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views.py
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views.py
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from django.http import HttpResponse
from datetime import date, datetime, timedelta
import operator
import datatracker.data as data
def _csv_response(matrix):
res = list(map(lambda x: ','.join(map(str, x)), matrix))
response = HttpResponse(content_type='plain/text')
response.write("\n".join(res))
return response
def _append_param(param, key, GET, res):
if key in GET:
res.append([param] + GET[key].split(','))
def _add_custom_cyfe_parameters(GET, res):
# Add custom Cyfe parameters
for item in GET:
if item.startswith('Cy_'):
_append_param(item.replace('Cy_', ''), item, GET, res)
DATA_FUNCTIONS = data.DATA_FUNC
def stats(request, func):
return _csv_response(DATA_FUNCTIONS[func]())
def _get_metric(metric, start, end, agg_by, last=False):
override_name = None
mtuple = metric.split(',')
if len(mtuple) == 5:
group, name, filter_by, count, override_name = mtuple
else:
group, name, filter_by, count = mtuple
if len(filter_by):
filter_by = {x[0]: x[1] for x in map(lambda y: y.split(':'), filter_by.split(';'))}
print("Filtering by: " + str(filter_by))
return data.get_events(name, group, start, end, filter_by_properties=filter_by, aggregate_by=agg_by, count_by_property=count if len(count) else None, override_name=override_name, last=last).items()
# Pivot metrics matrix
# Input = [ ['Invite sent', {'20141008': 10, '20141009', 20}],
# ['Member acquired', {'20141008': 150, '20141009', 145}],
# ]
# Output = [ ['20141008', 10, 150]
# ['20141009', 20, 140]
# ]
def _pivot_metrics(metrics, formulas, sortby="0"):
res = {}
for i in range(len(metrics)):
formula = None
if i < len(formulas):
formula = formulas[i][1]
metric = metrics[i][1]
for key in metric:
if key not in res:
res[key] = []
for y in range(len(res[key]), i):
res[key].append(0)
if formula:
if not key in formula or formula[key] == 0:
# Skip if we can't proceed with the formula
continue
else:
res[key].append(round(float(100 * metric[key]) / float(formula[key]), 1))
else:
res[key].append(metric[key])
return sorted(list(map(lambda x: [x[0]] + x[1], res.items())), key=operator.itemgetter(int(sortby)), reverse=(sortby[0] == '-'))
#
# https://trampolinn.com/fr/datatrack/cohort/?main_metric=Member%20activity,,&trigger_metric=Member%20activity,,&name=User&granularity=month&nb_items=10
# https://ipaidthat.io/ima/cy/cohort/12/?tk={key}&Cy_Color=%234785E6
def cohort(request):
main_metric = request.GET.get('main_metric')
trigger_metric = request.GET.get('trigger_metric')
granularity = request.GET.get('granularity', 'week')
nb_items = int(request.GET.get('nb_items', '12'))
name = request.GET.get('name', 'metric')
res = [[granularity.capitalize(), name.capitalize()] + [str(i) for i in range(1, nb_items + 1)]]
res.extend(data.cohorts(main_metric, trigger_metric, granularity=granularity, nb_items=nb_items))
_add_custom_cyfe_parameters(request.GET, res)
return _csv_response(res)
def compare_weeks(request):
metrics = []
sum = request.GET.get('sum', False)
group, name, filter_by, count = request.GET['metric'].split(',')
today = date.today()
monday = today - timedelta(today.weekday())
past_sunday = (monday - timedelta(1)).strftime("%Y%m%d")
past_monday = (monday - timedelta(weeks=1)).strftime("%Y%m%d")
monday = monday.strftime("%Y%m%d")
today = today.strftime("%Y%m%d")
metrics.extend([list(data.get_events(name, group, past_monday, past_sunday, filter_by_properties=filter_by, aggregate_by=None, count_by_property=count if len(count) else None).values())[0],
