{ "info": { "author": "Government Digital Service", "author_email": "performance@digital.cabinet-office.gov.uk", "bugtrack_url": null, "classifiers": [], "description": ".. _Google Analytics: http://www.google.com/analytics/\n.. _Pingdom: https://www.pingdom.com/\n.. _Webtrends: http://webtrends.com/\n\nA python command line tool that aggregates data from third party sources and pushes\nthe result through to the Performance Platform (see http://alphagov.github.io/performanceplatform-documentation/\nfor more details). This tool uses the `Google Analytics`_, `Pingdom`_ and `Webtrends`_ APIs to retrieve data.\n\n.. image:: https://travis-ci.org/alphagov/performanceplatform-collector.svg?branch=master\n :target: https://travis-ci.org/alphagov/performanceplatform-collector\n\n.. image:: https://landscape.io/github/alphagov/performanceplatform-collector/master/landscape.png\n :target: https://landscape.io/github/alphagov/performanceplatform-collector/master\n :alt: Code Health\n\n.. contents:: :local:\n\n\nInstallation\n============\n\nUsing pip:\n\n::\n\n pip install performanceplatform-collector\n\nFrom source:\n\n::\n\n git clone https://github.com/alphagov/performanceplatform-collector.git\n cd performanceplatform-collector\n virtualenv venv\n source venv/bin/activate\n python setup.py install\n\nUsage\n=====\n\nCollectors are run from the command line using the Python progam pp-collector.\n\npp-collector takes paths to various JSON files as arguments::\n\n pp-collector (-l [collector slug] | -q [query file]) -b [backdrop file] -c [credentials file] -t [token file]\n\npp-collector also takes optional arguments::\n\n --console-logging\n Rather than logging out to log/collector.log it will output all logs to stdout/err\n\n --dry-run\n When it comes to submitting the gathered data to the Performance Platform it will skip\n making the POST requests and instead log out the url, headers and body to your terminal.\n\n --start, --end\n If you want the collector to gather past data, you can specify a start date in the format\n \"YYYY-MM-DD\". You must also specify an end date. e.g.\n\n --start=2014-08-03 --end=2014-09-03\n\nHere's an example of how to run a collector from the command line using a collector slug argument::\n\n venv/bin/python /var/govuk/performanceplatform-collector/venv/bin/pp-collector -l performance-platform-devices-7abb3a26 -b performanceplatform.json -c ga-credentials.json -t ga-token.json --console-logging\n\npp-collector file path arguments\n--------------------------------\n\n**-l (collector slug)**\n\nThe collector slug is used to query Stagecraft to get collector configuration settings. The collector configuration is stored as a Python dictionary in the query_schema field on the Collector model identified by the given slug.\n\n**-q (query file)**\n\nA path to a query file can be used in place of the collector slug. The query file will contain the same collector configuration settings as would be stored in the Collector#query_schema field in Stagecraft. In addition, it must contain an entrypoint key whose value points to the type of collector to be run in the performanceplatform-collector codebase.\n\nHere's an example of the contents of a query file::\n\n # pingdom example\n {\n \"entrypoint\": \"performanceplatform.collector.pingdom\",\n \"query\": {\n \"name\": \"govuk\"\n },\n \"options\": {\n \"additionalFields\": {\n # Every record sent to backdrop will have these additional fields\n \"foo\": \"bar\",\n \"sentAt\": \"specific-formatted-time-value\"\n }\n },\n \"plugins\": [\n \"Comment('Pingdom stats are aggregated using mycustomtemplate.py')\n ],\n \"data-set\": {\n \"data-group\": \"my-data-group\",\n \"data-set\": \"my-data-set\"\n }\n }\n\nEntrypoints\n~~~~~~~~~~~\n\nEntrypoints describe a python package path.