--- a/ckanext/ga_report/controller.py +++ b/ckanext/ga_report/controller.py @@ -1,6 +1,7 @@ import re import csv import sys +import json import logging import operator import collections @@ -9,10 +10,11 @@ import sqlalchemy from sqlalchemy import func, cast, Integer import ckan.model as model -from ga_model import GA_Url, GA_Stat, GA_ReferralStat +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 @@ -20,13 +22,39 @@ d = strptime(strdate, '%Y-%m') return '%s %s' % (calendar.month_name[d.tm_mon], d.tm_year) - -def _month_details(cls): +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 = [] - vals = model.Session.query(cls.period_name).filter(cls.period_name!='All').distinct().all() + 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 sorted(months, key=operator.itemgetter(0), reverse=True) + + return months, day class GaReport(BaseController): @@ -34,7 +62,7 @@ def csv(self, month): import csv - q = model.Session.query(GA_Stat) + 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() @@ -51,11 +79,12 @@ entry.key.encode('utf-8'), entry.value.encode('utf-8')]) + def index(self): # Get the month details by fetching distinct values and determining the # month names from the values. - c.months = _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 c.month_desc = 'all months' @@ -70,24 +99,39 @@ 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', 'Bounces']: + 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','Bounces']: + 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) - c.global_totals.append((key, val)) + sparkline = sparkline_data[e.key] + c.global_totals.append((key, val, sparkline)) else: d = collections.defaultdict(list) for e in entries: @@ -96,11 +140,19 @@ if k in ['Total page views', 'Total visits']: v = sum(v) else: - v = float(sum(v))/len(v) + v = float(sum(v))/float(len(v)) + sparkline = sparkline_data[k] key, val = clean_key(k,v) - c.global_totals.append((key, val)) - c.global_totals = sorted(c.global_totals, key=operator.itemgetter(0)) + 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', @@ -137,12 +189,13 @@ for k, v in keys.iteritems(): q = model.Session.query(GA_Stat).\ - filter(GA_Stat.stat_name==k) + 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) @@ -151,10 +204,27 @@ 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, + 'data': [] + }) + graph_dict[ stat.key ]['data'].append({ + 'x':_get_unix_epoch(stat.period_name), + 'y':float(stat.value) + }) + graph = [ graph_dict[x[0]] for x in entries ] + 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 in c.global_totals if n == 'Total visits']) + 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 ]) @@ -179,7 +249,9 @@ writer = csv.writer(response) writer.writerow(["Publisher Title", "Publisher Name", "Views", "Visits", "Period Name"]) - for publisher,view,visit in _get_top_publishers(None): + top_publishers, top_publishers_graph = _get_top_publishers(None) + + for publisher,view,visit in top_publishers: writer.writerow([publisher.title.encode('utf-8'), publisher.name.encode('utf-8'), view, @@ -205,13 +277,14 @@ str('attachment; filename=datasets_%s_%s.csv' % (c.publisher_name, month,)) writer = csv.writer(response) - writer.writerow(["Dataset Title", "Dataset Name", "Views", "Visits", "Period Name"]) - - for package,view,visit in packages: + 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): @@ -219,7 +292,7 @@ # Get the month details by fetching distinct values and determining the # month names from the values. - c.months = _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 c.month = request.params.get('month', '') @@ -227,16 +300,17 @@ 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() + c.top_publishers, graph_data = _get_top_publishers() + c.top_publishers_graph = json.dumps( _to_rickshaw(graph_data) ) return render('ga_report/publisher/index.html') def _get_packages(self, publisher=None, count=-1): - '''Returns the datasets in order of visits''' - if count == -1: - count = sys.maxint - + '''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)\ @@ -244,12 +318,28 @@ 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.visitors::int desc') + q = q.order_by('ga_url.pageviews::int desc') top_packages = [] - - for entry,package in q.limit(count): + if count == -1: + entries = q.all() + else: + entries = q.limit(count) + + for entry,package in entries: if package: - top_packages.append((package, entry.pageviews, entry.visitors)) + # 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') @@ -279,7 +369,7 @@ # Get the month details by fetching distinct values and determining the # month names from the values. - c.months = _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 c.month = request.params.get('month', '') @@ -288,7 +378,7 @@ else: c.month_desc = ''.join([m[1] for m in c.months if m[0]==c.month]) - month = c.mnth or 'All' + 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) @@ -297,45 +387,142 @@ c.top_packages = self._get_packages(c.publisher, 20) + # Graph query + top_package_names = [ x[0].name for x in c.top_packages ] + 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)) + graph_dict = {} + for entry,package in graph_query: + if not package: continue + if entry.period_name=='All': continue + graph_dict[package.name] = graph_dict.get(package.name,{ + 'name':package.title, + 'data':[] + }) + graph_dict[package.name]['data'].append({ + 'x':_get_unix_epoch(entry.period_name), + 'y':int(entry.pageviews), + }) + graph = [ graph_dict[x] for x 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 + # Create a consistent x-axis between all series + num_points = [ len(series['data']) for series in data ] + ideal_index = num_points.index( max(num_points) ) + x_axis = [ point['x'] for point in data[ideal_index]['data'] ] + for series in data: + xs = [ point['x'] for point in series['data'] ] + assert set(xs).issubset( set(x_axis) ), (xs, x_axis) + # Zero pad any missing values + for x in set(x_axis).difference(set(xs)): + series['data'].append( {'x':x, 'y':0} ) + if percentageMode: + def get_totals(series_list): + totals = {} + for series in series_list: + for point in series['data']: + totals[point['x']] = totals.get(point['x'],0) + point['y'] + lengths = [ len(series['data']) for series in series_list ] + assert len(set(lengths))==1 + assert lengths[0] == len(totals) + return totals + # Transform data into percentage stacks + totals = get_totals(data) + # 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 intereting series + others = [ x for x in raw_data if not (x in data) ] + 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 + 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(visitors::int) visits + select department_id, sum(pageviews::int) views, sum(visits::int) visits from ga_url - where department_id <> ''""" - if c.month: - q = q + """ - and period_name=%s - """ - q = q + """ - group by department_id order by visits desc + 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) - # Add this back (before and period_name =%s) if you want to ignore publisher - # homepage views - # and not url like '/publisher/%%' - top_publishers = [] - res = connection.execute(q, c.month) - + res = connection.execute(q, month) + department_ids = [] for row in res: g = model.Group.get(row[0]) if g: + department_ids.append(row[0]) 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 + 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.period_name!='All' )\ + .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, + 'data' : [] + }) + graph_dict[dept_id]['data'].append({ + 'x': _get_unix_epoch(period_name), + 'y': views + }) + # Sort dict into ordered list + for id in department_ids: + graph.append( graph_dict[id] ) + return top_publishers, graph + def _get_publishers(): ''' Returns a list of all publishers. Each item is a tuple: - (names, title) + (name, title) ''' publishers = [] for pub in model.Session.query(model.Group).\