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  • jsignell · 3 ✖

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  • Tools for converting between xray.Dataset and nested dictionaries/JSON · 3 ✖

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  • CONTRIBUTOR · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
234598308 https://github.com/pydata/xarray/issues/432#issuecomment-234598308 https://api.github.com/repos/pydata/xarray/issues/432 MDEyOklzc3VlQ29tbWVudDIzNDU5ODMwOA== jsignell 4806877 2016-07-22T17:00:29Z 2016-07-22T17:16:16Z CONTRIBUTOR

Ok. That makes sense. I added a function to common and submitted a pull request: #917 

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   Tools for converting between xray.Dataset and nested dictionaries/JSON 88075523
234540415 https://github.com/pydata/xarray/issues/432#issuecomment-234540415 https://api.github.com/repos/pydata/xarray/issues/432 MDEyOklzc3VlQ29tbWVudDIzNDU0MDQxNQ== jsignell 4806877 2016-07-22T13:14:43Z 2016-07-22T13:14:43Z CONTRIBUTOR

I agree.

.3. Couldn't this make the dict blow up for large datasets? Maybe there could be a flag that lets the user decide whether to leave the data in its current form (could use self.data in case it is a dask array) 6. The trouble with xarray.DataArray is that it doesn't require a name but it can have one. Is that something that we would want to preserve? If not, then maybe it would look more like this.

``` tolist=True

d = {'coords': {}, 'attrs': dict(self.attrs), 'dims': self.dims}

def func(x, tolist): if tolist: return x.tolist() return x

for k in self.coords: d['coords'].update({k: {'data': func(self[k].data, tolist), 'dims': list(self[k].dims), 'attrs': dict(self[k].attrs)}}) if hasattr(self, 'data_vars'): d.update({'data_vars': {}}) for k in self.data_vars: d['data_vars'].update({k: {'data': func(self[k].data, tolist), 'dims': list(self[k].dims), 'attrs': dict(self[k].attrs)}}) else: d.update({'data': func(self.data, tolist)}) ```

 
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   Tools for converting between xray.Dataset and nested dictionaries/JSON 88075523
234082452 https://github.com/pydata/xarray/issues/432#issuecomment-234082452 https://api.github.com/repos/pydata/xarray/issues/432 MDEyOklzc3VlQ29tbWVudDIzNDA4MjQ1Mg== jsignell 4806877 2016-07-20T21:03:33Z 2016-07-20T21:03:33Z CONTRIBUTOR

Is this still of interest? I was thinking it would look something like this:

``` d = {'coordinates': {}, 'variables': {}, 'attributes': {}}

d['attributes'].update(dict(self.attrs))

for k in self.coords: d['coordinates'].update({k: {'data': self[k].data, 'dimensions': list(self[k].dims), 'attributes': dict(self[k].attrs)}}) if hasattr(self, 'data_vars'): for k in self.data_vars: d['variables'].update({k: {'data': self[k].data, 'dimensions': list(self[k].dims), 'attributes': dict(self[k].attrs)}}) else: d['variables'].update({'data': self.data, 'dimensions': list(self.dims), 'attributes': dict(self.attrs)}) ```

 
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   Tools for converting between xray.Dataset and nested dictionaries/JSON 88075523

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