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NumPy drops Python 2 support. Now you need Python 3.5 or later.

2 min read

In a GitHub pull request last week, the NumPy community decided to remove support for Python 2.7. Python 3.4 support will also be dropped with this pull request. So now, to use NumPy 1.17 and newer versions, you will need Python 3.5 or later. NumPy has been supporting both Python versions since 2010.

This move doesn’t come as a surprise with the Python core team itself dropping support for Python 2 in 2020. The NumPy team had mentioned that this move comes in “Python 2 is an increasing burden on our limited resources”.

The discussion to drop Python 2 support in NumPy started almost a year ago. Running pip install numpy on Python 2 will still install the last working version. But here on now, it may not contain the latest features as released for Python 3.5 or higher. However, NumPy on Python 2 will still be supported until December 31, 2019. After January 1, 2020, it may not contain the newest bug fixes.

The Twitter audience sees this as a welcome move:

A comment on Hacker News reads: “Let’s hope this move helps with the transitioning to Python 3. I’m not a Python programmer myself, but I’m tired of things getting hairy on Linux dependencies written in Python. It almost seems like I always got to have a Python 2 and a Python 3 version of some packages so my system doesn’t break.”

Another one reads: “I’ve said it before, I’ll say it again. I don’t care for everything-is-unicode-by-default. You can take my Python 2 when you pry it from my cold dead hands.” Some researchers who use NumPy and SciPy stick Python 2, this move from the NumPy team will help in getting everyone to work on a single version.

One single supported version will sure help with the fragmentation. Often, Python developers find themselves in a situation where they have one version installed and a specific module is available/works properly in another version. Some also argue about stability, that Python 2 has greater stability and x or y feature. But the general sentiment is more supportive of adopting Python 3.

Read next

Introducing numpywren, system for linear algebra built on a serverless architecture

NumPy 1.15.0 release is out!

Implementing matrix operations using SciPy and NumPy

 

Prasad Ramesh

Data science enthusiast. Cycling, music, food, movies. Likes FPS and strategy games.

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