--- 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
@@ -20,8 +22,12 @@
d = strptime(strdate, '%Y-%m')
return '%s %s' % (calendar.month_name[d.tm_mon], d.tm_year)
-
-def _month_details(cls):
+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
@@ -32,9 +38,13 @@
months = []
day = None
- vals = model.Session.query(cls.period_name,cls.period_complete_day)\
- .filter(cls.period_name!='All').distinct(cls.period_name)\
- .order_by("period_name desc").all()
+ 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 \
@@ -52,7 +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()
@@ -68,6 +78,7 @@
entry.stat_name.encode('utf-8'),
entry.key.encode('utf-8'),
entry.value.encode('utf-8')])
+
def index(self):
@@ -101,11 +112,26 @@
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:
@@ -114,11 +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',
@@ -155,7 +189,22 @@
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
+ graph = {}
+ for stat in q:
+ graph[ stat.key ] = graph.get(stat.key,{
+ 'name':stat.key,
+ 'data': []
+ })
+ graph[ stat.key ]['data'].append({
+ 'x':_get_unix_epoch(stat.period_name),
+ 'y':float(stat.value)
+ })
+ setattr(c, v+'_graph', json.dumps( _to_rickshaw(graph.values(),percentageMode=True) ))
+
+ # Buffer the tabular data
if c.month:
entries = []
q = q.filter(GA_Stat.period_name==c.month).\
@@ -172,7 +221,7 @@
# 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 ])
@@ -197,7 +246,9 @@
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,
@@ -223,13 +274,14 @@
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):
@@ -245,15 +297,17 @@
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 views'''
- if count == -1:
- count = sys.maxint
-
+ 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)\
@@ -263,9 +317,26 @@
q = q.filter(GA_Url.period_name==month)
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.visits))
+ # 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')
@@ -313,7 +384,74 @@
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, percentageMode=False):
+ if data==[]:
+ return data
+ # Create a consistent x-axis
+ num_points = [ len(package['data']) for package in data ]
+ ideal_index = num_points.index( max(num_points) )
+ x_axis = [ point['x'] for point in data[ideal_index]['data'] ]
+ for package in data:
+ xs = [ point['x'] for point in package['data'] ]
+ assert set(xs).issubset( set(x_axis) ), (xs, x_axis)
+ # Zero pad any missing values
+ for x in set(x_axis).difference(set(xs)):
+ package['data'].append( {'x':x, 'y':0} )
+ assert len(package['data'])==len(x_axis), (len(package['data']),len(x_axis),package['data'],x_axis,set(x_axis).difference(set(xs)))
+ if percentageMode:
+ # Transform data into percentage stacks
+ totals = {}
+ for x in x_axis:
+ for package in data:
+ for point in package['data']:
+ totals[ point['x'] ] = totals.get(point['x'],0) + point['y']
+ # Roll insignificant series into a catch-all
+ THRESHOLD = 0.01
+ significant_series = []
+ for package in data:
+ for point in package['data']:
+ fraction = float(point['y']) / totals[point['x']]
+ if fraction>THRESHOLD and not (package in significant_series):
+ significant_series.append(package)
+ temp = {}
+ for package in data:
+ if package in significant_series: continue
+ for point in package['data']:
+ temp[point['x']] = temp.get(point['x'],0) + point['y']
+ catch_all = { 'name':'Other','data': [ {'x':x,'y':y} for x,y in temp.items() ] }
+ # Roll insignificant series into one
+ data = significant_series
+ data.append(catch_all)
+ # Sort the points
+ for package in data:
+ package['data'] = sorted( package['data'], key=lambda x:x['x'] )
+ # Strip the latest month's incomplete analytics
+ package['data'] = package['data'][:-1]
+ return data
+
def _get_top_publishers(limit=20):
'''
@@ -336,11 +474,35 @@
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():
--- a/ckanext/ga_report/download_analytics.py
+++ b/ckanext/ga_report/download_analytics.py
@@ -13,6 +13,7 @@
FORMAT_MONTH = '%Y-%m'
MIN_VIEWS = 50
MIN_VISITS = 20
+MIN_DOWNLOADS = 10
class DownloadAnalytics(object):
'''Downloads and stores analytics info'''
@@ -122,8 +123,12 @@
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 )
@@ -179,6 +184,7 @@
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) # strips off domain e.g. www.data.gov.uk or data.gov.uk
@@ -203,7 +209,7 @@
start_date = '%s-01' % period_name
end_date = '%s-%s' % (period_name, last_day_of_month)
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:
log.info('Downloading analytics for %s' % f.split('_')[1])
getattr(self, f)(start_date, end_date, period_name, period_complete_day)
@@ -250,7 +256,7 @@
ids='ga:' + self.profile_id,
filters='ga:pagePath==%s' % (path,),
start_date=start_date,
- metrics='ga:bounces,ga:pageviews',
+ metrics='ga:visitBounceRate',
dimensions='ga:pagePath',
max_results=10000,
end_date=end_date).execute()
@@ -260,10 +266,10 @@
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},
+ 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)
@@ -290,6 +296,62 @@
self._filter_out_long_tail(data, MIN_VIEWS)
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
+
+ data = {}
+
+ results = self.service.data().ga().get(
+ ids='ga:' + self.profile_id,
+ start_date=start_date,
+ filters='ga:eventAction==download',
+ metrics='ga:totalEvents',
+ sort='-ga:totalEvents',
+ dimensions="ga:eventLabel",
+ max_results=10000,
+ end_date=end_date).execute()
+ result_data = results.get('rows')
+ if not result_data:
+ # We may not have data for this time period, so we need to bail
+ # early.
+ log.info("There is no download data for this time period")
+ return
+
+ def process_result_data(result_data, cached=False):
+ for result in result_data:
+ url = result[0].strip()
+
+ # Get package id associated with the resource that has this URL.
+ q = model.Session.query(model.Resource)
+ if cached:
+ r = q.filter(model.Resource.cache_url.like("%s%%" % url)).first()
+ else:
+ r = q.filter(model.Resource.url.like("%s%%" % url)).first()
+
+ package_name = r.resource_group.package.name if r else ""
+ if package_name:
+ data[package_name] = data.get(package_name, 0) + int(result[1])
+ else:
+ log.warning(u"Could not find resource for URL: {url}".format(url=url))
+ continue
+
+ process_result_data(results.get('rows'))
+
+ results = self.service.data().ga().get(
+ ids='ga:' + self.profile_id,
+ start_date=start_date,
+ filters='ga:eventAction==download-cache',
+ metrics='ga:totalEvents',
+ sort='-ga:totalEvents',
+ dimensions="ga:eventLabel",
+ max_results=10000,
+ end_date=end_date).execute()
+ process_result_data(results.get('rows'), cached=False)
+
+ self._filter_out_long_tail(data, MIN_DOWNLOADS)
+ ga_model.update_sitewide_stats(period_name, "Downloads", data, period_complete_day)
def _social_stats(self, start_date, end_date, period_name, period_complete_day):
""" Finds out which social sites people are referred from """
--- /dev/null
+++ b/ckanext/ga_report/public/scripts/vendor/d3.layout.min.js
@@ -1,1 +1,1 @@
-
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