Merge branch 'master' of git+ssh://maxious.lambdacomplex.org/git/ckanext-ga-report
Merge branch 'master' of git+ssh://maxious.lambdacomplex.org/git/ckanext-ga-report

import re import re
import csv import csv
import sys import sys
import json import json
import logging import logging
import operator import operator
import collections import collections
from ckan.lib.base import (BaseController, c, g, render, request, response, abort) from ckan.lib.base import (BaseController, c, g, render, request, response, abort)
   
import sqlalchemy import sqlalchemy
from sqlalchemy import func, cast, Integer from sqlalchemy import func, cast, Integer
import ckan.model as model import ckan.model as model
from ga_model import GA_Url, GA_Stat, GA_ReferralStat, GA_Publisher from ga_model import GA_Url, GA_Stat, GA_ReferralStat, GA_Publisher
   
log = logging.getLogger('ckanext.ga-report') log = logging.getLogger('ckanext.ga-report')
   
DOWNLOADS_AVAILABLE_FROM = '2012-12' DOWNLOADS_AVAILABLE_FROM = '2012-12'
   
def _get_month_name(strdate): def _get_month_name(strdate):
import calendar import calendar
from time import strptime from time import strptime
d = strptime(strdate, '%Y-%m') d = strptime(strdate, '%Y-%m')
return '%s %s' % (calendar.month_name[d.tm_mon], d.tm_year) return '%s %s' % (calendar.month_name[d.tm_mon], d.tm_year)
   
def _get_unix_epoch(strdate): def _get_unix_epoch(strdate):
from time import strptime,mktime from time import strptime,mktime
d = strptime(strdate, '%Y-%m') d = strptime(strdate, '%Y-%m')
return int(mktime(d)) return int(mktime(d))
   
def _month_details(cls, stat_key=None): def _month_details(cls, stat_key=None):
''' '''
Returns a list of all the periods for which we have data, unfortunately 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 knows too much about the type of the cls being passed as GA_Url has a
more complex query more complex query
   
This may need extending if we add a period_name to the stats This may need extending if we add a period_name to the stats
''' '''
months = [] months = []
day = None day = None
   
q = model.Session.query(cls.period_name,cls.period_complete_day)\ q = model.Session.query(cls.period_name,cls.period_complete_day)\
.filter(cls.period_name!='All').distinct(cls.period_name) .filter(cls.period_name!='All').distinct(cls.period_name)
if stat_key: if stat_key:
q= q.filter(cls.stat_name==stat_key) q= q.filter(cls.stat_name==stat_key)
   
vals = q.order_by("period_name desc").all() vals = q.order_by("period_name desc").all()
   
if vals and vals[0][1]: if vals and vals[0][1]:
day = int(vals[0][1]) day = int(vals[0][1])
ordinal = 'th' if 11 <= day <= 13 \ ordinal = 'th' if 11 <= day <= 13 \
else {1:'st',2:'nd',3:'rd'}.get(day % 10, 'th') else {1:'st',2:'nd',3:'rd'}.get(day % 10, 'th')
day = "{day}{ordinal}".format(day=day, ordinal=ordinal) day = "{day}{ordinal}".format(day=day, ordinal=ordinal)
   
for m in vals: for m in vals:
months.append( (m[0], _get_month_name(m[0]))) months.append( (m[0], _get_month_name(m[0])))
   
return months, day return months, day
   
   
class GaReport(BaseController): class GaReport(BaseController):
   
def csv(self, month): def csv(self, month):
import csv import csv
   
q = model.Session.query(GA_Stat).filter(GA_Stat.stat_name!='Downloads') q = model.Session.query(GA_Stat).filter(GA_Stat.stat_name!='Downloads')
if month != 'all': if month != 'all':
q = q.filter(GA_Stat.period_name==month) q = q.filter(GA_Stat.period_name==month)
entries = q.order_by('GA_Stat.period_name, GA_Stat.stat_name, GA_Stat.key').all() 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-Type'] = "text/csv; charset=utf-8"
response.headers['Content-Disposition'] = str('attachment; filename=stats_%s.csv' % (month,)) response.headers['Content-Disposition'] = str('attachment; filename=stats_%s.csv' % (month,))
   
writer = csv.writer(response) writer = csv.writer(response)
writer.writerow(["Period", "Statistic", "Key", "Value"]) writer.writerow(["Period", "Statistic", "Key", "Value"])
   
for entry in entries: for entry in entries:
writer.writerow([entry.period_name.encode('utf-8'), writer.writerow([entry.period_name.encode('utf-8'),
entry.stat_name.encode('utf-8'), entry.stat_name.encode('utf-8'),
entry.key.encode('utf-8'), entry.key.encode('utf-8'),
entry.value.encode('utf-8')]) entry.value.encode('utf-8')])
   
   
def index(self): def index(self):
   
