forked from DGNum/gestioCOF
On utilise Scale
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@ -238,12 +238,7 @@ urlpatterns = [
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# -----
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# Sales history urls
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# -----
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path("purchases", views.purchases_csv, name="kfet.purchases"),
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path(
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"purchases/<int:start_year>-<int:start_month>/<int:end_year>-<int:end_month>",
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views.purchases_csv,
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name="kfet.purchases",
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),
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path("purchases", views.SalesStatList.as_view(), name="kfet.purchases"),
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# -----
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# JSON urls
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# -----
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114
kfet/views.py
114
kfet/views.py
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@ -2,7 +2,7 @@ import csv
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import heapq
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import statistics
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from collections import defaultdict
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from datetime import date, datetime, timedelta
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from datetime import datetime, timedelta
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from decimal import Decimal
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from typing import List
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from urllib.parse import urlencode
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@ -13,12 +13,13 @@ from django.contrib.auth.decorators import login_required, permission_required
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from django.contrib.auth.mixins import PermissionRequiredMixin
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from django.contrib.auth.models import Permission, User
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from django.contrib.messages.views import SuccessMessageMixin
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from django.core.exceptions import SuspiciousOperation, ValidationError
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from django.core.exceptions import SuspiciousOperation
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from django.db import transaction
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from django.db.models import Count, F, Max, OuterRef, Prefetch, Q, Subquery, Sum
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from django.forms import ValidationError, formset_factory
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from django.http import (
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Http404,
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HttpResponse,
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HttpResponseBadRequest,
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HttpResponseForbidden,
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JsonResponse,
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@ -30,6 +31,7 @@ from django.utils.decorators import method_decorator
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from django.views.generic import DetailView, FormView, ListView, TemplateView
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from django.views.generic.detail import BaseDetailView
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from django.views.generic.edit import CreateView, DeleteView, UpdateView
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from django.views.generic.list import BaseListView
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from gestioncof.models import CofProfile
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from kfet import KFET_DELETED_TRIGRAMME, consumers
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@ -2456,81 +2458,61 @@ class ScaleMixin(object):
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# Export des ventes en CSV
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# ------------------------
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MONTHS = (
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"_Janvier_Février_Mars_Avril_Mai_Juin_Juillet_Août_Septembre_Octobre"
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"_Novembre_Décembre"
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).split("_")
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@teamkfet_required
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def purchases_csv(
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request, start_year=None, start_month=None, end_year=None, end_month=None
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):
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"""
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Renvoie un historique des achats en K-Fêt, par mois et sur une période donnée
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(Par défault les 12 mois précédents)
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"""
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# Si on ne spécifie pas tout l'intervalle, on prend les 12 derniers mois
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if (start_year and start_month and end_year and end_month) is None:
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# On utilise replace pour gérer le cas des années bissextiles sans
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# changer de mois
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end = date.today().replace(day=1)
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start = end - timedelta(days=365)
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start_year = start.year
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start_month = start.month
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end_year = end.year
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end_month = end.month
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# On calcule la liste des premiers jours des mois dont on veut avoir les
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# ventes
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dates = []
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@method_decorator(teamkfet_required, name="dispatch")
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class SalesStatList(BaseListView):
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model = Operation
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for year in range(start_year, end_year + 1):
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month_start = start_month if year == start_year else 1
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month_end = end_month if year == end_year else 12
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for month in range(month_start, month_end + 1):
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dates.append(date(year, month, 1))
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def get_queryset(self):
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return super().get_queryset().filter(type=Operation.PURCHASE, canceled_at=None)
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# On rajoute le mois suivant
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dates.append((dates[-1] + timedelta(days=31)).replace(day=1))
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# On récupère les données voulues
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articles_list = list(Article.objects.order_by("name"))
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nb_articles = len(articles_list)
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articles = {}
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for i in range(nb_articles):
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articles[articles_list[i].name] = i + 1
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ventes = (
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Operation.objects.filter(
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type="purchase", canceled_by=None, group__at__range=[dates[0], dates[-1]]
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def get_context_data(self, **kwargs):
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ctx = super().get_context_data(**kwargs)
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scale = MonthScale(n_steps=12, last=True)
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qs = self.get_queryset()
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articles = list(Article.objects.order_by("name"))
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indexes = {a.name: index for index, a in enumerate(articles)}
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ventes = scale.chunkify_qs(
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qs.values_list(
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"article__name", "group__at__month", "group__at__year"
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).annotate(Sum("article_nb")),
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field="group__at",
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)
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.exclude(article=None)
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.order_by("group__at")
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.select_related("group", "article")
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)
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# On crée le fichier CSV
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response = HttpResponse(content_type="text/csv")
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response["Content-Disposition"] = 'attachment; filename="historique_ventes.csv"'
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writer = csv.writer(response)
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ctx["header"] = ["Mois"] + [a.name for a in articles]
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ctx["ventes"] = []
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ctx["total"] = [0] * len(articles)
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for v in ventes:
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m_ventes = [0] * len(articles)
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for (a_name, month, year, nb_ventes) in v:
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index = indexes[a_name]
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m_ventes[index] = nb_ventes
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ctx["total"][index] += nb_ventes
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# On met un article par colonne
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header = ["Mois"] + [a for a in articles]
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writer.writerow(header)
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ctx["ventes"].append(["{} {}".format(MONTHS[month], year)] + m_ventes)
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# On calcule la consommation par mois sur la période donnée
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i_m = 0
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row = [f"{dates[i_m].month:02d}/{dates[i_m].year}"] + [0] * nb_articles
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last_row = ["Total"] + [0] * nb_articles
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for v in ventes:
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while v.group.at.date() > dates[i_m + 1]:
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writer.writerow(row)
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i_m += 1
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row = [f"{dates[i_m].month:02d}/{dates[i_m].year}"] + [0] * nb_articles
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return ctx
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row[articles[v.article.name]] += v.article_nb
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last_row[articles[v.article.name]] += v.article_nb
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def render_to_response(self, context):
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response = HttpResponse(content_type="text/csv")
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response["Content-Disposition"] = 'attachment; filename="historique_ventes.csv"'
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writer.writerow(row)
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writer.writerow(last_row)
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writer = csv.writer(response)
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writer.writerow(context["header"])
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return response
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# On écrit chaque mois
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for line in context["ventes"]:
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writer.writerow(line)
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writer.writerow([])
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writer.writerow(["Total"] + context["total"])
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return response
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# -----------------------
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