Python Software Foundation together with Jetbrains conduct their developer survey every year and at the end of 2017, over 9,500 developers from all over the world participated in this insightful Python developer survey. The learnings are pretty interesting and so, I thought I’d quickly summarise the most relevant points here. So here we go.
The above stats are quite interesting no doubt. This got me thinking about the why behind those numbers. Here’s my perspective on some of those findings. I would love to hear yours in the comments section below.
Starting with the usage of Python, the survey revealed that close to 80% of the respondents used Python as their primary language for development. When asked which languages they generally used it with, the top responses were JavaScript, HTML/CSS and SQL. On the other hand, a lot of Java developers and those using Bash/shell, seem to use Python as their secondary language. This shows that Python is quite interoperable with a number of other languages, making it versatile to use in web, enterprise and server side scripting.
Now when it comes to what tasks Python is used for in day to day development, it wasn’t a surprise when respondents mentioned Data Analysis. More than 50% use Python as their primary language for data analysis, however, only 32% claimed that they used it for Machine Learning. On the other hand, 54% mentioned that they used it for web development. 36% responded that they used Python for DevOps and system administration purposes. This isn’t surprising as most developers tend to stick to a particular tool/stack as far as possible.
Developers also responded that they used Python the most for Web Development, apart from anything else, with Machine Learning + Data Analysis close on its heels. Most DevOps and Sys admins use Python as their secondary language - that might be because shell/bash are their primary languages. In the 2016 survey, the percentage of web developers was much more than ML/Data Analysts, but the difference has reduced greatly.
When asked what roles these developers hold, the responses were quite interesting!
While nearly a quarter were in a combination of Data Analysis and Machine Learning roles, another quarter were in a combination of Data Analysis and Web Development! 15% claimed to be in Web Development and Machine Learning. This relationship, although quite unlikely, is extremely interesting and worth exploring further. One reason could be that developers are building machine learning solutions that are offered to customers as a web application, rather than as a desktop application. Another reason could also be that a lot of web apps these days are becoming more data driven and require some kind of machine learning components running under the hood.
A very surprising fact that surfaced from the survey was that 25% of developers still haven’t migrated their codebases to Python 3 and are still working with Python 2.
This is quite astonishing, since the support for Python 2 will be discontinued in less than two years (from Jan 1, 2020 to be precise). Although, the adoption for Python 3 has been growing steadily over the years, most of the developers who were still using Python 2 turned out to be web developers. This is so because data scientists might have moved into using Python quite recently, as compared to web developers who might have been using Python for a long time and hence, haven’t migrated their legacy code.
When asked about the tools that developers used, the web developers responded that a majority of them used Django(76%), while 53% used Requests and 49% used Flask.
When it came to GUI frameworks, 9% of developers used PyQT / PyGTK / wxPython while 6% used TkInter. 29% of these developers mentioned that they used scientific libraries like NumPy / pandas / Matplotlib / scipy. This is quite supportive of the overlap between both the GUI development and Data Science roles.
On the other hand, Data Scientists responded that 65% used NumPy / pandas / Matplotlib / scipy. 38% used Keras / Theano / TensorFlow / scikit-learn, while 31% and 27% used Django and Flask respectively. Django was a clear winner in the tools section, with an overall of 41% developers using it.
When asked about what tools they used along with Python, the web developers responded that 47% used Docker, 46% used an ORM like SQLAlchemy, PonyORM, etc. and 40% used Redis. 27% of them used Jupyter Notebook. The Data Scientists on the other hand, used Jupyter Notebook a lot (52%). 40% of them used Anaconda and 23% Docker. Of the various cloud platforms, developers chose AWS the most (65%).
When it came to Python features that were used the most, Code autocompletion (84%), code refactorings (82%) and writing unit tests (81%), made the top of the list. 75% developers used SQL databases while only 46% used NoSQL.
Of the various IDEs and Editors, PyCharm in both its versions, community and professional, was the most popular, closely tailed by Sublime, Vim, IDLE, Atom, and VS Code. While Web Developers preferred PyCharm, data scientists prefer Jupyter Notebook.
Unsurprisingly, 52% of Python developers claimed that they were in a full-time job. This ties in well with the 2018 StackOverflow Developer survey which labeled Python as the “most wanted” programming language. So developers out there, if you’re well versed with Python, you’re more likely to be hired.
Talking about job roles, 73% held the role of a Developer/Programmer, while 19% held the role of a Data Analyst and 18% an Architect. Interestingly, 7% of them held the role of a CIO / CEO / CTO.
In terms of years of experience, the results were well balanced with almost as many developers having more than 5 years of experience as those with less than 5 years of experience.
67% of the respondents were in the age group of 21-39, meaning that a majority of young folk seem to be using Python. If you’re one of them, and are looking to progress in your career, check out our extensive catalog of Python titles.
As for geographic location of the developers, 18% were from the US while 13% were from India and 7% from China.
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