--- a/ckanext/ga_report/controller.py +++ b/ckanext/ga_report/controller.py @@ -191,32 +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 - 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) @@ -225,6 +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, + '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': @@ -305,7 +301,7 @@ 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_graph = json.dumps( _to_rickshaw(graph_data) ) return render('ga_report/publisher/index.html') @@ -397,34 +393,75 @@ .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 = {} + graph_dict = {} 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,{ + graph_dict[package.name] = graph_dict.get(package.name,{ 'name':package.title, 'data':[] }) - graph_data[package.id]['data'].append({ + graph_dict[package.name]['data'].append({ 'x':_get_unix_epoch(entry.period_name), 'y':int(entry.pageviews), }) - - c.graph_data = json.dumps( _to_rickshaw(graph_data.values()) ) + 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): - num_points = [] - for package in data: - package['data'] = sorted( package['data'], key=lambda x:x['x'] ) - num_points.append( len(package['data']) ) - if len(set(num_points))>1: - example = num_points[ num_points.index(max(num_points)) ] - for package in data: - while len(package['data'])<example: - package['data'].insert(0, package['data'][0]) +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): ''' @@ -454,7 +491,7 @@ department_ids.append(row[0]) top_publishers.append((g, row[1], row[2])) - graph = {} + graph = [] if limit is not None: # Query for a history graph of these publishers q = model.Session.query( @@ -466,15 +503,19 @@ .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[dept_id] = graph.get( dept_id, { + graph_dict[dept_id] = graph_dict.get( dept_id, { 'name' : model.Group.get(dept_id).title, 'data' : [] }) - graph[dept_id]['data'].append({ + 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