html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/1075#issuecomment-373541528,https://api.github.com/repos/pydata/xarray/issues/1075,373541528,MDEyOklzc3VlQ29tbWVudDM3MzU0MTUyOA==,3698640,2018-03-15T22:21:51Z,2018-03-16T01:33:24Z,CONTRIBUTOR,"xarray==0.10.2
netCDF4==1.3.1
Just tried it again and didn't have any issues:
```python
patt = (
'http://nasanex.s3.amazonaws.com/NEX-GDDP/BCSD/{scen}/day/atmos/{var}/' +
'r1i1p1/v1.0/{var}_day_BCSD_{scen}_r1i1p1_{model}_{year}.nc')
def open_url_dataset(url):
fname = os.path.splitext(os.path.basename(url))[0]
res = requests.get(url)
content = io.BytesIO(res.content)
nc4_ds = netCDF4.Dataset(fname, memory=res.content)
store = xr.backends.NetCDF4DataStore(nc4_ds)
ds = xr.open_dataset(store)
return ds
ds = open_url_dataset(url=patt.format(
model='GFDL-ESM2G', scen='historical', var='tasmax', year=1988))
ds
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186895655
https://github.com/pydata/xarray/issues/1075#issuecomment-357125148,https://api.github.com/repos/pydata/xarray/issues/1075,357125148,MDEyOklzc3VlQ29tbWVudDM1NzEyNTE0OA==,3698640,2018-01-12T02:27:27Z,2018-01-12T02:27:27Z,CONTRIBUTOR,"yes! Thanks @jhamman and @shoyer. I hadn't tried it yet, but just did. worked great!
```python
In [1]: import xarray as xr
...: import requests
...: import netCDF4
...:
...: %matplotlib inline
In [2]: res = requests.get(
...: 'http://nasanex.s3.amazonaws.com/NEX-GDDP/BCSD/rcp45/day/atmos/tasmin/' +
...: 'r1i1p1/v1.0/tasmin_day_BCSD_rcp45_r1i1p1_CESM1-BGC_2073.nc')
In [3]: res.status_code
Out [3]: 200
In [4]: res.headers['content-type']
Out [4]: 'application/x-netcdf'
In [5]: nc4_ds = netCDF4.Dataset('tasmin_day_BCSD_rcp45_r1i1p1_CESM1-BGC_2073', memory=res.content)
In [6]: store = xr.backends.NetCDF4DataStore(nc4_ds)
In [7]: ds = xr.open_dataset(store)
In [8]: ds.tasmin.isel(time=0).plot()
/global/home/users/mdelgado/git/public/xarray/xarray/plot/utils.py:51: FutureWarning: 'pandas.tseries.converter.register' has been moved and renamed to 'pandas.plotting.register_matplotlib_converters'.
converter.register()
Out [8]:
```
```python
In [9]: ds
Out [9]:
Dimensions: (lat: 720, lon: 1440, time: 365)
Coordinates:
* time (time) datetime64[ns] 2073-01-01T12:00:00 2073-01-02T12:00:00 ...
* lat (lat) float32 -89.875 -89.625 -89.375 -89.125 -88.875 -88.625 ...
* lon (lon) float32 0.125 0.375 0.625 0.875 1.125 1.375 1.625 1.875 ...
Data variables:
tasmin (time, lat, lon) float64 ...
Attributes:
parent_experiment: historical
parent_experiment_id: historical
parent_experiment_rip: r1i1p1
Conventions: CF-1.4
institution: NASA Earth Exchange, NASA Ames Research C...
institute_id: NASA-Ames
realm: atmos
modeling_realm: atmos
version: 1.0
downscalingModel: BCSD
experiment_id: rcp45
frequency: day
realization: 1
initialization_method: 1
physics_version: 1
tracking_id: 1865ff49-b20c-4268-852a-a9503efec72c
driving_data_tracking_ids: N/A
driving_model_ensemble_member: r1i1p1
driving_experiment_name: historical
driving_experiment: historical
model_id: BCSD
references: BCSD method: Thrasher et al., 2012, Hydro...
DOI: http://dx.doi.org/10.7292/W0MW2F2G
experiment: RCP4.5
title: CESM1-BGC global downscaled NEX CMIP5 Cli...
contact: Dr. Rama Nemani: rama.nemani@nasa.gov, Dr...
disclaimer: This data is considered provisional and s...
resolution_id: 0.25 degree
project_id: NEXGDDP
table_id: Table day (12 November 2010)
source: BCSD 2014
creation_date: 2015-01-07T19:18:31Z
forcing: N/A
product: output
```
","{""total_count"": 4, ""+1"": 4, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186895655
https://github.com/pydata/xarray/issues/1075#issuecomment-347705483,https://api.github.com/repos/pydata/xarray/issues/1075,347705483,MDEyOklzc3VlQ29tbWVudDM0NzcwNTQ4Mw==,3698640,2017-11-28T23:58:41Z,2017-11-28T23:58:41Z,CONTRIBUTOR,"Thanks @shoyer. So you can download the entire object into memory and then create a file image and read that? While not a full fix, it's definitely an improvement over download-to-disk-then-read workflow!","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186895655
https://github.com/pydata/xarray/issues/1075#issuecomment-258025809,https://api.github.com/repos/pydata/xarray/issues/1075,258025809,MDEyOklzc3VlQ29tbWVudDI1ODAyNTgwOQ==,3698640,2016-11-02T23:03:34Z,2016-11-02T23:03:34Z,CONTRIBUTOR,"Got it. :( Thanks!
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186895655