Only show the months for Downloads that we have
Only show the months for Downloads that we have

file:a/.gitignore -> file:b/.gitignore
*.py[co] *.py[co]
*.py~ *.py~
.gitignore .gitignore
  ckan.log
   
# Packages # Packages
*.egg *.egg
*.egg-info *.egg-info
dist dist
build build
eggs eggs
parts parts
bin bin
var var
sdist sdist
develop-eggs develop-eggs
.installed.cfg .installed.cfg
   
# Private info # Private info
credentials.json credentials.json
token.dat token.dat
   
# Installer logs # Installer logs
pip-log.txt pip-log.txt
   
# Unit test / coverage reports # Unit test / coverage reports
.coverage .coverage
.tox .tox
   
#Translations #Translations
*.mo *.mo
   
#Mr Developer #Mr Developer
.mr.developer.cfg .mr.developer.cfg
   
file:a/README.rst -> file:b/README.rst
ckanext-ga-report ckanext-ga-report
================= =================
   
**Status:** Development **Status:** Development
   
**CKAN Version:** 1.7.1+ **CKAN Version:** 1.7.1+
   
   
Overview Overview
-------- --------
   
For creating detailed reports of CKAN analytics, including totals per group. For creating detailed reports of CKAN analytics, including totals per group.
   
Whereas ckanext-googleanalytics focusses on providing page view stats a recent period and for all time (aimed at end users), ckanext-ga-report is more interested in building regular periodic reports (more for site managers to monitor). Whereas ckanext-googleanalytics focusses on providing page view stats a recent period and for all time (aimed at end users), ckanext-ga-report is more interested in building regular periodic reports (more for site managers to monitor).
   
Contents of this extension: Contents of this extension:
   
* Use the CLI tool to download Google Analytics data for each time period into this extension's database tables * Use the CLI tool to download Google Analytics data for each time period into this extension's database tables
   
* Users can view the data as web page reports * Users can view the data as web page reports
   
   
Installation Installation
------------ ------------
   
1. Activate you CKAN python environment and install this extension's software:: 1. Activate you CKAN python environment and install this extension's software::
   
$ pyenv/bin/activate $ pyenv/bin/activate
$ pip install -e git+https://github.com/okfn/ckanext-ga-report.git#egg=ckanext-ga-report $ pip install -e git+https://github.com/datagovuk/ckanext-ga-report.git#egg=ckanext-ga-report
   
2. Ensure you development.ini (or similar) contains the info about your Google Analytics account and configuration:: 2. Ensure you development.ini (or similar) contains the info about your Google Analytics account and configuration::
   
googleanalytics.id = UA-1010101-1 googleanalytics.id = UA-1010101-1
googleanalytics.account = Account name (i.e. data.gov.uk, see top level item at https://www.google.com/analytics) googleanalytics.account = Account name (e.g. data.gov.uk, see top level item at https://www.google.com/analytics)
  googleanalytics.token.filepath = ~/pyenv/token.dat
ga-report.period = monthly ga-report.period = monthly
  ga-report.bounce_url = /
   
Note that your credentials will be readable by system administrators on your server. Rather than use sensitive account details, it is suggested you give access to the GA account to a new Google account that you create just for this purpose. The ga-report.bounce_url specifies a particular path to record the bounce rate for. Typically it is / (the home page).
   
3. Set up this extension's database tables using a paster command. (Ensure your CKAN pyenv is still activated, run the command from ``src/ckanext-ga-report``, alter the ``--config`` option to point to your site config file):: 3. Set up this extension's database tables using a paster command. (Ensure your CKAN pyenv is still activated, run the command from ``src/ckanext-ga-report``, alter the ``--config`` option to point to your site config file)::
   
$ paster initdb --config=../ckan/development.ini $ paster initdb --config=../ckan/development.ini
   
4. Enable the extension in your CKAN config file by adding it to ``ckan.plugins``:: 4. Enable the extension in your CKAN config file by adding it to ``ckan.plugins``::
   
ckan.plugins = ga-report ckan.plugins = ga-report
   
  Problem shooting
  ----------------
   
  * ``(ProgrammingError) relation "ga_url" does not exist``
  This means that the ``paster initdb`` step has not been run successfully. Refer to the installation instructions for this extension.
   
   
Authorization Authorization
-------------- --------------
   
Before you can access the data, you need to set up the OAUTH details which you can do by following the `instructions <https://developers.google.com/analytics/resources/tutorials/hello-analytics-api>`_ the outcome of which will be a file called credentials.json which should look like credentials.json.template with the relevant fields completed. These steps are below for convenience: Before you can access the data, you need to set up the OAUTH details which you can do by following the `instructions <https://developers.google.com/analytics/resources/tutorials/hello-analytics-api>`_ the outcome of which will be a file called credentials.json which should look like credentials.json.template with the relevant fields completed. These steps are below for convenience:
   
1. Visit the `Google APIs Console <https://code.google.com/apis/console>`_ 1. Visit the `Google APIs Console <https://code.google.com/apis/console>`_
   
2. Sign-in and create a project or use an existing project. 2. Sign-in and create a project or use an existing project.
   
3. In the `Services pane <https://code.google.com/apis/console#:services>`_ , activate Analytics API for your project. If prompted, read and accept the terms of service. 3. In the `Services pane <https://code.google.com/apis/console#:services>`_ , activate Analytics API for your project. If prompted, read and accept the terms of service.
   
