Done integrating graphs onto site_usage/publishers and site_usage/datasets. Including some interesting queries.
--- a/.gitignore
+++ b/.gitignore
@@ -1,6 +1,7 @@
*.py[co]
*.py~
.gitignore
+ckan.log
# Packages
*.egg
--- a/README.rst
+++ b/README.rst
@@ -32,11 +32,11 @@
googleanalytics.id = UA-1010101-1
googleanalytics.account = Account name (e.g. data.gov.uk, see top level item at https://www.google.com/analytics)
+ googleanalytics.token.filepath = ~/pyenv/token.dat
ga-report.period = monthly
- ga-report.bounce_url = /data
+ ga-report.bounce_url = /
- The ga-report.bounce_url specifies the path to use when calculating bounces. For DGU this is /data
- but you may want to set this to /.
+ The ga-report.bounce_url specifies a particular path to record the bounce rate for. Typically it is / (the home page).
3. Set up this extension's database tables using a paster command. (Ensure your CKAN pyenv is still activated, run the command from ``src/ckanext-ga-report``, alter the ``--config`` option to point to your site config file)::
@@ -83,13 +83,17 @@
$ paster getauthtoken --config=../ckan/development.ini
+Now ensure you reference the correct path to your token.dat in your CKAN config file (e.g. development.ini)::
+
+ googleanalytics.token.filepath = ~/pyenv/token.dat
+
Tutorial
--------
Download some GA data and store it in CKAN's database. (Ensure your CKAN pyenv is still activated, run the command from ``src/ckanext-ga-report``, alter the ``--config`` option to point to your site config file) and specifying the name of your auth file (token.dat by default) from the previous step::
- $ paster loadanalytics token.dat latest --config=../ckan/development.ini
+ $ paster loadanalytics latest --config=../ckan/development.ini
The value after the token file is how much data you want to retrieve, this can be
--- a/ckanext/ga_report/command.py
+++ b/ckanext/ga_report/command.py
@@ -1,5 +1,8 @@
import logging
import datetime
+import os
+
+from pylons import config
from ckan.lib.cli import CkanCommand
# No other CKAN imports allowed until _load_config is run,
@@ -53,25 +56,52 @@
self.args[0] if self.args
else 'credentials.json')
+class FixTimePeriods(CkanCommand):
+ """
+ Fixes the 'All' records for GA_Urls
+
+ It is possible that older urls that haven't recently been visited
+ do not have All records. This command will traverse through those
+ records and generate valid All records for them.
+ """
+ summary = __doc__.split('\n')[0]
+ usage = __doc__
+ max_args = 0
+ min_args = 0
+
+ def __init__(self, name):
+ super(FixTimePeriods, self).__init__(name)
+
+ def command(self):
+ import ckan.model as model
+ from ga_model import post_update_url_stats
+ self._load_config()
+ model.Session.remove()
+ model.Session.configure(bind=model.meta.engine)
+
+ log = logging.getLogger('ckanext.ga_report')
+
+ log.info("Updating 'All' records for old URLs")
+ post_update_url_stats()
+ log.info("Processing complete")
+
+
class LoadAnalytics(CkanCommand):
"""Get data from Google Analytics API and save it
in the ga_model
- Usage: paster loadanalytics <tokenfile> <time-period>
+ Usage: paster loadanalytics <time-period>
- Where <tokenfile> is the name of the auth token file from
- the getauthtoken step.
