Determine a method for matching people in a localized area
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- Dominant language
- Python
- Stars
- 97
- Forks
- 36
- Avg merge
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- Merged PRs (30d)
- 1
Description
If beans were to support matching in a specific city and support neighborhood matching in that city, we would want an expandable way to match people based on their location. There are a few ways to do this.
- Set up individual instances of the service for each sub region
- + simplifies logic
- - doesn't allow you to save history from meetings across regions (ie if someone met before and they switch regions, the datastore would be different and wouldn't know if they met anyone before in the new region)
- Use the metadata field for the User entity to specify the User's "location". From there we could specify a matching filter to only look at people in the same area (we do the exact opposite for keeping people from matching in the same department) This would explicitly bucket you based on your area.
- - increases complexity
- + allows for management of an entire area in one app
- - this increases the number of matching bins, meaning low activity areas would be more prone to
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 by reading yelp_beans/match.py around the existing department-based matching exclusion, then inspect how the User metadata field is represented. Compare the two location approaches described in the issue, including their effects on history and matching groups. Done means selecting and documenting an expandable approach for city and neighborhood matching.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- backend-api-design
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100