4. Go to the `API Access pane <https://code.google.com/apis/console/#:access>`_ 4. Go to the `API Access pane <https://code.google.com/apis/console/#:access>`_
   
5. Click Create an OAuth 2.0 client ID.... 5. Click Create an OAuth 2.0 client ID....
   
6. Fill out the Branding Information fields and click Next. 6. Fill out the Branding Information fields and click Next.
   
7. In Client ID Settings, set Application type to Installed application. 7. In Client ID Settings, set Application type to Installed application.
   
8. Click Create client ID 8. Click Create client ID
   
9. The details you need below are Client ID, Client secret, and Redirect URIs 9. The details you need below are Client ID, Client secret, and Redirect URIs
   
   
Once you have set up your credentials.json file you can generate an oauth token file by using the Once you have set up your credentials.json file you can generate an oauth token file by using the
following command, which will store your oauth token in a file called token.dat once you have finished following command, which will store your oauth token in a file called token.dat once you have finished
giving permission in the browser:: giving permission in the browser::
   
$ paster getauthtoken --config=../ckan/development.ini $ paster getauthtoken --config=../ckan/development.ini
   
  Now ensure you reference the correct path to your token.dat in your CKAN config file (e.g. development.ini)::
   
  googleanalytics.token.filepath = ~/pyenv/token.dat
   
   
Tutorial Tutorial
-------- --------
   
Download some GA data and store it in CKAN's db. (Ensure your CKAN pyenv is still activated, run the command from ``src/ckanext-ga-report``, alter the ``--config`` option to point to your site config file) and specifying the name of your auth file (token.dat by default) from the previous step:: Download some GA data and store it in CKAN's database. (Ensure your CKAN pyenv is still activated, run the command from ``src/ckanext-ga-report``, alter the ``--config`` option to point to your site config file) and specifying the name of your auth file (token.dat by default) from the previous step::
   
$ paster loadanalytics token.dat latest --config=../ckan/development.ini $ paster loadanalytics latest --config=../ckan/development.ini
   
The value after the token file is how much data you want to retrieve, this can be The value after the token file is how much data you want to retrieve, this can be
   
* **all** - data for all time (since 2010) * **all** - data for all time (since 2010)
   
* **latest** - (default) just the 'latest' data * **latest** - (default) just the 'latest' data
   
* **YYYY-MM-DD** - just data for all time periods going back to (and including) this date * **YYYY-MM-DD** - just data for all time periods going back to (and including) this date
   
   
   
Software Licence Software Licence
================ ================
   
This software is developed by Cabinet Office. It is Crown Copyright and opened up under the Open Government Licence (OGL) (which is compatible with Creative Commons Attibution License). This software is developed by Cabinet Office. It is Crown Copyright and opened up under the Open Government Licence (OGL) (which is compatible with Creative Commons Attibution License).
   
OGL terms: http://www.nationalarchives.gov.uk/doc/open-government-licence/ OGL terms: http://www.nationalarchives.gov.uk/doc/open-government-licence/
   
import logging import logging
import datetime import datetime
  import os
   
  from pylons import config
   
from ckan.lib.cli import CkanCommand from ckan.lib.cli import CkanCommand
# No other CKAN imports allowed until _load_config is run, # No other CKAN imports allowed until _load_config is run,
# or logging is disabled # or logging is disabled
   
   
class InitDB(CkanCommand): class InitDB(CkanCommand):
"""Initialise the extension's database tables """Initialise the extension's database tables
""" """
summary = __doc__.split('\n')[0] summary = __doc__.split('\n')[0]
usage = __doc__ usage = __doc__
max_args = 0 max_args = 0
min_args = 0 min_args = 0
   
def command(self): def command(self):
self._load_config() self._load_config()
   
import ckan.model as model import ckan.model as model
model.Session.remove() model.Session.remove()
model.Session.configure(bind=model.meta.engine) model.Session.configure(bind=model.meta.engine)
log = logging.getLogger('ckanext.ga-report') log = logging.getLogger('ckanext.ga-report')
   
import ga_model import ga_model
ga_model.init_tables() ga_model.init_tables()
log.info("DB tables are setup") log.info("DB tables are setup")
   
   
class GetAuthToken(CkanCommand): class GetAuthToken(CkanCommand):
""" Get's the Google auth token """ Get's the Google auth token
   
Usage: paster getauthtoken <credentials_file> Usage: paster getauthtoken <credentials_file>
   
Where <credentials_file> is the file name containing the details Where <credentials_file> is the file name containing the details
for the service (obtained from https://code.google.com/apis/console). for the service (obtained from https://code.google.com/apis/console).
By default this is set to credentials.json By default this is set to credentials.json
""" """
summary = __doc__.split('\n')[0] summary = __doc__.split('\n')[0]
usage = __doc__ usage = __doc__
max_args = 0 max_args = 0
min_args = 0 min_args = 0
   
def command(self): def command(self):
""" """
In this case we don't want a valid service, but rather just to In this case we don't want a valid service, but rather just to
force the user through the auth flow. We allow this to complete to force the user through the auth flow. We allow this to complete to
act as a form of verification instead of just getting the token and act as a form of verification instead of just getting the token and
assuming it is correct. assuming it is correct.
""" """
from ga_auth import init_service from ga_auth import init_service
init_service('token.dat', init_service('token.dat',
self.args[0] if self.args self.args[0] if self.args
else 'credentials.json') else 'credentials.json')
   
   
class LoadAnalytics(CkanCommand): class LoadAnalytics(CkanCommand):
"""Get data from Google Analytics API and save it """Get data from Google Analytics API and save it
in the ga_model in the ga_model
   
Usage: paster loadanalytics <tokenfile> <time-period> Usage: paster loadanalytics <time-period>
   
Where <tokenfile> is the name of the auth token file from Where <time-period> is:
the getauthtoken step.  
   
