v2026.5.1.4

PyAutoFit v2026.5.1.4

Highlights

Python 3.9–3.13 supported, 3.12 / 3.13 recommended

This release expands supported Python versions to 3.9 through 3.13 (#1244). 3.12 and 3.13 are first-class recommended; 3.9, 3.10, 3.11 are supported but emit a loud (bypassable) banner on import. Silence the banner via version.python_version_check: False in your workspace's config/general.yaml. Python 3.14 is not yet supported (parked on a known FactorGraphModel iteration bug).

Key impacts for users:

• requires-python = ">=3.9" in pyproject.toml (lower floor than before)
• Classifiers now cover 3.9, 3.10, 3.11, 3.12, 3.13
• JAX is now an optional extra: pip install autofit[jax], gated on python_version >= '3.11'. Plain pip install autofit no longer pulls JAX as a transitive dep.
• Analysis(use_jax=True) falls back to numpy with a UserWarning when JAX isn't installed, instead of failing at import time.

JAX-jitted likelihoods in Dynesty (use_jax_jit)

Dynesty searches now support JAX-jitted likelihood evaluation via the new use_jax_jit option (#1243). For likelihood-bound runs, this can deliver substantial speedups by JIT-compiling the likelihood once instead of evaluating it interpretively per sample.

Bug Fixes

• compute_latent_samples now skips samples that raised a FitException instead of crashing the whole computation (#1233)

Internal / Cleanup

• Remove unused pyprojroot dependency (#1242) — pip install autofit no longer pulls pyprojroot
• Delete jax-using unit tests; cross-xp checks live in autofit_workspace_test (#1247) — keeps the library's unit suite numpy-only

Upstream Changes

PyAutoConf

• Support Python 3.9–3.13, first-class 3.12/3.13 (PyAutoConf#102)
• Soften Python version check with general.yaml bypass (PyAutoConf#96)

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Full changelog: 2026.4.13.6...2026.5.1.4

v2026.4.13.6

PyAutoFit v2026.4.13.6

What's New

Bug Fixes

• fix: pin autoconf dependency version and update homepage URL (#1206)

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Full changelog: 2026.4.13.5...2026.4.13.6

v2026.4.13.5

PyAutoFit v2026.4.13.5

What's New

Bug Fixes

• fix: pin autoconf dependency version and update homepage URL (#1206)

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Full changelog: 2026.4.13.3...2026.4.13.5

v2026.4.13.3

PyAutoFit v2026.4.13.3

What's New

Breaking Changes

• fix: guard interpolator and grid search against edge cases (#1201)

New Features

• docs: update Python version to 3.12-3.13 (#1199)

Bug Fixes

• fix: bump scipy cap to <=1.15.2 (#1196)

Internal

• refactor: replace search YAML config with explicit Python defaults (#1202)
• build: add Python 3.13 support (#1198)
• build: raise scipy cap, relax threadpoolctl and SQLAlchemy pins (#1197)
• refactor: separate PYAUTOFIT_TEST_MODE into distinct PYAUTO_* env vars (#1195)

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Full changelog: 2026.4.5.3...2026.4.13.3

v2026.4.5.3

PyAutoFit v2026.4.5.3

What's New

New Features

• Flatten plot API: replace Plotter classes with module-level functions (#1174)

Bug Fixes

• fixes to figure of merit (#1166)

Internal

• Drop Python 3.9-3.11, add 3.13 (#1177)
• Make search logging JAX-aware (#1176)
• Add expanded model mapping unit tests (#1172)
• feature/jax_cpu_jit (#1170)
• feature/jax_cpu_batch_size_1 (#1169)
• feature/samples_summary_failsafe (#1168)

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Full changelog: 2025.5.10.1...2026.4.5.3

May 2025

• Remove Analysis summing API, replacing all dataset combinations with AnalysisFactor and FactorGraphModel API used for graphical modeling:

https://github.com/Jammy2211/autofit_workspace/blob/main/notebooks/cookbooks/multiple_datasets.ipynb

• Results workflow API, which generates .csv, .png and .fits files of large libraries of results for quick and efficient inspection:

https://github.com/Jammy2211/autolens_workspace/tree/main/notebooks/results/workflow

• Latent variable API bug fixes and now used in some test example scripts.

January 2025

This update is mostly bug fixes and small improvements, with no major new functionality added.

What's Changed

• Feature/enviroment warning by @Jammy2211 in #1077
• cache hdus to avoid object deletion causing files to be closed by @rhayes777 in #1081
• feature/constant comparison by @rhayes777 in #1080
• Remove database test path by @Jammy2211 in #1083
• analysis_summed_latent by @Jammy2211 in #1084
• monkey patch abstract_search.gc during testing to prevent expensive calls to gc.collect() by @rhayes777 in #1088
• feature/aggregate summary by @rhayes777 in #1089

Full Changelog: 2024.11.13.2...2025.1.18.7

November 2024 update

Garbage collection and other things to improve memory use.

November 2024

Minor release with stability updates and one main feature.

• Sensitivity Mapping improvements.

• Start point for MCMC.

September 2024

This release updates all projects to support Python 3.12, with support tested for Python 3.9 - 3.12 and 3.11 regarded as most stable.

This includes many project dependency updates:

https://github.com/rhayes777/PyAutoFit/blob/main/requirements.txt
https://github.com/rhayes777/PyAutoFit/blob/main/optional_requirements.txt

PyAutoFit:

https://github.com/rhayes777/PyAutoFit/pulls?q=is%3Apr+is%3Aclosed

• Improvements to HowToFit lectures: #1022
• Support for NumPy arrays in model composition and prior creation, for example creating an ndarray of input shape where each value is a free parameter in the seach: #1021
• Name of optimize searches renamed to mle, for maximum likelihood estimator, with improvements to visualization: #1029
• Improvement to sensitivity mapping functionality and results: https://github.com/rhayes777/PyAutoFit/pulls?q=is%3Apr+is%3Aclosed
• More improvements to JAX Pytree interface, documentation still to come.