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Implement multiprocessing

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
30/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
numpy, python
Domain
api, backend, data

Research direction

Start by reviewing the repository's existing count and count-pairs operations, then compare the proposed architecture with Rio Mucho. Done means parallelizable operations use multiple cores while returning numpy arrays suitable for an HTTP geoprocessing service.

Written by the indexing model from the issue text.

Description

For operations that lend themselves to being parallellized (count & count pairs should both apply), implement a multiprocessing architecture to take advantage of multiple cores. This is similar in spirit and design to Rio Mucho, however that library expects a disk path to write output to, instead of returning numpy arrays which would be useful for an HTTP geoprocessing service.

Dominant language
Python
Stars
6
Forks
1
No merged PRs in 30d

Getting set up

  • Ships a Dockerfile or Docker Compose file
  • No pull request template
  • No contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

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