And where <time-period> is:  
all - data for all time all - data for all time
latest - (default) just the 'latest' data latest - (default) just the 'latest' data
YYYY-MM-DD - just data for all time periods going YYYY-MM - just data for the specific month
back to (and including) this date  
""" """
summary = __doc__.split('\n')[0] summary = __doc__.split('\n')[0]
usage = __doc__ usage = __doc__
max_args = 2 max_args = 1
min_args = 1 min_args = 0
   
  def __init__(self, name):
  super(LoadAnalytics, self).__init__(name)
  self.parser.add_option('-d', '--delete-first',
  action='store_true',
  default=False,
  dest='delete_first',
  help='Delete data for the period first')
  self.parser.add_option('-s', '--skip_url_stats',
  action='store_true',
  default=False,
  dest='skip_url_stats',
  help='Skip the download of URL data - just do site-wide stats')
   
def command(self): def command(self):
self._load_config() self._load_config()
   
from download_analytics import DownloadAnalytics from download_analytics import DownloadAnalytics
from ga_auth import (init_service, get_profile_id) from ga_auth import (init_service, get_profile_id)
   
  ga_token_filepath = os.path.expanduser(config.get('googleanalytics.token.filepath', ''))
  if not ga_token_filepath:
  print 'ERROR: In the CKAN config you need to specify the filepath of the ' \
  'Google Analytics token file under key: googleanalytics.token.filepath'
  return
   
try: try:
svc = init_service(self.args[0], None) svc = init_service(ga_token_filepath, None)
except TypeError: except TypeError:
print ('Have you correctly run the getauthtoken task and ' print ('Have you correctly run the getauthtoken task and '
'specified the correct file here') 'specified the correct token file in the CKAN config under '
  '"googleanalytics.token.filepath"?')
return return
   
downloader = DownloadAnalytics(svc, profile_id=get_profile_id(svc)) downloader = DownloadAnalytics(svc, profile_id=get_profile_id(svc),
  delete_first=self.options.delete_first,
  skip_url_stats=self.options.skip_url_stats)
   
time_period = self.args[1] if self.args and len(self.args) > 1 \ time_period = self.args[0] if self.args else 'latest'
else 'latest'  
if time_period == 'all': if time_period == 'all':
downloader.all_() downloader.all_()
elif time_period == 'latest': elif time_period == 'latest':
downloader.latest() downloader.latest()
else: else:
since_date = datetime.datetime.strptime(time_period, '%Y-%m-%d') # The month to use
downloader.since_date(since_date) for_date = datetime.datetime.strptime(time_period, '%Y-%m')
  downloader.specific_month(for_date)
   
  import re
  import csv
  import sys
import logging import logging
from ckan.lib.base import BaseController, c, render import operator
import report_model import collections
  from ckan.lib.base import (BaseController, c, g, render, request, response, abort)
   
  import sqlalchemy
  from sqlalchemy import func, cast, Integer
  import ckan.model as model
  from ga_model import GA_Url, GA_Stat, GA_ReferralStat, GA_Publisher
   
log = logging.getLogger('ckanext.ga-report') log = logging.getLogger('ckanext.ga-report')
   
   
  def _get_month_name(strdate):
  import calendar
  from time import strptime
  d = strptime(strdate, '%Y-%m')
  return '%s %s' % (calendar.month_name[d.tm_mon], d.tm_year)
   
   
  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 = []
  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 months, day
   
   
class GaReport(BaseController): class GaReport(BaseController):
   
  def csv(self, month):
  import csv
   
  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()
   
  response.headers['Content-Type'] = "text/csv; charset=utf-8"
  response.headers['Content-Disposition'] = str('attachment; filename=stats_%s.csv' % (month,))
   
  writer = csv.writer(response)
  writer.writerow(["Period", "Statistic", "Key", "Value"])
   
  for entry in entries:
  writer.writerow([entry.period_name.encode('utf-8'),
  entry.stat_name.encode('utf-8'),
  entry.key.encode('utf-8'),
  entry.value.encode('utf-8')])
   
  def csv_downloads(self, month):
  import csv
   
  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.key').all()
   
  response.headers['Content-Type'] = "text/csv; charset=utf-8"
  response.headers['Content-Disposition'] = str('attachment; filename=downloads_%s.csv' % (month,))
   
  writer = csv.writer(response)
  writer.writerow(["Period", "Resource URL", "Count"])
   
  for entry in entries:
  writer.writerow([entry.period_name.encode('utf-8'),
  entry.key.encode('utf-8'),
  entry.value.encode('utf-8')])
   
   
def index(self): def index(self):
return render('index.html')  
  # Get the month details by fetching distinct values and determining the
  # month names from the values.
  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'
  c.month = request.params.get('month', '')
  if c.month:
  c.month_desc = ''.join([m[1] for m in c.months if m[0]==c.month])
   
  q = model.Session.query(GA_Stat).\
  filter(GA_Stat.stat_name=='Totals')
  if c.month:
  q = q.filter(GA_Stat.period_name==c.month)
  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', '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','Bounce rate (home page)']:
  val = "%s%%" % val
  if key in ['Total page views', 'Total visits']:
  val = int(val)
   
  return key, val
   
  c.global_totals = []
  if c.month:
  for e in entries:
  key, val = clean_key(e.key, e.value)
  c.global_totals.append((key, val))
  else:
  d = collections.defaultdict(list)
  for e in entries:
  d[e.key].append(float(e.value))
  for k, v in d.iteritems():
  if k in ['Total page views', 'Total visits']:
  v = sum(v)
  else:
  v = float(sum(v))/float(len(v))
  key, val = clean_key(k,v)
   
