188 lines
5 KiB
Python
188 lines
5 KiB
Python
# -*- coding: utf-8 -*-
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import ast
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from dateutil.relativedelta import relativedelta
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from django.utils import timezone
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from django.db.models import Sum
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KFET_WAKES_UP_AT = 7
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def kfet_day(year, month, day, start_at=KFET_WAKES_UP_AT):
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return timezone.datetime(year, month, day, hour=start_at)
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def to_kfet_day(dt, start_at=KFET_WAKES_UP_AT):
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kfet_dt = kfet_day(year=dt.year, month=dt.month, day=dt.day)
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if dt.hour < start_at:
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kfet_dt -= timezone.timedelta(days=1)
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return kfet_dt
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class StatScale(object):
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name = None
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step = None
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def __init__(self, n_steps=0, begin=None, end=None,
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last=False, std_chunk=True):
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self.std_chunk = std_chunk
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if last:
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end = timezone.now()
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if begin is not None and n_steps != 0:
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self.begin = self.get_from(begin)
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self.end = self.do_step(self.begin, n_steps=n_steps)
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elif end is not None and n_steps != 0:
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self.end = self.get_from(end)
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self.begin = self.do_step(self.end, n_steps=-n_steps)
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elif begin is not None and end is not None:
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self.begin = self.get_from(begin)
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self.end = self.get_from(end)
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else:
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raise Exception('Two of these args must be specified: '
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'n_steps, begin, end; '
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'or use last and n_steps')
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self.datetimes = self.get_datetimes()
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@staticmethod
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def by_name(name):
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for cls in StatScale.__subclasses__():
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if cls.name == name:
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return cls
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return None
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def get_from(self, dt):
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return self.std_chunk and self.get_chunk_start(dt) or dt
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def __getitem__(self, i):
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return self.datetimes[i], self.datetimes[i+1]
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def __len__(self):
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return len(self.datetimes) - 1
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def do_step(self, dt, n_steps=1):
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return dt + self.step * n_steps
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def get_datetimes(self):
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datetimes = [self.begin]
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tmp = self.begin
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while tmp <= self.end:
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tmp = self.do_step(tmp)
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datetimes.append(tmp)
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return datetimes
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def get_labels(self, label_fmt=None):
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if label_fmt is None:
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label_fmt = self.label_fmt
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return [begin.strftime(label_fmt) for begin, end in self]
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class DayStatScale(StatScale):
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name = 'day'
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step = timezone.timedelta(days=1)
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label_fmt = '%A'
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@classmethod
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def get_chunk_start(cls, dt):
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return to_kfet_day(dt)
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class WeekStatScale(StatScale):
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name = 'week'
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step = timezone.timedelta(days=7)
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label_fmt = 'Semaine %W'
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@classmethod
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def get_chunk_start(cls, dt):
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dt_kfet = to_kfet_day(dt)
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offset = timezone.timedelta(days=dt_kfet.weekday())
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return dt_kfet - offset
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class MonthStatScale(StatScale):
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name = 'month'
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step = relativedelta(months=1)
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label_fmt = '%B'
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@classmethod
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def get_chunk_start(cls, dt):
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return to_kfet_day(dt).replace(day=1)
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def stat_manifest(scales_def=None, scale_args=None, **url_params):
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if scales_def is None:
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scales_def = []
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if scale_args is None:
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scale_args = {}
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return [
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dict(
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label=label,
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url_params=dict(
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scale=cls.name,
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scale_args=scale_args,
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**url_params,
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),
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)
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for label, cls in scales_def
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]
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def last_stats_manifest(scales_def=None, scale_args=None, **url_params):
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scales_def = [
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('Derniers mois', MonthStatScale, ),
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('Dernières semaines', WeekStatScale, ),
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('Derniers jours', DayStatScale, ),
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]
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if scale_args is None:
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scale_args = {}
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scale_args.update(dict(
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last=True,
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n_steps=7,
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))
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return stat_manifest(scales_def=scales_def, scale_args=scale_args,
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**url_params)
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# Étant donné un queryset d'operations
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# rend la somme des article_nb
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def tot_ventes(queryset):
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res = queryset.aggregate(Sum('article_nb'))['article_nb__sum']
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return res and res or 0
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class ScaleMixin(object):
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def get_context_data(self, *args, **kwargs):
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context = super().get_context_data(*args, **kwargs)
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scale_name = self.request.GET.get('scale', None)
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cls = StatScale.by_name(scale_name)
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if cls is None:
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scale = self.get_default_scale()
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else:
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scale_args = self.request.GET.get('scale_args', {})
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if isinstance(scale_args, str):
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scale_args = ast.literal_eval(scale_args)
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scale = cls(**scale_args)
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self.scale = scale
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context['labels'] = scale.get_labels()
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return context
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def get_default_scale(self):
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return DayStatScale(n_steps=7, last=True)
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def chunkify_qs(self, qs, scale, field=None):
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if field is None:
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field = 'at'
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begin_f = '{}__gte'.format(field)
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end_f = '{}__lte'.format(field)
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return [
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qs.filter(**{begin_f: begin, end_f: end})
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for begin, end in scale
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]
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