\n\n.. _performanceplatform.collector.ga: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/ga\n.. _performanceplatform.collector.ga.trending: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/ga/trending.py\n.. _performanceplatform.collector.ga.realtime: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/ga/realtime.py\n.. _performanceplatform.collector.gcloud: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/gcloud\n.. _performanceplatform.collector.ga.trending: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/ga/trending.py\n.. _performanceplatform.collector.pingdom: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/pingdom\n.. _performanceplatform.collector.piwik: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/piwik\n.. _performanceplatform.collector.piwik.core: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/piwik/core.py\n.. _performanceplatform.collector.piwik.realtime: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/piwik/realtime.py\n.. _performanceplatform.collector.webtrends: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/webtrends\n.. _performanceplatform.collector.webtrends.keymetrics: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/webtrends/keymetrics.py\n.. _performanceplatform.collector.webtrends.reports: https://github.com/alphagov/performanceplatform-collector/tree/master/performanceplatform/collector/webtrends/reports.py\n\nThe following entrypoints are currently available:\n\n- `performanceplatform.collector.ga`_\n- `performanceplatform.collector.ga.trending`_\n- `performanceplatform.collector.ga.realtime`_\n- `performanceplatform.collector.gcloud`_\n- `performanceplatform.collector.pingdom`_\n- `performanceplatform.collector.piwik`_\n- `performanceplatform.collector.piwik.core`_\n- `performanceplatform.collector.piwik.realtime`_\n- `performanceplatform.collector.webtrends`_\n- `performanceplatform.collector.webtrends.keymetrics`_\n- `performanceplatform.collector.webtrends.reports`_\n\n**-b (backdrop file)**\n\nThis is a simple pointer to the Performance Platform's data management application (Backdrop). It will define the endpoint for your collector to send all data to.\n\n::\n\n {\n \"backdrop_url\": \"https://www.performance.service.gov.uk/data\",\n \"stagecraft_url\": \"http://stagecraft.development.performance.service.gov.uk\",\n \"omniscient_api_token\": \"some-omniscient-token\"\n }\n\nstagecraft_url and omniscient_api_token token need only be defined when using the -l option to pass in a collector slug. The omniscient_api_token enables read-only access to the collector configuration settings stored in Stagecraft.\n\n**-t (token file)**\n\nThe token file file holds the bearer token to be used by this collector when POSTing to the Performance Platform::\n\n {\n \"token\": \"some long hex value\"\n }\n\nMake sure you update the content of the token file to match the token expected by the Backdrop data set being written to.\n\nNeed a token? Email The Performance Platform performance-platform@digital.cabinet-office.gov.uk\n\n**-c (credentials file)**\n\nThe credentials file is used to pass through any usernames, passwords, API keys etc that are required to communicate to the third party service you desire.\n\n::\n\n # Google Analytics example\n credentials = {\n \"CLIENT_SECRETS\": path/to/client_secret.json,\n \"STORAGE_PATH\": path/to/oauth/db,\n }\n\n # Piwik example\n {\n \"token_auth\": \"your Piwik secret token\",\n \"url\": \"your Piwik API url\"\n }\n\n You can get your Piwik secret token from the Manage Users\n admin area in your Piwik account.\n\n # Pingdom example\n {\n \"user\": \"your Pingdom user\",\n \"password\": \"your Pingdom password\",\n \"app_key\": \"your Pingdom application key\"\n }\n\n # WebTrends example\n {\n \"user\": \"your WebTrends user\",\n \"password\": \"your WebTrends password\",\n \"reports_url\": \"your WebTrends report url\",\n \"keymetrics_url\": \"your WebTrends keymetrics url\",\n \"api_version\": \"your WebTrends API version e.g. v3\"\n }\n\nSetting up Google Analytics credentials\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe following steps will enable you to generate the credentials files that you will need to provide paths to in your credentials file (pointed to by the -c argument):\n\n - Go to the `Google API Console `_\n - Sign in to your Google account\n - If you don't have an active project, click on Create Project to create a new one. Give your project any name.