def calculate(list):
# sort list by date integer in order to get transactions in right order
list.sort(key=lambda x: x.dateint, reverse=True)
# transaction calcuations
mrr = sum(
x.amount for x in list if get_datetime(x.dateint) >= one_month_ago
and x.type in ("charge.succeeded", "charge.refunded") and len([
y
for y in list if y.type in ("charge.succeeded", "charge.refunded")
and y.customer_id == x.customer_id
]) > 1)
prev_mrr = sum(
x.amount for x in list if get_datetime(x.dateint) < one_month_ago
and x.type in ("charge.succeeded", "charge.refunded") and len([
y
for y in list if y.type in ("charge.succeeded", "charge.refunded")
and y.customer_id == x.customer_id
]) > 1)
canceled = len(
set([
x.customer_id for x in list
if x.type == "customer.subscription.deleted"
and get_datetime(x.dateint) >= one_month_ago
]))
upgrades = len([
x for x in list
if x.type == "Upgrade" and get_datetime(x.dateint) >= one_month_ago
])
prev_upgrades = len([
x for x in list
if x.type == "Upgrade" and get_datetime(x.dateint) < one_month_ago
])
downgrades = len([
x for x in list
if x.type == "Downgrade" and get_datetime(x.dateint) >= one_month_ago
])
prev_downgrades = len([
x for x in list
if x.type == "Downgrade" and get_datetime(x.dateint) < one_month_ago
])
prev_canceled = len(
set([
x.customer_id for x in list
if x.type == "customer.subscription.deleted"
and get_datetime(x.dateint) < one_month_ago
]))
refunds = sum(x.amount for x in list if x.type == "charge.refunded"
and get_datetime(x.dateint) >= one_month_ago)
prev_refunds = sum(x.amount for x in list if x.type == "charge.refunded"
and get_datetime(x.dateint) < one_month_ago)
net_revenue = sum(
x.amount for x in list
if get_datetime(x.dateint) >= one_month_ago and x.type in (
"charge.succeeded", "charge.refunded"))
prev_net_revenue = sum(
x.amount for x in list
if get_datetime(x.dateint) < one_month_ago and x.type in (
"charge.succeeded", "charge.refunded"))
annual = mrr * 12
prev_annual = prev_mrr * 12
customers = len(
set([
x.customer_id for x in list
if get_datetime(x.dateint) >= one_month_ago
]))
prev_customers = len(
set([
x.customer_id for x in list
if get_datetime(x.dateint) < one_month_ago
]))
new_customers = len(
set([
x.customer_id for x in list
if x.type == "customer.subscription.created"
and get_datetime(x.dateint) >= one_month_ago
]))
prev_new_customers = len(
set([
x.customer_id for x in list
if x.type == "customer.subscription.created"
and get_datetime(x.dateint) < one_month_ago
]))
arpu = ((float(mrr) / customers) if customers != 0 else 0)
prev_arpu = ((prev_mrr / prev_customers) if prev_customers != 0 else 0)
#save the events list in session, so that we don't have to do an api call every time.
