Kinemotion Development Standards

Pre-Commit Checklist

Always run before committing:

uv run ruff check --fix   # Auto-fix linting
uv run ruff format        # Format code
uv run pyright            # Type check (strict)
uv run pytest             # Run all tests

Or combined:

uv run ruff check --fix && uv run ruff format && uv run pyright && uv run pytest

Quality Targets

Metric	Target	Current
Test coverage	≥ 50%	80.86%
Code duplication	< 3%	2.96%
Type errors	0	0
Lint errors	0	0

Check duplication:

npx jscpd src/kinemotion

Type Hints

• Use

  NDArray[np.float64]

  for numpy arrays
• Use

  TypedDict

  for metric dictionaries
• Use

  Literal

  for string unions
• Pyright strict mode enforced

from numpy.typing import NDArray
from typing import TypedDict, Literal

QualityPreset = Literal["fast", "balanced", "accurate"]

class CMJMetrics(TypedDict):
    jump_height_cm: float
    flight_time_ms: float

Module Structure

src/kinemotion/
├── cli.py                  # Main CLI entry point
├── api.py                  # Public Python API
├── core/                   # Shared utilities
│   ├── validation.py       # Base validation classes
│   ├── pose.py             # MediaPipe wrapper
│   ├── filtering.py        # Signal processing
│   └── video_io.py         # Video I/O handling
├── cmj/                    # CMJ analysis module
│   ├── cli.py              # CMJ CLI subcommand
│   ├── analysis.py         # Core CMJ algorithm
│   ├── kinematics.py       # Velocity, position calc
│   └── validation_bounds.py # CMJ-specific bounds
└── dropjump/               # Drop jump module
    ├── cli.py              # Drop jump CLI subcommand
    ├── analysis.py         # Core drop jump algorithm
    └── validation_bounds.py # Drop jump bounds

Testing

Structure

Mirror source:

tests/core/

,

tests/cmj/

,

tests/dropjump/

,

tests/cli/

Fixtures

Use centralized fixtures from

tests/conftest.py

:

• cli_runner

  : Click test runner

• minimal_video

  : Synthetic test video

• sample_video_path

  : Path to test fixture

Edge Cases to Test

• Empty arrays
• Single frame videos
• NaN values in landmarks
• Missing landmarks (occlusion)
• Zero velocity scenarios

@pytest.mark.parametrize("input_data,expected", [
    (np.array([]), None),  # Empty
    (np.array([1.0]), 1.0),  # Single value
    (np.array([np.nan, 1.0, 2.0]), None),  # NaN handling
])
def test_edge_cases(input_data, expected):
    ...

Key Algorithm Differences

Aspect	CMJ	Drop Jump
Search direction	Backward (from peak)	Forward
Velocity type	Signed (direction matters)	Absolute (magnitude)
Key phase	Countermovement detection	Ground contact
Starting position	Floor level	Elevated (box)

Common Gotchas

1. CMJ velocity must be signed - backward search requires knowing direction
2. Convert NumPy for JSON - use

   int()

   ,

   float()

   before serialization
3. Handle video rotation - mobile videos have rotation metadata
4. Read first frame for dimensions - don't trust OpenCV properties

Commit Format

Use Conventional Commits:

<type>(<scope>): <description>

Types: feat, fix, docs, test, refactor, perf, chore

Examples:

feat(cmj): add triple extension tracking
fix(dropjump): correct ground contact detection
test(core): add filtering edge case tests

Code Style

• 88 character line limit (ruff)
• Use early returns to reduce nesting
• Extract methods for complexity > 15
• Prefer composition over inheritance
• Single Responsibility for all functions

Adding New Analysis Type

1. Create module directory:

   src/kinemotion/<type>/

2. Implement:

   cli.py

   ,

   analysis.py

   ,

   kinematics.py

3. Add validation bounds in

   validation_bounds.py

4. Register CLI in main

   cli.py

5. Export in

   api.py

   and

   __init__.py

6. Add tests mirroring structure
7. Update CLAUDE.md quick reference