  c.global_totals.append((key, val))
  c.global_totals = sorted(c.global_totals, key=operator.itemgetter(0))
   
  keys = {
  'Browser versions': 'browser_versions',
  'Browsers': 'browsers',
  'Operating Systems versions': 'os_versions',
  'Operating Systems': 'os',
  'Social sources': 'social_networks',
  'Languages': 'languages',
  'Country': 'country'
  }
   
  def shorten_name(name, length=60):
  return (name[:length] + '..') if len(name) > 60 else name
   
  def fill_out_url(url):
  import urlparse
  return urlparse.urljoin(g.site_url, url)
   
  c.social_referrer_totals, c.social_referrers = [], []
  q = model.Session.query(GA_ReferralStat)
  q = q.filter(GA_ReferralStat.period_name==c.month) if c.month else q
  q = q.order_by('ga_referrer.count::int desc')
  for entry in q.all():
  c.social_referrers.append((shorten_name(entry.url), fill_out_url(entry.url),
  entry.source,entry.count))
   
  q = model.Session.query(GA_ReferralStat.url,
  func.sum(GA_ReferralStat.count).label('count'))
  q = q.filter(GA_ReferralStat.period_name==c.month) if c.month else q
  q = q.order_by('count desc').group_by(GA_ReferralStat.url)
  for entry in q.all():
  c.social_referrer_totals.append((shorten_name(entry[0]), fill_out_url(entry[0]),'',
  entry[1]))
   
  for k, v in keys.iteritems():
  q = model.Session.query(GA_Stat).\
  filter(GA_Stat.stat_name==k)
  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)
  entries = []
  for key, val in d.iteritems():
  entries.append((key,val,))
  entries = sorted(entries, key=operator.itemgetter(1), reverse=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'])
  else:
  total = sum([num for _,num in entries])
  setattr(c, v, [(k,_percent(v,total)) for k,v in entries ])
   
  return render('ga_report/site/index.html')
   
  def downloads(self):
   
  # Get the month details by fetching distinct values and determining the
  # month names from the values.
  c.months, c.day = _month_details(GA_Stat, "Downloads")
   
  # Work out which month to show, based on query params of the first item
  c.month_desc = 'all months'
  c.month = request.params.get('month', '')
  if c.month:
  c.month_desc = ''.join([m[1] for m in c.months if m[0]==c.month])
   
  c.downloads = []
  q = model.Session.query(GA_Stat).filter(GA_Stat.stat_name=='Downloads')
  q = q.filter(GA_Stat.period_name==c.month) if c.month else q
  q = q.order_by("ga_stat.value::int desc")
   
  data = collections.defaultdict(int)
  for entry in q.all():
  r = model.Session.query(model.Resource).filter(model.Resource.url==entry.key).first()
  if not r:
  continue
  data[r] += int(entry.value)
   
  c.downloads = [(k,v,) for k,v in data.iteritems()]
  c.downloads = sorted(c.downloads, key=operator.itemgetter(1), reverse=True)
   
  return render('ga_report/site/downloads.html')
   
   
  class GaDatasetReport(BaseController):
  """
  Displays the pageview and visit count for datasets
  with options to filter by publisher and time period.
  """
  def publisher_csv(self, month):
  '''
  Returns a CSV of each publisher with the total number of dataset
  views & visits.
  '''
  c.month = month if not month == 'all' else ''
  response.headers['Content-Type'] = "text/csv; charset=utf-8"
  response.headers['Content-Disposition'] = str('attachment; filename=publishers_%s.csv' % (month,))
   
  writer = csv.writer(response)
  writer.writerow(["Publisher Title", "Publisher Name", "Views", "Visits", "Period Name"])
   
  for publisher,view,visit in _get_top_publishers(None):
  writer.writerow([publisher.title.encode('utf-8'),
  publisher.name.encode('utf-8'),
  view,
  visit,
  month])
   
  def dataset_csv(self, id='all', month='all'):
  '''
  Returns a CSV with the number of views & visits for each dataset.
   
  :param id: A Publisher ID or None if you want for all
  :param month: The time period, or 'all'
  '''
  c.month = month if not month == 'all' else ''
  if id != 'all':
  c.publisher = model.Group.get(id)
  if not c.publisher:
  abort(404, 'A publisher with that name could not be found')
   
  packages = self._get_packages(c.publisher)
  response.headers['Content-Type'] = "text/csv; charset=utf-8"
  response.headers['Content-Disposition'] = \
  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([package.title.encode('utf-8'),
  package.name.encode('utf-8'),
  view,
  visit,
  month])
   
  def publishers(self):
  '''A list of publishers and the number of views/visits for each'''
   
  # Get the month details by fetching distinct values and determining the
  # month names from the values.
  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', '')
  c.month_desc = 'all months'
  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()
  return render('ga_report/publisher/index.html')
   
  def _get_packages(self, publisher=None, count=-1):
  '''Returns the datasets in order of views'''
  if count == -1:
  count = sys.maxint
   
  month = c.month or 'All'
   
  q = model.Session.query(GA_Url,model.Package)\
  .filter(model.Package.name==GA_Url.package_id)\
  .filter(GA_Url.url.like('/dataset/%'))
  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.pageviews::int desc')
  top_packages = []
  for entry,package in q.limit(count):
  if package:
  top_packages.append((package, entry.pageviews, entry.visits))
  else:
  log.warning('Could not find package associated package')
   
  return top_packages
   
  def read(self):
  '''
  Lists the most popular datasets across all publishers
  '''
  return self.read_publisher(None)
   
  def read_publisher(self, id):
  '''
  Lists the most popular datasets for a publisher (or across all publishers)
  '''
  count = 20
   
  c.publishers = _get_publishers()
   
  id = request.params.get('publisher', id)
  if id and id != 'all':
  c.publisher = model.Group.get(id)
  if not c.publisher:
  abort(404, 'A publisher with that name could not be found')
  c.publisher_name = c.publisher.name
  c.top_packages = [] # package, dataset_views in c.top_packages
   