# Get the month details by fetching distinct values and determining the # Get the month details by fetching distinct values and determining the
# month names from the values. # month names from the values.
c.months, c.day = _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 # Work out which month to show, based on query params of the first item
c.month_desc = 'all months' c.month_desc = 'all months'
c.month = request.params.get('month', '') c.month = request.params.get('month', '')
if c.month: if c.month:
c.month_desc = ''.join([m[1] for m in c.months if m[0]==c.month]) c.month_desc = ''.join([m[1] for m in c.months if m[0]==c.month])
   
q = model.Session.query(GA_Stat).\ q = model.Session.query(GA_Stat).\
filter(GA_Stat.stat_name=='Totals') filter(GA_Stat.stat_name=='Totals')
if c.month: if c.month:
q = q.filter(GA_Stat.period_name==c.month) q = q.filter(GA_Stat.period_name==c.month)
entries = q.order_by('ga_stat.key').all() entries = q.order_by('ga_stat.key').all()
   
def clean_key(key, val): def clean_key(key, val):
if key in ['Average time on site', 'Pages per visit', 'New visits', 'Bounce rate (home page)']: if key in ['Average time on site', 'Pages per visit', 'New visits', 'Bounce rate (home page)']:
val = "%.2f" % round(float(val), 2) val = "%.2f" % round(float(val), 2)
if key == 'Average time on site': if key == 'Average time on site':
mins, secs = divmod(float(val), 60) mins, secs = divmod(float(val), 60)
hours, mins = divmod(mins, 60) hours, mins = divmod(mins, 60)
val = '%02d:%02d:%02d (%s seconds) ' % (hours, mins, secs, val) val = '%02d:%02d:%02d (%s seconds) ' % (hours, mins, secs, val)
if key in ['New visits','Bounce rate (home page)']: if key in ['New visits','Bounce rate (home page)']:
val = "%s%%" % val val = "%s%%" % val
if key in ['Total page views', 'Total visits']: if key in ['Total page views', 'Total visits']:
val = int(val) val = int(val)
   
return key, val return key, val
   
# Query historic values for sparkline rendering # Query historic values for sparkline rendering
sparkline_query = model.Session.query(GA_Stat)\ sparkline_query = model.Session.query(GA_Stat)\
.filter(GA_Stat.stat_name=='Totals')\ .filter(GA_Stat.stat_name=='Totals')\
.order_by(GA_Stat.period_name) .order_by(GA_Stat.period_name)
sparkline_data = {} sparkline_data = {}
for x in sparkline_query: for x in sparkline_query:
sparkline_data[x.key] = sparkline_data.get(x.key,[]) sparkline_data[x.key] = sparkline_data.get(x.key,[])
key, val = clean_key(x.key,float(x.value)) key, val = clean_key(x.key,float(x.value))
tooltip = '%s: %s' % (_get_month_name(x.period_name), val) tooltip = '%s: %s' % (_get_month_name(x.period_name), val)
sparkline_data[x.key].append( (tooltip,x.value) ) sparkline_data[x.key].append( (tooltip,x.value) )
# Trim the latest month, as it looks like a huge dropoff # Trim the latest month, as it looks like a huge dropoff
for key in sparkline_data: for key in sparkline_data:
sparkline_data[key] = sparkline_data[key][:-1] sparkline_data[key] = sparkline_data[key][:-1]
   
c.global_totals = [] c.global_totals = []
if c.month: if c.month:
for e in entries: for e in entries:
key, val = clean_key(e.key, e.value) key, val = clean_key(e.key, e.value)
sparkline = sparkline_data[e.key] sparkline = sparkline_data[e.key]
c.global_totals.append((key, val, sparkline)) c.global_totals.append((key, val, sparkline))
else: else:
d = collections.defaultdict(list) d = collections.defaultdict(list)
for e in entries: for e in entries:
d[e.key].append(float(e.value)) d[e.key].append(float(e.value))
for k, v in d.iteritems(): for k, v in d.iteritems():
if k in ['Total page views', 'Total visits']: if k in ['Total page views', 'Total visits']:
v = sum(v) v = sum(v)
else: else:
v = float(sum(v))/float(len(v)) v = float(sum(v))/float(len(v))
sparkline = sparkline_data[k] sparkline = sparkline_data[k]
key, val = clean_key(k,v) key, val = clean_key(k,v)
   
c.global_totals.append((key, val, sparkline)) c.global_totals.append((key, val, sparkline))
# Sort the global totals into a more pleasant order # Sort the global totals into a more pleasant order
def sort_func(x): def sort_func(x):
key = x[0] key = x[0]
total_order = ['Total page views','Total visits','Pages per visit'] total_order = ['Total page views','Total visits','Pages per visit']
if key in total_order: if key in total_order:
return total_order.index(key) return total_order.index(key)
return 999 return 999
c.global_totals = sorted(c.global_totals, key=sort_func) c.global_totals = sorted(c.global_totals, key=sort_func)
   
keys = { keys = {
'Browser versions': 'browser_versions', 'Browser versions': 'browser_versions',
'Browsers': 'browsers', 'Browsers': 'browsers',
'Operating Systems versions': 'os_versions', 'Operating Systems versions': 'os_versions',
'Operating Systems': 'os', 'Operating Systems': 'os',
'Social sources': 'social_networks', 'Social sources': 'social_networks',
'Languages': 'languages', 'Languages': 'languages',
'Country': 'country' 'Country': 'country'
} }
   
