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Happython 2019!


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Happy PyHolidays and Happy New Year!

We are approaching the end of the year 2018! And as it turns out this was an incredible year for Python! Even though Guido stepped out of his role as BDFL (this alone is worth a couple of blogposts so this one will not extend the discussion), there are a lot of happy recollections from this year. In 2017 StackOverflow stated that Python was the fastest-growing major programming language and the trend seems to persist this year too. Even so that Python has achieved 4th place at the TIOBE index, surpassing C# by a landmile and getting close to the 3rd place, C++. Not only that, but a prediction from Quartz claims that “It looks set to pass JavaScript [...] as the most queried about language in 2019.” since it grew from 4% of all queries in 2012 to a full 10% by the end of this year.

This outcome is no surprise once you consider the growth of Data Science and Machine Learning during that same period. The growing interest follows a steep rise in jobs in this areas different companies from different businesses learn that there is much intelligence to be gained from their data. Also, the growth of Django and Flask, although small in comparison, can’t be ignored. Two hypotheses for this growth in web are:

1) As JS frameworks get more complex and web development is almost ubiquitous, Python community’s ability to keep up-to-date with that has guaranteed it’s relevance;

2) Given that you are already doing data-science or machine learning with Python, it makes sense to use its web frameworks as well, even if it’s just to keep it all under the same stack.

It’s worth noting that even most of their data coming from high-income countries, the growth was global and countries like India, Brazil and Russia contributed a lot to the trend too.

Python Community

Being in Brazil we could see this contribution first hand. It feels great and the main reason behind it seems to be Python Brazil, the community that has developed over the years around the language. Although it began some years ago with a couple of lone enthusiasts spreaded around several companies, now it’s a vast network of people and companies who develop open source tools, share talks, organize tutorials and so much more. This year alone we had 8 regional events all over the country, each with around 200 people. Although there were several other events with varied sizes and purposes, they all culminated to PyBR[14], our equivalent off PyCon. This year there were over 800 participants, a lot of amazing talks (including 3 from Vinta), tutorials and sprints. This was also the year that the community released its code of conduct, formalizing our ideas and making clear what we consider to be an acceptable behaviour. We’re very grateful for the moments and discussions the event made possible and cannot recommend enough that people should attend it next year.

Also this year, we’ve seen an amazing project, called Operação Serenata de Amor, take off and fly at new heights. They are an open source project in Python that uses AI to create tools that society can use to fiscalize its governments. Part of what makes this project amazing is that it bridges together high-end technology (making good contributions to the data science field) with a social relevant problem. Brazil has a lot of corruption scandals and political problems, so an open source tool to increase social-accountability means a lot to us. This year they became partners of the Open Knowledge International on the civic innovation front!

Another project worth mentioning was Fernando Masanori’s classes using Python to teach programming skills to journalists. It was a project from Google News Lab and Folha de São Paulo, it happened in São Paulo and the classes lasted 3 months. They started with programming logic, learned how to interact with public APIs and how to scrape data from the web, closing with data visualization and how to produce images that helped them state their point. This project highlights how people who don’t necessarily work programming can learn and understand enough to improve their jobs/lives. You can check what they wrote and the graphics they generated on Masanori's talk here, available only in portugues.

Python: a Community-driven language

That very same community is one of the main reasons we program in Python from day one here at Vinta. Also we hypothesize that it’s of the reasons the language keeps growing so much over the years. Because the language quality/simplicity/power is important to attract people, but the steps that the community takes to keep improving it is what makes them stick with it. That’s where we try to contribute more. Be through creating open source tools, generating blogposts and talks, or simply supporting events that include more people in the discussion, we believe the language and the community can go a long way. The events and blogposts are great to help newcomers understand the language better and clear initial doubts, while the open source tools are a great way to improve code quality for more experienced programmers. On these fronts, this year we’ve become maintainers of 8 new libs (some our own and some that were orphan), we’ve produced approximately 20 blogposts and sponsored DjangoCon US, DjangoGirls Recife, DjangoGirls São Paulo, AfroPython, and Pyladies Teresina. We’ve also given around 10 talks, both in Brazil and in the US in multiple events and compiled over 808 links in our microblog. We expect to beat this mark next year and keep helping both the community and the language growing. And as a farewell lesson from year 2018 we can only stress what we’ve already stated in the philosophy section of our playbook: Community is one of the most important features of a programming language, keep this in mind when choosing one.


Thank you notes

Thanks a lot to @jesstemporal and @queirozMario21 for contributing with this post even after such a short notice!

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About Rob Novelino

Creator of organizational tools, whether they have code lines or not. Likes to read about crazy things like futurism, psychology, education and new economic models. When coding, goes for Python/Django.

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