a-b-street / a-b-street/ltn

Improve perf for predict impact

Open
#129 7 comments 0 reactions 0 assignees View on GitHub
Dominant language
Rust
Stars
21
Forks
7
PR merge metrics
No merged PRs in 30d

Description

Perf:

- [ ] Parallelize
- [ ] ~~Reuse the PathCalculator~~ Already done.
- [ ] Pass back road GJ once, and then just counts after that
- [x] Use a basic loading screen (switch to web workers?)
- [ ] Vec for counts, not HashMap
- [ ] Profiling
- [ ] ~~Dedupe requests upfront~~ Not enough duplication to be worthwhile
- [ ] Measure how long loading the demand model adds. Maybe async load it?
- [ ] Could speed up the Scotland demand data builder with rstar

Contributor guide

No contributing guide indexed for this repository

Research direction

The issue is about optimizing the 'predict impact' feature. Start by profiling the current implementation to identify bottlenecks. Look for the PathCalculator, demand model loading, and data structures like HashMap/Vec for counts. Check if web workers or async loading are applicable. The Scotland demand data builder and rstar are mentioned for potential speed-up.

Written by the indexing model from the issue text.

Assessment

Tech stack
rust
Domain
performance
Issue type
Refactor
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
45/100

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