def get(self):
user = users.get_current_user()
# GA API Base parameters
kwargs = {
'ids' : 'ga:9060294', # comma-separated string of analytics accounts.
'start-index' : '1', # used in combination with max-results to pull more than 1000 entries, defaults to 1
}
# populate GA API parameters
kwargs['max-results'] = self.request.get('max-results','1000')
kwargs['dimensions'] = self.request.get('dimensions','')
kwargs['metrics'] = self.request.get('metrics','ga:visits')
kwargs['sort'] = self.request.get('sort','')
kwargs['filters'] = self.request.get('filters','')
if self.request.get('segment',''):
kwargs['segment'] = self.request.get('segment','')
# last year
d = datetime.date.today()
last_year = d.year - 1
kwargs['end-date'] = self.request.get('end-date', str(datetime.date(last_year, 12, 31)))
kwargs['start-date'] = self.request.get('start-date', str(datetime.date(last_year, 1, 1)))
# Search cache
cache_key = user.user_id() + str(kwargs)
total = memcache.get(cache_key)
if total is not None:
self.response.out.write('%.2f' % total)
return
logging.info('Cache Miss')
# Initialize a client to talk to Google Data API services.
auth_token = gdata.gauth.ae_load(user.user_id())
client = gdata.analytics.client.AnalyticsClient()
# Query GA API
try:
logging.debug(str(kwargs))
query = gdata.analytics.client.DataFeedQuery(kwargs)
feed = client.get_data_feed(query, auth_token)
except RequestError:
logging.error('RequestError:' + str(kwargs))
self.response.out.write(gviz_api.Error(reason='invalid_request',
message='Request Error',
tqx=self.request.get('tqx','out:json')))
return
except DownloadError:
# usually triggers for GA API timeouts
logging.error('DownloadError:' + str(kwargs))
self.response.out.write(gviz_api.Error(reason='internal_error',
message='API Timeout',
tqx=self.request.get('tqx','out:json')))
return
last_year_total = ''
if feed.entry:
# dispense title
for entry in feed.entry:
if entry.dimension:
for dimension in entry.dimension:
pass
for metric in entry.metric:
pass
break
# get visits
for entry in feed.entry:
if entry.dimension:
for dimension in entry.dimension:
pass
for metric in entry.metric:
last_year_total = int(metric.value)
in_million = last_year_total / 1000000
# Cache response
memcache.set(cache_key, in_million, 60*60*12)
# Write
self.response.out.write('%.2f' % in_million)
def get(self):
self.response.headers['Content-Type'] = 'application/json'
user = users.get_current_user()
# GA API Base parameters
kwargs = {
'ids' : 'ga:9060294', # comma-separated string of analytics accounts.
'start-index' : '1', # used in combination with max-results to pull more than 1000 entries, defaults to 1
}
# populate GA API parameters
kwargs['max-results'] = self.request.get('max-results','50')
kwargs['dimensions'] = self.request.get('dimensions','ga:keyword')
kwargs['metrics'] = self.request.get('metrics','ga:visits')
kwargs['sort'] = self.request.get('sort','-ga:visits')
kwargs['filters'] = self.request.get('filters','ga:keyword!~(not set)')
if self.request.get('segment',''):
kwargs['segment'] = self.request.get('segment','')
# last year
default_end_date = datetime.date.today()
kwargs['end-date'] = self.request.get('end-date', str(default_end_date))
default_start_date = datetime.date.fromordinal((default_end_date.toordinal() - default_end_date.day) + 1)
kwargs['start-date'] = self.request.get('start-date', str(default_start_date))
# Search cache
cache_key = user.user_id() + str(kwargs)
keywords = memcache.get(cache_key)
if keywords is not None:
self.response.out.write(simplejson.dumps(keywords))
return
logging.info('Cache Miss')
# Initialize a client to talk to Google Data API services.
auth_token = gdata.gauth.ae_load(user.user_id())
client = gdata.analytics.client.AnalyticsClient()
# Query GA API
try:
logging.debug(str(kwargs))
query = gdata.analytics.client.DataFeedQuery(kwargs)
feed = client.get_data_feed(query, auth_token)
except RequestError:
logging.error('RequestError:' + str(kwargs))
self.response.out.write(gviz_api.Error(reason='invalid_request',
message='Request Error',
tqx=self.request.get('tqx','out:json')))
return
except DownloadError:
# usually triggers for GA API timeouts
logging.error('DownloadError:' + str(kwargs))
self.response.out.write(gviz_api.Error(reason='internal_error',
message='API Timeout',
tqx=self.request.get('tqx','out:json')))
return
tag_cloud = []
if feed.entry:
# dispense title
for entry in feed.entry:
if entry.dimension:
for dimension in entry.dimension:
pass
for metric in entry.metric:
pass
break
# get visits
for entry in feed.entry:
row = {}
if entry.dimension:
for dimension in entry.dimension:
row['keyword'] = (dimension.value)
for metric in entry.metric:
row['visits'] = (metric.value)
tag_cloud.append(row)
ks = {}
ks['feed'] = tag_cloud
# Cache response
memcache.set(cache_key, ks, 60*60*12)
# Write
self.response.out.write(simplejson.dumps(ks))
def get(self):
self.response.headers['Content-Type'] = 'application/json'
user = users.get_current_user()
# GA API Base parameters
kwargs = {
'ids' : 'ga:9060294', # comma-separated string of analytics accounts.
