Testing PyMC models with pytest. Use when writing unit tests for Bayesian models, setting up test fixtures, mocking MCMC sampling, or testing model structure. Covers pymc.testing.mock_sample, pytest fixtures, and the distinction between fast structure-only tests (mocking) and slow posterior inference tests. Triggers on: testing PyMC, pytest, unit tests for models, mock sampling, test fixtures, CI/CD for Bayesian models.
Quickly install pymc-testing AI skill to your development environment via command line
Source: pymc-labs/python-analytics-skills.
PyMC provides testing utilities to speed up test suites by mocking MCMC sampling with prior predictive sampling. This is useful for checking model structure without running expensive inference.
| Speed | Fast (seconds) | Slow (minutes) | | Use case | Model structure, downstream code | Posterior values, convergence | | Output | prior, priorpredictive | Full posterior, samplestats, warmup groups | | Divergences | Mocked (configurable) | Real diagnostics |
Use mocking when: Testing model specification, CI/CD pipelines, plotting code, API integration, serialization.
Testing PyMC models with pytest. Use when writing unit tests for Bayesian models, setting up test fixtures, mocking MCMC sampling, or testing model structure. Covers pymc.testing.mock_sample, pytest fixtures, and the distinction between fast structure-only tests (mocking) and slow posterior inference tests. Triggers on: testing PyMC, pytest, unit tests for models, mock sampling, test fixtures, CI/CD for Bayesian models. Source: pymc-labs/python-analytics-skills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/pymc-labs/python-analytics-skills --skill pymc-testingTesting PyMC models with pytest. Use when writing unit tests for Bayesian models, setting up test fixtures, mocking MCMC sampling, or testing model structure. Covers pymc.testing.mock_sample, pytest fixtures, and the distinction between fast structure-only tests (mocking) and slow posterior inference tests. Triggers on: testing PyMC, pytest, unit tests for models, mock sampling, test fixtures, CI/CD for Bayesian models. Source: pymc-labs/python-analytics-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/pymc-labs/python-analytics-skills --skill pymc-testing Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/pymc-labs/python-analytics-skills