Find pytest-fixture-fixture on GitHub and install via pip or uv

github.com/fferegrino/p...

It works with CV, JSON, JSONL and YAML,
has custom deserialisation, many (many!) out of the box fixtures, and even parameterisation.

Pytest fixtures great but are slightly strange things. They feel a bit too much like magic sometimes.

@feregri.no solution is pytest-fixture-fixture (really!)

Fixtures, for fixtures. Handy fixtures to access your test fixtures from your pytest tests.

Data-driven testing is an approach where test logic stays the same, but the input data and expected outputs come from external sources.

Here’s a Pytest example.

Agents mean we can store data collected in the agent state and use that to feel more comfortable in what they predict vs a single (overconfident) LLM.

But don’t add AI tools if you don’t have to! Deterministic code is simpler and more reliable.

There are many frameworks for creating agents but Geir is a fan of @hf.co smolagents. It’s simple to use and powerful enough for production.

We’re entering the ALL CAPS era of doctstrings—because they end up in system prompts.

Just asking an LLM to predict which team will win doesn’t work that well. It misinterprets data and doesn’t have enough domain knowledge to build trust and consistency.

From small beginnings to great things! @emlynclay.bsky.social tells us the history of PyData London.