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2 rows where author_association = "CONTRIBUTOR", issue = 259058863 and user = 4414299 sorted by updated_at descending

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  • maaleske · 2 ✖

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  • Parsing wavelength info from rasterio tags · 2 ✖

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  • CONTRIBUTOR · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
343601202 https://github.com/pydata/xarray/pull/1583#issuecomment-343601202 https://api.github.com/repos/pydata/xarray/issues/1583 MDEyOklzc3VlQ29tbWVudDM0MzYwMTIwMg== maaleske 4414299 2017-11-10T22:13:48Z 2017-11-10T22:13:48Z CONTRIBUTOR

@jhamman Any comments on the current implementation? I'm not sure how to handle possible collisions with the tag parsing and existing xarray attributes / coordinates with the same name.

Also, while writing the test for this, I found out that rasterio < 1.0a doesn't support saving the tags to the file, so I added a version check there.

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  Parsing wavelength info from rasterio tags 259058863
335827523 https://github.com/pydata/xarray/pull/1583#issuecomment-335827523 https://api.github.com/repos/pydata/xarray/issues/1583 MDEyOklzc3VlQ29tbWVudDMzNTgyNzUyMw== maaleske 4414299 2017-10-11T14:23:24Z 2017-10-11T14:23:24Z CONTRIBUTOR

I think I found a way to make the metadata parsing a bit more general and extendable. I implemented a more general parser for the ENVI case as a proof of concept.

Now if a recognized driver is detected, instead of parsing tags(band) for each band, it queries the metadata domain for the driver using riods.tags(ns=riods.driver) and then munges any known arrays into a numpy format. Later the resulting dictionary is slotted into either coordinates or attributes based on the values type. This should make it pretty easy to implement parsers for different file formats without caring about the partial parsing done by GDAL for the other tags() calls.

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  Parsing wavelength info from rasterio tags 259058863

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