What Made Python the Top Language in 2017? Key Trends and Milestones

In 2017 Python experienced a series of significant milestones that solidified its position across AI, data science, and general software development.

1. Python’s popularity in machine‑learning hiring (January 2017)

Python ranked highest in deep‑learning job demand, followed by C++, Java, C, and R, indicating a strong focus on high‑performance computing languages; Java showed rapid growth, while Lua’s presence remained low despite powering the Torch framework.

2. Migration to GitHub (February 2017)

Python officially moved its source code from Mercurial to GitHub, adopting Git version control to improve development workflows.

3. AI programming language ranking – Python #1 (March 2017)

At the third Internet Conference, Baidu CEO Li Yanhong emphasized AI as the next growth frontier, and surveys placed Python as the top language for artificial‑intelligence programming.

4. Python named the most popular language (July 2017)

According to IEEE Spectrum, Python overtook C and Java to become the world’s most popular programming language in 2017.

5. Python surpasses R in data science and machine learning (August 2017)

A KDnuggets survey of 954 respondents showed Python usage at 41% versus R at 36%, indicating Python’s ecosystem had overtaken R as the leading platform for data analysis, data science, and ML.

6. Fastest‑growing language in high‑income countries (September 2017)

Stack Overflow traffic analysis revealed Python’s growth rate in high‑income nations outpaces global trends, making it the fastest‑expanding language in those regions.

7. Ubuntu 17.10 drops default Python 2 (October 2017)

First Ubuntu release to drop 32‑bit support for the main edition.

Switches default desktop from Unity to GNOME 3.26.1.

Adopts Wayland as the default display server, with X.Org optional.

Python 2 is no longer installed by default; Python 3 is updated to 3.6.

8. NumPy ends support for Python 2.7 (November 2017)

NumPy announced that after 31 December 2018 all releases will support only Python 3, and from 1 January 2019 new feature versions will be Python 3‑only.

9. Google Research releases Tangent (2020 preview)

Tangent is an open‑source Python library for automatic differentiation that operates as a source‑to‑source system, improving gradient visibility and ease of debugging compared with existing ML libraries.

10. Python enters K‑12 curricula (December 2017)

Python was added to Zhejiang’s information‑technology textbooks, replacing VB, and is slated for inclusion in the national computer‑level exam; similar curriculum updates are planned for Beijing and Shandong, bringing Python to primary‑school students.

11. Microsoft considers Python for Excel scripting (December 2017)

Microsoft is evaluating Python as an official scripting language for Excel, which would allow users to automate Excel tasks with Python similarly to VBA.

12. Django 2.0 released (December 2017)

Django 2.0 drops support for Python 2.7, supports Python 3.4‑3.6, and marks the final release for Python 3.4 compatibility.

The above events illustrate how Python’s ecosystem expanded dramatically in 2017, reinforcing its status as the premier language for AI, data science, and modern software development.