[601] Make sure only active datasets are shown in popular datasets on publisher homepage
--- a/ckanext/ga_report/controller.py
+++ b/ckanext/ga_report/controller.py
@@ -191,25 +191,11 @@
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
- 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).\
order_by('ga_stat.value::int desc')
-
d = collections.defaultdict(int)
for e in q.all():
d[e.key] += int(e.value)
@@ -218,6 +204,23 @@
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,
+ 'raw': {}
+ })
+ graph_dict[ stat.key ]['raw'][stat.period_name] = float(stat.value)
+ stats_in_table = [x[0] for x in entries]
+ stats_not_in_table = set(graph_dict.keys()) - set(stats_in_table)
+ stats = stats_in_table + sorted(list(stats_not_in_table))
+ graph = [graph_dict[x] for x in stats]
+ 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':
@@ -246,7 +249,7 @@
writer = csv.writer(response)
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:
writer.writerow([publisher.title.encode('utf-8'),
@@ -268,7 +271,7 @@
if not c.publisher:
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-Disposition'] = \
str('attachment; filename=datasets_%s_%s.csv' % (c.publisher_name, month,))
@@ -297,15 +300,16 @@
if 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_graph = json.dumps( _to_rickshaw(graph_data.values()) )
+ c.top_publishers = _get_top_publishers()
+ graph_data = _get_top_publishers_graph()
+ 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):
+ def _get_packages(self, publisher=None, month='', count=-1):
'''Returns the datasets in order of views'''
have_download_data = True
- month = c.month or 'All'
+ month = month or 'All'
if month != 'All':
have_download_data = month >= DOWNLOADS_AVAILABLE_FROM
@@ -382,78 +386,71 @@
entry = q.filter(GA_Url.period_name==c.month).first()
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
- 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)\
.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 = {}
+ all_series = {}
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,{
+ all_series[package.name] = all_series.get(package.name,{
'name':package.title,
- 'data':[]
+ 'raw': {}
})
- 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()) )
+ all_series[package.name]['raw'][entry.period_name] = int(entry.pageviews)
+ graph = [ all_series[series_name] for series_name 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
- 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]
+ # x-axis is every month in c.months. Note that data might not exist
+ # for entire history, eg. for recently-added datasets
+ x_axis = [x[0] for x in c.months]
+ x_axis.reverse() # Ascending order
+ x_axis = x_axis[:-1] # Remove latest month
+ totals = {}
+ 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']:
+ percentage = (100*float(point['y'])) / totals[point['x']]
+ if not (series in data) and percentage>THRESHOLD:
+ data.append(series)
+ point['y'] = percentage
+ others = [ x for x in raw_data if not (x in data) ]
+ if len(others):
+ data_other = []
+ for i in range(len(x_axis)):
+ x = _get_unix_epoch(x_axis[i])
+ y = 0
+ for series in others:
+ y += series['data'][i]['y']
+ data_other.append({'x':x,'y':y})
+ data.append({
+ 'name':'Other',
+ 'data': data_other
+ })
return data
@@ -478,35 +475,51 @@
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]))
-
- 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
+ return top_publishers
+
+
+def _get_top_publishers_graph(limit=20):
+ '''
+ Returns a list of the top 20 publishers by dataset visits.
+ (The number to show can be varied with 'limit')
+ '''
+ connection = model.Session.connection()
+ q = """
+ select department_id, sum(pageviews::int) views
+ from ga_url
+ where department_id <> ''
+ and package_id <> ''
+ and url like '/dataset/%%'
+ and period_name='All'
+ group by department_id order by views desc
+ """
+ if limit:
+ q = q + " limit %s;" % (limit)
+
+ res = connection.execute(q)
+ department_ids = [ row[0] for row in res ]
+
+ # Query for a history graph of these department ids
+ 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.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():
--- a/ckanext/ga_report/public/scripts/vendor/d3.layout.min.js
+++ b/ckanext/ga_report/public/scripts/vendor/d3.layout.min.js
@@ -1,2 +1,1 @@
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