Prepare graphs for an expected time period (since July 2012) rather than for the time period found in the DB, which can be reduced to absurdity with certain queries. Graphs always have a consistent X-axis, ugly logic to combine disparate data series can be removed.
On 'Publisher' and 'Dataset' tabs, always graph the *top 20* series regardless of the month currently rendered in the table. This makes more sense from a useability POV.
Finally, some client side error checking was improved.
--- /dev/null
+++ b/ckanext/ga_report/controller.py
@@ -1,1 +1,541 @@
-
+import re
+import csv
+import sys
+import json
+import logging
+import operator
+import collections
+from ckan.lib.base import (BaseController, c, g, render, request, response, abort)
+
+import sqlalchemy
+from sqlalchemy import func, cast, Integer
+import ckan.model as model
+from ga_model import GA_Url, GA_Stat, GA_ReferralStat, GA_Publisher
+
+log = logging.getLogger('ckanext.ga-report')
+
+DOWNLOADS_AVAILABLE_FROM = '2012-12'
+
+def _get_month_name(strdate):
+ import calendar
+ from time import strptime
+ d = strptime(strdate, '%Y-%m')
+ return '%s %s' % (calendar.month_name[d.tm_mon], d.tm_year)
+
+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 = []
+ 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 months, day
+
+
+class GaReport(BaseController):
+
+ def csv(self, month):
+ import csv
+
+ 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()
+
+ response.headers['Content-Type'] = "text/csv; charset=utf-8"
+ response.headers['Content-Disposition'] = str('attachment; filename=stats_%s.csv' % (month,))
+
+ writer = csv.writer(response)
+ writer.writerow(["Period", "Statistic", "Key", "Value"])
+
+ for entry in entries:
+ writer.writerow([entry.period_name.encode('utf-8'),
+ entry.stat_name.encode('utf-8'),
+ 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, 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'
+ c.month = request.params.get('month', '')
+ if c.month:
+ c.month_desc = ''.join([m[1] for m in c.months if m[0]==c.month])
+
+ q = model.Session.query(GA_Stat).\
+ filter(GA_Stat.stat_name=='Totals')
+ if c.month:
+ q = q.filter(GA_Stat.period_name==c.month)
+ 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', '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','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)
+ sparkline = sparkline_data[e.key]
+ c.global_totals.append((key, val, sparkline))
+ else:
+ d = collections.defaultdict(list)
+ for e in entries:
+ d[e.key].append(float(e.value))
+ for k, v in d.iteritems():
+ if k in ['Total page views', 'Total visits']:
+ v = sum(v)
+ else:
+ v = float(sum(v))/float(len(v))
+ sparkline = sparkline_data[k]
+ key, val = clean_key(k,v)
+
+ 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',
+ 'Browsers': 'browsers',
+ 'Operating Systems versions': 'os_versions',
+ 'Operating Systems': 'os',
+ 'Social sources': 'social_networks',
+ 'Languages': 'languages',
+ 'Country': 'country'
+ }
+
+ def shorten_name(name, length=60):
+ return (name[:length] + '..') if len(name) > 60 else name
+
+ def fill_out_url(url):
+ import urlparse
+ return urlparse.urljoin(g.site_url, url)
+
+ c.social_referrer_totals, c.social_referrers = [], []
+ q = model.Session.query(GA_ReferralStat)
+ q = q.filter(GA_ReferralStat.period_name==c.month) if c.month else q
+ q = q.order_by('ga_referrer.count::int desc')
+ for entry in q.all():
+ c.social_referrers.append((shorten_name(entry.url), fill_out_url(entry.url),
