def test_week(self):
with self.settings(LANGUAGE_CODE='en-us'):
s, e = get_date_ranges(
datetime.date(2015, 4, 29), GRANULARITY_WEEK
)
self.assertEqual(s, datetime.date(2015, 4, 26))
self.assertEqual(e, datetime.date(2015, 5, 2))
with self.settings(LANGUAGE_CODE='fr-fr'):
s, e = get_date_ranges(
datetime.date(2015, 4, 29), GRANULARITY_WEEK
)
self.assertEqual(s, datetime.date(2015, 4, 27))
self.assertEqual(e, datetime.date(2015, 5, 3))
with self.settings(LANGUAGE_CODE='fr-fr'):
s, e = get_date_ranges(
datetime.date(2015, 7, 13), GRANULARITY_WEEK
)
self.assertEqual(s, datetime.date(2015, 7, 13))
self.assertEqual(e, datetime.date(2015, 7, 19))
with self.settings(LANGUAGE_CODE='fa'):
s, e = get_date_ranges(
datetime.date(2015, 4, 29), GRANULARITY_WEEK
)
self.assertEqual(s, datetime.date(2015, 4, 25))
self.assertEqual(e, datetime.date(2015, 5, 1))
def test_month(self):
s, e = get_date_ranges(
datetime.date(2015, 2, 15), GRANULARITY_MONTH
)
self.assertEqual(s, datetime.date(2015, 2, 1))
self.assertEqual(e, datetime.date(2015, 2, 28))
s, e = get_date_ranges(
datetime.date(2016, 2, 15), GRANULARITY_MONTH
)
self.assertEqual(s, datetime.date(2016, 2, 1))
self.assertEqual(e, datetime.date(2016, 2, 29))
def get_total_unscheduled_period(self, bankaccount,
granularity=GRANULARITY_MONTH):
"""
Returns the total sum for the current period of bank transactions not
scheduled.
"""
return (
self
.filter(
bankaccount=bankaccount,
date__range=get_date_ranges(timezone.now(), granularity),
scheduled=False,
)
.exclude(status=BankTransaction.STATUS_INACTIVE)
.aggregate(total=models.Sum('amount'))
)['total']
def get_context_data(self, **kwargs):
context = super(TrendTimeView, self).get_context_data(**kwargs)
context['bankaccount'] = self.bankaccount
filters = self.session_data.get('filters', {})
context['has_filters'] = bool(filters)
if filters:
# Get first and last bank transaction to prevent infinite pager. If
# one is missing, it just mean that there is no data at all.
first, last = self.get_queryset_dates_delimiters()
if first and last:
base_date = datetime.date(**filters['date_kwargs'])
granularity = filters['granularity']
if self.request.GET.get('date'):
try:
base_date = datetime.datetime.strptime(
self.request.GET.get('date'),
'%Y-%m-%d',
).date()
except ValueError:
pass
# Requested date is not out of range?
first_range = get_date_ranges(first, granularity)[0]
last_range = get_date_ranges(last, granularity)[1]
if first_range <= base_date <= last_range:
date_start, date_end = get_date_ranges(
base_date,
granularity,
)
balance = self.get_queryset_balance(date_start)['sum'] or 0
balance += self.bankaccount.balance_initial
context['balance_initial'] = balance
items_qs = self.get_queryset_items(date_start, date_end)
items = {item['date']: item for item in items_qs}
# Start and end iterator at first/last bank transaction,
# not the range calculated.
iterator = DateIterator(
first if first > date_start else date_start,
last if last < date_end else date_end,
)
rows = []
for date_step in iterator:
delta = percentage = count = 0
# If no new bank transaction, same as previous.
if date_step in items:
delta = items[date_step]['sum']
percentage = (delta * 100 /
balance) if balance else 0
balance += items[date_step]['sum']
count = items[date_step]['count']
rows.append({
'date': date_step,
'count': count,
'balance': balance,
'delta': delta,
'percentage': round(percentage, 2),
})
context['rows'] = rows
context['chart_data'] = json.dumps({
'data': {
'labels': [
formats.date_format(
row['date'],
'SHORT_DATE_FORMAT',
) for row in rows
],
'datasets': [{
'fillColor':
"rgba(66, 139, 202, 0.5)",
'strokeColor':
"rgba(66, 139, 202, 0.8)",
'pointColor':
"rgba(66, 139, 202, 0.75)",
'pointHighlightFill':
"#fff",
'pointHighlightStroke':
"rgba(66, 139, 202, 1)",
'data':
[float(row['balance']) for row in rows],
}],
},
'type':
filters['chart'],
})
paginator = DatePaginator(first_range, last_range,
granularity)
context['page_obj'] = paginator.page(base_date)
return context
def list(self, request, *args, **kwargs):
serializer = TrendTimeInputSerializer(data=request.query_params)
serializer.is_valid(raise_exception=True)
