Updates examples to newer Icechunk syntax

docs/usage.md

@@ -426,15 +426,15 @@ By default references are placed in separate parquet file when the total number
 
 ### Writing to an Icechunk Store
 
-We can also write these references out as an [IcechunkStore](https://icechunk.io/). `Icechunk` is a Open-source, cloud-native transactional tensor storage engine that is compatible with zarr version 3. To export our virtual dataset to an `Icechunk` Store, we simply use the {py:meth}`vds.virtualize.to_icechunk <virtualizarr.VirtualiZarrDatasetAccessor.to_icechunk>` accessor method.
+We can also write these references out as an [IcechunkStore](https://icechunk.io/). `Icechunk` is an open-source, cloud-native transactional tensor storage engine that is compatible with Zarr version 3. To export our virtual dataset to an `Icechunk` Store, we simply use the {py:meth}`vds.virtualize.to_icechunk <virtualizarr.VirtualiZarrDatasetAccessor.to_icechunk>` accessor method.
 
 ```python
 # create an icechunk repository, session and write the virtual dataset to the session
-from icechunk import Repository, Storage, VirtualChunkContainer, local_filesystem_storage
+import icechunk
 storage = local_filesystem_storage("./local/icechunk/store")
 
 # By default, local virtual references and public remote virtual references can be read wihtout extra configuration.
-repo = Repository.create(storage=storage)
+repo = icechunk.Repository.create(storage)
 session = repo.writeable_session("main")
 
 # write the virtual dataset to the session with the IcechunkStore
@@ -455,7 +455,7 @@ session.commit("Appended second dataset")
 ```
 
 See the [Icechunk documentation](https://icechunk.io/icechunk-python/virtual/#creating-a-virtual-dataset-with-virtualizarr) for more details.
-
+icechunk-python/virtual/#creating-a-virtual-dataset-with-virtualizarr
 
 
 ## Opening Kerchunk references as virtual datasets