-
- And where <time-period> is:
+ Where <time-period> is:
all - data for all time
latest - (default) just the 'latest' data
YYYY-MM - just data for the specific month
"""
summary = __doc__.split('\n')[0]
usage = __doc__
- max_args = 2
- min_args = 1
+ max_args = 1
+ min_args = 0
def __init__(self, name):
super(LoadAnalytics, self).__init__(name)
@@ -80,6 +110,11 @@
default=False,
dest='delete_first',
help='Delete data for the period first')
+ self.parser.add_option('-s', '--skip_url_stats',
+ action='store_true',
+ default=False,
+ dest='skip_url_stats',
+ help='Skip the download of URL data - just do site-wide stats')
def command(self):
self._load_config()
@@ -87,18 +122,25 @@
from download_analytics import DownloadAnalytics
from ga_auth import (init_service, get_profile_id)
+ ga_token_filepath = os.path.expanduser(config.get('googleanalytics.token.filepath', ''))
+ if not ga_token_filepath:
+ print 'ERROR: In the CKAN config you need to specify the filepath of the ' \
+ 'Google Analytics token file under key: googleanalytics.token.filepath'
+ return
+
try:
- svc = init_service(self.args[0], None)
+ svc = init_service(ga_token_filepath, None)
except TypeError:
print ('Have you correctly run the getauthtoken task and '
- 'specified the correct token file?')
+ 'specified the correct token file in the CKAN config under '
+ '"googleanalytics.token.filepath"?')
return
downloader = DownloadAnalytics(svc, profile_id=get_profile_id(svc),
- delete_first=self.options.delete_first)
+ delete_first=self.options.delete_first,
+ skip_url_stats=self.options.skip_url_stats)
- time_period = self.args[1] if self.args and len(self.args) > 1 \
- else 'latest'
+ time_period = self.args[0] if self.args else 'latest'
if time_period == 'all':
downloader.all_()
elif time_period == 'latest':
--- a/ckanext/ga_report/controller.py
+++ b/ckanext/ga_report/controller.py
@@ -1,6 +1,7 @@
import re
import csv
import sys
+import json
import logging
import operator
import collections
@@ -13,6 +14,7 @@
log = logging.getLogger('ckanext.ga-report')
+DOWNLOADS_AVAILABLE_FROM = '2012-12'
def _get_month_name(strdate):
import calendar
@@ -20,14 +22,39 @@
d = strptime(strdate, '%Y-%m')
return '%s %s' % (calendar.month_name[d.tm_mon], d.tm_year)
-
-def _month_details(cls):
- '''Returns a list of all the month names'''
+def _get_unix_epoch(strdate):
+ from time import strptime,mktime
+ d = strptime(strdate, '%Y-%m')
+ return int(mktime(d))
+
+def _month_details(cls, stat_key=None):
+ '''
+ Returns a list of all the periods for which we have data, unfortunately
+ knows too much about the type of the cls being passed as GA_Url has a
+ more complex query
+
+ This may need extending if we add a period_name to the stats
+ '''
months = []
- vals = model.Session.query(cls.period_name).filter(cls.period_name!='All').distinct().all()
+ day = None
+
+ q = model.Session.query(cls.period_name,cls.period_complete_day)\
+ .filter(cls.period_name!='All').distinct(cls.period_name)
+ if stat_key:
+ q= q.filter(cls.stat_name==stat_key)
+
+ vals = q.order_by("period_name desc").all()
+
+ if vals and vals[0][1]:
+ day = int(vals[0][1])
+ ordinal = 'th' if 11 <= day <= 13 \
+ else {1:'st',2:'nd',3:'rd'}.get(day % 10, 'th')
+ day = "{day}{ordinal}".format(day=day, ordinal=ordinal)
+
for m in vals:
months.append( (m[0], _get_month_name(m[0])))
- return sorted(months, key=operator.itemgetter(0), reverse=True)
+
+ return months, day
class GaReport(BaseController):
@@ -35,7 +62,7 @@
def csv(self, month):
import csv
- q = model.Session.query(GA_Stat)
+ q = model.Session.query(GA_Stat).filter(GA_Stat.stat_name!='Downloads')
if month != 'all':
q = q.filter(GA_Stat.period_name==month)
entries = q.order_by('GA_Stat.period_name, GA_Stat.stat_name, GA_Stat.key').all()
@@ -52,11 +79,12 @@
entry.key.encode('utf-8'),
entry.value.encode('utf-8')])
+
def index(self):