self.filters = serializer.validated_data
results, links = [], {}
# Get first and last bank transaction to prevent infinite pager. If
# one is missing, it just mean that there is no data at all.
first, last = self.get_queryset_dates_delimiters()
if first and last:
base_date = self.filters['date']
granularity = self.filters['granularity']
# Requested date is out of range?
first_range = get_date_ranges(first, granularity)[0]
last_range = get_date_ranges(last, granularity)[1]
if first_range <= base_date <= last_range:
date_start, date_end = get_date_ranges(
base_date,
granularity,
)
balance = self.get_queryset_balance(date_start)['sum'] or 0
balance += self.bankaccount.balance_initial
items_qs = self.get_queryset_items(date_start, date_end)
items = {item['date']: item for item in items_qs}
# Start and end iterator at first/last bank transaction,
# not the range calculated.
iterator = DateIterator(
first if first > date_start else date_start,
last if last < date_end else date_end,
)
instances = []
for date_step in iterator:
delta = percentage = count = 0
# If no new bank transaction, same as previous.
if date_step in items:
delta = items[date_step]['sum']
percentage = (delta * 100 / balance) if balance else 0
balance += items[date_step]['sum']
count = items[date_step]['count']
instances.append({
'date': date_step,
'count': count,
'delta': delta,
'balance': balance,
'percentage': percentage,
})
results = TrendTimeOuputSerializer(instances, many=True).data
paginator = DatePaginator(first_range, last_range, granularity)
links = paginator.get_links(base_date, request)
return Response({
'results': results,
'previous': links.get('previous'),
'next': links.get('next'),
})
def get_context_data(self, **kwargs):
context = super(TrendTimeView, self).get_context_data(**kwargs)
context['bankaccount'] = self.bankaccount
filters = self.session_data.get('filters', {})
context['has_filters'] = bool(filters)
if filters:
# Get first and last bank transaction to prevent infinite pager. If
# one is missing, it just mean that there is no data at all.
first, last = self.get_queryset_dates_delimiters()
if first and last:
base_date = datetime.date(**filters['date_kwargs'])
granularity = filters['granularity']
if self.request.GET.get('date'):
try:
base_date = datetime.datetime.strptime(
self.request.GET.get('date'),
'%Y-%m-%d',
).date()
except ValueError:
pass
# Requested date is not out of range?
first_range = get_date_ranges(first, granularity)[0]
last_range = get_date_ranges(last, granularity)[1]
if first_range <= base_date <= last_range:
date_start, date_end = get_date_ranges(
base_date,
granularity,
)
balance = self.get_queryset_balance(date_start)['sum'] or 0
balance += self.bankaccount.balance_initial
context['balance_initial'] = balance
items_qs = self.get_queryset_items(date_start, date_end)
items = {item['date']: item for item in items_qs}
# Start and end iterator at first/last bank transaction,
# not the range calculated.
iterator = DateIterator(
first if first > date_start else date_start,
last if last < date_end else date_end,
)
rows = []
for date_step in iterator:
delta = percentage = count = 0
# If no new bank transaction, same as previous.
if date_step in items:
delta = items[date_step]['sum']
percentage = (delta * 100 / balance) if balance else 0
balance += items[date_step]['sum']
count = items[date_step]['count']
rows.append({
'date': date_step,
'count': count,
'balance': balance,
'delta': delta,
'percentage': round(percentage, 2),
})
context['rows'] = rows
context['chart_data'] = json.dumps({
'data': {
'labels': [
formats.date_format(
row['date'], 'SHORT_DATE_FORMAT',
)
for row in rows
],
'datasets': [
{
'fillColor': "rgba(66, 139, 202, 0.5)",
'strokeColor': "rgba(66, 139, 202, 0.8)",
'pointColor': "rgba(66, 139, 202, 0.75)",
'pointHighlightFill': "#fff",
'pointHighlightStroke': "rgba(66, 139, 202, 1)",
'data': [
float(row['balance']) for row in rows
],
}
],
},
'type': filters['chart'],
})
paginator = DatePaginator(
first_range, last_range, granularity
)
context['page_obj'] = paginator.page(base_date)
return context