Code · ukaea · UK Public Sector GitHub Observatory

Language figures come from GitHub's own per-repository byte counts, which measure source rather than a single headline label. File counts and repository sizes come from the mirrors themselves. The two tell different stories, and the difference is the point.

The codebase

languages in use

129.5 MB of source

22.6k

files at HEAD

across every analysed repository

0 B

on disk as mirrors

full history, every branch and tag

443.1 MB

largest repository

fair-mast

What stands out

One archived repository holds 26% of all the bytes.

fair-mast is 443.1 MB of git - a 2013 static snapshot of www.gov.uk, not source code. It single-handedly makes HTML the largest language by volume (1% of all source bytes). Any size or language statistic that does not exclude it is measuring an archive, not a codebase.

Sizes here are GitHub's reported figures.

This organisation was harvested with blobless partial clones, which fetch every commit and file path but not file contents, so there is no local size to measure against. Checked elsewhere in this dataset against 1,526 fully mirrored repositories, GitHub's reported size is accurate to within about six percent.

Ruby is the house language, but its share is falling.

Ruby is the primary language of 0% of archived repositories but only 0% of live ones. Python, Go, TypeScript and HCL have taken the difference - the signature of a shift from monolithic Rails publishing apps toward data pipelines, infrastructure-as-code and platform tooling.

Most repositories are small; a handful are enormous.

46% of repositories are under a megabyte of git data. The estate is not a monolith - it is a very long tail of small services, gems and prototypes around a few large publishing applications.

Languages, two ways

By volume of source

Bytes of code. Dominated by archived static HTML.

By number of repositories

How many repositories name each language as their primary one. A better guide to what engineers actually work in.

Live estate versus archive

The same language ranking, split by whether the repository is still active. The shift is the clearest signal of technical direction in the whole dataset.

Active repositories

Archived repositories

Scale

Repository size distribution

Git data per repository, log-ish buckets.

Commits against files

Each circle is a repository, sized by number of distinct authors. Both axes are logarithmic. The diagonal band is the normal relationship between codebase size and churn; outliers above it are long-lived apps with heavy iteration, below it are dumps and imports.

The shape of a repository

Directory layout is the cheapest reliable signal of what a repository actually is. app/ with config/ and spec/ is a Rails application; src/ with test/ is Java or Node. Counted by how many repositories contain each top-level directory at HEAD.

Most common top-level directories

Most common file extensions

By total file count across the estate.

The twenty largest repositories

Repository	Language	Git size	Commits	Files	Status
fair-mast	Python	443.1 MB	1,273	64	active
toktagger	Python	313.2 MB	3,028	293	active
epics	C	217.3 MB	1,382	9,502	active
tglfnn-ukaea	Python	168.0 MB	110	309	active
PROCESS	Python	104.9 MB	8,281	552	active
ReMKiT1D-Python	Python	64.8 MB	615	114	active
MARTe2	C++	55.7 MB	4,277	2,005	active
fuel	Python	37.7 MB	83	12	active
openmc_workshop	Jupyter Notebook	35.3 MB	1,133	1	active
ReMKiT1D	Fortran	30.8 MB	205	416	active
neutronics_material_maker	Python	30.5 MB	760	1	active
CLOCK	Fortran	27.3 MB	62	100	active
SLMRME	Python	16.0 MB	20	12	active
UDA	C++	15.5 MB	2,143	659	active
piezo	Python	14.2 MB	1,051	221	archived
Glovebox-Simulator	C++	14.1 MB	43	1,135	active
imas_mapping_workshop	CSS	13.8 MB	58	1,540	active
ditto	Python	11.1 MB	705	170	archived
MARTe2-components	C++	11.0 MB	1,805	1,141	active
fair-mast-ingestion	Jupyter Notebook	10.6 MB	722	85	active