  # Get the month details by fetching distinct values and determining the
  # month names from the values.
  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', '')
  if not c.month:
  c.month_desc = 'all months'
  else:
  c.month_desc = ''.join([m[1] for m in c.months if m[0]==c.month])
   
  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)
  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)
   
  return render('ga_report/publisher/read.html')
   
  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(visits::int) visits
  from ga_url
  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)
   
  top_publishers = []
  res = connection.execute(q, month)
  for row in res:
  g = model.Group.get(row[0])
  if g:
  top_publishers.append((g, row[1], row[2]))
  return top_publishers
   
   
  def _get_publishers():
  '''
  Returns a list of all publishers. Each item is a tuple:
  (name, title)
  '''
  publishers = []
  for pub in model.Session.query(model.Group).\
  filter(model.Group.type=='publisher').\
  filter(model.Group.state=='active').\
  order_by(model.Group.name):
  publishers.append((pub.name, pub.title))
  return publishers
   
  def _percent(num, total):
  p = 100 * float(num)/float(total)
  return "%.2f%%" % round(p, 2)
   
import os import os
import logging import logging
import datetime import datetime
  import collections
from pylons import config from pylons import config
  from ga_model import _normalize_url
import ga_model import ga_model
   
#from ga_client import GA #from ga_client import GA
   
log = logging.getLogger('ckanext.ga-report') log = logging.getLogger('ckanext.ga-report')
   
FORMAT_MONTH = '%Y-%m' FORMAT_MONTH = '%Y-%m'
  MIN_VIEWS = 50
  MIN_VISITS = 20
  MIN_DOWNLOADS = 10
   
class DownloadAnalytics(object): class DownloadAnalytics(object):
'''Downloads and stores analytics info''' '''Downloads and stores analytics info'''
   
def __init__(self, service=None, profile_id=None): def __init__(self, service=None, profile_id=None, delete_first=False,
  skip_url_stats=False):
self.period = config['ga-report.period'] self.period = config['ga-report.period']
self.service = service self.service = service
self.profile_id = profile_id self.profile_id = profile_id
  self.delete_first = delete_first
  self.skip_url_stats = skip_url_stats
def all_(self):  
self.since_date(datetime.datetime(2010, 1, 1)) def specific_month(self, date):
  import calendar
   
  first_of_this_month = datetime.datetime(date.year, date.month, 1)
  _, last_day_of_month = calendar.monthrange(int(date.year), int(date.month))
  last_of_this_month = datetime.datetime(date.year, date.month, last_day_of_month)
  periods = ((date.strftime(FORMAT_MONTH),
  last_day_of_month,
  first_of_this_month, last_of_this_month),)
  self.download_and_store(periods)
   
   
def latest(self): def latest(self):
if self.period == 'monthly': if self.period == 'monthly':
# from first of this month to today # from first of this month to today
now = datetime.datetime.now() now = datetime.datetime.now()
first_of_this_month = datetime.datetime(now.year, now.month, 1) first_of_this_month = datetime.datetime(now.year, now.month, 1)
periods = ((now.strftime(FORMAT_MONTH), periods = ((now.strftime(FORMAT_MONTH),
now.day, now.day,
first_of_this_month, now),) first_of_this_month, now),)
else: else:
raise NotImplementedError raise NotImplementedError
self.download_and_store(periods) self.download_and_store(periods)
   
   
def since_date(self, since_date): def for_date(self, for_date):
assert isinstance(since_date, datetime.datetime) assert isinstance(since_date, datetime.datetime)
periods = [] # (period_name, period_complete_day, start_date, end_date) periods = [] # (period_name, period_complete_day, start_date, end_date)
if self.period == 'monthly': if self.period == 'monthly':
first_of_the_months_until_now = [] first_of_the_months_until_now = []
year = since_date.year year = for_date.year
month = since_date.month month = for_date.month
now = datetime.datetime.now() now = datetime.datetime.now()
first_of_this_month = datetime.datetime(now.year, now.month, 1) first_of_this_month = datetime.datetime(now.year, now.month, 1)
while True: while True:
first_of_the_month = datetime.datetime(year, month, 1) first_of_the_month = datetime.datetime(year, month, 1)
if first_of_the_month == first_of_this_month: if first_of_the_month == first_of_this_month:
periods.append((now.strftime(FORMAT_MONTH), periods.append((now.strftime(FORMAT_MONTH),
now.day, now.day,
first_of_this_month, now)) first_of_this_month, now))
break break
elif first_of_the_month < first_of_this_month: elif first_of_the_month < first_of_this_month:
in_the_next_month = first_of_the_month + datetime.timedelta(40) in_the_next_month = first_of_the_month + datetime.timedelta(40)
last_of_the_month = datetime.datetime(in_the_next_month.year, last_of_the_month = datetime.datetime(in_the_next_month.year,
in_the_next_month.month, 1)\ in_the_next_month.month, 1)\
- datetime.timedelta(1) - datetime.timedelta(1)
periods.append((now.strftime(FORMAT_MONTH), 0, periods.append((now.strftime(FORMAT_MONTH), 0,
first_of_the_month, last_of_the_month)) first_of_the_month, last_of_the_month))
else: else:
# first_of_the_month has got to the future somehow # first_of_the_month has got to the future somehow
break break
month += 1 month += 1
if month > 12: if month > 12:
year += 1 year += 1
month = 1 month = 1
else: else:
raise NotImplementedError raise NotImplementedError
self.download_and_store(periods) self.download_and_store(periods)
   