list(data.get_events(name, group, monday, today, filter_by_properties=filter_by, aggregate_by=None, count_by_property=count if len(count) else None).values())[0]
])
result = [["Day of week", "Past week", "Current week"]]
res = {}
for metric in metrics:
for datekey, val in metric.items():
dt = datetime.strptime(datekey, '%Y%m%d')
key = "%d_%s" % (dt.weekday(), dt.strftime('%A'))
if key not in res:
res[key] = []
res[key].append(val)
result.extend(sorted(list(map(lambda x: [x[0]] + x[1], res.items())), key=operator.itemgetter(0)))
if sum == 'True':
for i in range(len(metrics)):
sum = 0
for y in range(len(result)):
if len(result[y]) > i+1:
if type(result[y][i+1]) in [float, int]:
sum += result[y][i+1]
result[y][i+1] = sum
_add_custom_cyfe_parameters(request.GET, result)
return _csv_response(result)
def prevision(request):
metrics = request.GET.getlist('metric', [])
to_date_str = request.GET['date']
to_date = datetime.strptime(to_date_str, "%Y%m%d").date()
today = date.today()
week = timedelta(weeks=1)
# Monday to monday
start = today - timedelta(today.weekday())
end = to_date - timedelta(to_date.weekday())
result = [["Week"]]
res = {}
for metric in metrics:
group, name, filter_by, count, offset = metric.split(',')
result[0].append(name)
base, inc, growth = data.scan_metric(group, name, filter_by, count, int(offset))
edate = start
while edate <= end:
key = edate.strftime("%Y%m%d")
if key not in res:
res[key] = []
res[key].append(base)
# Compute current week growth
inc = int(inc + (growth * inc))
base = base + inc
edate = edate + week
result.extend(sorted(list(map(lambda x: [x[0]] + x[1], res.items())), key=operator.itemgetter(0)))
_add_custom_cyfe_parameters(request.GET, result)
return _csv_response(result)
# Example: /datatrack/gevents?start=20140901&end=20141010&agg_by=date&sort_by=-0&&metric=Acquisition,Invite sent,City:Paris,Nb invite&formula=Acquisition,Member aquired
# https://ipaidthat.io/datatrack/gevents?
# metric=gen_orgs,org_signup,is_license:False%3Bis_paid:True%3Bsource:Ads,,Conversions
# &formula=gen_orgs,org_signup,is_license:False%3Bsource:Ads,,Signups
# &metric=gen_orgs,org_signup,is_license:False%3Bsource:Ads,,Signups
# &metric=gen_orgs,org_signup,is_license:False%3Bis_paid:True%3Bsource:Ads,,Conversions
# &Cy_Type=line,column,column
def events_gen(request):
agg_by = request.GET.get('agg_by', None)
sort_by = request.GET.get('sort_by', '0')
start = request.GET.get('start')
end = request.GET.get('end')
sum = request.GET.get('sum', False)
last = request.GET.get('last', False) == 'True'
metrics = []
formulas = []
for metric in request.GET.getlist('metric', []):
metrics.extend(_get_metric(metric, start, end, agg_by, last=last))
for metric in request.GET.getlist('formula', []):
formulas.extend(_get_metric(metric, start, end, agg_by, last=last))
# Generete the final data
if 'reversed' in request.GET:
# if reversed data is requested, only valid for one metric
res = [list(map(operator.itemgetter(0), metrics[0][1].items())),
list(map(operator.itemgetter(1), metrics[0][1].items()))]
elif 'normal' in request.GET:
res = [
[m[0] for m in metrics],
[list(m[1].values())[0] for m in metrics],
]
else:
# build metric list
mnames = []
for i in range(len(metrics)):
if i < len(formulas):
mnames.append("%s / %s(%%)" % (metrics[i][0], formulas[i][0]))
else:
mnames.append(metrics[i][0])
res = [[agg_by if agg_by is not None else "Date"] + mnames]
res.extend(_pivot_metrics(metrics, formulas, sort_by))
if sum == 'True':
for i in range(len(mnames)):
sum = 0
for y in range(len(res)):
if len(res[y]) > i + 1:
if type(res[y][i + 1]) in [float, int]:
sum += res[y][i + 1]
res[y][i + 1] = sum
_add_custom_cyfe_parameters(request.GET, res)
return _csv_response(res)