gestioCOF/kfet/statistic.py

# -*- coding: utf-8 -*-

from dateutil.relativedelta import relativedelta

from django.utils import timezone
from django.db.models import Sum

KFET_WAKES_UP_AT = 7


def kfet_day(year, month, day, start_at=KFET_WAKES_UP_AT):
    return timezone.datetime(year, month, day, hour=start_at)


def to_kfet_day(dt, start_at=KFET_WAKES_UP_AT):
    kfet_dt = kfet_day(year=dt.year, month=dt.month, day=dt.day)
    if dt.hour < start_at:
        kfet_dt -= timezone.timedelta(days=1)
    return kfet_dt


class StatScale(object):
    name = None
    step = None

    def __init__(self, n_steps=0, begin=None, end=None,
                 last=False, std_chunk=True):
        self.std_chunk = std_chunk
        if last:
            end = timezone.now()

        if begin is not None and n_steps != 0:
            self.begin = self.get_from(begin)
            self.end = self.do_step(self.begin, n_steps=n_steps)
        elif end is not None and n_steps != 0:
            self.end = self.get_from(end)
            self.begin = self.do_step(self.end, n_steps=-n_steps)
        elif begin is not None and end is not None:
            self.begin = self.get_from(begin)
            self.end = self.get_from(end)
        else:
            raise Exception('Two of these args must be specified: '
                            'n_steps, begin, end; '
                            'or use last and n_steps')

        self.datetimes = self.get_datetimes()

    @staticmethod
    def by_name(name):
        for cls in StatScale.__subclasses__():
            if cls.name == name:
                return cls
        raise Exception('scale %s not found' % name)

    def get_from(self, dt):
        return self.std_chunk and self.get_chunk_start(dt) or dt

    def __getitem__(self, i):
        return self.datetimes[i], self.datetimes[i+1]

    def __len__(self):
        return len(self.datetimes) - 1

    def do_step(self, dt, n_steps=1):
        return dt + self.step * n_steps

    def get_datetimes(self):
        datetimes = [self.begin]
        tmp = self.begin
        while tmp <= self.end:
            tmp = self.do_step(tmp)
            datetimes.append(tmp)
        return datetimes

    def get_labels(self, label_fmt=None):
        if label_fmt is None:
            label_fmt = self.label_fmt
        return [begin.strftime(label_fmt) for begin, end in self]

    @classmethod
    def get_chunk_start(cls, dt):
        dt_kfet = to_kfet_day(dt)
        start = dt_kfet - cls.offset_to_chunk_start(dt_kfet)
        return start


class DayStatScale(StatScale):
    name = 'day'
    step = timezone.timedelta(days=1)
    label_fmt = '%A'

    @classmethod
    def get_chunk_start(cls, dt):
        return to_kfet_day(dt)


class WeekStatScale(StatScale):
    name = 'week'
    step = timezone.timedelta(days=7)
    label_fmt = 'Semaine %W'

    @classmethod
    def offset_to_chunk_start(cls, dt):
        return timezone.timedelta(days=dt.weekday())


class MonthStatScale(StatScale):
    name = 'month'
    step = relativedelta(months=1)
    label_fmt = '%B'

    @classmethod
    def get_chunk_start(cls, dt):
        return to_kfet_day(dt).replace(day=1)


def this_first_month_day():
    now = timezone.now()
    first_day = timezone.datetime(year=now.year,
                                  month=now.month,
                                  day=1,
                                  hour=KFET_WAKES_UP_AT)
    return first_day


def this_monday_morning():
    now = timezone.now()
    monday = now - timezone.timedelta(days=now.isoweekday()-1)
    monday_morning = timezone.datetime(year=monday.year,
                                       month=monday.month,
                                       day=monday.day,
                                       hour=KFET_WAKES_UP_AT)
    return monday_morning


def this_morning():
    now = timezone.now()
    morning = timezone.datetime(year=now.year,
                                month=now.month,
                                day=now.day,
                                hour=KFET_WAKES_UP_AT)
    return morning


# Étant donné un queryset d'operations
# rend la somme des article_nb
def tot_ventes(queryset):
    res = queryset.aggregate(Sum('article_nb'))['article_nb__sum']
    return res and res or 0