eventsList = []
for x in list:
y = json.dumps(x.__dict__)
eventsList.append(y)
# cut the list down for the live transactions on main dashboard
del list[19:]
# calculate churn and ltv
churn = (((float(canceled) / prev_customers) *
100) if prev_customers != 0 else 0)
ltv = ((arpu / churn) * 100 if churn != 0 else 0)
# the metrics that we are going to be sending to the dashboards to occupy metric tiles
current = (mrr, refunds, net_revenue, annual, customers, new_customers,
arpu, canceled, upgrades, downgrades)
prev = (prev_mrr, prev_refunds, prev_net_revenue, prev_annual,
prev_customers, prev_new_customers, prev_arpu, prev_canceled,
prev_upgrades, prev_downgrades)
percentages = [
convert_to_percent(
(x - y) / float(y)) if y != 0 else convert_to_percent(0)
for x, y in zip(current, prev)
]
# add results to the session to avoid multiple calls to the API
session['events'] = eventsList
session['current'] = current
session['percentages'] = percentages
session['churn'] = churn
session['ltv'] = ltv
#print "just put events into the session"
#print session['events']
return list, current, percentages, churn, ltv
def chartify(events, metric):
d = OrderedDict()
dates = []
amounts = []
data = sorted(events, key=lambda x: x.dateint)
#data = [x for x in data if get_datetime(x.dateint) >= one_month_ago and x.type in ("charge.succeeded",
# "charge.refunded")]
if 'net' in metric:
data = [x for x in data if get_datetime(x.dateint) >= one_month_ago and x.type in ("charge.succeeded", "charge.refunded")]
elif 'monthly' in metric:
data = [x for x in data if get_datetime(x.dateint) >= one_month_ago and x.type in ("charge.succeeded","charge.refunded") and len([y for y in data if y.type in ("charge.succeeded","charge.refunded") and y.customer_id == x.customer_id]) > 1]
elif 'annual' in metric:
print
elif 'average' in metric:
print
elif 'total' in metric:
data = len(set([x.customer_id for x in list if get_datetime(x.dateint) >= one_month_ago]))
elif 'refunds' in metric:
print
elif 'churn' in metric:
print
elif 'lifetime' in metric:
print
elif 'new' in metric:
data = [x for x in data]
elif 'canceled' in metric:
print
elif 'upgrades' in metric:
print
elif 'downgrades' in metric:
print
if len(data) == 0:
dates.append(yesterday.strftime("%B %d"))
amounts.append(0)
dates.append(now.strftime("%B %d"))
amounts.append(0)
elif len(data) == 1:
dates.append((get_datetime(data[0].dateint) - datetime.timedelta(days=7)).strftime("%B %d"))
amounts.append(0)
dates.append(get_short_date_string(data[0].dateint))
amounts.append(data[0].amount)
if get_short_date_string(data[0].dateint) != now.strftime("%B %d"):
dates.append(now.strftime("%B %d"))
amounts.append(0)
else:
for item in data:
key = get_short_date_string(item.dateint)
if key not in d:
d[key] = []
d[key].append(item.amount)
for k, v in d.items():
dates.append(k)
amounts.append(sum(v))
#session['dates'] = dates
#session['amounts'] = amounts
return dates, amounts
def chartify(events, metric):
d = OrderedDict()
dates = []
amounts = []
data = sorted(events, key=lambda x: x.dateint)
#data = [x for x in data if get_datetime(x.dateint) >= one_month_ago and x.type in ("charge.succeeded",
# "charge.refunded")]
if 'net' in metric:
data = [
x for x in data
if get_datetime(x.dateint) >= one_month_ago and x.type in (
"charge.succeeded", "charge.refunded")
]
elif 'monthly' in metric:
data = [
x for x in data
if get_datetime(x.dateint) >= one_month_ago and x.type in (
"charge.succeeded", "charge.refunded") and len([
y for y in data if y.type in
("charge.succeeded",
"charge.refunded") and y.customer_id == x.customer_id
]) > 1
]
elif 'annual' in metric:
print
elif 'average' in metric:
print
elif 'total' in metric:
data = len(
set([
x.customer_id for x in list
if get_datetime(x.dateint) >= one_month_ago
]))
elif 'refunds' in metric:
print
elif 'churn' in metric:
print
elif 'lifetime' in metric:
print
elif 'new' in metric:
data = [x for x in data]
elif 'canceled' in metric:
print
elif 'upgrades' in metric:
print
elif 'downgrades' in metric:
print
if len(data) == 0:
dates.append(yesterday.strftime("%B %d"))
amounts.append(0)
dates.append(now.strftime("%B %d"))
amounts.append(0)
elif len(data) == 1:
dates.append((get_datetime(data[0].dateint) -
datetime.timedelta(days=7)).strftime("%B %d"))
