Author: Andreas Tille <tille@debian.org>
Last-Update: Wed, 15 Nov 2023 08:48:20 +0100
Description: This example which should enrich the doc needs scanpy.
  While the packaging for scanpy has started it is not finished yet.
  Thus the example is excluded here.
FIXME: Just drop this patch once python3-scanpy might be available

--- a/src/anndata/experimental/merge.py
+++ b/src/anndata/experimental/merge.py
@@ -507,37 +507,8 @@ def concat_on_disk(
     The following examples highlight the differences this function has.
 
     First, let’s get some “big” datasets with a compatible ``var`` axis:
+    Example removed for the Debian package since scanpy packaging is not finished yet
 
-    >>> import httpx
-    >>> import scanpy as sc
-    >>> base_url = "https://datasets.cellxgene.cziscience.com"
-    >>> def get_cellxgene_data(id_: str):
-    ...     out_path = sc.settings.datasetdir / f'{id_}.h5ad'
-    ...     if out_path.exists():
-    ...         return out_path
-    ...     file_url = f"{base_url}/{id_}.h5ad"
-    ...     sc.settings.datasetdir.mkdir(parents=True, exist_ok=True)
-    ...     out_path.write_bytes(httpx.get(file_url).content)
-    ...     return out_path
-    >>> path_b_cells = get_cellxgene_data('a93eab58-3d82-4b61-8a2f-d7666dcdb7c4')
-    >>> path_fetal = get_cellxgene_data('d170ff04-6da0-4156-a719-f8e1bbefbf53')
-
-    Now we can concatenate them on-disk:
-
-    >>> import anndata as ad
-    >>> ad.experimental.concat_on_disk(
-    ...     dict(b_cells=path_b_cells, fetal=path_fetal),
-    ...     'merged.h5ad',
-    ...     label='dataset',
-    ... )
-    >>> adata = ad.read_h5ad('merged.h5ad', backed=True)
-    >>> adata.X
-    CSRDataset: backend hdf5, shape (490, 15585), data_dtype float32
-    >>> adata.obs['dataset'].value_counts()  # doctest: +SKIP
-    dataset
-    fetal      344
-    b_cells    146
-    Name: count, dtype: int64
     """
     if len(in_files) == 0:
         msg = "No objects to concatenate."