@staticmethod @staticmethod
def get_full_period_name(period_name, period_complete_day): def get_full_period_name(period_name, period_complete_day):
if period_complete_day: if period_complete_day:
return period_name + ' (up to %ith)' % period_complete_day return period_name + ' (up to %ith)' % period_complete_day
else: else:
return period_name return period_name
   
   
def download_and_store(self, periods): def download_and_store(self, periods):
for period_name, period_complete_day, start_date, end_date in periods: for period_name, period_complete_day, start_date, end_date in periods:
log.info('Downloading Analytics for period "%s" (%s - %s)', log.info('Period "%s" (%s - %s)',
self.get_full_period_name(period_name, period_complete_day), self.get_full_period_name(period_name, period_complete_day),
start_date.strftime('%Y %m %d'), start_date.strftime('%Y-%m-%d'),
end_date.strftime('%Y %m %d')) end_date.strftime('%Y-%m-%d'))
data = self.download(start_date, end_date)  
log.info('Storing Analytics for period "%s"', if self.delete_first:
self.get_full_period_name(period_name, period_complete_day)) log.info('Deleting existing Analytics for this period "%s"',
self.store(period_name, period_complete_day, data) period_name)
  ga_model.delete(period_name)
   
def download(self, start_date, end_date): if not self.skip_url_stats:
  # Clean out old url data before storing the new
  ga_model.pre_update_url_stats(period_name)
   
  accountName = config.get('googleanalytics.account')
   
  log.info('Downloading analytics for dataset views')
  data = self.download(start_date, end_date, '~/%s/dataset/[a-z0-9-_]+' % accountName)
   
  log.info('Storing dataset views (%i rows)', len(data.get('url')))
  self.store(period_name, period_complete_day, data, )
   
  log.info('Downloading analytics for publisher views')
  data = self.download(start_date, end_date, '~/%s/publisher/[a-z0-9-_]+' % accountName)
   
  log.info('Storing publisher views (%i rows)', len(data.get('url')))
  self.store(period_name, period_complete_day, data,)
   
  log.info('Aggregating datasets by publisher')
  ga_model.update_publisher_stats(period_name) # about 30 seconds.
   
  log.info('Downloading and storing analytics for site-wide stats')
  self.sitewide_stats( period_name, period_complete_day )
   
  log.info('Downloading and storing analytics for social networks')
  self.update_social_info(period_name, start_date, end_date)
   
   
  def update_social_info(self, period_name, start_date, end_date):
  start_date = start_date.strftime('%Y-%m-%d')
  end_date = end_date.strftime('%Y-%m-%d')
  query = 'ga:hasSocialSourceReferral=~Yes$'
  metrics = 'ga:entrances'
  sort = '-ga:entrances'
   
  # Supported query params at
  # https://developers.google.com/analytics/devguides/reporting/core/v3/reference
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  filters=query,
  start_date=start_date,
  metrics=metrics,
  sort=sort,
  dimensions="ga:landingPagePath,ga:socialNetwork",
  max_results=10000,
  end_date=end_date).execute()
  data = collections.defaultdict(list)
  rows = results.get('rows',[])
  for row in rows:
  url = _normalize_url('http:/' + row[0])
  data[url].append( (row[1], int(row[2]),) )
  ga_model.update_social(period_name, data)
   
   
  def download(self, start_date, end_date, path=None):
'''Get data from GA for a given time period''' '''Get data from GA for a given time period'''
start_date = start_date.strftime('%Y-%m-%d') start_date = start_date.strftime('%Y-%m-%d')
end_date = end_date.strftime('%Y-%m-%d') end_date = end_date.strftime('%Y-%m-%d')
query = 'ga:pagePath=~/dataset/[a-z0-9-]+$' query = 'ga:pagePath=%s$' % path
metrics = 'ga:uniquePageviews' metrics = 'ga:pageviews, ga:visits'
sort = '-ga:uniquePageviews' sort = '-ga:pageviews'
   
# Supported query params at # Supported query params at
# https://developers.google.com/analytics/devguides/reporting/core/v3/reference # https://developers.google.com/analytics/devguides/reporting/core/v3/reference
results = self.service.data().ga().get( results = self.service.data().ga().get(
ids='ga:' + self.profile_id, ids='ga:' + self.profile_id,
filters=query, filters=query,
start_date=start_date, start_date=start_date,
metrics=metrics, metrics=metrics,
sort=sort, sort=sort,
dimensions="ga:pagePath", dimensions="ga:pagePath",
max_results=10000, max_results=10000,
end_date=end_date).execute() end_date=end_date).execute()
   
if os.getenv('DEBUG'):  
import pprint  
pprint.pprint(results)  
print 'Total results: %s' % results.get('totalResults')  
   
packages = [] packages = []
for entry in results.get('rows'): for entry in results.get('rows'):
(loc,size,) = entry (loc,pageviews,visits) = entry
packages.append( ('http:/' + loc,size, '',) ) # Temporary hack url = _normalize_url('http:/' + loc) # strips off domain e.g. www.data.gov.uk or data.gov.uk
   
