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With the second quarter looming, it’s time for us to drop our first quarter bi-annual Programming Language rankings. As always, these are a continuation of the work originally performed by Drew Conway and John Myles White late in 2010. While the specific means of collection has changed, the basic process remains the same: we extract language rankings from GitHub and Stack Overflow, and combine them for a ranking that attempts to reflect both code (GitHub) and discussion (Stack Overflow) traction. The idea is not to offer a statistically valid representation of current usage, but rather to correlate language discussion and usage in an effort to extract insights into potential future adoption trends.
The data source used for the GitHub portion of the analysis is the GitHub Archive. We query languages by pull request in a manner similar to the one GitHub used to assemble the 2016 State of the Octoverse. Our query is designed to be as comparable as possible to the previous process.
- Language is based on the base repository language. While this continues to have the caveats outlined below, it does have the benefit of cohesion with our previous methodology.
- We exclude forked repos.
- We use the aggregated history to determine ranking (though based on the table structure changes this can no longer be accomplished via a single query.)
For Stack Overflow, we simply collect the required metrics using their useful data explorer tool.
With that description out of the way, please keep in mind the other usual caveats.
- To be included in this analysis, a language must be observable within both GitHub and Stack Overflow.
- No claims are made here that these rankings are representative of general usage more broadly. They are nothing more or less than an examination of the correlation between two populations we believe to be predictive of future use, hence their value.
- There are many potential communities that could be surveyed for this analysis. GitHub and Stack Overflow are used here first because of their size and second because of their public exposure of the data necessary for the analysis. We encourage, however, interested parties to perform their own analyses using other sources.
- All numerical rankings should be taken with a grain of salt. We rank by numbers here strictly for the sake of interest. In general, the numerical ranking is substantially less relevant than the language’s tier or grouping. In many cases, one spot on the list is not distinguishable from the next. The separation between language tiers on the plot, however, is generally representative of substantial differences in relative popularity.
- In addition, the further down the rankings one goes, the less data available to rank languages by. Beyond the top tiers of languages, depending on the snapshot, the amount of data to assess is minute, and the actual placement of languages becomes less reliable the further down the list one proceeds.
- Languages that have communities based outside of Stack Overflow such as Mathematica will be under-represented on that axis. It is not possible to scale a process that measures one hundred different community sites, both because many do not have public metrics available and because measuring different community sites against one another is not statistically valid.
With that, here is the first quarter plot for 2019.
Besides the above plot, which can be difficult to parse even at full size, we offer the following numerical rankings. As will be observed, this run produced several ties which are reflected below (they are listed out here alphabetically rather than consolidated as ties because the latter approach led to misunderstandings).