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import zarr
import pandas as pd, numpy as np

from anndata.experimental import read_elem, write_elem
from anndata._core.sparse_dataset import SparseDataset

def _df_index(df: zarr.Group) -> np.ndarray:
    index_key = df.attrs["_index"]
    return read_elem(df[index_key])

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# Docs: https://docs.h5py.org/en/stable/vds.html

import h5py
import numpy as np

def virtual_concatenate(datasets: list[h5py.Dataset]) -> h5py.VirtualLayout:
    """Concatenate datasets along the first axis."""
    vds = h5py.VirtualLayout(shape=sum(d.shape[0] for d in datasets), dtype=datasets[0].dtype)
    offset = 0
    for d in datasets:

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import pandas as pd
import geopandas as gpd
import numpy as np
from scipy import sparse
import anndata as ad

def aggregate_polygons_on_points(
    polygons: gpd.GeoDataFrame,
    points: gpd.GeoDataFrame,
    point_id_column: str,

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import ibis
import awkward as ak

!wget https://bioconductorhubs.blob.core.windows.net/annotationhub/AHEnsDbs/v108/EnsDb.Hsapiens.v108.sqlite

connection = ibis.sqlite.connect("EnsDb.Hsapiens.v108.sqlite")

gene = connection.table("gene")
tx = connection.table("tx")
tx2exon = connection.table("tx2exon")

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import copy

import dask.dataframe as dd
import dask.array as da

import dask
from dask.base import tokenize
from dask.dataframe.io.io import from_map

import pandas as pd, numpy as np, zarr

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