Antoine Van Elstraete
c7a0a77d1f
Co-authored-by: OpenAI/GPT-5.6-Terra <vibecoder@antoineve.me> Co-authored-by: OpenAI/GPT-5.6-Luna <vibecoder@antoineve.me> Co-authored-by: MiniMax/MiniMax-M3 <vibecoder@antoineve.me> Co-authored-by: DeepSeek/DeepSeek-v4-Flash <vibecoder@antoineve.me>
102 lines
3.1 KiB
Python
102 lines
3.1 KiB
Python
from collections import defaultdict
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from datetime import date
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import sqlalchemy as sa
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from flask import Blueprint, render_template, request
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from app import db
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from app.business.time_calc import count_day_types, minutes_to_str, monthly_stats
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from app.business.travel_calc import compute_co2_grams, compute_frais_reels, compute_km_for_entry
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from app.config_loader import get_bareme, get_journeys, get_vehicles
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from app.models import WorkEntry
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bp = Blueprint("reports", __name__, url_prefix="/reports")
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MONTHS_FR = {
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1: "Janvier",
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2: "Février",
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3: "Mars",
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4: "Avril",
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5: "Mai",
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6: "Juin",
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7: "Juillet",
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8: "Août",
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9: "Septembre",
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10: "Octobre",
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11: "Novembre",
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12: "Décembre",
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}
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@bp.route("/")
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def index():
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year = request.args.get("year", date.today().year, type=int)
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start = date(year, 1, 1)
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end = date(year, 12, 31)
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entries = db.session.scalars(
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sa.select(WorkEntry).where(WorkEntry.date.between(start, end))
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).all()
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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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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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total_km[v] = total_km.get(v, 0) + d
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total_co2 += compute_co2_grams(km, vehicles)
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frais_reels = {}
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for vehicle_id, km in total_km.items():
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vehicle = vehicles.get(vehicle_id, {})
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cv = vehicle.get("cv")
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if cv:
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tranches = get_bareme(year, cv)
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electric = vehicle.get("fuel") == "electric"
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frais_reels[vehicle_id] = round(compute_frais_reels(km, tranches, electric=electric), 2)
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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"])
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if month_entries
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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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total_km=total_km,
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total_co2_kg=round(total_co2 / 1000, 2),
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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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