Why do responses take so long?
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- Dominant language
- Python
- Stars
- 1
- Forks
- 0
- PR merge metrics
- No merged PRs in 30d
Description
The initial suspicion was that the bbox queries and reading the surface data from the csv files is too slow. However, much much more time is spent on other things than on the functions that get the data for the response.
See https://github.com/3DGI/3dbag-api#performance and https://github.com/3DGI/3dbag-api/issues/14#issuecomment-1228159772 and https://github.com/3DGI/3dbag-api/issues/15#issuecomment-1226005813.
Thus these functions are by far not the bottlenecks in the response times, but what is?
The profiler statistics in /profiling is a good starting point.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the profiler statistics in /profiling and review the performance notes linked from the issue, including issues #14 and #15. Identify the operations that dominate response time beyond bbox queries and CSV surface-data reads. Done means documenting the bottleneck and addressing or clearly isolating the slow path with measured profiling evidence.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- backend-api-design, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100