Lars
49e9c9c214
- Enhanced the caliper listing and export functionalities to include enriched data from weight logs. - Updated the upsert and update operations to utilize new composition functions for body composition calculations. - Refactored the CaliperScreen component to streamline payload construction by removing unnecessary parameters.
112 lines
3.4 KiB
Python
112 lines
3.4 KiB
Python
"""Derive lean_mass and fat_mass from weight_log + body_fat_pct for caliper entries."""
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from datetime import date, datetime
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from decimal import Decimal
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from typing import Any, Dict, List, Optional, Tuple
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from db import get_cursor, r2d
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def as_date(d: Any) -> Optional[date]:
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if d is None:
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return None
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if isinstance(d, datetime):
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return d.date()
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if isinstance(d, date):
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return d
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if isinstance(d, str) and len(d) >= 10:
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return datetime.strptime(d[:10], "%Y-%m-%d").date()
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return None
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def _floaty(x: Any) -> float:
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if isinstance(x, Decimal):
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return float(x)
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return float(x)
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def load_weight_rows(conn: Any, profile_id: str) -> List[Dict[str, Any]]:
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cur = get_cursor(conn)
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cur.execute(
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"SELECT date, weight FROM weight_log WHERE profile_id=%s ORDER BY date",
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(profile_id,),
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)
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return [r2d(r) for r in cur.fetchall()]
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def nearest_weight_kg(weight_rows: List[Dict[str, Any]], caliper_date: Any) -> Optional[float]:
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td = as_date(caliper_date)
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if td is None or not weight_rows:
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return None
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best: Optional[float] = None
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best_delta: Optional[int] = None
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for row in weight_rows:
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wd = as_date(row.get("date"))
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if wd is None:
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continue
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wraw = row.get("weight")
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if wraw is None:
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continue
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delta = abs((wd - td).days)
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if best_delta is None or delta < best_delta:
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best_delta = delta
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best = _floaty(wraw)
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return best
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def nearest_weight_kg_from_map(wlog: Dict[Any, Any], target_date: Any) -> Optional[float]:
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if not wlog:
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return None
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td = as_date(target_date)
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if td is None:
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return None
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best_w: Optional[float] = None
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best_delta: Optional[int] = None
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for wd, wval in wlog.items():
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if wval is None:
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continue
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wdate = as_date(wd)
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if wdate is None:
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continue
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delta = abs((wdate - td).days)
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if best_delta is None or delta < best_delta:
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best_delta = delta
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best_w = _floaty(wval)
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return best_w
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def compute_lean_fat_kg(weight_kg: float, body_fat_pct: float) -> Tuple[float, float]:
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lean = round(weight_kg - (weight_kg * body_fat_pct / 100.0), 2)
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fat = round(weight_kg * body_fat_pct / 100.0, 2)
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return lean, fat
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def fill_caliper_body_comp(d: Dict[str, Any], conn: Any, profile_id: str) -> None:
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"""Mutate caliper API payload (model_dump) before INSERT/UPDATE."""
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bf = d.get("body_fat_pct")
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if bf is None:
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return
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if d.get("lean_mass") is not None and d.get("fat_mass") is not None:
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return
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rows = load_weight_rows(conn, profile_id)
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w = nearest_weight_kg(rows, d.get("date"))
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if w is None:
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return
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lean, fat = compute_lean_fat_kg(w, _floaty(bf))
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d["lean_mass"] = lean
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d["fat_mass"] = fat
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def enrich_caliper_row_for_response(row: Dict[str, Any], weight_rows: List[Dict[str, Any]]) -> None:
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"""Fill missing lean_mass / fat_mass for API responses (read path)."""
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bf = row.get("body_fat_pct")
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if bf is None:
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return
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if row.get("lean_mass") is not None and row.get("fat_mass") is not None:
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return
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w = nearest_weight_kg(weight_rows, row.get("date"))
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if w is None:
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return
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lean, fat = compute_lean_fat_kg(w, _floaty(bf))
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row["lean_mass"] = lean
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row["fat_mass"] = fat
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