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Type-hint coverage: ~89% overall, remaining gaps in ImageCore, Sources, blocks, bin #60
Tracks type-hint coverage of src/machinevisiontoolbox. Last refreshed 2026-10-17.
An AST audit counts annotated parameters (excluding self/cls) and return types over every function and method under src/machinevisiontoolbox, including subpackages (bin/, blocks/).
2026-10-17
Parameter annotations
86.1% (1620 / 1881)
Return annotations
92.7% (1082 / 1167)
Average
89.4%
Correction to the original report. The 2026-08-10 figures (54.3% params, 74.9% average) were wrong: the audit script counted self/cls, which are never annotated. Recomputed without them on 2026-10-03 the figure was already about 86.8% params / 95.6% returns. So the overall picture is that coverage was always mostly good, and the real gaps are a few specific modules, not a broad shortfall. Per-module parameter coverage now:
Return annotations: a handful of functions across ImageConstants.py, ImageProcessing.py, ImageMultiview.py, Sources.py
Modules now at or near 100%: ImageSpatial, ImageMorph, ImageTensor, ImageRegionFeatures, VisualServo, BundleAdjust, PointCloud, Kernel, ImageFiducials.
Guidelines for contributions
Use modern syntax: X | Y, X | None, list[X]; not Union, Optional, List.
Arrays: use ArrayLike from machinevisiontoolbox.mvtb_types for arguments. (There is no NDArray alias there yet.)
Type hints replace :type:/:rtype: in docstrings; keep those only where array shape adds information.
Annotation-only changes please: no behaviour changes in the same PR.
changed the title [-]Type-hint coverage audit: ~75% overall, parameter annotations lagging in several modules[/-][+]Type-hint coverage: ~89% overall, remaining gaps in ImageCore, Sources, blocks, bin[/+]on Oct 17, 2026
Activity
[-]Type-hint coverage audit: ~75% overall, parameter annotations lagging in several modules[/-][+]Type-hint coverage: ~89% overall, remaining gaps in ImageCore, Sources, blocks, bin[/+]