def shorten_name(name, length=60): def shorten_name(name, length=60):
return (name[:length] + '..') if len(name) > 60 else name return (name[:length] + '..') if len(name) > 60 else name
   
def fill_out_url(url): def fill_out_url(url):
import urlparse import urlparse
return urlparse.urljoin(g.site_url, url) return urlparse.urljoin(g.site_url, url)
   
c.social_referrer_totals, c.social_referrers = [], [] c.social_referrer_totals, c.social_referrers = [], []
q = model.Session.query(GA_ReferralStat) q = model.Session.query(GA_ReferralStat)
q = q.filter(GA_ReferralStat.period_name==c.month) if c.month else q q = q.filter(GA_ReferralStat.period_name==c.month) if c.month else q
q = q.order_by('ga_referrer.count::int desc') q = q.order_by('ga_referrer.count::int desc')
for entry in q.all(): for entry in q.all():
c.social_referrers.append((shorten_name(entry.url), fill_out_url(entry.url), c.social_referrers.append((shorten_name(entry.url), fill_out_url(entry.url),
entry.source,entry.count)) entry.source,entry.count))
   
q = model.Session.query(GA_ReferralStat.url, q = model.Session.query(GA_ReferralStat.url,
func.sum(GA_ReferralStat.count).label('count')) func.sum(GA_ReferralStat.count).label('count'))
q = q.filter(GA_ReferralStat.period_name==c.month) if c.month else q 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) q = q.order_by('count desc').group_by(GA_ReferralStat.url)
for entry in q.all(): for entry in q.all():
c.social_referrer_totals.append((shorten_name(entry[0]), fill_out_url(entry[0]),'', c.social_referrer_totals.append((shorten_name(entry[0]), fill_out_url(entry[0]),'',
entry[1])) entry[1]))
   
for k, v in keys.iteritems(): for k, v in keys.iteritems():
q = model.Session.query(GA_Stat).\ q = model.Session.query(GA_Stat).\
filter(GA_Stat.stat_name==k).\ filter(GA_Stat.stat_name==k).\
order_by(GA_Stat.period_name) order_by(GA_Stat.period_name)
# Buffer the tabular data # Buffer the tabular data
if c.month: if c.month:
entries = [] entries = []
q = q.filter(GA_Stat.period_name==c.month).\ q = q.filter(GA_Stat.period_name==c.month).\
order_by('ga_stat.value::int desc') order_by('ga_stat.value::int desc')
d = collections.defaultdict(int) d = collections.defaultdict(int)
for e in q.all(): for e in q.all():
d[e.key] += int(e.value) d[e.key] += int(e.value)
entries = [] entries = []
for key, val in d.iteritems(): for key, val in d.iteritems():
entries.append((key,val,)) entries.append((key,val,))
entries = sorted(entries, key=operator.itemgetter(1), reverse=True) entries = sorted(entries, key=operator.itemgetter(1), reverse=True)
   
# Run a query on all months to gather graph data # Run a query on all months to gather graph data
graph_query = model.Session.query(GA_Stat).\ graph_query = model.Session.query(GA_Stat).\
filter(GA_Stat.stat_name==k).\ filter(GA_Stat.stat_name==k).\
order_by(GA_Stat.period_name) order_by(GA_Stat.period_name)
graph_dict = {} graph_dict = {}
for stat in graph_query: for stat in graph_query:
graph_dict[ stat.key ] = graph_dict.get(stat.key,{ graph_dict[ stat.key ] = graph_dict.get(stat.key,{
'name':stat.key, 'name':stat.key,
'raw': {} 'raw': {}
}) })
graph_dict[ stat.key ]['raw'][stat.period_name] = float(stat.value) graph_dict[ stat.key ]['raw'][stat.period_name] = float(stat.value)
stats_in_table = [x[0] for x in entries] stats_in_table = [x[0] for x in entries]
stats_not_in_table = set(graph_dict.keys()) - set(stats_in_table) stats_not_in_table = set(graph_dict.keys()) - set(stats_in_table)
stats = stats_in_table + sorted(list(stats_not_in_table)) stats = stats_in_table + sorted(list(stats_not_in_table))
graph = [graph_dict[x] for x in stats] graph = [graph_dict[x] for x in stats]
setattr(c, v+'_graph', json.dumps( _to_rickshaw(graph,percentageMode=True) )) 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 # Get the total for each set of values and then set the value as
# a percentage of the total # a percentage of the total
if k == 'Social sources': if k == 'Social sources':
total = sum([x for n,x,graph in c.global_totals if n == 'Total visits']) total = sum([x for n,x,graph in c.global_totals if n == 'Total visits'])
else: else:
total = sum([num for _,num in entries]) total = sum([num for _,num in entries])
setattr(c, v, [(k,_percent(v,total)) for k,v in entries ]) setattr(c, v, [(k,_percent(v,total)) for k,v in entries ])
   
return render('ga_report/site/index.html') return render('ga_report/site/index.html')
   
