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Krzysztof kuhy Rudnicki
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Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
171 lines
6.7 KiB
Python
Executable File
171 lines
6.7 KiB
Python
Executable File
#!/usr/bin/env python3
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"""Regenerate the shared cross-language Body-tab parity fixture.
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The fixture (``tests/fixtures/body_calc.json``) is read by *both*
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``diet_guard/tests/test_body_parity.py`` and
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``app/test/services/body_parity_test.dart``: one shared input, one shared
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expected result, so the PC and the phone print the same BMI, ideal weights,
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calorie table, exercise kcal and week plan for the same person.
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``expected`` comes from the Python implementation, the reference the Dart
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port must reproduce -- so regenerating blesses whatever Python does now. Only
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run it after an intended change, and re-read the diff before committing.
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python3 scripts/build_body_fixture.py
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"""
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from __future__ import annotations
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from dataclasses import asdict
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from datetime import date
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import json
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from pathlib import Path
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from diet_guard._activity_kcal import Session, daily_exercise, session_kcal
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from diet_guard._body_calc import (
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bmi_report,
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bmr_formulas,
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healthy_range,
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ideal_summary,
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ideal_weights,
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table_bmr,
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)
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from diet_guard._body_energy import DEFAULT_GOAL, Goal, goal_target
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from diet_guard._body_prefs import goal_to_json
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from diet_guard._body_steps import step_kcal, stride_m
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from diet_guard._budget_biometrics import Biometrics
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from diet_guard._week_plan import plan_week
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FIXTURE = Path(__file__).resolve().parent.parent / "tests/fixtures/body_calc.json"
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_PEOPLE = (
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Biometrics(weight_kg=80.0, height_cm=180.0, age_years=30, is_male=True),
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Biometrics(weight_kg=62.5, height_cm=165.0, age_years=45, is_male=False),
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# Under five feet: the inch-based formulas must come out null.
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Biometrics(weight_kg=50.0, height_cm=150.0, age_years=25, is_male=False),
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# Under 20: adult BMI bands do not apply.
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Biometrics(weight_kg=65.0, height_cm=175.0, age_years=17, is_male=True),
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# Big and heavy: deep into the obese bands, targets far above the floor.
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Biometrics(weight_kg=121.3, height_cm=191.0, age_years=41, is_male=True),
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)
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_SESSIONS = (
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Session("2026-09-20", "run", 60.5, 5.61, "Running 5.6 km", "runnerup"),
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Session("2026-09-21", "run", 30.0, 7.5, "fast run", "runnerup"),
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Session("2026-09-22", "run", 45.0, 3.0, "slow jog", "runnerup"),
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Session("2026-09-23", "walk", 60.0, 5.0, "walk", "screen-locker"),
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Session("2026-09-24", "walk", 60.0, None, "walk, no distance", "screen-locker"),
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Session("2026-09-25", "strength", 86.2, None, "StrongLifts B", "screen-locker"),
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Session("2026-09-26", "cycle", 40.0, 12.0, "bike", "screen-locker"),
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Session("2026-09-27", "other", 50.0, None, "climbing", "screen-locker"),
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Session("2026-09-19", "walk", 45.0, 3.5, "walked 3500 m", "screen-locker"),
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# Outside the 14-day window for today=2026-09-28: must not count.
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Session("2026-09-13", "run", 60.0, 10.0, "old run", "runnerup"),
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# Today: in progress, must not count either.
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Session("2026-09-28", "run", 60.0, 10.0, "today's run", "runnerup"),
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)
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_PLANS = (
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# Wednesday: Mon/Tue logged, nothing typed.
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("2026-09-30", 2000, {"2026-09-28": 2500.4, "2026-09-29": 1800.0}, {}),
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# Typed Saturday feast wins over nothing; typed Monday wins over the log.
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("2026-09-30", 2000, {"2026-09-28": 2500.0}, {0: 2200, 5: 3500}),
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# Sunday with everything known: no remaining days.