\n - Create a new client ID\n\n + Go to **Use Google APIs**\n + Select **Credentials**\n + In the **New Credentials** drop-down list, select Oauth client ID.\n + If you see 'To create an OAuth client ID, you must first set a product name on the consent screen'; Configure your consent screen. The project name can be anything.\n - Choose **Application type** > \"Other\".\n - Enter a name. Again, the name can be anything\n - Once created click the download button. This will download a JSON file containing your client secrets.\n - To generate the storage path, run ``python tools/generate-ga-credentials.py path/to/client/secrets.json`` in your VM, where secrets.json is the JSON file downloaded in the previous step.\n\n + The script will output a link to follow in Google accounts. Following the link to with generate an authorization code\n + Copy and paste the authorization code back into the CLI at the prompt.\n + Google credentials will be created in `./creds/ga.json`. The corresponding client_secrets.json and storage.db files will be created in `./creds/ga/`. You can point to these files in the credentials file referenced in the 'credentials file' argument.\n + **Error**::\n\n * If you get an 'invalid client error', adding a name and support email under the \"\"APIs & auth\" -> \"Consent screen\" Should fix this.\n * See http://stackoverflow.com/questions/18677244/error-invalid-client-no-application-name for more.\n\nAbout Piwik Collectors\n======================\n\nExample Piwik query file\n------------------------\n\nHere is an example Piwik query file::\n\n {\n \"data-set\": {\n \"data-group\": \"consular-appointment-booking-service\",\n \"data-type\": \"journey-by-goal\"\n },\n \"entrypoint\": \"performanceplatform.collector.piwik.core\",\n \"query\": {\n \"site_id\": \"9\",\n \"api_method\": \"Goals.get\",\n \"frequency\": \"daily\",\n \"api_method_arguments\": {\n \"idGoal\": \"3\"\n }\n },\n \"options\": {\n \"mappings\": {\n \"nb_visits_converted\": \"converted\",\n \"nb_conversions\": \"sessions\"\n },\n \"idMapping\": [\"dataType\",\"_timestamp\",\"timeSpan\"]\n },\n \"token\": \"piwik_fco\"\n }\n\nThe above configuration will instruct the Piwik collector to fetch data\nvia the Goals.get method of your Piwik Reporting API endpoint. The\nendpoint is specified via the 'url' setting in your credentials file.\n\nThe 'site_id' and 'frequency' settings map to the standard\nPiwik Reporting API method arguments of 'idSite' and 'period' respectively.\n\n* site_id - a number representing your website\n* frequency - how statistics should be reported (daily, weekly, monthly)\n\nIf not specified, the 'frequency' setting defaults to 'weekly'.\n\nYou can specify API method-specific arguments using the 'api_method_arguments'\nkey in your query file as shown in the example. For a full list of methods\navailable in the Piwik Reporting API, see\nhttp://developer.piwik.org/api-reference/reporting-api.\n\nThe Piwik collector uses the 'mappings' settings in your query file to determine\nwhich data items to extract from an API response and how to map their\nkeys. The above query file, for example, will configure the collector\nto extract the 'nb_visits_converted' and 'nb_conversions' data items\nfrom the following example API response::\n\n {\n \"From 2015-05-25 to 2015-05-31\": {\n \"nb_visits_converted\": 791,\n \"nb_conversions\": 791,\n \"conversion_rate\": 18.09,\n \"revenue\": 0 }\n }\n\nThe keys of these data items will be replaced with\n'converted' and 'sessions' respectively, ready for storage in\nthe Performance Platform's data application, Backdrop.\n\nRunning the Piwik collector\n---------------------------\n\nThe Piwik collector is run from the command line in the normal\nway - see the Usage section above.\n\nIf you want to collect data by day, week or month over a period of time,\nspecify an appropriate value for the 'frequency' setting in your\nquery file and a start and end date in your run command using the\n'--start' and '--end' optional arguments. 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