 101–200, would be on the topic of Python. It may seem strange to restrict myself to such a specific topic when there is so much to write about within artificial intelligence, and when Python is not the only language. On the other hand it helps for me to focus on one specific topic; Python is one of the most popular languages in machine learning techniques; and I am currently learning the basics of Python at my university. Learning Python seems like quite a journey to undertake, yet there are many who have walked this path before.

Today I will start out lightly and give myself some slack since I reached the milestone of 100 articles this will therefore be a shorter article. Earlier in the day I had a presentation in digital anthropology from Julie Jung who works for Microsoft here. Her recent studies indicated that employees are increasingly required or expected to be learning programming almost regardless of the profession that they find themselves in. There is as such an expectation for those in work to constantly develop themselves in their spare time, as such having less time off. Me as such aspiring to become a great employee or a neoliberal subject has therefore taken on the task of finding out what programming language is the most popular within artificial intelligence.

Kaggle is an online community of data scientists and machine learners, owned by Google LLC (aquired on the 8th of March). They allows people to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

Kaggle got its start by offering machine learning competitions and now also offers a public data platform, a cloud-based workbench for data science, and short form AI education. They have done a Data Science Survey for 2018 and the stats for the most preferred programming languages are Python, R and SQL. Python was clearly biggest among all groups and as you can see SQL were slightly more popular with data analysts. There were 23,859 responses in this survey performed by Kaggle:

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On the Kaggle website I found a really cool introduction to Python, a so-called micro course. It is introduced in the title as: “Python. Learn the most important language for Data Science.”

SlashData, one of the largest surveys of developers worldwide says 11.7 million developers use Javascript (with web and cloud applications or services being the most popular use-case)s. Python was a natural second place; 8.2 million developers use it for tasks such as machine learning and the Internet of Things.”

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An actual Python snake, photo by @davidclode

According to the Python software foundation the reasoning for the name is as follows:

“Why is it called Python? When he began implementing Python, Guido van Rossum was also reading the published scripts from “Monty Python’s Flying Circus”, a BBC comedy series from the 1970s. Van Rossum thought he needed a name that was short, unique, and slightly mysterious, so he decided to call the language Python.”

As such the name itself carried with it humour.

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Me trying to learn how to Python

I decided to read further through the general information on the official Python website.

The Python Software Foundation is according to its website descriptions an independent non-profit organisation that holds the copyright on versions 2.1 and newer. The PSF’s mission is to advance open source technology related to the Python programming language and to publicise the use of Python. Guido van Rossum did as mentioned set up the programming language however it does now per 2019 have officers and a board. As far as I can see from their website their current leading team is as follows.

Officers:

  • Guido van Rossum, President
  • Chair: Naomi Ceder, Chair
  • Jackie Kazil, Vice Chair Elect
  • Van Lindberg, Vice Chair
  • Thomas Wouters, Vice Chair
  • Marlene Mhangami, Communication Chair
  • Lorena Mesa, Communication Chair
  • Ernest W. Durbin III, PyCon Chair
  • Ewa Jodlowska, Director of Operations
  • Kurt Kaiser, Treasurer
  • Van Lindberg, General Counsel
  • Ewa Jodlowska, Secretary
  • Betsy Waliszewski, Assistant Secretary
  • Ewa Jodlowska & Betsy Waliszewski, Event Coordinators

Board of Directors:

  • Van Lindberg
  • Naomi Ceder
  • Eric Holscher
  • Jackqueline Kazil
  • Anna Ossowski
  • Lorena Mesa
  • Thomas Wouters
  • Kushal Das
  • Marlene Mhangami
  • Christopher Neugebauer
  • Jeff Triplett
  • Katie McLaughlin
  • Ewa Jodlowska

I will not go into who each of these people are right now, but it is sufficient to say that although this is a language it does have governance. Additionally the homepage of Python has links to a lot of learning resources such as the Beginners Guide to Python and the Python Tutorial:

This was only a short article, but I hope you enjoyed it.

This is day 101 of #500daysofAI. My current focus for day 101–200 is on Python programming. If you enjoy this article please give me a response as I do want to improve my writing or discover new research, companies and projects.

Written by

AI Policy and Ethics at www.nora.ai. Student at University of Copenhagen MSc in Social Data Science. All views are my own. twitter.com/AlexMoltzau

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