  if not url.startswith('/dataset/') and not url.startswith('/publisher/'):
  # filter out strays like:
  # /data/user/login?came_from=http://data.gov.uk/dataset/os-code-point-open
  # /403.html?page=/about&from=http://data.gov.uk/publisher/planning-inspectorate
  continue
  packages.append( (url, pageviews, visits,) ) # Temporary hack
return dict(url=packages) return dict(url=packages)
   
def store(self, period_name, period_complete_day, data): def store(self, period_name, period_complete_day, data):
if 'url' in data: if 'url' in data:
ga_model.update_url_stats(period_name, period_complete_day, data['url']) ga_model.update_url_stats(period_name, period_complete_day, data['url'])
   
  def sitewide_stats(self, period_name, period_complete_day):
  import calendar
  year, month = period_name.split('-')
  _, last_day_of_month = calendar.monthrange(int(year), int(month))
   
  start_date = '%s-01' % period_name
  end_date = '%s-%s' % (period_name, last_day_of_month)
  funcs = ['_totals_stats', '_social_stats', '_os_stats',
  '_locale_stats', '_browser_stats', '_mobile_stats', '_download_stats']
  for f in funcs:
  log.info('Downloading analytics for %s' % f.split('_')[1])
  getattr(self, f)(start_date, end_date, period_name, period_complete_day)
   
  def _get_results(result_data, f):
  data = {}
  for result in result_data:
  key = f(result)
  data[key] = data.get(key,0) + result[1]
  return data
   
  def _totals_stats(self, start_date, end_date, period_name, period_complete_day):
  """ Fetches distinct totals, total pageviews etc """
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  start_date=start_date,
  metrics='ga:pageviews',
  sort='-ga:pageviews',
  max_results=10000,
  end_date=end_date).execute()
  result_data = results.get('rows')
  ga_model.update_sitewide_stats(period_name, "Totals", {'Total page views': result_data[0][0]},
  period_complete_day)
   
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  start_date=start_date,
  metrics='ga:pageviewsPerVisit,ga:avgTimeOnSite,ga:percentNewVisits,ga:visits',
  max_results=10000,
  end_date=end_date).execute()
  result_data = results.get('rows')
  data = {
  'Pages per visit': result_data[0][0],
  'Average time on site': result_data[0][1],
  'New visits': result_data[0][2],
  'Total visits': result_data[0][3],
  }
  ga_model.update_sitewide_stats(period_name, "Totals", data, period_complete_day)
   
  # Bounces from / or another configurable page.
  path = '/%s%s' % (config.get('googleanalytics.account'),
  config.get('ga-report.bounce_url', '/'))
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  filters='ga:pagePath==%s' % (path,),
  start_date=start_date,
  metrics='ga:visitBounceRate',
  dimensions='ga:pagePath',
  max_results=10000,
  end_date=end_date).execute()
  result_data = results.get('rows')
  if not result_data or len(result_data) != 1:
  log.error('Could not pinpoint the bounces for path: %s. Got results: %r',
  path, result_data)
  return
  results = result_data[0]
  bounces = float(results[1])
  # visitBounceRate is already a %
  log.info('Google reports visitBounceRate as %s', bounces)
  ga_model.update_sitewide_stats(period_name, "Totals", {'Bounce rate (home page)': float(bounces)},
  period_complete_day)
   
   
  def _locale_stats(self, start_date, end_date, period_name, period_complete_day):
  """ Fetches stats about language and country """
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  start_date=start_date,
  metrics='ga:pageviews',
  sort='-ga:pageviews',
  dimensions="ga:language,ga:country",
  max_results=10000,
  end_date=end_date).execute()
  result_data = results.get('rows')
  data = {}
  for result in result_data:
  data[result[0]] = data.get(result[0], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
  ga_model.update_sitewide_stats(period_name, "Languages", data, period_complete_day)
   
  data = {}
  for result in result_data:
  data[result[1]] = data.get(result[1], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
  ga_model.update_sitewide_stats(period_name, "Country", data, period_complete_day)
   
   
  def _download_stats(self, start_date, end_date, period_name, period_complete_day):
  """ Fetches stats about language and country """
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  start_date=start_date,
  filters='ga:eventAction==download',
  metrics='ga:totalEvents',
  sort='-ga:totalEvents',
  dimensions="ga:eventLabel",
  max_results=10000,
  end_date=end_date).execute()
  result_data = results.get('rows')
  if not result_data:
  # We may not have data for this time period, so we need to bail
  # early.
  log.info("There is no download data for this time period")
  return
   
  # [[url, count], [url],count]
  data = {}
  for result in result_data:
  data[result[0]] = data.get(result[0], 0) + int(result[1])
  self._filter_out_long_tail(data, MIN_DOWNLOADS)
  ga_model.update_sitewide_stats(period_name, "Downloads", data, period_complete_day)
   
  def _social_stats(self, start_date, end_date, period_name, period_complete_day):
  """ Finds out which social sites people are referred from """
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  start_date=start_date,
  metrics='ga:pageviews',
  sort='-ga:pageviews',
  dimensions="ga:socialNetwork,ga:referralPath",
  max_results=10000,
  end_date=end_date).execute()
  result_data = results.get('rows')
  data = {}
  for result in result_data:
  if not result[0] == '(not set)':
  data[result[0]] = data.get(result[0], 0) + int(result[2])
  self._filter_out_long_tail(data, 3)
  ga_model.update_sitewide_stats(period_name, "Social sources", data, period_complete_day)
   
