Race Engineer

C+ 78 completed
Cli Tool
unknown / python · tiny
47
Files
5,518
LOC
1
Frameworks
3
Languages

Pipeline State

completed
Run ID
#358099
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
43.26
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #48057
Member of a group with 1 similar repo(s) — canonical #6835 view group →
Top concepts (2)
Project DescriptionTesting
All rows above produced by Repobility · https://repobility.com

AI Prompt

Create a personal racing engineer tool for iRacing users using Python. I need it to analyze telemetry data from iRacing's .ibt files. The system should have two main features: a "Scouting Report" that uses Claude AI and web search to provide pre-session briefings on car/track combos, and a "Lap Coaching" feature for post-session analysis. The coaching should compare laps to the user's best performance, pinpointing the 2-3 corners where time is lost, and providing actionable advice. The architecture should handle IBT parsing, distance normalization, automated corner detection, and lap-to-lap comparison. The UI should be built using Streamlit.
python streamlit ai telemetry racing iracing pytorch analysis coaching web-scraping
Generated by gemma4:latest

Catalog Information

This project provides a personal racing engineer for iRacing users, offering telemetry analysis and AI-based coaching.

Description

The personal-race-engineer is a tool designed to help iRacing users improve their driving skills through advanced telemetry analysis and AI-powered coaching. It leverages various libraries such as numpy, pandas, and scipy to process data, while plotly is used for visualization. The project utilizes streamlit for building the user interface. This application aims to provide actionable insights and recommendations to enhance racing performance.

الوصف

هذا المشروع يقدم مهندس سباق شخصي للمستخدمين من iRacing، يقدّم تحليلات تكنولوجيا السباق وتدريب آي-ماشين. يستفيد هذا الأداة من مجموعة من المكتبات مثل numpy و pandas و scipy لتحليل البيانات، بينما تستخدم plotly للرسم الجرافيكي. كما يستخدم streamlit لبناء الواجهة المستخدمة. يهدف هذا التطبيق إلى تقديم معلومات قابلة للتطبيق وتوصيات لتطوير أداء السباق.

Novelty

7/10

Tags

telemetry-analysis ai-coaching racing-performance-improvement iracing data-visualization driver-insights

Technologies

anthropic numpy pandas plotly pydantic scipy streamlit

Claude Models

claude-opus-4.6

Quality Score

C+
77.7/100
Structure
75
Code Quality
88
Documentation
67
Testing
60
Practices
78
Security
100
Dependencies
60

Strengths

  • Good test coverage (46% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected

Weaknesses

  • No LICENSE file \u2014 legal ambiguity for contributors
  • No CI/CD configuration \u2014 manual testing and deployment
  • 147 duplicate lines detected \u2014 consider DRY refactoring

Recommendations

  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a LICENSE file (MIT recommended for open source)

Security & Health

6.1h
Tech Debt (C)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (3)
Repobility · code-quality intelligence · https://repobility.com
Unknown
License
0.6%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
87.2%
markdown
12.3%
toml
0.5%

Frameworks

pytest

Concepts (2)

Open data · scored by Repobility · https://repobility.com
CategoryNameDescriptionConfidence
Generated by Repobility's multi-pass static-analysis pipeline (https://repobility.com)
auto_descriptionProject DescriptionA personal racing engineer for iRacing. Analyzes telemetry, sources community knowledge, and delivers opinionated coaching that helps intermediate drivers get faster.80%
auto_categoryTestingtesting70%

Quality Timeline

1 quality score recorded.

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