Driving Python’s growth is increased use by data science professionals as well as hobbyists, GitHub reasons.
The rankings were based on the number of unique contributors to public and private repos tagged with the appropriate primary language.
Overall, developers collaborated in more than 370 languages on GitHub in the last year, according to the GitHub report.
The State of the Octoverse report is based on data from October 1, 2018, to September 30, 2019. GitHub also noted that there were more 40 million developers building on GitHub, with 80 per cent coming from outside the United States, while ten million persons have joined in the last year and 1.3 million made their first contribution to open source.
More than 44 million repos were created in the past year with dependencies key in GitHub repos. On average, each public and private repo relies on more than 200 packages.
Delving deeper, more than seven million vulnerability alerts have been remediated by the community since GitHub launched its security alerts capability in November.
Usage of Jupyter notebooks has grown by more than 100 per cent year to year for the past three years. The figures are based on the number of repos that cite Jupyter as their primary language.
In addition contributors to the Python-friendly TensorFlow machine learning library have grown from 2,238 to 25,166 people (when including contributors to dependencies in the total), while natural language processing is picking up steam on GitHub, with packages like NLTK lowering the barrier to entry.
GitHub’s language rankings differ from the Tiobe index of language popularity, which assesses language popularity based on a formula that counts searches in popular search engines. Tiobe’s index this month ranks Java first, closely followed by C, then Python.