Analytics table for Vipul Naik's projects

Live at https://analytics.vipulnaik.com/

Project layout

• fetch_pageviews.py: this script queries Google Analytics using its API, and stores the data in a local database. This script should be run in a cron job.
• print_table.py: this script queries the local database and prints pageviews data in an HTML table.
• sql/: table schema and some data for the local database.
• access-portal/: if this project is served over the web, this is where users will access the site.

Database layout

The database should be named analyticstable.

The database has two tables:

• projects: this stores some metadata about each project. The data for this is stored directly in the SQL file.
• pageviews: this stores the pageviews. The data for this is inserted by fetch_pageviews.py.

Setting up Google Analytics

There are several parts to this:

1. You must set up a project on the Google developers console. From the project, you will create a service account, which will have an email address associated with it as well as a credentials JSON file.
2. For each website tracked via Google Analytics, you must give your special email address access to the analytics data.
3. For each website tracked via Google Analytics, you must add the project metadata to sql/projects.sql.
4. Optional: change the Google Analytics quota.

Each step is covered below.

Set up a Google developers project and a service account

A project seems to be some sort of umbrella thing for the Google developers console, whereas a service account is a thing that gets an email. You will create a single project and a single service account for that project.

1. Go to https://console.developers.google.com
2. Create a new project somehow (I can't go back to the screen displayed before I had any projects, so I can't write up the exact steps).
3. Enable analytics API for your project: https://www.dundas.com/support/learning/documentation/connect-to-data/how-to/connecting-to-google-analytics
4. Go to https://console.developers.google.com/iam-admin/serviceaccounts
5. Click "create service account". You can enter arbitrary stuff here; you don't need to give the service account any permissions.
6. Create a key for the service account. If you're creating a new service account, there should be a section called "Create key (optional)". Click "create key", and make sure JSON is selected. Now create the key and save it as key.json (I think Google's documentation refers to this file as client_secrets.json) in this repo's directory. If you already have a service account, in the table that lists your service accounts, there is a column called "Actions". Click the hamburger and select "Create key", and save as key.json (I think Google's documentation refers to this file as client_secrets.json).

How to give access to the script

For this step, you will need the email address associated with your service account.

From the analytics home page, you can go to admin → then under the View column User Management → and then the (+) in the upper right corner → "Add new users" → and use email address for your service account, and make sure "Read & Analyze" is checked, then click Add.

How to find the view ID

Admin → under the View column "View Settings" → under "Basic Settings" there should be a "View ID" heading.

Change Google Analytics quota

1. Go to https://console.developers.google.com/iam-admin/serviceaccounts
2. In left bar, click "Quotas"
3. Under services dropdown, restrict to "Google Analytics Reporting API".
4. The one that might cause problems is "Google Analytics Reporting API - Requests per 100 seconds", so click that, and in the next screen you can click the pencil to change it up to 50,000.

Setting up the portal

Set up the database

# Create database
mysql -e "create database analyticstable"

# Create tables
mysql analyticstable < sql/projects.sql
mysql analyticstable < sql/pageviews.sql

Create login file

In this repo's directory, create a file called login.py with the database login info. For example:

USER = "issa"
DATABASE = "analyticstable"
PASSWORD = ""

Install Google Analytics API library and MySQL connector

Run:

sudo pip install --upgrade google-api-python-client mysql-connector-python

(source)

Run the data fetching script

If everything is set up correctly, you should now be able to run the data fetching script:

./fetch_pageviews.py key.json

If it works, try running it again:

./fetch_pageviews.py key.json

The script checks the most recently stored date for each project, and only queries for more recent data, so the second run should be much quicker. (If a website got zero pageviews on the most recent days, it might try to query a small number of dates.)

Fetch auxiliary files

make fetch_tablesorter

Serve the website

If you're trying to run the website locally, run from the access-portal/ directory:

php -S localhost:8000

If you're trying to serve the website over the web, edit your nginx/apache config; make sure the root directory is access-portal/.

See also

• https://github.com/riceissa/timelines-wiki-main-page-table