From the experiment

Do coding agents recommend Django translation framework?

Django translation framework was chosen in 20% of 224 judged internationalization sessions, ranking second. Measured with Claude Code, Codex and Cursor.

Published September 11, 2026 Read as Markdown

Django translation framework was chosen in 20% of 224 judged internationalization sessions, ranking second. It was also raised as a candidate in 7 further sessions without being chosen.

This page reports what happened when Claude Code, Codex and Cursor had to solve a problem in internationalization inside a realistic codebase. Not what a chat assistant says about Django translation framework. What an agent actually installed.

The numbers

CategoryInternationalization
Sessions in the category224
Sessions where Django translation framework was chosen45
Install share20%
Rank in category2 of 20
Codebases it won in3
Raised as a candidate, not chosen7
Chosen when considered87%
Sitedocs.djangoproject.com

By agent

The three agents agree closely on Django translation framework, choosing it at rates within 2 points of each other.

AgentSessionsChose Django translation frameworkShare
Claude Code771621%
Codex781519%
Cursor691420%

By who was asking

Django translation framework does much better with one kind of buyer than another. It won 52% of sessions asked as enterprise team and 0% of those asked as senior engineer.

Who is askingSessionsChose Django translation frameworkShare
Vibe coder5400%
Junior developer691725%
Senior engineer4700%
Enterprise team542852%

What Django translation framework was up against

The full ranking in internationalization, from the same sessions:

#ProductRuns wonShare
1next-intl5725%
2Django translation framework (this page)4520%
3Symfony Translation188%
4Paraglide JS188%
5Rails I18n178%
6i18next146%
7Built in-house (no product adopted)125%
8Vue I18n104%

What this means

A solid second or third position in a category means the agent is genuinely choosing rather than reaching automatically. That is a winnable position, because the inputs it uses can be changed.

The fastest gains are usually in the sessions that were nearly won: read them, find the step where the agent moved on, and fix that step.

Where these numbers come from

The 224 sessions in internationalization are part of a published set of 6,458, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.

Every internationalization run can be replayed on the board.

If you work on Django translation framework: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts.

<!-- generated by scripts/write-data-pages.mjs -->

Common questions

Do coding agents recommend Django translation framework?

Yes. Django translation framework was chosen in 45 of the 224 judged sessions in internationalization, a 20% install share, ranking second in its category.

Does Claude Code recommend Django translation framework?

In 16 of the 77 sessions in internationalization run with Claude Code, which is 21%.

Do different coding agents treat Django translation framework differently?

Not much. The three agents chose it at similar rates, between 19% and 21% of their runs.

How was this measured?

Real coding agents at pinned versions were run in sandboxes inside 63 realistic codebases and asked to solve real tasks. A simulated project owner approved or questioned each recommendation before any code was written, and a judge from a model family that builds none of the agents read every session blind.

How often is Django translation framework considered but not chosen?

It was raised as a candidate in 7 sessions without being chosen, and chosen in 45. That is a 87% conversion from considered to chosen.

Where this comes from

Armature ran 6,458 judged sessions with Claude Code, Codex and Cursor inside 63 realistic codebases, and published every run. The numbers on this page come from that work.

Read next

All library pages