def apply_term_extensions(item, revrec_schedule, term_extensions):
"""Adjusts the specified revrec schedule for term extensions.
:param item: InvoiceItem object.
:param revrec_schedule: Dictionary of debits and credits by day
:param term_extensions: Term Extension objects.
"""
for ext in term_extensions:
defrev = revrec_schedule[day_before(ext.grant_date)]['ending_defrev']
start = ext.grant_date
end = ext.service_end
daily_amort = defrev / days_elapsed(start, end)
for date in daterange(start, end):
defrev = defrev - daily_amort
template = dict(revrec_daily_template)
template['cr_rev'] = daily_amort
template['dr_defrev'] = daily_amort
template['ending_defrev'] = defrev
try:
revrec_schedule[date]['cr_rev'] = daily_amort
revrec_schedule[date]['ending_defrev'] = defrev
except KeyError:
revrec_schedule[date] = template
def apply_term_extensions(item, revrec_schedule, term_extensions):
"""Adjusts the specified revrec schedule for term extensions.
:param item: InvoiceItem object.
:param revrec_schedule: Dictionary of debits and credits by day
:param term_extensions: Term Extension objects.
"""
for ext in term_extensions:
defrev = revrec_schedule[day_before(ext.grant_date)]['ending_defrev']
start = ext.grant_date
end = ext.service_end
daily_amort = defrev / days_elapsed(start, end)
for date in daterange(start, end):
defrev = defrev - daily_amort
template = dict(revrec_daily_template)
template['cr_rev'] = daily_amort
template['dr_defrev'] = daily_amort
template['ending_defrev'] = defrev
try:
revrec_schedule[date]['cr_rev'] = daily_amort
revrec_schedule[date]['ending_defrev'] = defrev
except KeyError:
revrec_schedule[date] = template
def get_weather_data(apikey, locs, cols, start_date, end_date, offset):
""" Retrieves daily historical weather data for the specified locations
using the Dark Sky API. Output is saved as a CSV in the 'data' folder.
Args:
api_key (str): Dark Sky API key.
locs (str): Geocoded locations file name (with extension).
cols (str): File name contain custom column names.
start_date (datetime.datetime): Start date for historical data range.
end_date (datetime.datetime): End date for historical data range.
offset (int): Step size for iterator (number of days).
"""
locs_path = get_datafile(locs)
locs = pd.read_csv(locs_path)
# get columns list
columns = get_datafile(cols)
with open(columns) as f:
cols = [line.strip() for line in f]
# extract data for each location for date range b/w start and end date
tbl = []
for index, row in locs.iterrows():
for single_date in daterange(start_date, end_date, offset):
forecast = forecastio.load_forecast(apikey,
row['Lat'],
row['Lng'],
time=single_date,
units='si')
h = forecast.daily()
tz = forecast.json['timezone']
d = h.data
for p in d:
# get date info
utc = p.d['time']
dts = dt.datetime.utcfromtimestamp(utc)
isodate = dt.datetime.utcfromtimestamp(utc).isoformat()
date_info = [tz, isodate, dts.year, dts.month, dts.day]
# get location info
loc, lat, lng = row['Location'], row['Lat'], row['Lng']
elevation = row['Elevation']
loc_info = [loc, lat, lng, elevation]
# get weather attributes - need to handle possible KeyErrors
temp_high = p.d.get('temperatureHigh', None)
temp_low = p.d.get('temperatureLow', None)
humidity = p.d.get('humidity', None) * 100
pressure = p.d.get('pressure', None)
attr_info = [temp_high, temp_low, humidity, pressure]
tbl.append(loc_info + date_info + attr_info)
# convert output to data frame
df = pd.DataFrame(tbl)
df.columns = cols
filename = 'historical_data.csv'
save_data(df, filename, sep='|')
def get_prayer_record_range(self, date, max_date=date.today()):
'''Get the prayer records of all days after the specified date and upto the maximum date'''
# Loop through the date range and ensure that record for all the dates exist
for dt in daterange(date, max_date + timedelta(1)):
self.create_record(dt)
cursor = self.db.cursor()
cursor.execute("SELECT fajr, dhuhr, asr, maghrib, isha FROM record WHERE date >= ? AND date <= ? ", (date, max_date))
return cursor.fetchall()
def amortize_service_fee(item, payment_date):
"""
Creates a daily revenue recognition schedule for the specified invoice item
based on daily amortization of deferred revenue to revenue.
