Uncommenting needed code
[ckanext-ga-report.git] / ckanext / ga_report / download_analytics.py
blob:a/ckanext/ga_report/download_analytics.py -> blob:b/ckanext/ga_report/download_analytics.py
import os import os
import logging import logging
import datetime import datetime
  import collections
from pylons import config from pylons import config
  from ga_model import _normalize_url
import ga_model import ga_model
   
#from ga_client import GA #from ga_client import GA
   
log = logging.getLogger('ckanext.ga-report') log = logging.getLogger('ckanext.ga-report')
   
FORMAT_MONTH = '%Y-%m' FORMAT_MONTH = '%Y-%m'
  MIN_VIEWS = 50
  MIN_VISITS = 20
   
class DownloadAnalytics(object): class DownloadAnalytics(object):
'''Downloads and stores analytics info''' '''Downloads and stores analytics info'''
   
def __init__(self, service=None, profile_id=None): def __init__(self, service=None, profile_id=None, delete_first=False,
  skip_url_stats=False):
self.period = config['ga-report.period'] self.period = config['ga-report.period']
self.service = service self.service = service
self.profile_id = profile_id self.profile_id = profile_id
  self.delete_first = delete_first
  self.skip_url_stats = skip_url_stats
def all_(self):  
self.since_date(datetime.datetime(2010, 1, 1)) def specific_month(self, date):
  import calendar
   
  first_of_this_month = datetime.datetime(date.year, date.month, 1)
  _, last_day_of_month = calendar.monthrange(int(date.year), int(date.month))
  last_of_this_month = datetime.datetime(date.year, date.month, last_day_of_month)
  periods = ((date.strftime(FORMAT_MONTH),
  last_day_of_month,
  first_of_this_month, last_of_this_month),)
  self.download_and_store(periods)
   
   
def latest(self): def latest(self):
if self.period == 'monthly': if self.period == 'monthly':
# from first of this month to today # from first of this month to today
now = datetime.datetime.now() now = datetime.datetime.now()
first_of_this_month = datetime.datetime(now.year, now.month, 1) first_of_this_month = datetime.datetime(now.year, now.month, 1)
periods = ((now.strftime(FORMAT_MONTH), periods = ((now.strftime(FORMAT_MONTH),
now.day, now.day,
first_of_this_month, now),) first_of_this_month, now),)
else: else:
raise NotImplementedError raise NotImplementedError
self.download_and_store(periods) self.download_and_store(periods)
   
   
def since_date(self, since_date): def for_date(self, for_date):
assert isinstance(since_date, datetime.datetime) assert isinstance(since_date, datetime.datetime)
periods = [] # (period_name, period_complete_day, start_date, end_date) periods = [] # (period_name, period_complete_day, start_date, end_date)
if self.period == 'monthly': if self.period == 'monthly':
first_of_the_months_until_now = [] first_of_the_months_until_now = []
year = since_date.year year = for_date.year
month = since_date.month month = for_date.month
now = datetime.datetime.now() now = datetime.datetime.now()
first_of_this_month = datetime.datetime(now.year, now.month, 1) first_of_this_month = datetime.datetime(now.year, now.month, 1)
while True: while True:
first_of_the_month = datetime.datetime(year, month, 1) first_of_the_month = datetime.datetime(year, month, 1)
if first_of_the_month == first_of_this_month: if first_of_the_month == first_of_this_month:
periods.append((now.strftime(FORMAT_MONTH), periods.append((now.strftime(FORMAT_MONTH),
now.day, now.day,
first_of_this_month, now)) first_of_this_month, now))
break break
elif first_of_the_month < first_of_this_month: elif first_of_the_month < first_of_this_month:
in_the_next_month = first_of_the_month + datetime.timedelta(40) in_the_next_month = first_of_the_month + datetime.timedelta(40)
last_of_the_month = datetime.datetime(in_the_next_month.year, last_of_the_month = datetime.datetime(in_the_next_month.year,
in_the_next_month.month, 1)\ in_the_next_month.month, 1)\
- datetime.timedelta(1) - datetime.timedelta(1)
periods.append((now.strftime(FORMAT_MONTH), 0, periods.append((now.strftime(FORMAT_MONTH), 0,
first_of_the_month, last_of_the_month)) first_of_the_month, last_of_the_month))
else: else:
# first_of_the_month has got to the future somehow # first_of_the_month has got to the future somehow
break break
month += 1 month += 1
if month > 12: if month > 12:
year += 1 year += 1
month = 1 month = 1
else: else:
raise NotImplementedError raise NotImplementedError
self.download_and_store(periods) self.download_and_store(periods)
   
