The State of Developer Ecosystem in 2018 (opens in new tab)

I'd love to see signs of Julia growing in that space

What's making you leave the Ruby ecosystem?

I wouldn't call it sudden at all. Python is great for the reason Java is great: diverse robust ecosystem for a ton of different fields. It's about ubiquity.

It's installed on virtually everything already. It's one of the easiest languages to learn (the basics), and is used as a teaching language. Even outside of CS everyone knows it.

Used in web programming (Django, Flask, etc.), numerical computing (Jupyter, numpy, scipy, pandas), AI/ML (TensorFlow, scikit-learn), bioinformatics, easy bindings to EVERYTHING (openCV, bullet physics, kafka, zookeeper, protobuf, json, xml).

It's usually concise enough, mostly straightforward to read, reasonably structured (though big codebases can become a pain). In most companies you see python used in tooling ALL THE TIME. It's fantastic for ducktape programming; often 'promoting' a largeish bash script to python. It ate perl's place there before.

I've even seen ipython work well as a login shell. Jeezz.

Sure the 2.7 -> 3 thing was a ton of drama, the package manager situation changes ever few years, but hey: a lesser language and ecosystem would have fallen apart under it.

Disclaimer: I'm a Java+Python fan boy in all their incarnations.

> why is it suddenly gaining tracking in 2017-18

For data science and machine learning, it makes sense because the most popular packages are all in Python at this moment (strictly speaking, they have interfaces in Python but the underlying native code is in C++).

For academics who do data analysis and scientific computing, the last few years have seen an explosion of scientific packages available in Python. The major packages, NumPy/SciPy/matplotlib/pandas, also become more feature-complete to the point that one can do everything that is used to be done in MATLAB now in this set of packages. That's free MATLAB with better performance and more potential for optimization. No wonder people are switching to the Python ecosystem.

FWIW: For the first ten years of my career, I primarily developed using Java. By about 2008 or so I was tired of looking at SomeAbstractFactoryVistorSingleton messes. I got into a project where I had green-field opportunity to try something different and Python just felt like a breath of fresh air. A few years went by and I gave node.js a try, thinking that Javascript would inevitably win out on the server side as well. Didn't take long to go back to Python - its stable, mature, performant, and syntactically simple. It does what I need it to for now.

Python mostly replaced Ruby(Rails) as the first choice for beginners learning backend for the web.

And Python is becoming the first choice for the Machine Learning and even Data Science.

As you can see from the Python usage chart most use it for Data Analysis

Data analysis 52% Web development 45%

And most popular libraries :

NumPy / matplotlib / SciPy / Pandas and similar 47% Django 45%

I agree with the other commenters about data science and web dev. And as a result, it’s extremely well situated to be the language non-coders reach to when trying to learn to code. I work at a trading firm that has pretty much fully invested in python as a tool to bring preciously non-technical users closer to engineering.

I don't know for sure, but some possible reasons include: 1. I've read that a lot of universities have adopted it as the first language to teach CS students (the local high school also uses it to teach programming to students), 2. When I read questions about what to move to from PHP for a web backend there are lots of recommendations to use Python, 3. It seems like a lot of people use it for data analysis tasks, 4. Python is often used with hardware like Arduino, 5. It is often used for scripting tasks.

Merely anecdotal but: many people interested in machine learning start with Python; many people wanting to do "serverless" things choose Python; many younger devs find Python a nice place to run away to from Java; and all this together means it's pretty easy to find devs who either know Python or are quite happy to learn it; and that in turn makes it a "safe" language choice when you aren't otherwise committed to the features of any particular language. (And running in Lambda can be a pretty big deal.)

It's a virtuous/vicious circle, depending on what you think of Python. But I think "Python is for ML" is the unofficial motivation behind a lot of it, because if you're starting to build your career and Python is an option then for sure you're going to mess around with scikit-learn and put that on your CV.

[edit]: Oh and boto3 probably accounts for a fair amount of Python use these days. I actually prefer the AWS support in golang but boto3 usually "just works" despite some very weird quirks.

I believe it's due to consistently good performance over the years:

* The outstanding documentation site.

* Execution speed for an interpreted language.

* Highly transparent language evolution, managed by the nonprofit Python Foundation.

* Semantic versioning.

* Core developer communication is in English.

* Excellent module definition and import system.

* Culture of explicitness, not implicitness.

The ecosystem has a few huge weaknesses (e.g. packaging and dependency management) which put me off for the most part. But the strengths seem to be overwhelming enough to put Python on a success trajectory.

Look at the SentDex Python Programming Youtube channel.

The amount of crazy stuff he teaches with python is amazing. No other language can promise that calibre of idea expressing power coupled with ease of development.

Deep/Machine Learning

Nothing changed. It had traction for more than a decade.

Machine learning/data science, definitely.

I'm personally not a big fan of Python at all (actually I hate it), but one can't deny its overwhelming dominance in those spaces.

I feel that it's only just starting to grow, and will continue to get bigger.

AI, ML & data science. Pity Ruby never got off it's ass to compete otherwise the impending Ruby speed boosts might have actually made a difference.

More universities adopting it might be one of many reasons.

I take it that you don't use node? I write all my scripts in node instead of bash.

Was also expecting a higher number ;).