:param item: InvoiceItem object.
:param payment_date: Date of payment.
:return dict. Daily revrec schedule of debit and credit journal entries.
"""
# Daily revenue recognition schedule
revrec_schedule = {}
# The amortization period begins on the day of the payment and continues
# until the end of the invoice item's service term
revrec_start = max(payment_date, item.service_start)
revrec_end = item.service_end
# Fee amount
amount = item.total_amount
# Deferred revenue does not exist until payment is made
defrev = 0
daily_amort = 0
cumul_rev = 0
# Generating revenue recognition schedule. Iterate over service period by day.
for date in daterange(item.service_start, item.service_end):
# On payment date, set the deferred revenue balance and daily revenue amortization
if date == payment_date:
defrev = amount
daily_amort = amount / days_elapsed(revrec_start, revrec_end)
# From payment date and onwards, amortize deferred revenue to revenue
if date >= payment_date:
defrev = defrev - daily_amort
cumul_rev += daily_amort
values = {
'cr_rev': daily_amort,
'dr_defrev': daily_amort,
'ending_defrev': defrev,
'cumul_rev': cumul_rev,
}
revrec_schedule[date] = create_schedule(values)
return revrec_schedule
def amortize_service_fee(item, payment_date):
"""
Creates a daily revenue recognition schedule for the specified invoice item
based on daily amortization of deferred revenue to revenue.
:param item: InvoiceItem object.
:param payment_date: Date of payment.
:return dict. Daily revrec schedule of debit and credit journal entries.
"""
# Daily revenue recognition schedule
revrec_schedule = {}
# The amortization period begins on the day of the payment and continues
# until the end of the invoice item's service term
revrec_start = max(payment_date, item.service_start)
revrec_end = item.service_end
# Fee amount
amount = item.total_amount
# Deferred revenue does not exist until payment is made
defrev = 0
daily_amort = 0
cumul_rev = 0
# Generating revenue recognition schedule. Iterate over service period by day.
for date in daterange(item.service_start, item.service_end):
# On payment date, set the deferred revenue balance and daily revenue amortization
if date == payment_date:
defrev = amount
daily_amort = amount / days_elapsed(revrec_start, revrec_end)
# From payment date and onwards, amortize deferred revenue to revenue
if date >= payment_date:
defrev = defrev - daily_amort
cumul_rev += daily_amort
values = {
'cr_rev': daily_amort,
'dr_defrev': daily_amort,
'ending_defrev': defrev,
'cumul_rev': cumul_rev,
}
revrec_schedule[date] = create_schedule(values)
return revrec_schedule
def amortize_amount(revrec_schedule, amt, start_date, end_date):
"""
Modifies an existing revrec_schedule by amortizing the amount over the
specified period. Existing revenue and deferred revenue values will be
overwritten for the period.
:param revrec_schedule: Dictionary of debits and credits by day
:param amt: Amount of deferred revenue to be amortized.
"""
daily_amort = amt / days_elapsed(start_date, end_date)
defrev = amt
for date in daterange(start_date, end_date):
defrev = defrev - daily_amort
revrec_schedule[date]['cr_rev'] = daily_amort
revrec_schedule[date]['ending_defrev'] = defrev
revrec_schedule[date]['dr_defrev'] = daily_amort
def amortize_amount(revrec_schedule, amt, start_date, end_date):
"""
Modifies an existing revrec_schedule by amortizing the amount over the
specified period. Existing revenue and deferred revenue values will be
overwritten for the period.
:param revrec_schedule: Dictionary of debits and credits by day
:param amt: Amount of deferred revenue to be amortized.
"""
daily_amort = amt / days_elapsed(start_date, end_date)
defrev = amt
for date in daterange(start_date, end_date):
defrev = defrev - daily_amort
revrec_schedule[date]['cr_rev'] = daily_amort
revrec_schedule[date]['ending_defrev'] = defrev
revrec_schedule[date]['dr_defrev'] = daily_amort
def apply_grace_period(revrec_schedule, item, payment_date):
"""Adjusts the specified revrec schedule for late payment, which requires journal entries
related to grace period.