   
class GaDatasetReport(BaseController): class GaDatasetReport(BaseController):
""" """
Displays the pageview and visit count for datasets Displays the pageview and visit count for datasets
with options to filter by publisher and time period. with options to filter by publisher and time period.
""" """
def publisher_csv(self, month): def publisher_csv(self, month):
''' '''
Returns a CSV of each publisher with the total number of dataset Returns a CSV of each publisher with the total number of dataset
views & visits. views & visits.
''' '''
c.month = month if not month == 'all' else '' c.month = month if not month == 'all' else ''
response.headers['Content-Type'] = "text/csv; charset=utf-8" response.headers['Content-Type'] = "text/csv; charset=utf-8"
response.headers['Content-Disposition'] = str('attachment; filename=publishers_%s.csv' % (month,)) response.headers['Content-Disposition'] = str('attachment; filename=publishers_%s.csv' % (month,))
   
writer = csv.writer(response) writer = csv.writer(response)
writer.writerow(["Publisher Title", "Publisher Name", "Views", "Visits", "Period Name"]) writer.writerow(["Publisher Title", "Publisher Name", "Views", "Visits", "Period Name"])
   
top_publishers = _get_top_publishers(limit=None) top_publishers = _get_top_publishers(limit=None)
   
for publisher,view,visit in top_publishers: for publisher,view,visit in top_publishers:
writer.writerow([publisher.title.encode('utf-8'), writer.writerow([publisher.title.encode('utf-8'),
publisher.name.encode('utf-8'), publisher.name.encode('utf-8'),
view, view,
visit, visit,
month]) month])
   
def dataset_csv(self, id='all', month='all'): def dataset_csv(self, id='all', month='all'):
''' '''
Returns a CSV with the number of views & visits for each dataset. 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 id: A Publisher ID or None if you want for all
:param month: The time period, or 'all' :param month: The time period, or 'all'
''' '''
c.month = month if not month == 'all' else '' c.month = month if not month == 'all' else ''
if id != 'all': if id != 'all':
c.publisher = model.Group.get(id) c.publisher = model.Group.get(id)
if not c.publisher: if not c.publisher:
abort(404, 'A publisher with that name could not be found') abort(404, 'A publisher with that name could not be found')
   
packages = self._get_packages(publisher=c.publisher, month=c.month) packages = self._get_packages(publisher=c.publisher, month=c.month)
response.headers['Content-Type'] = "text/csv; charset=utf-8" response.headers['Content-Type'] = "text/csv; charset=utf-8"
response.headers['Content-Disposition'] = \ response.headers['Content-Disposition'] = \
str('attachment; filename=datasets_%s_%s.csv' % (c.publisher_name, month,)) str('attachment; filename=datasets_%s_%s.csv' % (c.publisher_name, month,))
   
writer = csv.writer(response) writer = csv.writer(response)
writer.writerow(["Dataset Title", "Dataset Name", "Views", "Visits", "Resource downloads", "Period Name"]) writer.writerow(["Dataset Title", "Dataset Name", "Views", "Visits", "Resource downloads", "Period Name"])
   
for package,view,visit,downloads in packages: for package,view,visit,downloads in packages:
writer.writerow([package.title.encode('utf-8'), writer.writerow([package.title.encode('utf-8'),
package.name.encode('utf-8'), package.name.encode('utf-8'),
view, view,
visit, visit,
downloads, downloads,
month]) month])
   
def publishers(self): def publishers(self):
'''A list of publishers and the number of views/visits for each''' '''A list of publishers and the number of views/visits for each'''
   
# Get the month details by fetching distinct values and determining the # Get the month details by fetching distinct values and determining the
# month names from the values. # month names from the values.
c.months, c.day = _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 # Work out which month to show, based on query params of the first item
c.month = request.params.get('month', '') c.month = request.params.get('month', '')
c.month_desc = 'all months' c.month_desc = 'all months'
if c.month: if c.month:
c.month_desc = ''.join([m[1] for m in c.months if m[0]==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 = _get_top_publishers()
graph_data = _get_top_publishers_graph() graph_data = _get_top_publishers_graph()
c.top_publishers_graph = json.dumps( _to_rickshaw(graph_data) ) c.top_publishers_graph = json.dumps( _to_rickshaw(graph_data) )
   
x = render('ga_report/publisher/index.html') x = render('ga_report/publisher/index.html')
   
return x return x
   
def _get_packages(self, publisher=None, month='', count=-1): def _get_packages(self, publisher=None, month='', count=-1):
'''Returns the datasets in order of views''' '''Returns the datasets in order of views'''
have_download_data = True have_download_data = True
month = month or 'All' month = month or 'All'
if month != 'All': if month != 'All':
have_download_data = month >= DOWNLOADS_AVAILABLE_FROM have_download_data = month >= DOWNLOADS_AVAILABLE_FROM
   
q = model.Session.query(GA_Url,model.Package)\ q = model.Session.query(GA_Url,model.Package)\
.filter(model.Package.name==GA_Url.package_id)\ .filter(model.Package.name==GA_Url.package_id)\
.filter(GA_Url.url.like('/dataset/%')) .filter(GA_Url.url.like('/dataset/%'))
if publisher: if publisher:
q = q.filter(GA_Url.department_id==publisher.name) q = q.filter(GA_Url.department_id==publisher.name)
q = q.filter(GA_Url.period_name==month) q = q.filter(GA_Url.period_name==month)
q = q.order_by('ga_url.pageviews::int desc') q = q.order_by('ga_url.pageviews::int desc')
top_packages = [] top_packages = []
if count == -1: if count == -1:
entries = q.all() entries = q.all()
else: else:
entries = q.limit(count) entries = q.limit(count)
   
