We can't publish non-tabular data because we do tabular data validation of all resources (irrespective of type) on every publish.
More info: We validate the data prior to uploading to data package registry. Previously we focused on publishing csv data to DPR. But recently we tried geojson data and found a bug because dpmpy is throwing an error that geojson is invalid when it auto checks its validity [because it is not tabular data].
Ref: #88
Tasks
[x] Write a test with a data package with some non-tabular data
[x] Skip data validation for any non-tabular data
[x] Check the file type is tabular
[x] resources --> format (is csv)
[x] resources --> mediatype (text/csv)
[x] filename filename ends with csv.
[x] If non tabular skip the validation
Acceptance Criteria:
[ ] Non tabular data can be uploaded from command line.
Analysis
Options:
Turn off default validation and make it an optional switch
Skip data validation for any non-tabular data (tabular data = OR(format csv, filename ends in .csv, mediatype=text/csv)
Validation option for geojson data [NO]
We recommend option 1 or 2 as we do not need data validation for geojson data (right now). For now we will just implement option 2 and can revisit option 1 later if needed.
User may not always need to check data validation
For not tabular data we do not need data validation.
We can't publish non-tabular data because we do tabular data validation of all resources (irrespective of type) on every publish.
More info: We validate the data prior to uploading to data package registry. Previously we focused on publishing csv data to DPR. But recently we tried geojson data and found a bug because dpmpy is throwing an error that geojson is invalid when it auto checks its validity [because it is not tabular data].
Ref: #88
Tasks
Acceptance Criteria:
Analysis
Options:
We recommend option 1 or 2 as we do not need data validation for geojson data (right now). For now we will just implement option 2 and can revisit option 1 later if needed.