You can track website traffic with various tools, but each time, you have to open the application and log in. If you want to monitor multiple aspects, you need to repeat this process every time, which can be time-consuming if done regularly.
The website monitoring project was created to track the BeOptimized website traffic from a central, multi-page dashboard. This way, the DASH app is always open, up-to-date, and displays only the information I need. The dashboard is simple, showing active users over time, stats about the user's country, operating system, search engine, and the most visited web pages. For me, this information is sufficient. To access the data, I used the Google Analytics API using Python.

Basically, it was created using the following steps:

• First, you need to register with Google Analytics and add a JavaScript function to your website so that Google can monitor the statistics (I am still using analytics.js in my case). You can find more information on this topic here. This function collects statistics into a database accessible from the Google Analytics website.
• Next, to access the data in Python, the google.analytics.data package was installed. This package allows you to run parameterized report requests and returns the statistics in JSON format. Parameters include metrics (e.g., number of active users) and dimensions (e.g., country, city, page title). You can also combine dimensions, such as country and year, or month and apply filters.
• Then, the JSON data is extracted and stored into an SQLite database using SQLAlchemy.
• Finally, the data is displayed on the dashboard using DASH.

• Python
• Dash Plotly
• Pandas
• SQLAlchemy
• Google Analytics API
• Docker