@staticmethod @staticmethod
def get_full_period_name(period_name, period_complete_day): def get_full_period_name(period_name, period_complete_day):
if period_complete_day: if period_complete_day:
return period_name + ' (up to %ith)' % period_complete_day return period_name + ' (up to %ith)' % period_complete_day
else: else:
return period_name return period_name
   
   
def download_and_store(self, periods): def download_and_store(self, periods):
for period_name, period_complete_day, start_date, end_date in periods: for period_name, period_complete_day, start_date, end_date in periods:
log.info('Downloading Analytics for period "%s" (%s - %s)', log.info('Period "%s" (%s - %s)',
self.get_full_period_name(period_name, period_complete_day), self.get_full_period_name(period_name, period_complete_day),
start_date.strftime('%Y %m %d'), start_date.strftime('%Y-%m-%d'),
end_date.strftime('%Y %m %d')) end_date.strftime('%Y-%m-%d'))
   
data = self.download(start_date, end_date, '~/dataset/[a-z0-9-_]+') if self.delete_first:
log.info('Storing Dataset Analytics for period "%s"', log.info('Deleting existing Analytics for this period "%s"',
self.get_full_period_name(period_name, period_complete_day)) period_name)
self.store(period_name, period_complete_day, data, ) ga_model.delete(period_name)
   
data = self.download(start_date, end_date, '~/publisher/[a-z0-9-_]+') if not self.skip_url_stats:
log.info('Storing Publisher Analytics for period "%s"', # Clean out old url data before storing the new
self.get_full_period_name(period_name, period_complete_day)) ga_model.pre_update_url_stats(period_name)
self.store(period_name, period_complete_day, data,)  
  accountName = config.get('googleanalytics.account')
ga_model.update_publisher_stats(period_name) # about 30 seconds.  
  log.info('Downloading analytics for dataset views')
  data = self.download(start_date, end_date, '~/%s/dataset/[a-z0-9-_]+' % accountName)
   
  log.info('Storing dataset views (%i rows)', len(data.get('url')))
  self.store(period_name, period_complete_day, data, )
   
  log.info('Downloading analytics for publisher views')
  data = self.download(start_date, end_date, '~/%s/publisher/[a-z0-9-_]+' % accountName)
   
  log.info('Storing publisher views (%i rows)', len(data.get('url')))
  self.store(period_name, period_complete_day, data,)
   
  log.info('Aggregating datasets by publisher')
  ga_model.update_publisher_stats(period_name) # about 30 seconds.
   
  log.info('Downloading and storing analytics for site-wide stats')
self.sitewide_stats( period_name ) self.sitewide_stats( period_name )
   
  log.info('Downloading and storing analytics for social networks')
def download(self, start_date, end_date, path='~/dataset/[a-z0-9-_]+'): self.update_social_info(period_name, start_date, end_date)
   
   
  def update_social_info(self, period_name, start_date, end_date):
  start_date = start_date.strftime('%Y-%m-%d')
  end_date = end_date.strftime('%Y-%m-%d')
  query = 'ga:hasSocialSourceReferral=~Yes$'
  metrics = 'ga:entrances'
  sort = '-ga:entrances'
   
