Introduced new test_read_netcdf.py function for directly converting netCDF files into XarrayContext.#226
Introduced new test_read_netcdf.py function for directly converting netCDF files into XarrayContext.#226dfang843 wants to merge 1 commit into
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directly converting netCDF files into XarrayContext.
alxmrs
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alxmrs
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First (quick) pass. Thanks for the PR!
| self.register_udf(cft.make_cftime_udf(units, cal)) | ||
| break # One UDF per context is enough. | ||
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| @classmethod |
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I think this should be an instance method.
| """ | ||
| path = Path(path) | ||
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| ds = xr.open_dataset(path, engine=engine, **open_kwargs) |
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The engine should be best-effort a netcdf engine IMO, and users won't need to pass it in, since the method name implies the type of data.
| XarrayContext | ||
| A context with the dataset already registered. | ||
| """ | ||
| path = Path(path) |
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I think open dataset handles this.
| engine: str | None = "netcdf4", | ||
| **open_kwargs, | ||
| ): | ||
| """ |
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We use Google style docstrings.
| table_name = path.stem | ||
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| if chunks is None: | ||
| chunks = {"time": 24} if "time" in ds.dims else {d: -1 for d in ds.dims} |
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Let's be correct, not polite. The users must pass in chunks.
| from .reader import read_xarray_table | ||
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| from pathlib import Path | ||
| from matplotlib.dates import date2num |
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These libraries have been imported to ensure that test_read_netcdf.py doesn't throw errors when running.
| from metpy.cbook import get_test_data | ||
| from xarray_sql import XarrayContext | ||
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| path = get_test_data('irma_gfs_example.nc', False) |
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Let's use pytest conventions for tests.
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