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Merge pull request #28 from xcube-dev/konstntokas-xxx-fix_netcdf_access
Access NetCDF via preloead API
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CHANGES.md

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# Changes in 1.2.0
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- Lazy access to NetCDF datasets via Zenodo is no longer supported. NetCDF files
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must now be preloaded using the `preload_data` method.
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## Changes in 1.1.1
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- Add support for configuring the number of concurrent workers in `preload_data`,

README.md

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## How to use the xcube-zenodo plugin
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### Lazy access of datasets published as `tif` or `netcdfs` and zipped (uncompressed) `zarr`
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### Lazy access of datasets published as `tif` and zipped (uncompressed) `zarr`
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To access datasets published on Zenodo, locate the **record ID** in the URL of the
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respective Zenodo webpage. This ID is required when initializing the Zenodo data store.
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To learn more check out the Example note books:
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- [Access TIF](examples/01_lazy_access_tif.ipynb)
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- [Access NetCDF](examples/02_lazy_access_netcdf.ipynb)
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- [Access zipped Zarr](examples/03_lazy_access_zarr.ipynb)
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- [Access zipped Zarr](examples/02_lazy_access_zarr.ipynb)
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### Access compressed datasets via the xcube's preload API
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### Access compressed datasets and datasets published as `netcdf` via the xcube's preload API
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If datasets are published as `zip`, `tar`, `tar.gz`, or `.rar` you can use the preload
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API to preload the data into the local file system. If the compressed file contains
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multiple datasets, the data IDs will be extended by one layer. A short example is shown
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below.
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If datasets are published as `nc`, `zip`, `tar`, `tar.gz`, or `.rar` you can use the
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preload API to preload the data into the local file system. If the compressed file
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contains multiple datasets, the data IDs will be extended by one layer. A short
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example is shown below.
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```python
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from xcube.core.store import new_data_store
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To learn more check out the example notebooks:
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- [Access NetCDF](examples/03_preload_netcdf.ipynb)
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- [Access zipped TIF files](examples/04_preload_zip.ipynb)
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- [Access RAR-compressed files](examples/05_preload_rar.ipynb)
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