| import re | |
| import csv | |
| import sys | |
| import json | |
| import logging | import logging |
| from ckan.lib.base import BaseController, c, render | import operator |
| import report_model | 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') | 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): | 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): | 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) | |
| # 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).\ | |
| 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) | |
| # 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"]) | |
| for publisher,view,visit in _get_top_publishers(None): | |
| 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(c.publisher) | |
| 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() | |
| return render('ga_report/publisher/index.html') | |
| def _get_packages(self, publisher=None, count=-1): | |
| '''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)\ | |
| .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 ac |