issue_comments: 272715240

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https://github.com/pydata/xarray/pull/1162#issuecomment-272715240 https://api.github.com/repos/pydata/xarray/issues/1162 272715240 MDEyOklzc3VlQ29tbWVudDI3MjcxNTI0MA== 743508 2017-01-15T18:53:26Z 2017-01-15T18:53:26Z CONTRIBUTOR

Completed changes based on recommendations and cleaned up old code and comments.

As for benchmarks, I don't have anything rigourous but I do have the following example dataset weather data from the CFSR dataset, 7 variables at hourly resolution, collected in one netCDF3 file per variable per month. In the particular case the difference is striking!

python %%time data = dataset.isel_points(time=np.arange(0,1000), lat=np.ones(1000, dtype=int), lon=np.ones(1000, dtype=int)) data.load()

Results:

``` xarray 0.8.2 CPU times: user 1min 21s, sys: 41.5 s, total: 2min 2s Wall time: 47.8 s

master CPU times: user 385 ms, sys: 238 ms, total: 623 ms Wall time: 288 ms ```

 
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