#167 Togglable graph legend. Disabled mouseover.
--- 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
@@ -21,6 +22,10 @@
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):
'''
@@ -107,11 +112,26 @@
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:
@@ -121,10 +141,18 @@
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))
- 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',
@@ -161,7 +189,22 @@
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)
+ # Run the query on all months to gather graph data
+ graph = {}
+ for stat in q:
+ graph[ stat.key ] = graph.get(stat.key,{
+ 'name':stat.key,
+ 'data': []
+ })
+ graph[ stat.key ]['data'].append({
+ 'x':_get_unix_epoch(stat.period_name),
+ 'y':float(stat.value)
+ })
+ setattr(c, v+'_graph', json.dumps( _to_rickshaw(graph.values(),percentageMode=True) ))
+
+ # Buffer the tabular data
if c.month:
entries = []
q = q.filter(GA_Stat.period_name==c.month).\
@@ -178,7 +221,7 @@
# 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 ])
@@ -203,7 +246,9 @@
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,
@@ -252,7 +297,9 @@
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.values()) )
+
return render('ga_report/publisher/index.html')
def _get_packages(self, publisher=None, count=-1):
@@ -284,8 +331,9 @@
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 = sum(int(d.value) for d in dls.all())
+ downloads = 0
+ for x in dls:
+ downloads += int(x.value)
else:
downloads = 'No data'
top_packages.append((package, entry.pageviews, entry.visits, downloads))
@@ -336,7 +384,78 @@
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_data = {}
+ for entry,package in graph_query:
+ if not package: continue
+ if entry.period_name=='All': continue
+ graph_data[package.id] = graph_data.get(package.id,{
+ 'name':package.title,
+ 'data':[]
+ })
+ graph_data[package.id]['data'].append({
+ 'x':_get_unix_epoch(entry.period_name),
+ 'y':int(entry.pageviews),
+ })
+
+ c.graph_data = json.dumps( _to_rickshaw(graph_data.values()) )
+
return render('ga_report/publisher/read.html')
+
+def _to_rickshaw(data, percentageMode=False):
+ if data==[]:
+ return data
+ # Create a consistent x-axis
+ num_points = [ len(package['data']) for package in data ]
+ ideal_index = num_points.index( max(num_points) )
+ x_axis = [ point['x'] for point in data[ideal_index]['data'] ]
+ for package in data:
+ xs = [ point['x'] for point in package['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)):
+ package['data'].append( {'x':x, 'y':0} )
+ assert len(package['data'])==len(x_axis), (len(package['data']),len(x_axis),package['data'],x_axis,set(x_axis).difference(set(xs)))
+ if percentageMode:
+ # Transform data into percentage stacks
+ totals = {}
+ for x in x_axis:
+ for package in data:
+ for point in package['data']:
+ totals[ point['x'] ] = totals.get(point['x'],0) + point['y']
+ # Roll insignificant series into a catch-all
+ THRESHOLD = 0.01
+ significant_series = []
+ for package in data:
+ for point in package['data']:
+ fraction = float(point['y']) / totals[point['x']]
+ if fraction>THRESHOLD and not (package in significant_series):
+ significant_series.append(package)
+ temp = {}
+ for package in data:
+ if package in significant_series: continue
+ for point in package['data']:
+ temp[point['x']] = temp.get(point['x'],0) + point['y']
+ catch_all = { 'name':'Other','data': [ {'x':x,'y':y} for x,y in temp.items() ] }
+ # Roll insignificant series into one
+ data = significant_series
+ data.append(catch_all)
+ # Turn each point into a percentage
+ for package in data:
+ for point in package['data']:
+ point['y'] = (point['y']*100) / totals[point['x']]
+ # Sort the points
+ for package in data:
+ package['data'] = sorted( package['data'], key=lambda x:x['x'] )
+ # Strip the latest month's incomplete analytics
+ package['data'] = package['data'][:-1]
+ return data
+
def _get_top_publishers(limit=20):
'''
@@ -359,11 +478,35 @@
top_publishers = []
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 )
+ for dept_id,period_name,views in q:
+ graph[dept_id] = graph.get( dept_id, {
+ 'name' : model.Group.get(dept_id).title,
+ 'data' : []
+ })
+ graph[dept_id]['data'].append({
+ 'x': _get_unix_epoch(period_name),
+ 'y': views
+ })
+ return top_publishers, graph
def _get_publishers():
--- /dev/null
+++ b/ckanext/ga_report/public/scripts/vendor/d3.layout.min.js
@@ -1,1 +1,1 @@
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