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Cookiecut #8
Cookiecut #8
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Hi @MaceKuailv,
import xarray as xr
import fsspec
def test_dummy():
url = "https://github.com/pydata/xarray-data/raw/master/air_temperature.nc"
with fsspec.open(f"simplecache::{url}") as f:
ds = xr.open_dataset(f) |
And most importantly, make sure you reduce as much as possible the size of data to download. import xarray as xr
import numpy as np
ds = xr.Dataset(
{"foo": xr.DataArray(np.random.randn(2, 3, 4), dims=("time", "lat", "lon"))}
) |
I think the first one is pretty straightforward to implement. But I am not sure how much do I need to reduce the size of the data. I am reluctant to generate the velocity field purely from scratch so I will preserve at least one snapshot of it. And of course, I need to store many of the coords. My estimate is that I could probably reduce it to around 20-50 mb. Is that enough? Every time I upload to zenodo, it asks me something like "are you sure you want to do this? we will create a doi that will be forever". Is it OK to upload things frequently? If I were to generate the data, where should I store the function that open and generate the data? Do you have any other comments not related to the tests? I developed the test from main branch, so every change I made on the test from cookiecut branch will almost certainly cause a merge conflict. I would prefer we merge it first, and create a new branch for the test data problem. |
How about you merge this, and I will open issues with a few tips? I also want to show you a couple of improvements/changes to the template, but I think it's easier if I open a PR. I'll reply to the test question in a dedicated issue! |
OK, issue opened. After you merge this, I will open a PR with a couple of improvements for stuff like CI and packaging. |
Very nice |
Changes related to CI