On utilise Scale

kfet/urls.py

@@ -238,12 +238,7 @@ urlpatterns = [
     # -----
     # Sales history urls
     # -----
-    path("purchases", views.purchases_csv, name="kfet.purchases"),
+    path("purchases", views.SalesStatList.as_view(), name="kfet.purchases"),
-    path(
-        "purchases/<int:start_year>-<int:start_month>/<int:end_year>-<int:end_month>",
-        views.purchases_csv,
-        name="kfet.purchases",
-    ),
     # -----
     # JSON urls
     # -----

kfet/views.py

@@ -2,7 +2,7 @@ import csv
 import heapq
 import statistics
 from collections import defaultdict
-from datetime import date, datetime, timedelta
+from datetime import datetime, timedelta
 from decimal import Decimal
 from typing import List
 from urllib.parse import urlencode
@@ -13,12 +13,13 @@ from django.contrib.auth.decorators import login_required, permission_required
 from django.contrib.auth.mixins import PermissionRequiredMixin
 from django.contrib.auth.models import Permission, User
 from django.contrib.messages.views import SuccessMessageMixin
-from django.core.exceptions import SuspiciousOperation, ValidationError
+from django.core.exceptions import SuspiciousOperation
 from django.db import transaction
 from django.db.models import Count, F, Max, OuterRef, Prefetch, Q, Subquery, Sum
 from django.forms import ValidationError, formset_factory
 from django.http import (
     Http404,
+    HttpResponse,
     HttpResponseBadRequest,
     HttpResponseForbidden,
     JsonResponse,
@@ -30,6 +31,7 @@ from django.utils.decorators import method_decorator
 from django.views.generic import DetailView, FormView, ListView, TemplateView
 from django.views.generic.detail import BaseDetailView
 from django.views.generic.edit import CreateView, DeleteView, UpdateView
+from django.views.generic.list import BaseListView
 
 from gestioncof.models import CofProfile
 from kfet import KFET_DELETED_TRIGRAMME, consumers
@@ -2456,81 +2458,61 @@ class ScaleMixin(object):
 # Export des ventes en CSV
 # ------------------------
 
+MONTHS = (
+    "_Janvier_Février_Mars_Avril_Mai_Juin_Juillet_Août_Septembre_Octobre"
+    "_Novembre_Décembre"
+).split("_")
 
-@teamkfet_required
-def purchases_csv(
-    request, start_year=None, start_month=None, end_year=None, end_month=None
-):
-    """
-    Renvoie un historique des achats en K-Fêt, par mois et sur une période donnée
-    (Par défault les 12 mois précédents)
-    """
-    # Si on ne spécifie pas tout l'intervalle, on prend les 12 derniers mois
-    if (start_year and start_month and end_year and end_month) is None:
-        # On utilise replace pour gérer le cas des années bissextiles sans
-        # changer de mois
-        end = date.today().replace(day=1)
-        start = end - timedelta(days=365)
-        start_year = start.year
-        start_month = start.month
-        end_year = end.year
-        end_month = end.month
 
-    # On calcule la liste des premiers jours des mois dont on veut avoir les
+@method_decorator(teamkfet_required, name="dispatch")
-    # ventes
+class SalesStatList(BaseListView):
-    dates = []
+    model = Operation
 
-    for year in range(start_year, end_year + 1):
+    def get_queryset(self):
-        month_start = start_month if year == start_year else 1
+        return super().get_queryset().filter(type=Operation.PURCHASE, canceled_at=None)
-        month_end = end_month if year == end_year else 12
-        for month in range(month_start, month_end + 1):
-            dates.append(date(year, month, 1))
 
-    # On rajoute le mois suivant
+    def get_context_data(self, **kwargs):
-    dates.append((dates[-1] + timedelta(days=31)).replace(day=1))
+        ctx = super().get_context_data(**kwargs)
-
+        scale = MonthScale(n_steps=12, last=True)
-    # On récupère les données voulues
+        qs = self.get_queryset()
-    articles_list = list(Article.objects.order_by("name"))
+        articles = list(Article.objects.order_by("name"))
-    nb_articles = len(articles_list)
+        indexes = {a.name: index for index, a in enumerate(articles)}
-    articles = {}
+        ventes = scale.chunkify_qs(
-    for i in range(nb_articles):
+            qs.values_list(
-        articles[articles_list[i].name] = i + 1
+                "article__name", "group__at__month", "group__at__year"
-
+            ).annotate(Sum("article_nb")),
-    ventes = (
+            field="group__at",
-        Operation.objects.filter(
-            type="purchase", canceled_by=None, group__at__range=[dates[0], dates[-1]]
         )
-        .exclude(article=None)
-        .order_by("group__at")
-        .select_related("group", "article")
-    )
 
-    # On crée le fichier CSV
+        ctx["header"] = ["Mois"] + [a.name for a in articles]
-    response = HttpResponse(content_type="text/csv")
+        ctx["ventes"] = []
-    response["Content-Disposition"] = 'attachment; filename="historique_ventes.csv"'
+        ctx["total"] = [0] * len(articles)
-    writer = csv.writer(response)
+        for v in ventes:
+            m_ventes = [0] * len(articles)
+            for (a_name, month, year, nb_ventes) in v:
+                index = indexes[a_name]
+                m_ventes[index] = nb_ventes
+                ctx["total"][index] += nb_ventes
 
-    # On met un article par colonne
+            ctx["ventes"].append(["{} {}".format(MONTHS[month], year)] + m_ventes)
-    header = ["Mois"] + [a for a in articles]
-    writer.writerow(header)
 
-    # On calcule la consommation par mois sur la période donnée
+        return ctx
-    i_m = 0
-    row = [f"{dates[i_m].month:02d}/{dates[i_m].year}"] + [0] * nb_articles
-    last_row = ["Total"] + [0] * nb_articles
-    for v in ventes:
-        while v.group.at.date() > dates[i_m + 1]:
-            writer.writerow(row)
-            i_m += 1
-            row = [f"{dates[i_m].month:02d}/{dates[i_m].year}"] + [0] * nb_articles
 
-        row[articles[v.article.name]] += v.article_nb
+    def render_to_response(self, context):
-        last_row[articles[v.article.name]] += v.article_nb
+        response = HttpResponse(content_type="text/csv")
+        response["Content-Disposition"] = 'attachment; filename="historique_ventes.csv"'
 
-    writer.writerow(row)
+        writer = csv.writer(response)
-    writer.writerow(last_row)
+        writer.writerow(context["header"])
 
-    return response
+        # On écrit chaque mois
+        for line in context["ventes"]:
+            writer.writerow(line)
+
+        writer.writerow([])
+        writer.writerow(["Total"] + context["total"])
+
+        return response
 
 
 # -----------------------