Entelect
GP Solver
Python hackathon solver for generating validated race strategies across multi-level Grand Prix constraints.
- My role
- Hackathon Developer
- Build window
- 2026
- Evidence state
- Public repository
- Proof signal
- Public Repository / Automated Checks
- Primary stack
- Python
What was delivered
A challenge-focused solver that turns race constraints into a validated, deterministic submission.
- Reads level data and generates a race strategy for the defined constraints
- Validates generated output against the challenge rules before submission
- Packages repeatable submission artefacts through a pre-submit flow
Developer view
A Python constraint-solving project combining simulation, scoring, validation and deterministic CLI-oriented tooling.
- Handled braking, speed, fuel, weather, tyre-wear and pit-stop decisions in the strategy model
- Added validation and scoring helpers so generated strategies could be checked locally
- Kept the generated strategy deterministic so optimisation and debugging could be repeated locally
Project context
The Entelect Grand Prix challenge required a program that could generate valid race strategies under changing constraints such as braking distance, fuel, weather, tyre wear and pit stops.
Entelect GP Solver is a Python hackathon project that reads level data, generates a race strategy and validates the output against the challenge rules. The work focused on deterministic problem solving, simulation, scoring and packaging submission-ready artefacts.
Hackathon project for the Entelect Grand Prix problem, centred on algorithmic thinking rather than a user-facing web interface.
My contribution Built a deterministic solver, validation pipeline, scoring helpers and pre-submit packaging flow for the hackathon problem.
Key Outcomes
Built a deterministic strategy generator for braking, speed, tyre and pit-stop decisions
Implemented validation and scoring helpers for checking generated submissions against the race rules
Added a pre-submit flow that regenerates outputs, checks determinism and packages submission artefacts
Verified the local quality pipeline with 6/6 unittest checks on 07 September 2026
Engineering reflection
- Constraint-heavy problems need a validator as much as they need a solver
- Deterministic output makes optimisation and debugging easier under hackathon time pressure
Technical Stack
Visual Evidence