+ entry.source,entry.count))
+
+ q = model.Session.query(GA_ReferralStat.url,
+ func.sum(GA_ReferralStat.count).label('count'))
+ q = q.filter(GA_ReferralStat.period_name==c.month) if c.month else q
+ q = q.order_by('count desc').group_by(GA_ReferralStat.url)
+ for entry in q.all():
+ c.social_referrer_totals.append((shorten_name(entry[0]), fill_out_url(entry[0]),'',
+ entry[1]))
+
+ for k, v in keys.iteritems():
+ q = model.Session.query(GA_Stat).\
+ filter(GA_Stat.stat_name==k).\
+ order_by(GA_Stat.period_name)
+ # Buffer the tabular data
+ if c.month:
+ entries = []
+ q = q.filter(GA_Stat.period_name==c.month).\
+ order_by('ga_stat.value::int desc')
+ d = collections.defaultdict(int)
+ for e in q.all():
+ d[e.key] += int(e.value)
+ entries = []
+ for key, val in d.iteritems():
+ entries.append((key,val,))
+ entries = sorted(entries, key=operator.itemgetter(1), reverse=True)
+
+ # Run a query on all months to gather graph data
+ graph_query = model.Session.query(GA_Stat).\
+ filter(GA_Stat.stat_name==k).\
+ order_by(GA_Stat.period_name)
+ graph_dict = {}
+ for stat in graph_query:
+ graph_dict[ stat.key ] = graph_dict.get(stat.key,{
+ 'name':stat.key,
+ 'raw': {}
+ })
+ graph_dict[ stat.key ]['raw'][stat.period_name] = float(stat.value)
+ stats_in_table = [x[0] for x in entries]
+ stats_not_in_table = set(graph_dict.keys()) - set(stats_in_table)
+ stats = stats_in_table + sorted(list(stats_not_in_table))
+ graph = [graph_dict[x] for x in stats]
+ setattr(c, v+'_graph', json.dumps( _to_rickshaw(graph,percentageMode=True) ))
+
+ # 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,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 ])
+
+ return render('ga_report/site/index.html')
+
+
+class GaDatasetReport(BaseController):
+ """
+ Displays the pageview and visit count for datasets
+ with options to filter by publisher and time period.
+ """
+ def publisher_csv(self, month):
+ '''
+ Returns a CSV of each publisher with the total number of dataset
+ views & visits.
+ '''
+ c.month = month if not month == 'all' else ''
+ response.headers['Content-Type'] = "text/csv; charset=utf-8"
+ response.headers['Content-Disposition'] = str('attachment; filename=publishers_%s.csv' % (month,))
+
+ writer = csv.writer(response)
+ writer.writerow(["Publisher Title", "Publisher Name", "Views", "Visits", "Period Name"])
+
+ top_publishers = _get_top_publishers(limit=None)
+
+ for publisher,view,visit in top_publishers:
+ writer.writerow([publisher.title.encode('utf-8'),
+ publisher.name.encode('utf-8'),
+ view,
+ visit,
+ month])
+
+ def dataset_csv(self, id='all', month='all'):
+ '''
+ Returns a CSV with the number of views & visits for each dataset.
+
+ :param id: A Publisher ID or None if you want for all
+ :param month: The time period, or 'all'
+ '''
+ c.month = month if not month == 'all' else ''
+ if id != 'all':
+ c.publisher = model.Group.get(id)
+ if not c.publisher:
+ abort(404, 'A publisher with that name could not be found')
+
+ packages = self._get_packages(publisher=c.publisher, month=c.month)
+ response.headers['Content-Type'] = "text/csv; charset=utf-8"
+ response.headers['Content-Disposition'] = \
+ str('attachment; filename=datasets_%s_%s.csv' % (c.publisher_name, month,))
+
+ writer = csv.writer(response)
+ 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):
+ '''A list of publishers and the number of views/visits for each'''
+
+ # Get the month details by fetching distinct values and determining the
+ # month names from the values.
