Kinemotion Development Standards

Pre-Commit Checklist

Always run before committing:

bash

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:

bash

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

python

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

code

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

python

@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

•CMJ velocity must be signed - backward search requires knowing direction
•Convert NumPy for JSON - use int(), float() before serialization
•Handle video rotation - mobile videos have rotation metadata
•Read first frame for dimensions - don't trust OpenCV properties

Commit Format

Use Conventional Commits:

code

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

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

Examples:

code

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

Tools Usage

•Documentation: Use ref_search_documentation and ref_read_url to consult external library documentation (OpenCV, MediaPipe, NumPy, etc.) when needing clarification on APIs.
•Code Context: Use get_code_context_exa to find best practices and modern examples for specific coding tasks.
•Memory: Use save_memory or write_note (Serena) to persist important architectural decisions or validation results.