   
  def _os_stats(self, start_date, end_date, period_name, period_complete_day):
  """ Operating system stats """
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  start_date=start_date,
  metrics='ga:pageviews',
  sort='-ga:pageviews',
  dimensions="ga:operatingSystem,ga:operatingSystemVersion",
  max_results=10000,
  end_date=end_date).execute()
  result_data = results.get('rows')
  data = {}
  for result in result_data:
  data[result[0]] = data.get(result[0], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
  ga_model.update_sitewide_stats(period_name, "Operating Systems", data, period_complete_day)
   
  data = {}
  for result in result_data:
  if int(result[2]) >= MIN_VIEWS:
  key = "%s %s" % (result[0],result[1])
  data[key] = result[2]
  ga_model.update_sitewide_stats(period_name, "Operating Systems versions", data, period_complete_day)
   
   
  def _browser_stats(self, start_date, end_date, period_name, period_complete_day):
  """ Information about browsers and browser versions """
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  start_date=start_date,
  metrics='ga:pageviews',
  sort='-ga:pageviews',
  dimensions="ga:browser,ga:browserVersion",
  max_results=10000,
  end_date=end_date).execute()
  result_data = results.get('rows')
  # e.g. [u'Firefox', u'19.0', u'20']
   
  data = {}
  for result in result_data:
  data[result[0]] = data.get(result[0], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
  ga_model.update_sitewide_stats(period_name, "Browsers", data, period_complete_day)
   
  data = {}
  for result in result_data:
  key = "%s %s" % (result[0], self._filter_browser_version(result[0], result[1]))
  data[key] = data.get(key, 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
  ga_model.update_sitewide_stats(period_name, "Browser versions", data, period_complete_day)
   
  @classmethod
  def _filter_browser_version(cls, browser, version_str):
  '''
  Simplifies a browser version string if it is detailed.
  i.e. groups together Firefox 3.5.1 and 3.5.2 to be just 3.
  This is helpful when viewing stats and good to protect privacy.
  '''
  ver = version_str
  parts = ver.split('.')
  if len(parts) > 1:
  if parts[1][0] == '0':
  ver = parts[0]
  else:
  ver = "%s" % (parts[0])
  # Special case complex version nums
  if browser in ['Safari', 'Android Browser']:
  ver = parts[0]
  if len(ver) > 2:
  num_hidden_digits = len(ver) - 2
  ver = ver[0] + ver[1] + 'X' * num_hidden_digits
  return ver
   
  def _mobile_stats(self, start_date, end_date, period_name, period_complete_day):
  """ Info about mobile devices """
   
  results = self.service.data().ga().get(
  ids='ga:' + self.profile_id,
  start_date=start_date,
  metrics='ga:pageviews',
  sort='-ga:pageviews',
  dimensions="ga:mobileDeviceBranding, ga:mobileDeviceInfo",
  max_results=10000,
  end_date=end_date).execute()
   
  result_data = results.get('rows')
  data = {}
  for result in result_data:
  data[result[0]] = data.get(result[0], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
  ga_model.update_sitewide_stats(period_name, "Mobile brands", data, period_complete_day)
   
  data = {}
  for result in result_data:
  data[result[1]] = data.get(result[1], 0) + int(result[2])
  self._filter_out_long_tail(data, MIN_VIEWS)
  ga_model.update_sitewide_stats(period_name, "Mobile devices", data, period_complete_day)
   
  @classmethod
  def _filter_out_long_tail(cls, data, threshold=10):
  '''
  Given data which is a frequency distribution, filter out
  results which are below a threshold count. This is good to protect
  privacy.
  '''
  for key, value in data.items():
  if value < threshold:
  del data[key]
   
import os import os
import httplib2 import httplib2
from apiclient.discovery import build from apiclient.discovery import build
from oauth2client.client import flow_from_clientsecrets from oauth2client.client import flow_from_clientsecrets
from oauth2client.file import Storage from oauth2client.file import Storage
from oauth2client.tools import run from oauth2client.tools import run
   
from pylons import config from pylons import config
   
   
def _prepare_credentials(token_filename, credentials_filename): def _prepare_credentials(token_filename, credentials_filename):
""" """
Either returns the user's oauth credentials or uses the credentials Either returns the user's oauth credentials or uses the credentials
file to generate a token (by forcing the user to login in the browser) file to generate a token (by forcing the user to login in the browser)
""" """
storage = Storage(token_filename) storage = Storage(token_filename)
credentials = storage.get() credentials = storage.get()
   
if credentials is None or credentials.invalid: if credentials is None or credentials.invalid:
flow = flow_from_clientsecrets(credentials_filename, flow = flow_from_clientsecrets(credentials_filename,
scope='https://www.googleapis.com/auth/analytics.readonly', scope='https://www.googleapis.com/auth/analytics.readonly',
message="Can't find the credentials file") message="Can't find the credentials file")
credentials = run(flow, storage) credentials = run(flow, storage)
   
return credentials return credentials
   
   
def init_service(token_file, credentials_file): def init_service(token_file, credentials_file):
""" """
Given a file containing the user's oauth token (and another with Given a file containing the user's oauth token (and another with
credentials in case we need to generate the token) will return a credentials in case we need to generate the token) will return a
service object representing the analytics API. service object representing the analytics API.
""" """
http = httplib2.Http() http = httplib2.Http()
   
credentials = _prepare_credentials(token_file, credentials_file) credentials = _prepare_credentials(token_file, credentials_file)
http = credentials.authorize(http) # authorize the http object http = credentials.authorize(http) # authorize the http object
   
return build('analytics', 'v3', http=http) return build('analytics', 'v3', http=http)
   
   
def get_profile_id(service): def get_profile_id(service):
""" """