feat: calcul stats mensuelles dans reports (km + médianes)
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@@ -1,14 +1,21 @@
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from flask import Blueprint, render_template, request
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from datetime import date
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from collections import defaultdict
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import sqlalchemy as sa
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from app import db
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from app.models import WorkEntry
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from app.business.travel_calc import compute_km_for_entry, compute_co2_grams, compute_frais_reels
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from app.business.time_calc import count_day_types
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from app.business.time_calc import count_day_types, monthly_stats, minutes_to_str
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from app.config_loader import get_vehicles, get_journeys, get_bareme
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bp = Blueprint("reports", __name__, url_prefix="/reports")
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MONTHS_FR = {
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1: "Janvier", 2: "Février", 3: "Mars", 4: "Avril",
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5: "Mai", 6: "Juin", 7: "Juillet", 8: "Août",
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9: "Septembre", 10: "Octobre", 11: "Novembre", 12: "Décembre",
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}
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@bp.route("/")
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def index():
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@@ -23,6 +30,7 @@ def index():
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vehicles = get_vehicles()
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journeys = get_journeys()
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# --- Stats annuelles (inchangées) ---
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total_km = {}
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total_co2 = 0.0
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for entry in entries:
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@@ -42,6 +50,32 @@ def index():
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day_type_counts = count_day_types(entries)
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# --- Stats mensuelles ---
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entries_by_month: dict[int, list] = defaultdict(list)
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for entry in entries:
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entries_by_month[entry.date.month].append(entry)
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monthly_data = {}
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for month in range(1, 13):
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month_entries = entries_by_month.get(month, [])
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month_km: dict[str, int] = {}
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for entry in month_entries:
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km = compute_km_for_entry(entry.journey_profile_id, journeys, entry.motor_vehicle_id)
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for v, d in km.items():
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month_km[v] = month_km.get(v, 0) + d
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stats = monthly_stats(month_entries)
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monthly_data[month] = {
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"month_name": MONTHS_FR[month],
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"entry_count": len(month_entries),
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"km_by_vehicle": month_km,
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"km_total": sum(month_km.values()),
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"median_daily_str": minutes_to_str(stats["median_daily_min"]) if month_entries else "–",
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"median_weekly_str": minutes_to_str(stats["median_weekly_min"]) if month_entries else "–",
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}
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return render_template(
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"reports.html",
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year=year,
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@@ -50,4 +84,5 @@ def index():
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frais_reels=frais_reels,
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vehicles=vehicles,
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day_type_counts=day_type_counts,
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monthly_data=monthly_data,
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)
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