# Get the month details by fetching distinct values and determining the
# month names from the values.
- c.months = _month_details(GA_Stat)
+ c.months, c.day = _month_details(GA_Stat)
# Work out which month to show, based on query params of the first item
c.month_desc = 'all months'
@@ -71,24 +99,39 @@
entries = q.order_by('ga_stat.key').all()
def clean_key(key, val):
- if key in ['Average time on site', 'Pages per visit', 'New visits', 'Bounces']:
+ if key in ['Average time on site', 'Pages per visit', 'New visits', 'Bounce rate (home page)']:
val = "%.2f" % round(float(val), 2)
if key == 'Average time on site':
mins, secs = divmod(float(val), 60)
hours, mins = divmod(mins, 60)
val = '%02d:%02d:%02d (%s seconds) ' % (hours, mins, secs, val)
- if key in ['New visits','Bounces']:
+ if key in ['New visits','Bounce rate (home page)']:
val = "%s%%" % val
if key in ['Total page views', 'Total visits']:
val = int(val)
return key, val
+
+ # Query historic values for sparkline rendering
+ sparkline_query = model.Session.query(GA_Stat)\
+ .filter(GA_Stat.stat_name=='Totals')\
+ .order_by(GA_Stat.period_name)
+ sparkline_data = {}
+ for x in sparkline_query:
+ sparkline_data[x.key] = sparkline_data.get(x.key,[])
+ key, val = clean_key(x.key,float(x.value))
+ tooltip = '%s: %s' % (_get_month_name(x.period_name), val)
+ sparkline_data[x.key].append( (tooltip,x.value) )
+ # Trim the latest month, as it looks like a huge dropoff
+ for key in sparkline_data:
+ sparkline_data[key] = sparkline_data[key][:-1]
c.global_totals = []
if c.month:
for e in entries:
key, val = clean_key(e.key, e.value)
- c.global_totals.append((key, val))
+ sparkline = sparkline_data[e.key]
+ c.global_totals.append((key, val, sparkline))
else:
d = collections.defaultdict(list)
for e in entries:
@@ -97,11 +140,19 @@
if k in ['Total page views', 'Total visits']:
v = sum(v)
else:
- v = float(sum(v))/len(v)
+ v = float(sum(v))/float(len(v))
+ sparkline = sparkline_data[k]
key, val = clean_key(k,v)
- c.global_totals.append((key, val))
- c.global_totals = sorted(c.global_totals, key=operator.itemgetter(0))
+ c.global_totals.append((key, val, sparkline))
+ # Sort the global totals into a more pleasant order
+ def sort_func(x):
+ key = x[0]
+ total_order = ['Total page views','Total visits','Pages per visit']
+ if key in total_order:
+ return total_order.index(key)
+ return 999
+ c.global_totals = sorted(c.global_totals, key=sort_func)
keys = {
'Browser versions': 'browser_versions',
@@ -138,7 +189,29 @@
for k, v in keys.iteritems():
q = model.Session.query(GA_Stat).\
- filter(GA_Stat.stat_name==k)
+ filter(GA_Stat.stat_name==k).\
+ order_by(GA_Stat.period_name)
+ # Run the query on all months to gather graph data
+ series = {}
+ x_axis = set()
+ for stat in q:
+ x_val = _get_unix_epoch(stat.period_name)
+ series[ stat.key ] = series.get(stat.key,{})
+ series[ stat.key ][x_val] = float(stat.value)
+ x_axis.add(x_val)
+ # Common x-axis for all series. Exclude this month (incomplete data)
+ x_axis = sorted(list(x_axis))[:-1]
+ # Buffer a rickshaw dataset from the series
+ def create_graph(series_name, series_data):
+ return {
+ 'name':series_name,
+ 'data':[ {'x':x,'y':series_data.get(x,0)} for x in x_axis ]