  # Supported query params at
  # https://developers.google.com/analytics/devguides/reporting/core/v3/reference
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  filters=query,
  start_date=start_date,
  metrics=metrics,
  sort=sort,
  dimensions="ga:landingPagePath,ga:socialNetwork",
  max_results=10000,
  end_date=end_date).execute()
  data = collections.defaultdict(list)
  rows = results.get('rows',[])
  for row in rows:
  data[_normalize_url(row[0])].append( (row[1], int(row[2]),) )
  ga_model.update_social(period_name, data)
   
   
  def download(self, start_date, end_date, path=None):
'''Get data from GA for a given time period''' '''Get data from GA for a given time period'''
start_date = start_date.strftime('%Y-%m-%d') start_date = start_date.strftime('%Y-%m-%d')
end_date = end_date.strftime('%Y-%m-%d') end_date = end_date.strftime('%Y-%m-%d')
query = 'ga:pagePath=%s$' % path query = 'ga:pagePath=%s$' % path
metrics = 'ga:uniquePageviews, ga:visitors' metrics = 'ga:pageviews, ga:visits'
sort = '-ga:uniquePageviews' sort = '-ga:pageviews'
   
# Supported query params at # Supported query params at
# https://developers.google.com/analytics/devguides/reporting/core/v3/reference # https://developers.google.com/analytics/devguides/reporting/core/v3/reference
results = self.service.data().ga().get( results = self.service.data().ga().get(
ids='ga:' + self.profile_id, ids='ga:' + self.profile_id,
filters=query, filters=query,
start_date=start_date, start_date=start_date,
metrics=metrics, metrics=metrics,
sort=sort, sort=sort,
dimensions="ga:pagePath", dimensions="ga:pagePath",
max_results=10000, max_results=10000,
end_date=end_date).execute() end_date=end_date).execute()
   
if os.getenv('DEBUG'):  
import pprint  
pprint.pprint(results)  
print 'Total results: %s' % results.get('totalResults')  
   
packages = [] packages = []
for entry in results.get('rows'): for entry in results.get('rows'):
(loc,pageviews,visits) = entry (loc,pageviews,visits) = entry
packages.append( ('http:/' + loc, pageviews, visits,) ) # Temporary hack url = _normalize_url('http:/' + loc) # strips off domain e.g. www.data.gov.uk or data.gov.uk
   
  if not url.startswith('/dataset/') and not url.startswith('/publisher/'):
  # filter out strays like:
  # /data/user/login?came_from=http://data.gov.uk/dataset/os-code-point-open
  # /403.html?page=/about&from=http://data.gov.uk/publisher/planning-inspectorate
  continue
  packages.append( (url, pageviews, visits,) ) # Temporary hack
return dict(url=packages) return dict(url=packages)
   
def store(self, period_name, period_complete_day, data): def store(self, period_name, period_complete_day, data):
if 'url' in data: if 'url' in data:
ga_model.update_url_stats(period_name, period_complete_day, data['url']) ga_model.update_url_stats(period_name, period_complete_day, data['url'])
   
def sitewide_stats(self, period_name): def sitewide_stats(self, period_name):
import calendar import calendar
year, month = period_name.split('-') year, month = period_name.split('-')
_, last_day_of_month = calendar.monthrange(int(year), int(month)) _, last_day_of_month = calendar.monthrange(int(year), int(month))
   
start_date = '%s-01' % period_name start_date = '%s-01' % period_name
end_date = '%s-%s' % (period_name, last_day_of_month) end_date = '%s-%s' % (period_name, last_day_of_month)
print 'Sitewide_stats for %s (%s -> %s)' % (period_name, start_date, end_date)  
   
funcs = ['_totals_stats', '_social_stats', '_os_stats', funcs = ['_totals_stats', '_social_stats', '_os_stats',
'_locale_stats', '_browser_stats', '_mobile_stats'] '_locale_stats', '_browser_stats', '_mobile_stats']
for f in funcs: for f in funcs:
print ' + Fetching %s stats' % f.split('_')[1] log.info('Downloading analytics for %s' % f.split('_')[1])
getattr(self, f)(start_date, end_date, period_name) getattr(self, f)(start_date, end_date, period_name)
   
