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Showing content from https://www.jetbrains.com/lp/python-developers-survey-2017/ below:

Python Developers Survey 2017 - Results

Check out the results of the Python Developer Survey in 2016, 2018, 2019, 2020, 2021, 2022 and 2023.

To identify the most popular types of Python development (a.k.a. developer roles) and how they are combined, we asked two similar but different questions: “What do you use Python for?” with multiple answers, followed by a single-answer “What do you use Python for the most?”.

Combined

Python is main

Python is secondary

Data analysis is as popular as web development with Python.

Web development is the only category with a large gap (54% vs 33%) separating those using Python as their main language vs as a supplementary language. For other types of development, the differences are far less significant.

Interesting fact

Various studies show that the number of Python developers is growing steadily year by year. The rapid growth of Python popularity can be explained by the fact that many people are starting to use Python for data science and machine learning. This is the fastest-growing segment of Python users.

Many Python developers wear multiple hats. We’ve identified the roles that they combine most often (not necessarily as their main ones):

The intersection of data analysis and machine learning was expected, but the overlaps between web development and data analysis / machine learning are definitely noteworthy.

Combined

Python is main

Python is secondary

In this question, respondents could only select one option. At first glance, the results suggest that web development is a strong leader with 26%, beating Data analysis (18%) by a large margin. But if we take a closer look, there’s also Machine learning with 9%. If we bundle Data analysis and Machine learning together into a single ‘Data science’ category, this amounts to a stunning 27%.

Comparing the trends among those using Python as their main language vs a secondary language, web development has the biggest gap (29% vs 15%). For Data analysis and Machine learning, the difference is much smaller. Conversely, more DevOps and System administrators are using Python as a secondary language (13%) than as main language (8%).

Interesting fact

In a similar survey that JetBrains ran in 2016, 38% of respondents identified as web developers and only 21% as data scientists.

There are as many Python web developers as Python data scientists.

The most intriguing question in this survey concerned the ratio of web developers to data scientists in the Python world. We asked respondents to think about the ratio between the total number of Python web developers in the world and the total number of data scientists using Python. Respondents could answer based on their own experience, beliefs, and general ‘gut feeling’. Because in this same survey we explicitly asked about types of development, and the sample size is large enough to be statistically significant, we could compare and check if the community was right about the correct ratio. Here’s what we got:

What do you think is the ratio of these two numbers?

Web developers

:

Data scientists

As you can see, the most popular ratio is 5:1. You can also notice that a larger part of respondents (57%) thought there are more web developers than data scientists, while only 33% assumed the opposite.

Note: Percentages total 101%
because of rounding

Now, let’s revisit the types of development stats mentioned earlier. With 26% doing web development as their primary activity, and 18% primarily involved in data analysis + 9% primarily doing machine learning, the ratio is in fact 1:1! Only one in nine respondents guessed this correctly.

Interesting fact

Most respondents underestimated the total number of developers involved in data science. It's generally perceived that web development is the major application for Python. While this was true a couple of years ago, today the number of Python data scientists is growing rapidly and is already on par with the number of web developers.

This section highlights the popularity of various Python frameworks, libraries and technologies that Python developers use.

All respondents

Web developers

Data scientists

Django is the most popular framework used by 41% of Python developers.

Scientific packages such as NumPy/Pandas/Matplotlib, taken together, are in close second with 39%. In terms of roles, Django was selected by 76% of web developers, but only by 31% of those involved primarily in data science. Curiously, 29% of web developers are using scientific libraries. This corroborates a strong overlap between the two roles.

All developers

Web developers

Data scientists

Jupyter Notebook is the most popular technology used together with Python.

This is expected given the large number of developers involved in data science. Docker trails it by only 2%, at 29%. Breaking this down by roles, Docker is used by 47% of those mostly involved in web development, but only by 23% of data scientists. Similarly, cloud platforms such as AWS, Google App Engine, Heroku and others are used twice as often by web developers than by data scientists.

AWS

Google App Engine

Heroku

DigitalOcean

Microsoft Azure

AWS is the most popular cloud platform used by 67% of those who selected Cloud platforms in the previous question. GAE, Heroku, and DigitalOcean fall behind AWS with far smaller shares.

We couldn’t list all the cloud platforms as answer options for this question, but the “Other” field collected 13% of all responses. The top “other” platforms, not included in main results included Linode, PythonAnywhere, OpenShift, and OpenStack.

Half of developers are employed full-time, a little over a quarter are students, while 13% are self-employed or freelancing.

For job roles, we provided for multiple answers, so the total is greater than 100%. About three-quarters of respondents identify as developers, and almost 1 in 5 double as data analysts, architects, or team leads. In “Others”, which collected a total of 9%, the top write-in answers included data scientist, DevOps, researcher, and teacher.

The field we surveyed turned out rather diverse, with no clear leading categories.

There are just as many beginning Python developers as there are veterans.

Interestingly, three out of five developers work on independent projects.

About three-quarters of developers who work in teams work in very small teams.

16% have up to 12 teammates, and only 9% working in mid-size or large teams.

The vast majority seem to be developing multiple different projects at the same time.

Twenty-something was the prevalent age range among our respondents, with a quarter being in their thirties. Lots of young people also seem to be into Python.

• 18% United States
• 13% India
• 7% China
• 6% United Kingdom
• 5% Germany
• 4% Brazil
• 3% France
• 3% Russia
• 2% Poland
• 2% Canada
• 2% Australia
• 2% Spain
• 33% Others

We reached Python users living in 150+ different countries.
“Others” includes countries with fewer than 2%.

Windows

Linux

MacOS

Unfortunately, in this survey we didn’t ask respondents what operating systems they use for development. However, we did track what OS they were using to complete the survey, and we believe there’s a strong correlation between the two.

Around half of all respondents used Windows, while macOS and Linux accounted for 15% and 19%, respectively. That said, devices used to complete the survey may differ from one’s usual development environment.

1

The adoption rate of Python 3 is quickly growing and already at 75%, while Python 2 is used by only 25% of developers.

2

There are as many Python developers doing primarily data science as those focused on web development.

3

For 4 out of 5 developers using Python, it is their main language.

4

Half of all developers using Python as their main language also use JavaScript. Python is also used with HTML/CSS, SQL, Bash/Shell, C/C++ and Java.

5

Django, NumPy, pandas, and Matplotlib are the most popular frameworks and libraries among Python developers. Jupyter Notebook and Docker are the most popular technologies used together with Python. AWS is the most popular cloud platform.

6

PyCharm with its two editions is the most popular tool for Python development, followed by Sublime, Vim, IDLE, Atom, and VS Code.

Disclaimer: The Python Software Foundation doesn’t endorse any of the products, tools, or services mentioned in the survey and this report.

Check out the results of the Python Developer Survey in 2016, 2018, 2019, 2020, 2021, 2022 and 2023.

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