Home 5 Personal 5 F1 Telemetry App, 2020

Tech stack:

Python

Python

GCP

GCP

F1 2019 Telemetry

F1 2019 Telemetry

Dash

Dash

SQL

SQL

Docker

Docker

Pandas

Pandas

NumPy

NumPy

Flask

Flask

Apache Beam

Apache Beam

Click to Expand section and show all tech used for this project

Story

During COVID-19 pandemic I had fun driving virtual laps as a Formula 1 driver. When I noticed that all data describing the vast world of Codemasters F1 2019 Playstation 4 game could be transmitted out of my console to the Internet world – I didn’t hesitate: I knew that it could become a fun project. And boy, I was so right.

 

Solution

It all started with Sidney Cadot’s F1 2019 telemetry Python package – by modifying it, I understood that the raw game data needed: streaming, storing, cleaning and organizing. All these activities were realized by Google Cloud Platform’s products (mentioned above). Later on, I told my friend, Kacper Rzosiński, the F1 newbie, about my idea – instead of negotiating, he joined the hype train party right away and designed the final dashboard user interface, as well as its usage experience. It was so intriguing to him, that since this cooperation, we have been watching many races together.

 

Dashboard look

 

Lesson Learned

I have discovered that for me coding my own projects, apart from being fun, needs to have a big scope and a direct connection to my hobbies. Moreover, lots of solutions implemented in this side-project came from the Internet (Stack Overflow, I still adore you so much!) – I just have blended them together successfully, at the end making something quite useful and very rewarding for myself.

Google Cloud Platform Components

Below you may find a list of components used within dashboard’s GCP deployment:

App Future

As for 2024, this dashboard has been integrated as a vital part of Fullstack MLOps Platform for Formula 1the Driver’s Academy component.

        Statistics

        • 1: dashboard,
        • 2: sections,
        • 3: BigQuery databases,
        • 6: months,
        • 8: languages,
        • 21: tags,
        • 25: BigQuery tables,
        • 162: commits,
        • 5277: lines of code,
        • 157412: total BigQuery data rows.