'start-index' : '1', # used in combination with max-results to pull more than 1000 entries, defaults to 1
}
# populate GA API parameters
kwargs['max-results'] = self.request.get('max-results','1000')
kwargs['dimensions'] = self.request.get('dimensions','ga:date')
kwargs['metrics'] = self.request.get('metrics','ga:visits')
kwargs['sort'] = self.request.get('sort','')
kwargs['filters'] = self.request.get('filters','')
if self.request.get('segment',''):
kwargs['segment'] = self.request.get('segment','')
# current month
default_end_date = datetime.date.today()
kwargs['end-date'] = self.request.get('end-date', str(default_end_date))
default_start_date = datetime.date.fromordinal((default_end_date.toordinal() - default_end_date.day) + 1)
kwargs['start-date'] = self.request.get('start-date', str(default_start_date))
# Search cache
cache_key = user.user_id() + str(kwargs)
data_table = memcache.get(cache_key)
if data_table is not None:
self.response.out.write(data_table.ToResponse(tqx=self.request.get('tqx','out:json')))
return
logging.info('Cache Miss')
# Initialize a client to talk to Google Data API services.
auth_token = gdata.gauth.ae_load(user.user_id())
client = gdata.analytics.client.AnalyticsClient()
# Query GA API
try:
logging.debug(str(kwargs))
query = gdata.analytics.client.DataFeedQuery(kwargs)
feed = client.get_data_feed(query, auth_token)
except RequestError:
logging.error('RequestError:' + str(kwargs))
self.response.out.write(gviz_api.Error(reason='invalid_request',
message='Request Error',
tqx=self.request.get('tqx','out:json')))
return
except DownloadError:
# usually triggers for GA API timeouts
logging.error('DownloadError:' + str(kwargs))
self.response.out.write(gviz_api.Error(reason='internal_error',
message='API Timeout',
tqx=self.request.get('tqx','out:json')))
return
vcm = []
if feed.entry:
# dispense title
for entry in feed.entry:
if entry.dimension:
for dimension in entry.dimension:
pass
for metric in entry.metric:
pass
break
# populate data_table
for entry in feed.entry:
for metric in entry.metric:
vcm.append(int(metric.value))
# last month
default_end_date = datetime.date.today()
default_end_date = datetime.date.fromordinal(default_end_date.toordinal() - default_end_date.day)
kwargs['end-date'] = self.request.get('end-date', str(default_end_date))
default_start_date = datetime.date.fromordinal((default_end_date.toordinal() - default_end_date.day) + 1)
kwargs['start-date'] = self.request.get('start-date', str(default_start_date))
# Query GA API
try:
logging.debug(str(kwargs))
query = gdata.analytics.client.DataFeedQuery(kwargs)
feed = client.get_data_feed(query, auth_token)
except RequestError:
logging.error('RequestError:' + str(kwargs))
self.response.out.write(gviz_api.Error(reason='invalid_request',
message='Request Error',
tqx=self.request.get('tqx','out:json')))
return
except DownloadError:
# usually triggers for GA API timeouts
logging.error('DownloadError:' + str(kwargs))
self.response.out.write(gviz_api.Error(reason='internal_error',
message='API Timeout',
tqx=self.request.get('tqx','out:json')))
return
description = []
data = []
i = 0
description.append(tuple(['Dia','date']))
description.append(tuple([unicode(unquote('Visitas mês atual'), 'utf-8'),'number']))
description.append(tuple([unicode(unquote('Visitas mês anterior'), 'utf-8'),'number']))
if feed.entry:
# dispense title
for entry in feed.entry:
if entry.dimension:
for dimension in entry.dimension:
pass
for metric in entry.metric:
pass
break
# populate data_table
for entry in feed.entry:
ga_entry = []
if entry.dimension:
for dimension in entry.dimension:
if dimension.name == 'ga:date':
ga_entry.append(tuple([
datetime.datetime.strptime(dimension.value,'%Y%m%d'),
datetime.datetime.strptime(dimension.value,'%Y%m%d').strftime('%d')
]))
else:
ga_entry.append(dimension.value)
for metric in entry.metric:
try:
ga_entry.append(tuple([int(vcm[i]), splitThousands(vcm[i])]))
except:
ga_entry.append(0)
ga_entry.append(tuple([int(metric.value), splitThousands(metric.value)]))
i = i + 1
data.append(ga_entry)
# Init Viz
data_table = gviz_api.DataTable(description)
# Load data into viz
data_table.LoadData(data)
# Cache response
memcache.set(cache_key, data_table, 60*60*12)
# Write JSON
self.response.out.write(data_table.ToResponse(tqx=self.request.get('tqx','out:json')))