:param revrec_schedule: Dictionary of debits and credits by day to be adjusted due to
application of grace period.
:param item: InvoiceItem object
:param payment_date: Date of payment
:return list. Supporting notes on grace period calculations. Displayed in UI output.
"""
gp_notes = []
service_start = item.service_start
service_end = item.service_end
# Identify the details of the prev paid service period.
shift = {'Monthly': 30, 'Yearly': 365, 'Biyearly': 730}
prev_service_end = day_before(service_start)
prev_service_start = prev_service_end - timedelta(shift[item.billperiod] -
1)
prev_service_term = days_elapsed(prev_service_start, prev_service_end)
prev_amount = item.total_amount
prev_amort = prev_amount / prev_service_term
# Financial reporting days. Important for determining debit and credit entries.
current_reporting_day = datetime(
service_start.year, service_start.month,
last_day_of_month(service_start.year, service_start.month))
prev_reporting_day = day_before(
datetime(prev_service_end.year, prev_service_end.month, 1))
# Notes for display in the UI output.
gp_notes.append('JOURNAL ENTRIES FOR GRACE PERIOD')
gp_notes.append('---' * 60)
gp_notes.append(
'payment date: %s, current term: %s -> %s, prev term: %s -> %s' %
(pretty_date(payment_date), pretty_date(service_start),
pretty_date(service_end), pretty_date(prev_service_start),
pretty_date(prev_service_end)))
gp_notes.append(
'current reporting day: %s, prev reporting day: %s, days reserved for: %s -> %s'
% (pretty_date(current_reporting_day), pretty_date(prev_reporting_day),
prev_service_start, prev_reporting_day))
# For each date that payment is late...
running_total_dr_reserve = 0
for date in daterange(service_start, day_before(payment_date)):
# The previous service term is extended by the grace period used
revised_service_term = prev_service_term + days_elapsed(
service_start, date)
# Revenue amortization for the extended service term
revised_amort = prev_amount / revised_service_term
# Difference in the daily amortization for the previous service term
amort_difference = prev_amort - revised_amort
# The difference b/n revenue that should have been recognized vs. what was recognized in the period
# prior to the previous reporting day. This amount has already been reserved for, so the journal
# entry is a debit against the reserve for grace periods.
revised_dr_reserve_graceperiod = days_elapsed(
prev_service_start, prev_reporting_day) * amort_difference
# We have been debiting the reserve for each day late, this day's debit amount is equal to the
# incremental debit against the reserve. The other side of the entry is credit contra-revenue.
dr_reserve_graceperiod = revised_dr_reserve_graceperiod - running_total_dr_reserve
cr_contra_rev = dr_reserve_graceperiod
revrec_schedule[date][
'dr_reserve_graceperiod'] = dr_reserve_graceperiod
revrec_schedule[date]['cr_contra_rev'] = cr_contra_rev
gp_notes.append(
'%s, PrevTerm: %s->%s, PrevAmort: $%s->$%s, Value: %s, DaysReservedFor: %s, \
PrevTotalReserve %s, TotalReserve: %s, DR reserve: %s'
% (pretty_date(date), prev_service_term, revised_service_term,
round(prev_amort, 3), round(
revised_amort, 3), revised_service_term * revised_amort,
(prev_reporting_day - prev_service_start).days + 1,
round(running_total_dr_reserve,
3), round(revised_dr_reserve_graceperiod,
3), round(dr_reserve_graceperiod, 3)))
running_total_dr_reserve += dr_reserve_graceperiod
gp_notes.append('---' * 60)
return gp_notes
def apply_refunds(revrec_schedule, invoice_amount, item, refunds):
"""Adjusts the specified revrec schedule for refunds.
:param revrec_schedule: Dictionary of debits and credits by day
:param invoice_amount: Total amount of the invoice
:param item: The Item object
:param refunds: Refund objects
"""
# Adjustment amortization due to refunds
for ref in refunds:
proportion = item.total_amount / invoice_amount
refund_applied = ref.refund_amount * proportion
last_day_of_schedule = max(revrec_schedule.keys())
# Deferred revenue and total revenue recognized as of beginning of refund date
stats_as_of_refund_date = {
'ending_defrev':
revrec_schedule[day_before(ref.refund_date)]['ending_defrev'],
'cr_rev':
sum([
row['cr_rev'] for date, row in revrec_schedule.iteritems()
if date < ref.refund_date
])
