Digging deeper into rich countries (defined by the World Bank as high-income countries) tend to have access to different technologies than the rest of the world. The biggest difference we see is in the programming language of Python. When we focus on high-income countries, Python's growth outpaces even tools like Stack Overflow Trends, or other rankings that take into account global software development.
In this post, we'll explore the extraordinary growth of the Python programming language over the past five years, as shown by Stack Overflow traffic in high-income countries. The term "fastest growing" may be difficult to define, but we believe that Python can be the fastest growing major programming language. Here I would like to recommend my own Python learning group: 483546416, if you are learning python, the editor welcomes you to join, everyone is a Python party, sharing dry goods from time to time (only Python related ), including a 2017 latest Python material and a zero-based introductory tutorial compiled by myself, welcome to beginners and advanced partners.
All numbers discussed in this post are for high-income countries ; they generally represent trends in the US, UK, Germany, Canada, and other such countries, which combined account for 64% of Stack Overflow traffic. Many other countries, such as India, Brazil, Russia, and China, also contribute significantly to the global software development ecosystem, and this post doesn't describe many of these economies, although as we'll see, Python is also growing.
It's worth emphasizing that the number of users of a language is not a measure of language quality: we're describing the language developers use, not prescribing it. (Full disclosure: I used to program mostly in Python, although I've switched to R completely).
The growth of Python in high-income countries
As you can see in Stack Overflow Trends, Python has been growing rapidly over the past few years. But for this post, we'll focus on high-income countries and consider access issues, rather than asking questions (which tend to give similar results, but with less month-to-month noise, especially for smaller labels) .
We have data on Stack Overflow question views going back to the end of 2011, during which time we can consider the growth of Python relative to the other five major programming languages. (Note, therefore a shorter time frame than the Trends tool, going back to 2008). These are currently six of the top 10 most visited Stack Overflow tags in high-income countries; the four we didn't include are CSS, HTML, Android, and JQuery.
June 2017 was the first month that Python was the most visited month on Stack Overflow in high-income countries. This includes the most visited tags outside the US and UK, and the top two in almost every other high-income country (except Java or JavaScript). This is particularly impressive as it had fewer visits than the other 5 languages in 2012, when it grew 2.5 times.
Part of the reason is because of the seasonality of Java's traffic. Since the teaching of undergraduate courses is important, Java traffic rises in both the fall and fall in the summer. Will it catch up to Python again by the end of the year? We can try to forecast growth over the next two years using the "STL" model, which combines growth with seasonal trends to predict future values.
According to this pattern, Python may stay in the lead or be covered by Java in the fall (it's roughly within the variance predicted by the model), but in 2018, becoming the most popular tag is clearly in the works. STL also suggested that JavaScript and Java traffic between high-income countries will remain at similar levels as they have been for the past two years.
What tags are growing the fastest overall?
The above has only looked at six of the most popular programming languages. What other notable technologies are currently growing fastest in high-income countries?
We define the growth rate as a proportion of the traffic volume from 2017 to 2016. In this analysis, we decided to consider only programming languages (such as Java and Python) and platforms (such as iOS, Android, Windows, and Linux), rather than frameworks like Angular or TensorFlow (although many of these show significant Growth will be reviewed in future posts).
Because of the challenges of defining "fastest growth" described in this comic, we compare growth to the mean difference population average.
With an annual growth rate of 27%, Python is uniquely large and growing rapidly ; the second largest tag showing similar growth is R. We see that traffic for most other large tags remains stable in high-income countries, accessing Android , iOS and PHP declined slightly. We previously found some shrinking tags like Objective-C, Perl and Ruby on Flash. We can also note that among functional programming languages, Scala is the largest and growing, while F# and Clojure are smaller and shrinking, with Haskell remaining stable.
There's an important omission in the graph above: last year, typescript issue traffic grew by a staggering 142%, enough to keep us away from overwhelming the rest of the scale. You can also see that some other smaller languages are growing at a similar rate or faster than Python (such as R, Go, and Rust), and there are many tags, such as Swift and Scala, which are also showing impressive growth. How does their traffic compare to time compared to Python?
The growth of languages like R and Swift has been impressive indeed, and TypeScript has shown particularly rapid expansion in less time. Many of these smaller languages have grown from barely-there traffic to becoming a significant presence in the software ecosystem. But as shown, it's easier to show rapid growth when the labels start relatively small.
Note that we are not saying these languages compete with "Python". Instead, we're explaining why we're treating their growth in another category; these are lower-traffic labels. Python is an unusual example, being both one of the most popular tags on Stack Overflow and one of the fastest growing. (By the way, it's also accelerating! It's been growing faster every year since 2013).
Rest of the world
So far in this article, we have been analyzing trends in high-income countries. How is Python growing in the rest of the world in countries like India, Brazil, Russia and China?
It does.
Python is still the fastest-growing major programming language outside of high-income countries; it only started at a lower level and started growing two years later (2014 instead of 2012). In fact, year-over-year growth in Python in non-high-income countries was slightly higher than in high-income countries. We're not going to look at it here, but another language, R, whose use is positively correlated with GDP, is also growing.
Many of the conclusions in this article on label growth and decline in high-income countries (as opposed to absolute rankings) apply to the rest of the world; there is a 0.979 Spearman correlation between the growth rates of the two sectors. In some cases, you can see a "lag" phenomenon similar to what happens with Python, where a technology is widely adopted in high-income countries, and it takes a year or two to scale up in the rest of the world. (This is an interesting phenomenon and may be the subject of a future blog!)
next time
We do not intend to contribute to any "language wars". The number of users of a language doesn't mean its quality, and it certainly doesn't tell you which language is better for a particular situation. However, with this perspective in mind, we think it's worth understanding what languages make up the developer ecosystem, and how the ecosystem is changing.
This article shows that Python has shown phenomenal growth over the past five years, especially in high-income countries. In our next article, we'll start exploring "why." We'll break down the growth by country and industry, and look at which other technologies tend to be used with Python (e.g., estimate how much of the growth is due to the increased use of Python for web development rather than data science).