cancervariants / cancervariants/therapy-normalization
Optimize normalized concept generation
- Dominant language
- Python
- Stars
- 15
- Forks
- 3
- PR merge metrics
- No merged PRs in 30d
Description
Brainstorming:
* Don't create new DB entries unless the new concept differs from the old one, and keep updates to a minimum
* Rather than scanning for all concept IDs, querying to build concept groups, and querying again to build the record itself, try to combine steps
Contributor guide
No contributing guide indexed for this repository
Research direction
No files, tests, or entry points are named. Start by locating normalized concept generation and its database writes, then compare the current queries and updates with the two optimization goals; done means avoiding unchanged concept entries and minimizing the query steps without changing the generated record.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- bioinformatics, databases
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100