}
# positive_item_amount: is the invoice item a charge vs. discount/pro-rated credit?
# service_cancelled: is refund related to service being cancelled?
flags = {
'positive_item_amount': item.total_amount >= 0,
'service_cancelled': ref.cancel_flag
}
# Calculate debits and credits associated with refund event
results = refund_calc(flags=flags,
revrec_start_date=min(revrec_schedule.keys()),
refund_date=ref.refund_date,
refund_amount=refund_applied,
stats_as_of_refund_date=stats_as_of_refund_date)
# Remaining deferred revenue
remaining_defrev = stats_as_of_refund_date['ending_defrev'] - results[
'dr_defrev']
# Copy over results of refund calculation to schedule; debits/credits are effective the refund day
for (key, value) in results.iteritems():
revrec_schedule[ref.refund_date][key] = value
# If service term is cancelled, any remaining deferred revenue is recognized on the day of the refund
if ref.cancel_flag:
revrec_schedule[ref.refund_date]['cr_rev'] = remaining_defrev
revrec_schedule[ref.refund_date]['cumul_rev'] = revrec_schedule[
ref.refund_date - timedelta(1)]['cumul_rev'] + remaining_defrev
revrec_schedule[ref.refund_date]['ending_defrev'] = 0
# Now that DR is zeroed out, there is no more amortization
# print 'Clearing schedule from %s to %s' % (ref.refund_date + timedelta(1), last_day_of_schedule)
for date in daterange(ref.refund_date + timedelta(1),
last_day_of_schedule):
revrec_schedule[date]['cr_rev'] = 0
revrec_schedule[date]['ending_defrev'] = 0
revrec_schedule[date]['cumul_rev'] = 0
revrec_schedule[date]['dr_defrev'] = 0
# If service term not cancelled, remaining deferred revenue is amortized through end of service term
else:
amortize_amount(revrec_schedule=revrec_schedule,
amt=remaining_defrev,
start_date=ref.refund_date,
end_date=last_day_of_schedule)
"gis") + 1 # setup unique IDs
df_dim_vals = dfh.build_dimension_values_df(
pid_meta, df_dims, next_dim_val_id)
dim_val_result = db.insert_dataframe_rows(df_dim_vals,
"DimensionValues", "gis")
h.delete_var_and_release_mem([df_dims, df_dim_vals])
###########################################################
# APPEND - runs whether inserting or updating a table
merged_prod_dict = jh.get_merged_tables_from_json(
products_to_merge_json) # find info about any merged tables
products_to_update = [] # create list of products to be updated
if start_date and end_date:
# update products for specified date range - this section only executes if --start and --end args are present
for dt in h.daterange(start_date, end_date):
changed_cubes = wds.get_changed_cube_list(
dt.strftime("%Y-%m-%d")) # find out which cubes have changed
prod_list = db.get_matching_product_list(
changed_cubes) # find out which of these cubes exist in the db
logger.info(
str(len(prod_list)) + " table(s) found for " +
dt.strftime("%Y-%m-%d") + ": " + str(prod_list))
products_to_update.extend(prod_list)
# if any product in the changed cube list is part of a merged product, remove the prodid from the list to be
# processed and notify the user that they will have to update that product separately
check_pids = products_to_update.copy()
for check_pid in check_pids:
if jh.is_master_in_merged_product(check_pid, merged_prod_dict):
logger.warning(
def apply_refunds(revrec_schedule, invoice_amount, item, refunds):
"""Adjusts the specified revrec schedule for refunds.
:param revrec_schedule: Dictionary of debits and credits by day
:param invoice_amount: Total amount of the invoice
:param item: The Item object
:param refunds: Refund objects
"""
# Adjustment amortization due to refunds
for ref in refunds:
proportion = item.total_amount/invoice_amount
refund_applied = ref.refund_amount * proportion
last_day_of_schedule = max(revrec_schedule.keys())
# Deferred revenue and total revenue recognized as of beginning of refund date
stats_as_of_refund_date = {
'ending_defrev': revrec_schedule[day_before(ref.refund_date)]['ending_defrev'],
'cr_rev': sum([row['cr_rev'] for date, row
in revrec_schedule.iteritems() if date < ref.refund_date])
