[385] Use page_heading helper function consistently
--- 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,
@@ -20,7 +23,7 @@
import ckan.model as model
model.Session.remove()
model.Session.configure(bind=model.meta.engine)
- log = logging.getLogger('ckanext.ga-report')
+ log = logging.getLogger('ckanext.ga_report')
import ga_model
ga_model.init_tables()
@@ -53,26 +56,65 @@
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-DD - just data for all time periods going
- back to (and including) this date
+ 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)
+ self.parser.add_option('-d', '--delete-first',
+ action='store_true',
+ 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()
@@ -80,22 +122,31 @@
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 file here')
+ 'specified the correct token file in the CKAN config under '
+ '"googleanalytics.token.filepath"?')
return
- downloader = DownloadAnalytics(svc, profile_id=get_profile_id(svc))
+ downloader = DownloadAnalytics(svc, profile_id=get_profile_id(svc),
+ 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':
downloader.latest()
else:
- since_date = datetime.datetime.strptime(time_period, '%Y-%m-%d')
- downloader.since_date(since_date)
+ # The month to use
+ for_date = datetime.datetime.strptime(time_period, '%Y-%m')
+ downloader.specific_month(for_date)
--- a/ckanext/ga_report/controller.py
+++ b/ckanext/ga_report/controller.py
@@ -1,10 +1,541 @@
+import re
+import csv
+import sys
+import json
import logging
-from ckan.lib.base import BaseController, c, render
-import report_model
+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):
- return render('index.html')
-
+
+ # 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 <> ''
+ and url like '/dataset/%%'
+ and period_name=%s
+ group by department_id order by views desc
+ """
+ if limit:
+ q = q + " limit %s;" % (limit)
+
+ top_publishers = []
+ res = connection.execute(q, month)
+ for row in res:
+ g = model.Group.get(row[0])
+ if g:
+ top_publishers.append((g, row[1], row[2]))
+ return top_publishers
+
+
+def _get_top_publishers_graph(limit=20):
+ '''
+ Returns a list of the top 20 publishers by dataset visits.
+ (The number to show can be varied with 'limit')
+ '''
+ connection = model.Session.connection()
+ q = """
+ select department_id, sum(pageviews::int) views
+ from ga_url
+ where department_id <> ''
+ and package_id <> ''
+ and url like '/dataset/%%'
+ and period_name='All'
+ group by department_id order by views desc
+ """
+ if limit:
+ q = q + " limit %s;" % (limit)
+
+ res = connection.execute(q)
+ department_ids = [ row[0] for row in res ]
+
+ # Query for a history graph of these department ids
+ 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.url.like('/dataset/%') )\
+ .filter( GA_Url.package_id!='' )\
+ .group_by( GA_Url.department_id, GA_Url.period_name )
+ graph_dict = {}
+ for dept_id,period_name,views in q:
+ graph_dict[dept_id] = graph_dict.get( dept_id, {
+ 'name' : model.Group.get(dept_id).title,
+ 'raw' : {}
+ })
+ graph_dict[dept_id]['raw'][period_name] = views
+ return [ graph_dict[id] for id in department_ids ]
+
+
+def _get_publishers():
+ '''
+ Returns a list of all publishers. Each item is a tuple:
+ (name, title)
+ '''
+ publishers = []
+ for pub in model.Session.query(model.Group).\
+ filter(model.Group.type=='publisher').\
+ filter(model.Group.state=='active').\
+ order_by(model.Group.name):
+ publishers.append((pub.name, pub.title))
+ return publishers
+
+def _percent(num, total):
+ p = 100 * float(num)/float(total)
+ return "%.2f%%" % round(p, 2)
+