This will likely be implemented in the BaseView class, which needs to know how to spot the .csv extension, call the underlying JSON generating function and then return the columns and rows as correctly formatted CSV.

Lines 201 to 207 in 9959a9e

    
           async def view_get(self, request, name, hash, **kwargs): 
        
               try: 
        
                   as_json = kwargs.pop("as_json") 
        
               except KeyError: 
        
                   as_json = False 
        
               extra_template_data = {} 
        
               start = time.time()

This means it will take ALL arguments that are available to the .json view. It may ignore some (e.g. _facet= makes no sense since CSV tables don't have space to show the facet results).

In streaming mode, things will behave a little bit differently - in particular, if _stream=1 then _next= will be forbidden.

It can't include a length header because we don't know how many bytes it will be

CSV output will throw an error if the endpoint doesn't have rows and columns keys eg /-/inspect.json

So the implementation...

looks for the .csv extension
internally fetches the .json data instead
If no _stream it just transposes that JSON to CSV with the correct content type header
If _stream=1 - checks for _next= and throws an error if it was provided
Otherwise... fetch first page and emit CSV header and first set of rows
Then start async looping, emitting more CSV rows and following the _next= internal reference until done

I like that this takes advantage of efficient pagination. It may not work so well for views which use offset/limit though.

It won't work at all for custom SQL because custom SQL doesn't support _next= pagination. That's fine.

For views... easiest fix is to cut off after first X000 records. That seems OK. View JSON would need to include a property that the mechanism can identify.

	async def view_get(self, request, name, hash, **kwargs):
	try:
	as_json = kwargs.pop("as_json")
	except KeyError:
	as_json = False
	extra_template_data = {}
	start = time.time()

Uh oh!

Export to CSV #266

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