}
# positive_item_amount: is the invoice item a charge vs. discount/pro-rated credit?
# service_cancelled: is refund related to service being cancelled?
flags = {
'positive_item_amount': item.total_amount >= 0,
'service_cancelled': ref.cancel_flag
}
# Calculate debits and credits associated with refund event
results = refund_calc(flags=flags,
revrec_start_date=min(revrec_schedule.keys()),
refund_date=ref.refund_date,
refund_amount=refund_applied,
stats_as_of_refund_date=stats_as_of_refund_date)
# Remaining deferred revenue
remaining_defrev = stats_as_of_refund_date['ending_defrev'] - results['dr_defrev']
# Copy over results of refund calculation to schedule; debits/credits are effective the refund day
for (key, value) in results.iteritems():
revrec_schedule[ref.refund_date][key] = value
# If service term is cancelled, any remaining deferred revenue is recognized on the day of the refund
if ref.cancel_flag:
revrec_schedule[ref.refund_date]['cr_rev'] = remaining_defrev
revrec_schedule[ref.refund_date]['cumul_rev'] = revrec_schedule[ref.refund_date -
timedelta(1)]['cumul_rev'] + remaining_defrev
revrec_schedule[ref.refund_date]['ending_defrev'] = 0
# Now that DR is zeroed out, there is no more amortization
# print 'Clearing schedule from %s to %s' % (ref.refund_date + timedelta(1), last_day_of_schedule)
for date in daterange(ref.refund_date + timedelta(1), last_day_of_schedule):
revrec_schedule[date]['cr_rev'] = 0
revrec_schedule[date]['ending_defrev'] = 0
revrec_schedule[date]['cumul_rev'] = 0
revrec_schedule[date]['dr_defrev'] = 0
# If service term not cancelled, remaining deferred revenue is amortized through end of service term
else:
amortize_amount(revrec_schedule=revrec_schedule,
amt=remaining_defrev,
start_date=ref.refund_date,
end_date=last_day_of_schedule)
def number_of_articles(project, startdate, enddate):
res = {}
for date in daterange(date_from_iso(startdate), date_from_iso(enddate)):
res[date_to_iso(date)] = 100
return res
def calculate_user_values(self, username):
memcache_data_key = '!data!{}'.format(username)
values = json.loads(memcache.get(memcache_data_key) or '{}')
if values:
return values
try:
github_user = User.get(username)
except pyresto.Error:
self.response.set_status(404) # not 100% sure but good enough
self.render('errors/404')
return
except Exception as err:
self.response.set_status(500)
logging.error(err)
return
languages = User.sort_languages(github_user.language_stats)
fork_count = sum((1 for repo in github_user.repos if repo.fork))
today = datetime.datetime.today()
recent_than = today - datetime.timedelta(days=RECENT_DAYS)
own_commits = github_user.get_latest_commits(recent_than)
commits_by_repo = reduce(self.reduce_commits_by_repo,
own_commits, dict())
if commits_by_repo:
last_project = max(commits_by_repo, key=commits_by_repo.get)
else:
last_project = ''
logging.info(commits_by_repo)
if last_project:
last_project_url = [repo.html_url for repo in github_user.repos
if repo.name == last_project][0]
else:
last_project_url = None
commits_by_date = reduce(self.reduce_commits_by_date,
own_commits, dict())
range = daterange(recent_than, today)
for d in range:
key = unicode(d.date())
if key not in commits_by_date:
commits_by_date[key] = 0
commit_data = [commits_by_date[d] for d in sorted(commits_by_date)]
max_commits = max(commit_data)
logging.debug('Commit data %s', str(commit_data))
commit_sparkline = 'data:image/png;base64,' +\
base64.b64encode(
sparklines.impulse(commit_data,
below_color='SlateGray',
width=3,
dmin=0,
dmax=max(commit_data)
),
)
values = {'user': github_user.__dict__,
'own_repos': github_user.public_repos - fork_count,
'fork_repos': fork_count,
'languages': languages,
'project_followers': github_user.project_followers -\
github_user.public_repos,
'commit_sparkline': commit_sparkline,
'max_commits': max_commits,
'last_project': last_project,
'last_project_url': last_project_url,
'days': RECENT_DAYS
}
if not memcache.set(memcache_data_key, json.dumps(values),
MEMCACHE_EXPIRATION):
logging.error('Memcache set failed for user data %s', username)
return values
def apply_grace_period(revrec_schedule, item, payment_date):
"""Adjusts the specified revrec schedule for late payment, which requires journal entries
related to grace period.