for entry,package in entries: for entry,package in entries:
if package: if package:
# Downloads .... # Downloads ....
if have_download_data: if have_download_data:
dls = model.Session.query(GA_Stat).\ dls = model.Session.query(GA_Stat).\
filter(GA_Stat.stat_name=='Downloads').\ filter(GA_Stat.stat_name=='Downloads').\
filter(GA_Stat.key==package.name) filter(GA_Stat.key==package.name)
if month != 'All': # Fetch everything unless the month is specific if month != 'All': # Fetch everything unless the month is specific
dls = dls.filter(GA_Stat.period_name==month) dls = dls.filter(GA_Stat.period_name==month)
downloads = 0 downloads = 0
for x in dls: for x in dls:
downloads += int(x.value) downloads += int(x.value)
else: else:
downloads = 'No data' downloads = 'No data'
top_packages.append((package, entry.pageviews, entry.visits, downloads)) if package.private == False:
  top_packages.append((package, entry.pageviews, entry.visits, downloads))
else: else:
log.warning('Could not find package associated package') log.warning('Could not find package associated package')
   
return top_packages return top_packages
   
def read(self): def read(self):
''' '''
Lists the most popular datasets across all publishers Lists the most popular datasets across all publishers
''' '''
return self.read_publisher(None) return self.read_publisher(None)
   
def read_publisher(self, id): def read_publisher(self, id):
''' '''
Lists the most popular datasets for a publisher (or across all publishers) Lists the most popular datasets for a publisher (or across all publishers)
''' '''
count = 20 count = 20
   
c.publishers = _get_publishers() c.publishers = _get_publishers()
   
id = request.params.get('publisher', id) id = request.params.get('publisher', id)
if id and id != 'all': if id and id != 'all':
c.publisher = model.Group.get(id) c.publisher = model.Group.get(id)
if not c.publisher: if not c.publisher:
abort(404, 'A publisher with that name could not be found') abort(404, 'A publisher with that name could not be found')
c.publisher_name = c.publisher.name c.publisher_name = c.publisher.name
c.top_packages = [] # package, dataset_views in c.top_packages c.top_packages = [] # package, dataset_views in c.top_packages
   
# Get the month details by fetching distinct values and determining the # Get the month details by fetching distinct values and determining the
# month names from the values. # month names from the values.
c.months, c.day = _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 # Work out which month to show, based on query params of the first item
c.month = request.params.get('month', '') c.month = request.params.get('month', '')
if not c.month: if not c.month:
c.month_desc = 'all months' c.month_desc = 'all months'
else: else:
c.month_desc = ''.join([m[1] for m in c.months if m[0]==c.month]) c.month_desc = ''.join([m[1] for m in c.months if m[0]==c.month])
   
month = c.month or 'All' month = c.month or 'All'
c.publisher_page_views = 0 c.publisher_page_views = 0
q = model.Session.query(GA_Url).\ q = model.Session.query(GA_Url).\
filter(GA_Url.url=='/publisher/%s' % c.publisher_name) filter(GA_Url.url=='/publisher/%s' % c.publisher_name)
entry = q.filter(GA_Url.period_name==c.month).first() entry = q.filter(GA_Url.period_name==c.month).first()
c.publisher_page_views = entry.pageviews if entry else 0 c.publisher_page_views = entry.pageviews if entry else 0
   
c.top_packages = self._get_packages(publisher=c.publisher, count=20, month=c.month) c.top_packages = self._get_packages(publisher=c.publisher, count=20, month=c.month)
   
# Graph query # Graph query
top_packages_all_time = self._get_packages(publisher=c.publisher, count=20, month='All') 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 ] top_package_names = [ x[0].name for x in top_packages_all_time ]
graph_query = model.Session.query(GA_Url,model.Package)\ graph_query = model.Session.query(GA_Url,model.Package)\
.filter(model.Package.name==GA_Url.package_id)\ .filter(model.Package.name==GA_Url.package_id)\
.filter(GA_Url.url.like('/dataset/%'))\ .filter(GA_Url.url.like('/dataset/%'))\
.filter(GA_Url.package_id.in_(top_package_names)) .filter(GA_Url.package_id.in_(top_package_names))
all_series = {} all_series = {}
for entry,package in graph_query: for entry,package in graph_query:
if not package: continue if not package: continue
if entry.period_name=='All': continue if entry.period_name=='All': continue
all_series[package.name] = all_series.get(package.name,{ all_series[package.name] = all_series.get(package.name,{
'name':package.title, 'name':package.title,
'raw': {} 'raw': {}
}) })
all_series[package.name]['raw'][entry.period_name] = int(entry.pageviews) all_series[package.name]['raw'][entry.period_name] = int(entry.pageviews)
graph = [ all_series[series_name] for series_name in top_package_names ] graph = [ all_series[series_name] for series_name in top_package_names ]
c.graph_data = json.dumps( _to_rickshaw(graph) ) c.graph_data = json.dumps( _to_rickshaw(graph) )
   