def _get_results(result_data, f): def _get_results(result_data, f):
data = {} data = {}
for result in result_data: for result in result_data:
key = f(result) key = f(result)
data[key] = data.get(key,0) + result[1] data[key] = data.get(key,0) + result[1]
return data return data
   
def _totals_stats(self, start_date, end_date, period_name): def _totals_stats(self, start_date, end_date, period_name):
""" Fetches distinct totals, total pageviews etc """ """ Fetches distinct totals, total pageviews etc """
results = self.service.data().ga().get( results = self.service.data().ga().get(
ids='ga:' + self.profile_id, ids='ga:' + self.profile_id,
start_date=start_date, start_date=start_date,
metrics='ga:uniquePageviews', metrics='ga:pageviews',
sort='-ga:uniquePageviews', sort='-ga:pageviews',
max_results=10000, max_results=10000,
end_date=end_date).execute() end_date=end_date).execute()
result_data = results.get('rows') result_data = results.get('rows')
ga_model.update_sitewide_stats(period_name, "Totals", {'Total pageviews': result_data[0][0]}) ga_model.update_sitewide_stats(period_name, "Totals", {'Total page views': result_data[0][0]})
   
results = self.service.data().ga().get( results = self.service.data().ga().get(
ids='ga:' + self.profile_id, ids='ga:' + self.profile_id,
start_date=start_date, start_date=start_date,
metrics='ga:pageviewsPerVisit,ga:bounces,ga:avgTimeOnSite,ga:percentNewVisits', metrics='ga:pageviewsPerVisit,ga:avgTimeOnSite,ga:percentNewVisits,ga:visits',
max_results=10000, max_results=10000,
end_date=end_date).execute() end_date=end_date).execute()
result_data = results.get('rows') result_data = results.get('rows')
data = { data = {
'Pages per visit': result_data[0][0], 'Pages per visit': result_data[0][0],
'Bounces': result_data[0][1], 'Average time on site': result_data[0][1],
'Average time on site': result_data[0][2], 'New visits': result_data[0][2],
'Percent new visits': result_data[0][3], 'Total visits': result_data[0][3],
} }
ga_model.update_sitewide_stats(period_name, "Totals", data) ga_model.update_sitewide_stats(period_name, "Totals", data)
   
  # Bounces from / or another configurable page.
  path = '/%s%s' % (config.get('googleanalytics.account'),
  config.get('ga-report.bounce_url', '/'))
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  filters='ga:pagePath==%s' % (path,),
  start_date=start_date,
  metrics='ga:bounces,ga:pageviews',
  dimensions='ga:pagePath',
  max_results=10000,
  end_date=end_date).execute()
  result_data = results.get('rows')
  if not result_data or len(result_data) != 1:
  log.error('Could not pinpoint the bounces for path: %s. Got results: %r',
  path, result_data)
  return
  results = result_data[0]
  bounces, total = [float(x) for x in result_data[0][1:]]
  pct = 100 * bounces/total
  log.info('%d bounces from %d total == %s', bounces, total, pct)
  ga_model.update_sitewide_stats(period_name, "Totals", {'Bounce rate (home page)': pct})
   
