The Coding Calendar

Tatjana Kleshnina — Thu, 28 Aug 2025 06:53:31 +0000

How seasons of year affect programming productivity in different countries

We've reverse-engineered five years of GitHub activity (2020-2024) to uncover the hidden seasonal trends that dictate how and when programmers ship code.

Find out how the seasons affect your peers worldwide:
– How programmer activity changes with the seasons. 🏖️
– Which regions have the biggest seasonal drops. 📉
– Who codes consistently no matter the time of year. 💻
– Which country completely flips the trend. 🤯

Northern Hemisphere

Devs slow down in Q3 across the region. They hit the brakes in July and August, with activity dropping 8.5% compared to the Q4 hustle.

South Hemisphere

Programmers take a break for summer and major holidays, making their code output 24% lower than in winter.

Subtropical, Tropical and Equatorial

Programmers from these regions start slow and build momentum throughout the year, with their peak activity increasing by 21% at the end of the year.

Exception

And then there's China with an opposite trend. Chinese developers slow down in Q4 by 17%, completely flipping the script on the global trend.

The Seasonal Swing

The top of this list takes Peru. Our data shows a 34.6% difference between their least and most active coding seasons.

The Flatliners

And there are countries where code output is consistent no matter what. Israel takes the top spot in this rating, with just a 4.4% range in its work patterns throughout the year.

Where does your country stand?

Check out the interactive report to find your country, discover a new trend or a surprising outlier.

Explore your country

Notes

The statistics are based on public activity only. Open-source productivity may not be the same as overall productivity.
For our ratings, we analyzed only countries with over 100,000 contributors in the five-year dataset.
On a personal note, this report was a fun project I completed in my first week of learning the Tableau tool. Any feedback is appreciated.

Data source
https://github.com/github/innovationgraph

DEV Community: Tatjana Kleshnina