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("2026-10-04", 1800, {}, dict.fromkeys(range(7), 1900)),
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# Over-eaten early: the rest must go under the floor.
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("2026-10-01", 1500, {"2026-09-28": 4000, "2026-09-29": 3900}, {}),
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)
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_BODY_FAT = 18.5
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# Goals exercising every direction, unit and activity kind.
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_GOALS = (
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DEFAULT_GOAL,
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Goal("gain", 0.25, "kg", "week", "sedentary"),
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Goal("maintain", 0.5, "kg", "week", "extra"),
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Goal("lose", 1.0, "lb", "week", "light"),
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Goal("lose", 500.0, "g", "day", "very"),
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Goal("lose", 0.5, "st", "month", "measured:ACSM"),
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Goal("lose", 12.0, "kg", "year", "measured:Per-km"),
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Goal("lose", 3.0, "kg", "week", "sedentary"), # far below the floor
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)
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# Phone-published steps outside workouts (one day under the baseline).
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_STEPS = {"2026-09-20": 9000, "2026-09-21": 3500, "2026-09-25": 12000}
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def _person(bio: Biometrics) -> dict[str, object]:
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today = date(2026, 9, 28)
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by_day = {day: step_kcal(n, bio) for day, n in _STEPS.items()}
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exercise = daily_exercise(_SESSIONS, bio.weight_kg, today, by_day)
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targets = []
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for fat in (None, _BODY_FAT):
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bmr = table_bmr(bio, fat)
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for goal in _GOALS:
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target = goal_target(goal, bmr.value or 0.0, bmr.name, exercise)
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targets.append(
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{"body_fat_pct": fat, "goal": goal_to_json(goal), **asdict(target)}
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)
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return {
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"bio": asdict(bio),
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"bmi": asdict(bmi_report(bio)),
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"ideal": [[f.name, f.value] for f in ideal_weights(bio)],
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"bmr": [[f.name, f.value] for f in bmr_formulas(bio)],
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"body_fat_pct": _BODY_FAT,
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"bmr_with_fat": [[f.name, f.value] for f in bmr_formulas(bio, _BODY_FAT)],
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"ideal_summary": ideal_summary(ideal_weights(bio)),
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"healthy_range": healthy_range(bio),
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"stride_m": stride_m(bio),
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"step_kcal": {day: step_kcal(n, bio) for day, n in _STEPS.items()},
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"exercise": exercise,
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"exercise_no_steps": daily_exercise(_SESSIONS, bio.weight_kg, today),
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# History younger than 14 days: averaged from its first day.
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"exercise_short": daily_exercise(
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tuple(x for x in _SESSIONS if x.day >= "2026-09-24"), bio.weight_kg, today
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),
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# Only today's (in-progress) session: no past data, all zero.
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"exercise_today_only": daily_exercise(
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tuple(x for x in _SESSIONS if x.day == "2026-09-28"), bio.weight_kg, today
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),
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"targets": targets,
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}
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def build() -> dict[str, object]:
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"""Evaluate every vector against the Python reference."""
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return {
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"today": "2026-09-28",
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"people": [_person(bio) for bio in _PEOPLE],
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"steps": _STEPS,
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"sessions": [asdict(s) for s in _SESSIONS],
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"session_kcal_80kg": [
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{
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"kcal": result.kcal,
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"fallback": sorted(result.fallback),
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}
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for result in (session_kcal(s, 80.0) for s in _SESSIONS)
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],
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"plans": [
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{
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"today": today,
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"target": target,
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"logged": logged,
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"typed": {str(k): v for k, v in typed.items()},
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"expected": asdict(
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plan_week(date.fromisoformat(today), target, logged, typed)
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),
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}
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for today, target, logged, typed in _PLANS
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],
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}
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def main() -> None:
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"""Write the fixture."""
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FIXTURE.write_text(json.dumps(build(), indent=1) + "\n", encoding="utf-8")
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if __name__ == "__main__":
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main()
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