+ }
+ rickshaw = [ create_graph(name,data) for name, data in series.items() ]
+ rickshaw = sorted(rickshaw,key=lambda x:x['data'][-1]['y'])
+ setattr(c, v+'_graph', json.dumps(rickshaw))
+
+ # Buffer the tabular data
if c.month:
entries = []
q = q.filter(GA_Stat.period_name==c.month).\
@@ -155,7 +228,7 @@
# Get the total for each set of values and then set the value as
# a percentage of the total
if k == 'Social sources':
- total = sum([x for n,x in c.global_totals if n == 'Total visits'])
+ total = sum([x for n,x,graph in c.global_totals if n == 'Total visits'])
else:
total = sum([num for _,num in entries])
setattr(c, v, [(k,_percent(v,total)) for k,v in entries ])
@@ -180,7 +253,9 @@
writer = csv.writer(response)
writer.writerow(["Publisher Title", "Publisher Name", "Views", "Visits", "Period Name"])
- for publisher,view,visit in _get_top_publishers(None):
+ top_publishers, top_publishers_graph = _get_top_publishers(None)
+
+ for publisher,view,visit in top_publishers:
writer.writerow([publisher.title.encode('utf-8'),
publisher.name.encode('utf-8'),
view,
@@ -206,13 +281,14 @@
str('attachment; filename=datasets_%s_%s.csv' % (c.publisher_name, month,))
writer = csv.writer(response)
- writer.writerow(["Dataset Title", "Dataset Name", "Views", "Visits", "Period Name"])
-
- for package,view,visit in packages:
+ writer.writerow(["Dataset Title", "Dataset Name", "Views", "Visits", "Resource downloads", "Period Name"])
+
+ for package,view,visit,downloads in packages:
writer.writerow([package.title.encode('utf-8'),
package.name.encode('utf-8'),
view,
visit,
+ downloads,
month])
def publishers(self):
@@ -220,7 +296,7 @@
# Get the month details by fetching distinct values and determining the
# month names from the values.
- c.months = _month_details(GA_Url)
+ c.months, c.day = _month_details(GA_Url)
# Work out which month to show, based on query params of the first item
c.month = request.params.get('month', '')
@@ -228,15 +304,17 @@
if c.month:
c.month_desc = ''.join([m[1] for m in c.months if m[0]==c.month])
- c.top_publishers = _get_top_publishers()
+ c.top_publishers, graph_data = _get_top_publishers()
+ c.top_publishers_graph = json.dumps( _to_rickshaw(graph_data.values()) )
+
return render('ga_report/publisher/index.html')
def _get_packages(self, publisher=None, count=-1):
- '''Returns the datasets in order of visits'''
- if count == -1:
- count = sys.maxint
-
+ '''Returns the datasets in order of views'''
+ have_download_data = True
month = c.month or 'All'
+ if month != 'All':
+ have_download_data = month >= DOWNLOADS_AVAILABLE_FROM
q = model.Session.query(GA_Url,model.Package)\
.filter(model.Package.name==GA_Url.package_id)\
@@ -244,11 +322,28 @@
if publisher:
q = q.filter(GA_Url.department_id==publisher.name)
q = q.filter(GA_Url.period_name==month)
- q = q.order_by('ga_url.visitors::int desc')
+ q = q.order_by('ga_url.pageviews::int desc')
top_packages = []
- for entry,package in q.limit(count):
+ if count == -1:
+ entries = q.all()
+ else:
+ entries = q.limit(count)
+
+ for entry,package in entries:
if package:
- top_packages.append((package, entry.pageviews, entry.visitors))
+ # Downloads ....