   
def _locale_stats(self, start_date, end_date, period_name): def _locale_stats(self, start_date, end_date, period_name):
""" Fetches stats about language and country """ """ Fetches stats about language and country """
results = self.service.data().ga().get( results = self.service.data().ga().get(
ids='ga:' + self.profile_id, ids='ga:' + self.profile_id,
start_date=start_date, start_date=start_date,
metrics='ga:uniquePageviews', metrics='ga:pageviews',
sort='-ga:uniquePageviews', sort='-ga:pageviews',
dimensions="ga:language,ga:country", dimensions="ga:language,ga:country",
max_results=10000, max_results=10000,
end_date=end_date).execute() end_date=end_date).execute()
result_data = results.get('rows') result_data = results.get('rows')
data = {} data = {}
for result in result_data: for result in result_data:
data[result[0]] = data.get(result[0], 0) + int(result[2]) data[result[0]] = data.get(result[0], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
ga_model.update_sitewide_stats(period_name, "Languages", data) ga_model.update_sitewide_stats(period_name, "Languages", data)
   
data = {} data = {}
for result in result_data: for result in result_data:
data[result[1]] = data.get(result[1], 0) + int(result[2]) data[result[1]] = data.get(result[1], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
ga_model.update_sitewide_stats(period_name, "Country", data) ga_model.update_sitewide_stats(period_name, "Country", data)
   
   
def _social_stats(self, start_date, end_date, period_name): def _social_stats(self, start_date, end_date, period_name):
""" Finds out which social sites people are referred from """ """ Finds out which social sites people are referred from """
results = self.service.data().ga().get( results = self.service.data().ga().get(
ids='ga:' + self.profile_id, ids='ga:' + self.profile_id,
start_date=start_date, start_date=start_date,
metrics='ga:uniquePageviews', metrics='ga:pageviews',
sort='-ga:uniquePageviews', sort='-ga:pageviews',
dimensions="ga:socialNetwork,ga:referralPath", dimensions="ga:socialNetwork,ga:referralPath",
max_results=10000, max_results=10000,
end_date=end_date).execute() end_date=end_date).execute()
result_data = results.get('rows') result_data = results.get('rows')
twitter_links = []  
data = {} data = {}
for result in result_data: for result in result_data:
if not result[0] == '(not set)': if not result[0] == '(not set)':
data[result[0]] = data.get(result[0], 0) + int(result[2]) data[result[0]] = data.get(result[0], 0) + int(result[2])
if result[0] == 'Twitter': self._filter_out_long_tail(data, 3)
twitter_links.append(result[1])  
ga_model.update_sitewide_stats(period_name, "Social sources", data) ga_model.update_sitewide_stats(period_name, "Social sources", data)
   
   
def _os_stats(self, start_date, end_date, period_name): def _os_stats(self, start_date, end_date, period_name):
""" Operating system stats """ """ Operating system stats """
results = self.service.data().ga().get( results = self.service.data().ga().get(
ids='ga:' + self.profile_id, ids='ga:' + self.profile_id,
start_date=start_date, start_date=start_date,
metrics='ga:uniquePageviews', metrics='ga:pageviews',
sort='-ga:uniquePageviews', sort='-ga:pageviews',
dimensions="ga:operatingSystem,ga:operatingSystemVersion", dimensions="ga:operatingSystem,ga:operatingSystemVersion",
max_results=10000, max_results=10000,
end_date=end_date).execute() end_date=end_date).execute()
result_data = results.get('rows') result_data = results.get('rows')
data = {} data = {}
for result in result_data: for result in result_data:
data[result[0]] = data.get(result[0], 0) + int(result[2]) data[result[0]] = data.get(result[0], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
ga_model.update_sitewide_stats(period_name, "Operating Systems", data) ga_model.update_sitewide_stats(period_name, "Operating Systems", data)
   
data = {} data = {}
for result in result_data: for result in result_data:
key = "%s (%s)" % (result[0],result[1]) if int(result[2]) >= MIN_VIEWS:
data[key] = result[2] key = "%s %s" % (result[0],result[1])
  data[key] = result[2]
ga_model.update_sitewide_stats(period_name, "Operating Systems versions", data) ga_model.update_sitewide_stats(period_name, "Operating Systems versions", data)
   
