Python usage survey 2014

Written by: Randy Olson

Primary Source: Randal S. Olson

Remember that Python usage survey that went around the interwebs late last year? Well, the results are finally out and I’ve visualized them below for your perusal. This survey has been running for two years now (2013-2014), so where we have data for both years, I’ve charted the results so we can see the changes in Python usage over time.

I’ll note that a big focus of this survey is to find out if Python users are transitioning over to Python 3, and if they aren’t, then why they aren’t making that transition. If you’re on the fence about switching from Python 2 to 3, there are some great articles out there about the key differences between the two versions and the many, many, …many advantages that Python 3 offers over Python 2.

If you want to check out the underlying data yourself, head on over to Bruno Cauet’s page.

The first big question that we all we know is: How many Python users have actually used Python 2 and 3?


As expected, nearly every Python user has used Python 2 at some point in their career. We also see good news for Python 3 over the past year: Python 3 usage increased 12 percentage points in 2014, up to nearly 3/4 of the surveyed Python users.

Of course, “writing code with Python 3 once” doesn’t mean that they actually use it regularly. The question below gets at that question more directly.


Here we see yet more good news for Python 3: As much as 10% more Python users are primarily using Python 3 than in 2013, now accounting for 1/3 of all Python users. It seems the transition to Python 3 will be slow but steady for the next few years.

The transition we see above may be caused by project managers at work. What version do Python users go to when working on their personal projects?


Here we see a more close divide between the two versions: Nearly half of all users will start up their own projects with Python 3, whereas the other half still ardently remains pro-Python 2.

Let’s break these usage patterns down by the specific version now.


Somehow, Python v. 2.5 and 2.6 are still in use in some places, but 2.7 still dominates the Python 2 landscape. We also see telltale signs that Python 3 is becoming a mature language in its own right, with users stuck in the older 3.2 and 3.3 versions.

To summarize so far: Over 2/3 of all Python users are still using Python 2, with the majority of them sitting at 2.7. This tells us that Python is still very much a divided language, with a large portion of the user base unwilling to upgrade to the latest version despite the fact that Python 2 nearly 5 years old now. (That’s ancient in programming language years!)

A common complaint of the ardent Python 2 users is that Python 3 was a huge mistake. How does that turn out in this survey?


Surprisingly, it seems the complainers are a minority: Only 12% of the Python users surveyed think Python 3 was a mistake. 1/3 of Python users think Python 3 is great (probably the ones who made the switch!), whereas over half of Python users think the Python developers could’ve made the Python 2 -> 3 transition more fluid.

So, most Python users don’t think Python 3 was a mistake, but 2 in 3 of them still haven’t made the switch. That leaves us to wonder: Why haven’t the Python 2 users made the switch yet?


Package dependencies are — by far — the most-cited reasons for refusing to switch to Python 3. Many of us rely on specific packages — such as numpy, scipy, pandas, etc. — for our day-to-day work. If the packages haven’t been upgraded to Python 3 yet, then why should we? Lucky for us, there’s a web site dedicated to tracking the packages that are Python 3 ready. Are all of your packages on there? Then maybe it’s time to make the switch.

Another common reason for refusing to switch to Python 3 is that there’s no incentive. We’re comfortable with Python 2, we know its ins and outs, and everything works fine. Why bother upgrading? If you fall in this category, I’ll point you to this article again that compares the key differences between Python 2 and 3. And don’t forget about the 2 pounds of reasons why Python 3 is a huge upgrade over Python 2.

The last two major reasons for refusing to switch to Python 3 are a little harder to address. If you have a large legacy code base or your manager simply refuses to make the upgrade, then it’s up to you to convince management (or yourself) that the upgrade is worth the work. The links I included in the above paragraph are a good start.

Finally, the survey wanted to look at cross-compatibility between Python 2 and 3.


Here we start to see more good news for the future of Python 3: We saw a significant increase in the number of users who have ported their code from Python 2 to 3.

It’s not very well-known that there Python has packages for converting code from Python 2 to 3 and Python 3 to 2. When the survey asked users whether they’d used either of these packages even once, well, see for yourself…


It seems like the Python devs need to do a better job of raising awareness of these code conversion packages.

Because Python 2 and 3 really aren’t that different, it’s not necessary to write code for just one version. As the famous taco shell commercial goes: “Por que no los dos?” (Why not both?)

To that end, the survey also polled users on whether they write Python 2- and 3- compatible code.


Apparently only 1 in 3 Python developers bother to write multi-version compatible code, and there hasn’t been much of a change since 2013.

I look forward to seeing how the Python 3 transition progresses in 2014. If you have any more resources for helping (and convincing!) Python developers to make the transition, please share them in the comments below.

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Randy Olson is a Computer Science graduate research assistant at Michigan State University in Dr. Chris Adami’s lab specializing in artificial intelligence, artificial life, and evolutionary computation. He runs a research blog where he writes about Python, scientific computing, evolution, and AI. Randy is an ardent advocate of open science and regularly travels the U.S. to teach researchers scientific computing skills at Software Carpentry workshops.