+ if have_download_data:
+ dls = model.Session.query(GA_Stat).\
+ filter(GA_Stat.stat_name=='Downloads').\
+ filter(GA_Stat.key==package.name)
+ if month != 'All': # Fetch everything unless the month is specific
+ dls = dls.filter(GA_Stat.period_name==month)
+ downloads = 0
+ for x in dls:
+ downloads += int(x.value)
+ else:
+ downloads = 'No data'
+ top_packages.append((package, entry.pageviews, entry.visits, downloads))
else:
log.warning('Could not find package associated package')
@@ -278,7 +373,7 @@
# Get the month details by fetching distinct values and determining the
# month names from the values.
- c.months = _month_details(GA_Url)
+ c.months, c.day = _month_details(GA_Url)
# Work out which month to show, based on query params of the first item
c.month = request.params.get('month', '')
@@ -296,7 +391,40 @@
c.top_packages = self._get_packages(c.publisher, 20)
+ # Graph query
+ top_package_names = [ x[0].name for x in c.top_packages ]
+ graph_query = model.Session.query(GA_Url,model.Package)\
+ .filter(model.Package.name==GA_Url.package_id)\
+ .filter(GA_Url.url.like('/dataset/%'))\
+ .filter(GA_Url.package_id.in_(top_package_names))
+ graph_data = {}
+ for entry,package in graph_query:
+ if not package: continue
+ if entry.period_name=='All': continue
+ graph_data[package.id] = graph_data.get(package.id,{
+ 'name':package.title,
+ 'data':[]
+ })
+ graph_data[package.id]['data'].append({
+ 'x':_get_unix_epoch(entry.period_name),
+ 'y':int(entry.pageviews),
+ })
+
+ c.graph_data = json.dumps( _to_rickshaw(graph_data.values()) )
+
return render('ga_report/publisher/read.html')
+
+def _to_rickshaw(data):
+ num_points = []
+ for package in data:
+ package['data'] = sorted( package['data'], key=lambda x:x['x'] )
+ num_points.append( len(package['data']) )
+ if len(set(num_points))>1:
+ example = num_points[ num_points.index(max(num_points)) ]
+ for package in data:
+ while len(package['data'])<example:
+ package['data'].insert(0, package['data'][0])
+ return data
def _get_top_publishers(limit=20):
'''
@@ -306,30 +434,54 @@
month = c.month or 'All'
connection = model.Session.connection()
q = """
- select department_id, sum(pageviews::int) views, sum(visitors::int) visits
+ select department_id, sum(pageviews::int) views, sum(visits::int) visits
from ga_url
where department_id <> ''
and package_id <> ''
and url like '/dataset/%%'
and period_name=%s
- group by department_id order by visits desc
+ group by department_id order by views desc
"""
if limit:
q = q + " limit %s;" % (limit)
top_publishers = []
res = connection.execute(q, month)
+ department_ids = []
for row in res:
g = model.Group.get(row[0])
if g:
+ department_ids.append(row[0])
top_publishers.append((g, row[1], row[2]))
- return top_publishers
+
+ graph = {}
+ if limit is not None:
+ # Query for a history graph of these publishers
+ q = model.Session.query(
+ GA_Url.department_id,
+ GA_Url.period_name,
+ func.sum(cast(GA_Url.pageviews,sqlalchemy.types.INT)))\
+ .filter( GA_Url.department_id.in_(department_ids) )\
+ .filter( GA_Url.period_name!='All' )\
+ .filter( GA_Url.url.like('/dataset/%') )\
+ .filter( GA_Url.package_id!='' )\
+ .group_by( GA_Url.department_id, GA_Url.period_name )
+ for dept_id,period_name,views in q:
+ graph[dept_id] = graph.get( dept_id, {
+ 'name' : model.Group.get(dept_id).title,
+ 'data' : []
+ })
+ graph[dept_id]['data'].append({
+ 'x': _get_unix_epoch(period_name),
+ 'y': views
+ })
+ return top_publishers, graph
def _get_publishers():
'''
Returns a list of all publishers. Each item is a tuple:
- (names, title)
+ (name, title)
'''
publishers = []
for pub in model.Session.query(model.Group).\
--- a/ckanext/ga_report/download_analytics.py
+++ b/ckanext/ga_report/download_analytics.py
@@ -13,15 +13,18 @@
FORMAT_MONTH = '%Y-%m'
MIN_VIEWS = 50
