ioos / ioos/ioos_code_lab

Issue on page /content/code_gallery/data_access_notebooks/2017-06-12-NCEI_RA_archive_history.html

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Dominant language
Jupyter Notebook
Stars
16
Forks
15
Avg merge
1h 39m
Merged PRs (30d)
6

Description

This notebook should be updated to use the One Stop Information Management (OSIM) system. See details below:

The Search API is best used for searching on collections or granules with filtering constraints to determine the UUID(s) or retrieve data parsed from the original record(s) as JSON. See https://app.swaggerhub.com/apis/cedarbot/OneStop-Search/3.0.0-RC1#/granule/searchGranule for an example of a granule search with filtering. Available filtering options can be found on the SwaggerHub page for the Search API under schemas. Note that the API endpoints for flattened-granule would likely return sparse results

If the original record content is needed, then the Registry API is the best choice to retrieve the record by UUID. For example, the full XML for this collection can be retrieved via a request to https://data.noaa.gov/onestop/api/registry/metadata/collection/bccea51e-7ecc-4b79-8ebe-8fe1dbf507c6/raw/xml. Note that OSIM supports both XML and JSON records with corresponding Registry API endpoints, and some records will have both present (typically for granules).

Contributor guide

Open the 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.

Research direction

Open content/code_gallery/data_access_notebooks/2017-06-12-NCEI_RA_archive_history.html and review its current data-access workflow. Use the linked OSIM Search API SwaggerHub documentation for filtered collection or granule searches, and the Registry API documentation when original XML or JSON records are needed. Done means the notebook uses the OSIM endpoints and still demonstrates the intended archive-history data retrieval.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook
Domain
api, data
Issue type
Refactor
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
45/100

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