:param revrec_schedule: Dictionary of debits and credits by day to be adjusted due to
application of grace period.
:param item: InvoiceItem object
:param payment_date: Date of payment
:return list. Supporting notes on grace period calculations. Displayed in UI output.
"""
gp_notes = []
service_start = item.service_start
service_end = item.service_end
# Identify the details of the prev paid service period.
shift = {'Monthly': 30, 'Yearly': 365, 'Biyearly': 730}
prev_service_end = day_before(service_start)
prev_service_start = prev_service_end - timedelta(shift[item.billperiod] - 1)
prev_service_term = days_elapsed(prev_service_start, prev_service_end)
prev_amount = item.total_amount
prev_amort = prev_amount / prev_service_term
# Financial reporting days. Important for determining debit and credit entries.
current_reporting_day = datetime(service_start.year, service_start.month,
last_day_of_month(service_start.year, service_start.month))
prev_reporting_day = day_before(datetime(prev_service_end.year, prev_service_end.month, 1))
# Notes for display in the UI output.
gp_notes.append('JOURNAL ENTRIES FOR GRACE PERIOD')
gp_notes.append('---'*60)
gp_notes.append('payment date: %s, current term: %s -> %s, prev term: %s -> %s' % (
pretty_date(payment_date),
pretty_date(service_start),
pretty_date(service_end),
pretty_date(prev_service_start),
pretty_date(prev_service_end)))
gp_notes.append('current reporting day: %s, prev reporting day: %s, days reserved for: %s -> %s' % (
pretty_date(current_reporting_day),
pretty_date(prev_reporting_day),
prev_service_start,
prev_reporting_day))
# For each date that payment is late...
running_total_dr_reserve = 0
for date in daterange(service_start, day_before(payment_date)):
# The previous service term is extended by the grace period used
revised_service_term = prev_service_term + days_elapsed(service_start, date)
# Revenue amortization for the extended service term
revised_amort = prev_amount / revised_service_term
# Difference in the daily amortization for the previous service term
amort_difference = prev_amort - revised_amort
# The difference b/n revenue that should have been recognized vs. what was recognized in the period
# prior to the previous reporting day. This amount has already been reserved for, so the journal
# entry is a debit against the reserve for grace periods.
revised_dr_reserve_graceperiod = days_elapsed(prev_service_start, prev_reporting_day) * amort_difference
# We have been debiting the reserve for each day late, this day's debit amount is equal to the
# incremental debit against the reserve. The other side of the entry is credit contra-revenue.
dr_reserve_graceperiod = revised_dr_reserve_graceperiod - running_total_dr_reserve
cr_contra_rev = dr_reserve_graceperiod
revrec_schedule[date]['dr_reserve_graceperiod'] = dr_reserve_graceperiod
revrec_schedule[date]['cr_contra_rev'] = cr_contra_rev
gp_notes.append('%s, PrevTerm: %s->%s, PrevAmort: $%s->$%s, Value: %s, DaysReservedFor: %s, \
PrevTotalReserve %s, TotalReserve: %s, DR reserve: %s' % (
pretty_date(date),
prev_service_term,
revised_service_term,
round(prev_amort, 3),
round(revised_amort, 3),
revised_service_term * revised_amort,
(prev_reporting_day - prev_service_start).days + 1,
round(running_total_dr_reserve, 3),
round(revised_dr_reserve_graceperiod, 3),
round(dr_reserve_graceperiod,3)))
running_total_dr_reserve += dr_reserve_graceperiod
gp_notes.append('---'*60)
return gp_notes
def calculate_user_values(self, username):
memcache_data_key = '!data!{}'.format(username)
values = json.loads(memcache.get(memcache_data_key) or '{}')
if values:
return values
try:
github_user = User.get(username)
except pyresto.Error:
self.response.set_status(404) # not 100% sure but good enough
self.render('errors/404')
return
except Exception as err:
self.response.set_status(500)
logging.error(err)
return
languages = User.sort_languages(github_user.language_stats)
fork_count = sum(1 for repo in github_user.repos if repo.fork)