MIN_VISITS = 20
+MIN_DOWNLOADS = 10
class DownloadAnalytics(object):
'''Downloads and stores analytics info'''
- def __init__(self, service=None, profile_id=None, delete_first=False):
+ def __init__(self, service=None, profile_id=None, delete_first=False,
+ skip_url_stats=False):
self.period = config['ga-report.period']
self.service = service
self.profile_id = profile_id
self.delete_first = delete_first
+ self.skip_url_stats = skip_url_stats
def specific_month(self, date):
import calendar
@@ -92,33 +95,45 @@
def download_and_store(self, periods):
for period_name, period_complete_day, start_date, end_date in periods:
+ log.info('Period "%s" (%s - %s)',
+ self.get_full_period_name(period_name, period_complete_day),
+ start_date.strftime('%Y-%m-%d'),
+ end_date.strftime('%Y-%m-%d'))
+
if self.delete_first:
- log.info('Deleting existing Analytics for period "%s"',
+ log.info('Deleting existing Analytics for this period "%s"',
period_name)
ga_model.delete(period_name)
- log.info('Downloading Analytics for period "%s" (%s - %s)',
- self.get_full_period_name(period_name, period_complete_day),
- start_date.strftime('%Y %m %d'),
- end_date.strftime('%Y %m %d'))
-
- # Clean up the entries before we run this
- ga_model.pre_update_url_stats(period_name)
-
- accountName = config.get('googleanalytics.account')
-
- data = self.download(start_date, end_date, '~/%s/dataset/[a-z0-9-_]+' % accountName)
- log.info('Storing Dataset Analytics for period "%s"',
- self.get_full_period_name(period_name, period_complete_day))
- self.store(period_name, period_complete_day, data, )
-
- data = self.download(start_date, end_date, '~/%s/publisher/[a-z0-9-_]+' % accountName)
- log.info('Storing Publisher Analytics for period "%s"',
- self.get_full_period_name(period_name, period_complete_day))
- self.store(period_name, period_complete_day, data,)
-
- ga_model.update_publisher_stats(period_name) # about 30 seconds.
- self.sitewide_stats( period_name )
-
+
+ if not self.skip_url_stats:
+ # Clean out old url data before storing the new
+ ga_model.pre_update_url_stats(period_name)
+
+ accountName = config.get('googleanalytics.account')
+
+ 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,)
+
+ # Make sure the All records are correct.
+ ga_model.post_update_url_stats()
+
+ 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, period_complete_day )
+
+ log.info('Downloading and storing analytics for social networks')
self.update_social_info(period_name, start_date, end_date)
@@ -143,7 +158,8 @@
data = collections.defaultdict(list)
rows = results.get('rows',[])
for row in rows:
- data[_normalize_url(row[0])].append( (row[1], int(row[2]),) )
+ url = _normalize_url('http:/' + row[0])
+ data[url].append( (row[1], int(row[2]),) )
ga_model.update_social(period_name, data)
@@ -152,8 +168,8 @@
start_date = start_date.strftime('%Y-%m-%d')
end_date = end_date.strftime('%Y-%m-%d')
query = 'ga:pagePath=%s$' % path
- metrics = 'ga:uniquePageviews, ga:visits'
- sort = '-ga:uniquePageviews'
+ metrics = 'ga:pageviews, ga:visits'
+ sort = '-ga:pageviews'
# Supported query params at
# https://developers.google.com/analytics/devguides/reporting/core/v3/reference
@@ -168,10 +184,15 @@
end_date=end_date).execute()
packages = []
+ log.info("There are %d results" % results['totalResults'])
for entry in results.get('rows'):
(loc,pageviews,visits) = entry
- url = _normalize_url('http:/' + loc)
+ 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)
@@ -180,20 +201,18 @@
if 'url' in data:
ga_model.update_url_stats(period_name, period_complete_day, data['url'])
- def sitewide_stats(self, period_name):
+ def sitewide_stats(self, period_name, period_complete_day):
import calendar
year, month = period_name.split('-')
_, last_day_of_month = calendar.monthrange(int(year), int(month))
