Skip to main content

Monaco 2018 Q1 lap-time report generator

Project description

🏎️ Monaco F1 2018 Q1 Lap Report

A command-line tool to analyze the best lap times of Formula 1 drivers during Q1 (first qualification stage) of the Monaco Grand Prix 2018.

This tool parses log files with start and end timestamps of the best laps (first 20 minutes only), calculates lap durations, and generates a clean, formatted report of the top 15 drivers who advance to Q2 — and those who don't.


📁 Dataset

The application works with the following three files:

  • abbreviations.txt: contains driver abbreviations, full names, and team names.
  • start.log: contains timestamps of when each driver's start race.
  • end.log: contains timestamps of when each driver's end race.

Example entry for start.log and end.log files:

SVF2018-05-24_12:02:58.917

  • SVF: Driver abbreviation
  • 2018-05-24: Date
  • 12:02:58.917: Start or end time (used for lap duration calculation)

Example entry for abbreviations.txt:

DRR_Daniel Riccardo_RED BULL RACING TAG HEUER

  • DRR: Driver abbreviation
  • Daniel Riccardo: Driver name
  • RED BULL RACING TAG HEUER: Driver team

🏁 Report Example

After parsing and calculating lap times, the output will look like:

1. Daniel Ricciardo      | RED BULL RACING TAG HEUER     | 1:12.013

2. Sebastian Vettel      | FERRARI                                            | 1:12.415

3. ...

------------------------------------------------------------------------

16. Brendon Hartley   | SCUDERIA TORO ROSSO HONDA | 1:13.179

17. Marcus Ericsson  | SAUBER FERRARI                            | 1:13.265

Instalation

Report-of-monaco-2018 can be installed by running pip install report-monaco==0.0.5. It requires Python 3.9+ to run.

🔧 Features

  • Calculates and sorts drivers by best lap time.
  • Separates top 15 drivers from the rest.
  • Command-line interface to choose sorting order or filter by driver.
  • Graceful error handling (missing files, invalid data).

💻 Usage

Install dependencies and run the CLI app:

Examples:

 `report-monaco --file data --desc`
 `report-monaco --file data --driver "Sebastian Vettel"`

Options:

--file (./data): Path to the folder containing the start.log, end.log, and abbreviations.txt files.

--asc: Sort report in ascending order (default).

--desc: Sort in descending order.

--driver "": Show info for a specific driver.

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

report_of_monaco_2018-0.0.5.tar.gz (3.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

report_of_monaco_2018-0.0.5-py3-none-any.whl (8.3 kB view details)

Uploaded Python 3

File details

Details for the file report_of_monaco_2018-0.0.5.tar.gz.

File metadata

  • Download URL: report_of_monaco_2018-0.0.5.tar.gz
  • Upload date:
  • Size: 3.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-httpx/0.28.1

File hashes

Hashes for report_of_monaco_2018-0.0.5.tar.gz
Algorithm Hash digest
SHA256 9b83d20a8b0bae4adcfad9b15c84cc3f15d858714424d9277b4eac95effa6eb1
MD5 2cc6446660d82f74e9ac0aa90ed6b295
BLAKE2b-256 c6f6c3ef61bdac56a0b12ef18dfbb067bd2071a798bf08b327fa5c7fd7c79a3f

See more details on using hashes here.

File details

Details for the file report_of_monaco_2018-0.0.5-py3-none-any.whl.

File metadata

File hashes

Hashes for report_of_monaco_2018-0.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 099f9f180df1f06fac65f490beaed09dd4bd5314c3e48e31ac3ccdc247c67ed4
MD5 df5fec8cceb3b94bf815ef29dd1e7718
BLAKE2b-256 8cfda027e2a39a00f336eda326db7d96d4e589e5b9e3aa9077daad91b05af223

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page