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Your numerical code,
automatically optimised

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we'll make it faster.

fastercode.ai connects to your GitHub repositories, launches your code in containers, finds performance bottlenecks, and opens Pull Requests with LLM optimised code. Correctness verified E2E, ready to merge.

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−90.1%
Best result
−47%
Avg improvement
100%
Correctness verified
Python
Language support
github.com / org / scientific-sim / pull / 52
Open optimise simulate_trajectory() #52
Runtime improvement
−90.1%
Tests
1 / 1 passing
Correctness
Verified
Trigger
push → main
How it works
Replaced slow_read_lines + naive_parse_csv with binary streaming and byte splitting, eliminating list and dict allocation per row.
Converted nested per-unit while accumulation from O(sum(qty)) to O(rows) via float(price) * n.
Cached int and float in locals, reducing global lookup overhead in the hot loop.
How it works

Automatic. Verified. Ready to merge.

fastercode.ai runs in the background on every push. No configuration needed after setup.

1
Connect your repo
Sign in with GitHub and connect your Python repositories. fastercode.ai installs as a GitHub App in minutes.
2
Containerised execution
On every push, fastercode.ai launches your code in isolated containers, runs end-to-end simulations, and identifies real performance bottlenecks under true execution conditions.
3
LLM optimisation
The LLM generates optimisations against your objective — faster, shorter, smarter — then verifies correctness end-to-end against your actual simulations before touching your repo.
4
Pull request opened
If the improvement meets your threshold and passes all tests, fastercode.ai opens a GitHub PR with a full explanation of what changed and why.
Objectives

Optimise for what matters to you

Set your objective per repository. fastercode.ai optimises accordingly.

Faster
Minimise wall-clock runtime. Ideal for simulation loops, solvers, and data pipelines.
Available now
Shorter
Reduce lines of code. Simplify complexity and eliminate redundancy.
Available now
Smarter
Reduce memory allocation. Built for memory-constrained scientific and HPC workloads.
Coming soon
Easier
Improve readability and maintainability. Ideal for teams onboarding engineers to complex codebases.
Coming soon
Private beta

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