return render('ga_report/publisher/read.html') return render('ga_report/publisher/read.html')
   
def _to_rickshaw(data, percentageMode=False): def _to_rickshaw(data, percentageMode=False):
if data==[]: if data==[]:
return data return data
# x-axis is every month in c.months. Note that data might not exist # x-axis is every month in c.months. Note that data might not exist
# for entire history, eg. for recently-added datasets # for entire history, eg. for recently-added datasets
x_axis = [x[0] for x in c.months] x_axis = [x[0] for x in c.months]
x_axis.reverse() # Ascending order x_axis.reverse() # Ascending order
x_axis = x_axis[:-1] # Remove latest month x_axis = x_axis[:-1] # Remove latest month
totals = {} totals = {}
for series in data: for series in data:
series['data'] = [] series['data'] = []
for x_string in x_axis: for x_string in x_axis:
x = _get_unix_epoch( x_string ) x = _get_unix_epoch( x_string )
y = series['raw'].get(x_string,0) y = series['raw'].get(x_string,0)
series['data'].append({'x':x,'y':y}) series['data'].append({'x':x,'y':y})
totals[x] = totals.get(x,0)+y totals[x] = totals.get(x,0)+y
if not percentageMode: if not percentageMode:
return data return data
# Turn all data into percentages # Turn all data into percentages
# Roll insignificant series into a catch-all # Roll insignificant series into a catch-all
THRESHOLD = 1 THRESHOLD = 1
raw_data = data raw_data = data
data = [] data = []
for series in raw_data: for series in raw_data:
for point in series['data']: for point in series['data']:
percentage = (100*float(point['y'])) / totals[point['x']] percentage = (100*float(point['y'])) / totals[point['x']]
if not (series in data) and percentage>THRESHOLD: if not (series in data) and percentage>THRESHOLD:
data.append(series) data.append(series)
point['y'] = percentage point['y'] = percentage
others = [ x for x in raw_data if not (x in data) ] others = [ x for x in raw_data if not (x in data) ]
if len(others): if len(others):
data_other = [] data_other = []
for i in range(len(x_axis)): for i in range(len(x_axis)):
x = _get_unix_epoch(x_axis[i]) x = _get_unix_epoch(x_axis[i])
y = 0 y = 0
for series in others: for series in others:
y += series['data'][i]['y'] y += series['data'][i]['y']
data_other.append({'x':x,'y':y}) data_other.append({'x':x,'y':y})
data.append({ data.append({
'name':'Other', 'name':'Other',
'data': data_other 'data': data_other
}) })
return data return data
   
   
def _get_top_publishers(limit=20): def _get_top_publishers(limit=20):
''' '''
Returns a list of the top 20 publishers by dataset visits. Returns a list of the top 20 publishers by dataset visits.
(The number to show can be varied with 'limit') (The number to show can be varied with 'limit')
''' '''
month = c.month or 'All' month = c.month or 'All'
connection = model.Session.connection() connection = model.Session.connection()
q = """ q = """
select department_id, sum(pageviews::int) views, sum(visits::int) visits select department_id, sum(pageviews::int) views, sum(visits::int) visits
from ga_url from ga_url
where department_id <> '' where department_id <> ''
and package_id <> '' and package_id <> ''
and url like '/dataset/%%' and url like '/dataset/%%'
and period_name=%s and period_name=%s
group by department_id order by views desc group by department_id order by views desc
""" """
if limit: if limit:
q = q + " limit %s;" % (limit) q = q + " limit %s;" % (limit)
   
top_publishers = [] top_publishers = []
res = connection.execute(q, month) res = connection.execute(q, month)
for row in res: for row in res:
g = model.Group.get(row[0]) g = model.Group.get(row[0])
if g: if g:
top_publishers.append((g, row[1], row[2])) top_publishers.append((g, row[1], row[2]))
return top_publishers return top_publishers
   
   
def _get_top_publishers_graph(limit=20): def _get_top_publishers_graph(limit=20):
''' '''
Returns a list of the top 20 publishers by dataset visits. Returns a list of the top 20 publishers by dataset visits.
(The number to show can be varied with 'limit') (The number to show can be varied with 'limit')
''' '''
connection = model.Session.connection() connection = model.Session.connection()
q = """ q = """
select department_id, sum(pageviews::int) views select department_id, sum(pageviews::int) views
from ga_url from ga_url
where department_id <> '' where department_id <> ''
and package_id <> '' and package_id <> ''
and url like '/dataset/%%' and url like '/dataset/%%'
and period_name='All' and period_name='All'
group by department_id order by views desc group by department_id order by views desc
""" """
if limit: if limit:
q = q + " limit %s;" % (limit) q = q + " limit %s;" % (limit)
   
res = connection.execute(q) res = connection.execute(q)
department_ids = [ row[0] for row in res ] department_ids = [ row[0] for row in res ]
   