amounts.append(0)
dates.append(get_short_date_string(data[0].dateint))
amounts.append(data[0].amount)
if get_short_date_string(data[0].dateint) != now.strftime("%B %d"):
dates.append(now.strftime("%B %d"))
amounts.append(0)
else:
for item in data:
key = get_short_date_string(item.dateint)
if key not in d:
d[key] = []
d[key].append(item.amount)
for k, v in d.items():
dates.append(k)
amounts.append(sum(v))
#session['dates'] = dates
#session['amounts'] = amounts
return dates, amounts
def calculate(list):
# sort list by date integer in order to get transactions in right order
list.sort(key=lambda x: x.dateint, reverse=True)
# transaction calcuations
mrr = sum(x.amount for x in list if get_datetime(x.dateint) >= one_month_ago and x.type in
("charge.succeeded","charge.refunded") and len([y for y in list if y.type in
("charge.succeeded","charge.refunded") and y.customer_id == x.customer_id]) > 1)
prev_mrr = sum(x.amount for x in list if get_datetime(x.dateint) < one_month_ago and x.type in
("charge.succeeded","charge.refunded") and len([y for y in list if y.type in
("charge.succeeded","charge.refunded") and y.customer_id == x.customer_id]) > 1)
canceled = len(set([x.customer_id for x in list if x.type == "customer.subscription.deleted"
and get_datetime(x.dateint) >= one_month_ago]))
upgrades = len([x for x in list if x.type == "Upgrade" and get_datetime(x.dateint) >= one_month_ago])
prev_upgrades = len([x for x in list if x.type == "Upgrade" and get_datetime(x.dateint) < one_month_ago])
downgrades = len([x for x in list if x.type == "Downgrade" and get_datetime(x.dateint) >= one_month_ago])
prev_downgrades = len([x for x in list if x.type == "Downgrade" and get_datetime(x.dateint) < one_month_ago])
prev_canceled = len(set([x.customer_id for x in list if x.type == "customer.subscription.deleted"
and get_datetime(x.dateint) < one_month_ago]))
refunds = sum(x.amount for x in list if x.type == "charge.refunded" and get_datetime(x.dateint) >= one_month_ago)
prev_refunds = sum(x.amount for x in list if x.type == "charge.refunded" and get_datetime(x.dateint) < one_month_ago)
net_revenue = sum(x.amount for x in list if get_datetime(x.dateint) >= one_month_ago and x.type in
("charge.succeeded","charge.refunded"))
prev_net_revenue = sum(x.amount for x in list if get_datetime(x.dateint) < one_month_ago and x.type in
("charge.succeeded","charge.refunded"))
annual = mrr * 12
prev_annual = prev_mrr * 12
customers = len(set([x.customer_id for x in list if get_datetime(x.dateint) >= one_month_ago]))
prev_customers = len(set([x.customer_id for x in list if get_datetime(x.dateint) < one_month_ago]))
new_customers = len(set([x.customer_id for x in list if x.type == "customer.subscription.created"
and get_datetime(x.dateint) >= one_month_ago]))
prev_new_customers = len(set([x.customer_id for x in list if x.type == "customer.subscription.created"
and get_datetime(x.dateint) < one_month_ago]))
arpu = ((float(mrr) / customers) if customers != 0 else 0)
prev_arpu = ((prev_mrr / prev_customers) if prev_customers != 0 else 0)
#save the events list in session, so that we don't have to do an api call every time.
eventsList = []
for x in list:
y = json.dumps(x.__dict__)
eventsList.append(y)
# cut the list down for the live transactions on main dashboard
del list[19:]
# calculate churn and ltv
churn = (((float(canceled) / prev_customers) * 100) if prev_customers != 0 else 0)
ltv = ((arpu / churn) * 100 if churn != 0 else 0)
# the metrics that we are going to be sending to the dashboards to occupy metric tiles
current = (mrr, refunds, net_revenue, annual, customers, new_customers, arpu, canceled, upgrades, downgrades)
prev = (prev_mrr, prev_refunds, prev_net_revenue, prev_annual, prev_customers, prev_new_customers, prev_arpu,
prev_canceled, prev_upgrades, prev_downgrades)
percentages = [convert_to_percent((x - y) / float(y)) if y != 0 else convert_to_percent(0) for x, y in zip(current,prev)]
# add results to the session to avoid multiple calls to the API
session['events'] = eventsList
session['current'] = current
session['percentages'] = percentages
session['churn'] = churn
session['ltv'] = ltv
#print "just put events into the session"
#print session['events']
return list, current, percentages, churn, ltv