   
def _browser_stats(self, start_date, end_date, period_name): def _browser_stats(self, start_date, end_date, period_name):
""" Information about browsers and browser versions """ """ Information about browsers and browser versions """
results = self.service.data().ga().get( results = self.service.data().ga().get(
ids='ga:' + self.profile_id, ids='ga:' + self.profile_id,
start_date=start_date, start_date=start_date,
metrics='ga:uniquePageviews', metrics='ga:pageviews',
sort='-ga:uniquePageviews', sort='-ga:pageviews',
dimensions="ga:browser,ga:browserVersion", dimensions="ga:browser,ga:browserVersion",
max_results=10000, max_results=10000,
end_date=end_date).execute() end_date=end_date).execute()
result_data = results.get('rows') result_data = results.get('rows')
  # e.g. [u'Firefox', u'19.0', u'20']
   
data = {} data = {}
for result in result_data: for result in result_data:
data[result[0]] = data.get(result[0], 0) + int(result[2]) data[result[0]] = data.get(result[0], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
ga_model.update_sitewide_stats(period_name, "Browsers", data) ga_model.update_sitewide_stats(period_name, "Browsers", data)
   
data = {} data = {}
for result in result_data: for result in result_data:
key = "%s (%s)" % (result[0], result[1]) key = "%s %s" % (result[0], self._filter_browser_version(result[0], result[1]))
data[key] = result[2] data[key] = data.get(key, 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
ga_model.update_sitewide_stats(period_name, "Browser versions", data) ga_model.update_sitewide_stats(period_name, "Browser versions", data)
   
  @classmethod
  def _filter_browser_version(cls, browser, version_str):
  '''
  Simplifies a browser version string if it is detailed.
  i.e. groups together Firefox 3.5.1 and 3.5.2 to be just 3.
  This is helpful when viewing stats and good to protect privacy.
  '''
  ver = version_str
  parts = ver.split('.')
  if len(parts) > 1:
  if parts[1][0] == '0':
  ver = parts[0]
  else:
  ver = "%s" % (parts[0])
  # Special case complex version nums
  if browser in ['Safari', 'Android Browser']:
  ver = parts[0]
  if len(ver) > 2:
  num_hidden_digits = len(ver) - 2
  ver = ver[0] + ver[1] + 'X' * num_hidden_digits
  return ver
   
def _mobile_stats(self, start_date, end_date, period_name): def _mobile_stats(self, start_date, end_date, period_name):
""" Info about mobile devices """ """ Info about mobile devices """
   
results = self.service.data().ga().get( results = self.service.data().ga().get(
ids='ga:' + self.profile_id, ids='ga:' + self.profile_id,
start_date=start_date, start_date=start_date,
metrics='ga:uniquePageviews', metrics='ga:pageviews',
sort='-ga:uniquePageviews', sort='-ga:pageviews',
dimensions="ga:mobileDeviceBranding, ga:mobileDeviceInfo", dimensions="ga:mobileDeviceBranding, ga:mobileDeviceInfo",
max_results=10000, max_results=10000,
end_date=end_date).execute() end_date=end_date).execute()
   
result_data = results.get('rows') result_data = results.get('rows')
data = {} data = {}
for result in result_data: for result in result_data:
data[result[0]] = data.get(result[0], 0) + int(result[2]) data[result[0]] = data.get(result[0], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
ga_model.update_sitewide_stats(period_name, "Mobile brands", data) ga_model.update_sitewide_stats(period_name, "Mobile brands", data)
   
data = {} data = {}
for result in result_data: for result in result_data:
data[result[1]] = data.get(result[1], 0) + int(result[2]) data[result[1]] = data.get(result[1], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
ga_model.update_sitewide_stats(period_name, "Mobile devices", data) ga_model.update_sitewide_stats(period_name, "Mobile devices", data)
   
  @classmethod
  def _filter_out_long_tail(cls, data, threshold=10):
  '''
  Given data which is a frequency distribution, filter out
  results which are below a threshold count. This is good to protect
  privacy.
  '''
  for key, value in data.items():
  if value < threshold:
  del data[key]