# Query for a history graph of these department ids # Query for a history graph of these department ids
q = model.Session.query( q = model.Session.query(
GA_Url.department_id, GA_Url.department_id,
GA_Url.period_name, GA_Url.period_name,
func.sum(cast(GA_Url.pageviews,sqlalchemy.types.INT)))\ func.sum(cast(GA_Url.pageviews,sqlalchemy.types.INT)))\
.filter( GA_Url.department_id.in_(department_ids) )\ .filter( GA_Url.department_id.in_(department_ids) )\
.filter( GA_Url.url.like('/dataset/%') )\ .filter( GA_Url.url.like('/dataset/%') )\
.filter( GA_Url.package_id!='' )\ .filter( GA_Url.package_id!='' )\
.group_by( GA_Url.department_id, GA_Url.period_name ) .group_by( GA_Url.department_id, GA_Url.period_name )
graph_dict = {} graph_dict = {}
for dept_id,period_name,views in q: for dept_id,period_name,views in q:
graph_dict[dept_id] = graph_dict.get( dept_id, { graph_dict[dept_id] = graph_dict.get( dept_id, {
'name' : model.Group.get(dept_id).title, 'name' : model.Group.get(dept_id).title,
'raw' : {} 'raw' : {}
}) })
graph_dict[dept_id]['raw'][period_name] = views graph_dict[dept_id]['raw'][period_name] = views
return [ graph_dict[id] for id in department_ids ] return [ graph_dict[id] for id in department_ids ]
   
   
def _get_publishers(): def _get_publishers():
''' '''
Returns a list of all publishers. Each item is a tuple: Returns a list of all publishers. Each item is a tuple:
(name, title) (name, title)
''' '''
publishers = [] publishers = []
for pub in model.Session.query(model.Group).\ for pub in model.Session.query(model.Group).\
filter(model.Group.type=='organization').\ filter(model.Group.type=='organization').\
filter(model.Group.state=='active').\ filter(model.Group.state=='active').\
order_by(model.Group.name): order_by(model.Group.name):
publishers.append((pub.name, pub.title)) publishers.append((pub.name, pub.title))
return publishers return publishers
   
def _percent(num, total): def _percent(num, total):
p = 100 * float(num)/float(total) p = 100 * float(num)/float(total)
return "%.2f%%" % round(p, 2) return "%.2f%%" % round(p, 2)
   
import logging import logging
import operator import operator
   
import ckan.lib.base as base import ckan.lib.base as base
import ckan.model as model import ckan.model as model
from ckan.logic import get_action from ckan.logic import get_action
   
from ckanext.ga_report.ga_model import GA_Url, GA_Publisher from ckanext.ga_report.ga_model import GA_Url, GA_Publisher
from ckanext.ga_report.controller import _get_publishers from ckanext.ga_report.controller import _get_publishers
_log = logging.getLogger(__name__) _log = logging.getLogger(__name__)
   
def popular_datasets(count=10): def popular_datasets(count=10):
import random import random
   
publisher = None publisher = None
publishers = _get_publishers(30) publishers = _get_publishers(30)
total = len(publishers) total = len(publishers)
while not publisher or not datasets: while not publisher or not datasets:
rand = random.randrange(0, total) rand = random.randrange(0, total)
publisher = publishers[rand][0] publisher = publishers[rand][0]
if not publisher.state == 'active': if not publisher.state == 'active':
publisher = None publisher = None
continue continue
datasets = _datasets_for_publisher(publisher, 10)[:count] datasets = _datasets_for_publisher(publisher, 10)[:count]
   
ctx = { ctx = {
'datasets': datasets, 'datasets': datasets,
'publisher': publisher 'publisher': publisher
} }
return base.render_snippet('ga_report/ga_popular_datasets.html', **ctx) return base.render_snippet('ga_report/ga_popular_datasets.html', **ctx)
   
def single_popular_dataset(top=20): def single_popular_dataset(top=20):
'''Returns a random dataset from the most popular ones. '''Returns a random dataset from the most popular ones.
   
:param top: the number of top datasets to select from :param top: the number of top datasets to select from
''' '''
import random import random
   
top_datasets = model.Session.query(GA_Url).\ top_datasets = model.Session.query(GA_Url).\
filter(GA_Url.url.like('/dataset/%')).\ filter(GA_Url.url.like('/dataset/%')).\
order_by('ga_url.pageviews::int desc') order_by('ga_url.pageviews::int desc')
num_top_datasets = top_datasets.count() num_top_datasets = top_datasets.count()
   
