| 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, |
| 'data': [] | 'raw': {} |
| }) | }) |
| graph_dict[ stat.key ]['data'].append({ | graph_dict[ stat.key ]['raw'][stat.period_name] = float(stat.value) |
| 'x':_get_unix_epoch(stat.period_name), | |
| 'y':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, top_publishers_graph = _get_top_publishers(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(c.publisher) | 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, graph_data = _get_top_publishers() | c.top_publishers = _get_top_publishers() |
| 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) ) |
| return render('ga_report/publisher/index.html') | x = render('ga_report/publisher/index.html') |
| def _get_packages(self, publisher=None, count=-1): | return x |
| 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 = c.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(c.publisher, 20) | c.top_packages = self._get_packages(publisher=c.publisher, count=20, month=c.month) |
| # Graph query | # Graph query |
| top_package_names = [ x[0].name for x in c.top_packages ] | 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)\ | 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)) |
| graph_dict = {} | 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 |
| graph_dict[package.name] = graph_dict.get(package.name,{ | all_series[package.name] = all_series.get(package.name,{ |
| 'name':package.title, | 'name':package.title, |
| 'data':[] | 'raw': {} |
| }) | }) |
| graph_dict[package.name]['data'].append({ | all_series[package.name]['raw'][entry.period_name] = int(entry.pageviews) |
| 'x':_get_unix_epoch(entry.period_name), | graph = [ all_series[series_name] for series_name in top_package_names ] |
| 'y':int(entry.pageviews), | |
| }) | |
| graph = [ graph_dict[x] for x 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 |
| # Create a consistent x-axis between all series | # x-axis is every month in c.months. Note that data might not exist |
| num_points = [ len(series['data']) for series in data ] | # for entire history, eg. for recently-added datasets |
| ideal_index = num_points.index( max(num_points) ) | x_axis = [x[0] for x in c.months] |
| x_axis = [] | x_axis.reverse() # Ascending order |
| x_axis = x_axis[:-1] # Remove latest month | |
| totals = {} | |
| for series in data: | 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']: | for point in series['data']: |
| x_axis.append(point['x']) | percentage = (100*float(point['y'])) / totals[point['x']] |
| x_axis = sorted( list( set(x_axis) ) ) | if not (series in data) and percentage>THRESHOLD: |
| # Zero pad any missing values | data.append(series) |
| for series in data: | point['y'] = percentage |
| xs = [ point['x'] for point in series['data'] ] | others = [ x for x in raw_data if not (x in data) ] |
| for x in set(x_axis).difference(set(xs)): | if len(others): |
| series['data'].append( {'x':x, 'y':0} ) | data_other = [] |
| if percentageMode: | for i in range(len(x_axis)): |
| def get_totals(series_list): | x = _get_unix_epoch(x_axis[i]) |
| totals = {} | y = 0 |
| for series in series_list: | for series in others: |
| for point in series['data']: | y += series['data'][i]['y'] |
| totals[point['x']] = totals.get(point['x'],0) + point['y'] | data_other.append({'x':x,'y':y}) |
| return totals | data.append({ |
| # Transform data into percentage stacks | 'name':'Other', |
| totals = get_totals(data) | 'data': data_other |
| # Roll insignificant series into a catch-all | }) |
| THRESHOLD = 0.01 | |
| raw_data = data | |
| data = [] | |
| for series in raw_data: | |
| for point in series['data']: | |
| fraction = float(point['y']) / totals[point['x']] | |
| if not (series in data) and fraction>THRESHOLD: | |
| data.append(series) | |
| # Overwrite data with a set of interesting series | |
| others = [ x for x in raw_data if not (x in data) ] | |
| if len(others): | |
| data.append({ | |
| 'name':'Other', | |
| 'data': [ {'x':x,'y':y} for x,y in get_totals(others).items() ] | |
| }) | |
| # Turn each point into a percentage | |
| for series in data: | |
| for point in series['data']: | |
| point['y'] = (point['y']*100) / totals[point['x']] | |
| # Sort the points | |
| for series in data: | |
| series['data'] = sorted( series['data'], key=lambda x:x['x'] ) | |
| # Strip the latest month's incomplete analytics | |
| series['data'] = series['data'][:-1] | |
| 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) |
| department_ids = [] | |
| for row in res: | for row in res: |
| g = model.Group.get(row[0]) | g = model.Group.get(row[0]) |
| if g: | if g: |
| department_ids.append(row[0]) | |
| top_publishers.append((g, row[1], row[2])) | 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 | def _get_top_publishers_graph(limit=20): |
| q = model.Session.query( | ''' |
| GA_Url.department_id, | Returns a list of the top 20 publishers by dataset visits. |
| GA_Url.period_name, | (The number to show can be varied with 'limit') |
| func.sum(cast(GA_Url.pageviews,sqlalchemy.types.INT)))\ | ''' |
| .filter( GA_Url.department_id.in_(department_ids) )\ | connection = model.Session.connection() |
| .filter( GA_Url.period_name!='All' )\ | q = """ |
| .filter( GA_Url.url.like('/dataset/%') )\ | select department_id, sum(pageviews::int) views |
| .filter( GA_Url.package_id!='' )\ | from ga_url |
| .group_by( GA_Url.department_id, GA_Url.period_name ) | where department_id <> '' |
| graph_dict = {} | and package_id <> '' |
| for dept_id,period_name,views in q: | and url like '/dataset/%%' |
| graph_dict[dept_id] = graph_dict.get( dept_id, { | and period_name='All' |
| 'name' : model.Group.get(dept_id).title, | group by department_id order by views desc |
| 'data' : [] | """ |
| }) | if limit: |
| graph_dict[dept_id]['data'].append({ | q = q + " limit %s;" % (limit) |
| 'x': _get_unix_epoch(period_name), | |
| 'y': views | res = connection.execute(q) |
| }) | department_ids = [ row[0] for row in res ] |
| # Sort dict into ordered list | |
| for id in department_ids: | # Query for a history graph of these department ids |
| graph.append( graph_dict[id] ) | q = model.Session.query( |
| return top_publishers, graph | 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(): | 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=='publisher').\ | 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) |