Refactor bundled example dataset interface
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 29
- Forks
- 9
- Avg merge
- 9d 9h
- Merged PRs (30d)
- 8
Description
Right now, each dataset has its own user-exposed loader function. I think it would be better to follow the pattern ArviZ takes: a single user-exposed az.load_arviz_dataset() that takes the name of the dataset to load as a string, plus an az.list_datasets() method that enumerates the available datasets, with description and documentation.
Thoughts @damonbayer @cdc-mitzimorris?
Contributor guide
No contributing guide indexed for this repository
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 locating the existing user-exposed dataset loader functions and reviewing how ArviZ provides load_arviz_dataset() and list_datasets(). Define the supported dataset names, descriptions, and documentation entries, then verify that the unified loading and listing interface covers the existing bundled datasets.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- api
- Issue type
- Refactor
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 42/100