dataset = None dataset = None
if num_top_datasets: if num_top_datasets:
count = 0 count = 0
while not dataset: while not dataset:
rand = random.randrange(0, min(top, num_top_datasets)) rand = random.randrange(0, min(top, num_top_datasets))
ga_url = top_datasets[rand] ga_url = top_datasets[rand]
dataset = model.Package.get(ga_url.url[len('/dataset/'):]) dataset = model.Package.get(ga_url.url[len('/dataset/'):])
if dataset and not dataset.state == 'active': if dataset and not dataset.state == 'active':
dataset = None dataset = None
# When testing, it is possible that top datasets are not available # When testing, it is possible that top datasets are not available
# so only go round this loop a few times before falling back on # so only go round this loop a few times before falling back on
# a random dataset. # a random dataset.
count += 1 count += 1
if count > 10: if count > 10:
break break
if not dataset: if not dataset:
# fallback # fallback
dataset = model.Session.query(model.Package)\ dataset = model.Session.query(model.Package)\
.filter_by(state='active').first() .filter_by(state='active').first()
if not dataset: if not dataset:
return None return None
dataset_dict = get_action('package_show')({'model': model, dataset_dict = get_action('package_show')({'model': model,
'session': model.Session, 'session': model.Session,
'validate': False}, 'validate': False},
{'id':dataset.id}) {'id':dataset.id})
return dataset_dict return dataset_dict
   
def single_popular_dataset_html(top=20): def single_popular_dataset_html(top=20):
dataset_dict = single_popular_dataset(top) dataset_dict = single_popular_dataset(top)
groups = package.get('groups', []) groups = package.get('groups', [])
publishers = [ g for g in groups if g.get('type') == 'organization' ] publishers = [ g for g in groups if g.get('type') == 'organization' ]
publisher = publishers[0] if publishers else {'name':'', 'title': ''} publisher = publishers[0] if publishers else {'name':'', 'title': ''}
context = { context = {
'dataset': dataset_dict, 'dataset': dataset_dict,
'publisher': publisher_dict 'publisher': publisher_dict
} }
return base.render_snippet('ga_report/ga_popular_single.html', **context) return base.render_snippet('ga_report/ga_popular_single.html', **context)
   
   
def most_popular_datasets(publisher, count=20, preview_image=None): def most_popular_datasets(publisher, count=20, preview_image=None):
   
if not publisher: if not publisher:
_log.error("No valid publisher passed to 'most_popular_datasets'") _log.error("No valid publisher passed to 'most_popular_datasets'")
return "" return ""
   
results = _datasets_for_publisher(publisher, count) results = _datasets_for_publisher(publisher, count)
   
ctx = { ctx = {
'dataset_count': len(results), 'dataset_count': len(results),
'datasets': results, 'datasets': results,
   
'publisher': publisher, 'publisher': publisher,
'preview_image': preview_image 'preview_image': preview_image
} }
   
return base.render_snippet('ga_report/publisher/popular.html', **ctx) return base.render_snippet('ga_report/publisher/popular.html', **ctx)
   
def _datasets_for_publisher(publisher, count): def _datasets_for_publisher(publisher, count):
datasets = {} datasets = {}
entries = model.Session.query(GA_Url).\ entries = model.Session.query(GA_Url).\
filter(GA_Url.department_id==publisher.name).\ filter(GA_Url.department_id==publisher.name).\
filter(GA_Url.url.like('/dataset/%')).\ filter(GA_Url.url.like('/dataset/%')).\
order_by('ga_url.pageviews::int desc').all() order_by('ga_url.pageviews::int desc').all()
for entry in entries: for entry in entries:
if len(datasets) < count: if len(datasets) < count:
p = model.Package.get(entry.url[len('/dataset/'):]) p = model.Package.get(entry.url[len('/dataset/'):])
   
if not p: if not p:
_log.warning("Could not find Package for {url}".format(url=entry.url)) _log.warning("Could not find Package for {url}".format(url=entry.url))
continue continue
   
if not p.state == 'active': if not p.state == 'active':
_log.warning("Package {0} is not active, it is {1}".format(p.name, p.state)) _log.warning("Package {0} is not active, it is {1}".format(p.name, p.state))
continue continue
   
  if not p.private == False:
  _log.warning("Package {0} is private {1}".format(p.name, p.state))
  continue
   
if not p in datasets: if not p in datasets:
datasets[p] = {'views':0, 'visits': 0} datasets[p] = {'views':0, 'visits': 0}
   
datasets[p]['views'] = datasets[p]['views'] + int(entry.pageviews) datasets[p]['views'] = datasets[p]['views'] + int(entry.pageviews)
datasets[p]['visits'] = datasets[p]['visits'] + int(entry.visits) datasets[p]['visits'] = datasets[p]['visits'] + int(entry.visits)
   
results = [] results = []
for k, v in datasets.iteritems(): for k, v in datasets.iteritems():
results.append((k,v['views'],v['visits'])) results.append((k,v['views'],v['visits']))
   
return sorted(results, key=operator.itemgetter(1), reverse=True) return sorted(results, key=operator.itemgetter(1), reverse=True)
   
def month_option_title(month_iso, months, day): def month_option_title(month_iso, months, day):
month_isos = [ iso_code for (iso_code,name) in months ] month_isos = [ iso_code for (iso_code,name) in months ]
try: try:
index = month_isos.index(month_iso) index = month_isos.index(month_iso)
except ValueError: except ValueError:
_log.error('Month "%s" not found in list of months.' % month_iso) _log.error('Month "%s" not found in list of months.' % month_iso)
return month_iso return month_iso
month_name = months[index][1] month_name = months[index][1]
if index==0: if index==0:
return month_name + (' (up to %s)'%day) return month_name + (' (up to %s)'%day)
return month_name return month_name