start_date = '%s-01' % period_name
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',
- '_locale_stats', '_browser_stats', '_mobile_stats']
+ '_locale_stats', '_browser_stats', '_mobile_stats', '_download_stats']
for f in funcs:
- print ' + Fetching %s stats' % f.split('_')[1]
- getattr(self, f)(start_date, end_date, period_name)
+ log.info('Downloading analytics for %s' % f.split('_')[1])
+ getattr(self, f)(start_date, end_date, period_name, period_complete_day)
def _get_results(result_data, f):
data = {}
@@ -202,17 +221,18 @@
data[key] = data.get(key,0) + result[1]
return data
- def _totals_stats(self, start_date, end_date, period_name):
+ def _totals_stats(self, start_date, end_date, period_name, period_complete_day):
""" Fetches distinct totals, total pageviews etc """
results = self.service.data().ga().get(
ids='ga:' + self.profile_id,
start_date=start_date,
- metrics='ga:uniquePageviews',
- sort='-ga:uniquePageviews',
- max_results=10000,
- end_date=end_date).execute()
- result_data = results.get('rows')
- ga_model.update_sitewide_stats(period_name, "Totals", {'Total page views': result_data[0][0]})
+ metrics='ga:pageviews',
+ sort='-ga:pageviews',
+ max_results=10000,
+ end_date=end_date).execute()
+ result_data = results.get('rows')
+ ga_model.update_sitewide_stats(period_name, "Totals", {'Total page views': result_data[0][0]},
+ period_complete_day)
results = self.service.data().ga().get(
ids='ga:' + self.profile_id,
@@ -227,36 +247,39 @@
'New visits': result_data[0][2],
'Total visits': result_data[0][3],
}
- ga_model.update_sitewide_stats(period_name, "Totals", data)
-
- # Bounces from /data. This url is specified in configuration because
- # for DGU we don't want /.
- path = config.get('ga-report.bounce_url','/')
- print path
- results = self.service.data().ga().get(
- ids='ga:' + self.profile_id,
- filters='ga:pagePath=~%s$' % (path,),
- start_date=start_date,
- metrics='ga:bounces,ga:uniquePageviews',
+ ga_model.update_sitewide_stats(period_name, "Totals", data, period_complete_day)
+
+ # 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:visitBounceRate',
dimensions='ga:pagePath',
max_results=10000,
end_date=end_date).execute()
result_data = results.get('rows')
- for results in result_data:
- if results[0] == path:
- bounce, total = [float(x) for x in results[1:]]
- pct = 100 * bounce/total
- print "%d bounces from %d total == %s" % (bounce, total, pct)
- ga_model.update_sitewide_stats(period_name, "Totals", {'Bounces': pct})
-
-
- def _locale_stats(self, start_date, end_date, period_name):
+ 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 = float(results[1])
+ # visitBounceRate is already a %
+ log.info('Google reports visitBounceRate as %s', bounces)
+ ga_model.update_sitewide_stats(period_name, "Totals", {'Bounce rate (home page)': float(bounces)},
+ period_complete_day)
+
+
+ def _locale_stats(self, start_date, end_date, period_name, period_complete_day):
""" Fetches stats about language and country """
results = self.service.data().ga().get(
ids='ga:' + self.profile_id,
start_date=start_date,
- metrics='ga:uniquePageviews',
- sort='-ga:uniquePageviews',
+ metrics='ga:pageviews',
+ sort='-ga:pageviews',
dimensions="ga:language,ga:country",
max_results=10000,
end_date=end_date).execute()
@@ -265,22 +288,78 @@
for result in result_data:
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, period_complete_day)
data = {}
for result in result_data:
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)
-
-
- def _social_stats(self, start_date, end_date, period_name):
+ ga_model.update_sitewide_stats(period_name, "Country", data, period_complete_day)
+
+
+ def _download_stats(self, start_date, end_date, period_name, period_complete_day):
+ """ Fetches stats about language and country """
+ import ckan.model as model
+