today = datetime.datetime.today()
recent_than = today - datetime.timedelta(days=RECENT_DAYS)
own_commits = github_user.get_latest_commits(recent_than)
commits_by_repo = reduce(self.reduce_commits_by_repo,
own_commits, dict())
if commits_by_repo:
last_project = max(commits_by_repo, key=commits_by_repo.get)
else:
last_project = ''
logging.info(commits_by_repo)
if last_project:
last_project_url = [repo.html_url for repo in github_user.repos
if repo.name == last_project][0]
else:
last_project_url = None
commits_by_date = reduce(self.reduce_commits_by_date,
own_commits, dict())
range = daterange(recent_than, today)
for d in range:
key = unicode(d.date())
if key not in commits_by_date:
commits_by_date[key] = 0
commit_data = [commits_by_date[d] for d in sorted(commits_by_date)]
max_commits = max(commit_data)
logging.debug('Commit data %s', str(commit_data))
commit_sparkline = data_uri(sparklines.impulse(commit_data,
below_color='SlateGray',
width=3,
dmin=0,
dmax=max(commit_data)))
try: # try to embed the scaled-down user avatar
avatar = Image(urllib2.urlopen(github_user.avatar_url).read())
avatar.resize(24, 24)
github_user.avatar_url = data_uri(avatar.execute_transforms())
except (AttributeError, ValueError, urllib2.URLError):
pass
user_info = dict((k, v) for k, v in github_user.__dict__.iteritems() if k[0] != '_')
values = {'user': user_info,
'own_repos': len(github_user.repos) - fork_count,
'fork_repos': fork_count,
'languages': languages,
'project_followers': github_user.project_followers -\
len(github_user.self_watched),
'commit_sparkline': commit_sparkline,
'max_commits': max_commits,
'last_project': last_project,
'last_project_url': last_project_url,
'days': RECENT_DAYS
}
if not memcache.set(memcache_data_key, json.dumps(values),
MEMCACHE_EXPIRATION):
logging.error('Memcache set failed for user data %s', username)
return values
def calculate_user_values(self, username):
memcache_data_key = '!data!{}'.format(username)
values = json.loads(memcache.get(memcache_data_key) or '{}')
if values:
return values
try:
github_user = User.get(username)
except pyresto.Error:
self.response.set_status(404) # not 100% sure but good enough
self.render('errors/404')
return
except Exception as err:
self.response.set_status(500)
logging.error(err)
return
languages = User.sort_languages(github_user.language_stats)
fork_count = sum((1 for repo in github_user.repos if repo.fork))
today = datetime.datetime.today()
recent_than = today - datetime.timedelta(days=RECENT_DAYS)
own_commits = github_user.get_latest_commits(recent_than)
commits_by_repo = reduce(self.reduce_commits_by_repo, own_commits,
dict())
if commits_by_repo:
last_project = max(commits_by_repo, key=commits_by_repo.get)
else:
last_project = ''
logging.info(commits_by_repo)
if last_project:
last_project_url = [
repo.html_url for repo in github_user.repos
if repo.name == last_project
][0]
else:
last_project_url = None
commits_by_date = reduce(self.reduce_commits_by_date, own_commits,
dict())
range = daterange(recent_than, today)
for d in range:
key = unicode(d.date())
if key not in commits_by_date:
commits_by_date[key] = 0
commit_data = [commits_by_date[d] for d in sorted(commits_by_date)]
max_commits = max(commit_data)
logging.debug('Commit data %s', str(commit_data))
commit_sparkline = 'data:image/png;base64,' +\
base64.b64encode(
sparklines.impulse(commit_data,
below_color='SlateGray',
width=3,
dmin=0,
dmax=max(commit_data)
),
)
values = {'user': github_user.__dict__,
'own_repos': github_user.public_repos - fork_count,
'fork_repos': fork_count,
'languages': languages,
'project_followers': github_user.project_followers -\
github_user.public_repos,
'commit_sparkline': commit_sparkline,
'max_commits': max_commits,
'last_project': last_project,
'last_project_url': last_project_url,
'days': RECENT_DAYS
}
if not memcache.set(memcache_data_key, json.dumps(values),
MEMCACHE_EXPIRATION):
logging.error('Memcache set failed for user data %s', username)
return values