+ 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', '')
+ c.month_desc = 'all months'
+ 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()
+ graph_data = _get_top_publishers_graph()
+ c.top_publishers_graph = json.dumps( _to_rickshaw(graph_data) )
+
+ return render('ga_report/publisher/index.html')
+
+ def _get_packages(self, publisher=None, month='', count=-1):
+ '''Returns the datasets in order of views'''
+ have_download_data = True
+ month = 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)\
+ .filter(GA_Url.url.like('/dataset/%'))
+ 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.pageviews::int desc')
+ top_packages = []
+ if count == -1:
+ entries = q.all()
+ else:
+ entries = q.limit(count)
+
+ for entry,package in entries:
+ if package:
+ # 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')
+
+ return top_packages
+
+ def read(self):
+ '''
+ Lists the most popular datasets across all publishers
+ '''
+ return self.read_publisher(None)
+
+ def read_publisher(self, id):
+ '''
+ Lists the most popular datasets for a publisher (or across all publishers)
+ '''
+ count = 20
+
+ c.publishers = _get_publishers()
+
+ id = request.params.get('publisher', id)
+ if id and id != 'all':
+ c.publisher = model.Group.get(id)
+ if not c.publisher:
+ abort(404, 'A publisher with that name could not be found')
+ c.publisher_name = c.publisher.name
+ c.top_packages = [] # package, dataset_views in c.top_packages
+
+ # Get the month details by fetching distinct values and determining the
+ # month names from the values.
+ 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', '')
+ if not c.month:
+ c.month_desc = 'all months'
+ else:
+ c.month_desc = ''.join([m[1] for m in c.months if m[0]==c.month])
+
+ month = c.month or 'All'
+ c.publisher_page_views = 0
+ q = model.Session.query(GA_Url).\
+ filter(GA_Url.url=='/publisher/%s' % c.publisher_name)
+ entry = q.filter(GA_Url.period_name==c.month).first()
+ c.publisher_page_views = entry.pageviews if entry else 0
+
+ c.top_packages = self._get_packages(publisher=c.publisher, count=20, month=c.month)
+
+ # Graph query
+ top_packages_all_time = self._get_packages(publisher=c.publisher, count=20, month='All')
+ top_package_names = [ x[0].name for x in top_packages_all_time ]
+ 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))
+ all_series = {}
+ for entry,package in graph_query:
+ if not package: continue
+ if entry.period_name=='All': continue
+ all_series[package.name] = all_series.get(package.name,{
+ 'name':package.title,
+ 'raw': {}
+ })
+ all_series[package.name]['raw'][entry.period_name] = int(entry.pageviews)
+ graph = [ all_series[series_name] for series_name in top_package_names ]
+ c.graph_data = json.dumps( _to_rickshaw(graph) )
+
+ return render('ga_report/publisher/read.html')
+
+def _to_rickshaw(data, percentageMode=False):
+ if data==[]:
+ return data
+ # x-axis is every month in c.months. Note that data might not exist
+ # for entire history, eg. for recently-added datasets
+ x_axis = [x[0] for x in c.months]
+ x_axis.reverse() # Ascending order
+ x_axis = x_axis[:-1] # Remove latest month
+ totals = {}
+ for series in data:
+ series['data'] = []
+ for x_string in x_axis:
+ x = _get_unix_epoch( x_string )
+ y = series['raw'].get(x_string,0)
+ series['data'].append({'x':x,'y':y})
+ totals[x] = totals.get(x,0)+y
+ if not percentageMode:
+ return data
+ # Turn all data into percentages
+ # Roll insignificant series into a catch-all
+ THRESHOLD = 1
+ raw_data = data
+ data = []
+ for series in raw_data:
+ for point in series['data']:
+ percentage = (100*float(point['y'])) / totals[point['x']]
+ if not (series in data) and percentage>THRESHOLD:
+ data.append(series)
+ point['y'] = percentage
+ others = [ x for x in raw_data if not (x in data) ]
+ if len(others):
+ data_other = []
+ for i in range(len(x_axis)):
+ x = _get_unix_epoch(x_axis[i])
+ y = 0
+ for series in others:
+ y += series['data'][i]['y']
+ data_other.append({'x':x,'y':y})
+ data.append({
+ 'name':'Other',
+ 'data': data_other
+ })
+ return data
+
+
+def _get_top_publishers(limit=20):
+ '''
+ Returns a list of the top 20 publishers by dataset visits.
+ (The number to show can be varied with 'limit')
+ '''
+ month = c.month or 'All'
+ connection = model.Session.connection()
+ q = """
+ select department_id, sum(pageviews::int) views, sum(visits::int) visits
+ from ga_url
+ where department_id <> ''
+ and package_id <> '