How to use the anndata.read function in anndata

if ext is not None and ext not in avail_exts:
        raise ValueError(
            'Please provide one of the available extensions.\n'
            f'{avail_exts}'
        )
    else:
        ext = is_valid_filename(filename, return_ext=True)
    is_present = _check_datafile_present_and_download(
        filename,
        backup_url=backup_url,
    )
    if not is_present: logg.debug(f'... did not find original file {filename}')
    # read hdf5 files
    if ext in {'h5', 'h5ad'}:
        if sheet is None:
            return read_h5ad(filename, backed=backed)
        else:
            logg.debug(f'reading sheet {sheet} from file {filename}')
            return read_hdf(filename, sheet)
    # read other file types
    path_cache = settings.cachedir / _slugify(filename).replace('.' + ext, '.h5ad')  # type: Path
    if path_cache.suffix in {'.gz', '.bz2'}:
        path_cache = path_cache.with_suffix('')
    if cache and path_cache.is_file():
        logg.info(f'... reading from cache file {path_cache}')
        return read_h5ad(path_cache)

    if not is_present:
        raise FileNotFoundError(f'Did not find file {filename}.')
    logg.debug(f'reading {filename}')
    if not cache and not suppress_cache_warning:
        logg.hint(

cache=cache,
            cache_compression=cache_compression,
            **kwargs,
        )
    # generate filename and read to dict
    filekey = str(filename)
    filename = settings.writedir / (filekey + '.' + settings.file_format_data)
    if not filename.exists():
        raise ValueError(
            f'Reading with filekey {filekey!r} failed, '
            f'the inferred filename {filename!r} does not exist. '
            'If you intended to provide a filename, either use a filename '
            f'ending on one of the available extensions {avail_exts} '
            'or pass the parameter `ext`.'
        )
    return read_h5ad(filename, backed=backed)

)
    if not is_present: logg.debug(f'... did not find original file {filename}')
    # read hdf5 files
    if ext in {'h5', 'h5ad'}:
        if sheet is None:
            return read_h5ad(filename, backed=backed)
        else:
            logg.debug(f'reading sheet {sheet} from file {filename}')
            return read_hdf(filename, sheet)
    # read other file types
    path_cache = settings.cachedir / _slugify(filename).replace('.' + ext, '.h5ad')  # type: Path
    if path_cache.suffix in {'.gz', '.bz2'}:
        path_cache = path_cache.with_suffix('')
    if cache and path_cache.is_file():
        logg.info(f'... reading from cache file {path_cache}')
        return read_h5ad(path_cache)

    if not is_present:
        raise FileNotFoundError(f'Did not find file {filename}.')
    logg.debug(f'reading {filename}')
    if not cache and not suppress_cache_warning:
        logg.hint(
            'This might be very slow. Consider passing `cache=True`, '
            'which enables much faster reading from a cache file.'
        )
    # do the actual reading
    if ext == 'xlsx' or ext == 'xls':
        if sheet is None:
            raise ValueError(
                "Provide `sheet` parameter when reading '.xlsx' files."
            )
        else:

if not os.path.exists(filename) and backup_url is None:
        raise FileNotFoundError('Did not find file {}.'.format(filename))

    elif not os.path.exists(filename):
        d = os.path.dirname(filename)
        if not os.path.exists(d): os.makedirs(d)
        urlretrieve(backup_url, filename)

    ext = Path(filename).suffixes[-1][1:]

    if ext in numpy_ext:
        return np.load(filename, **kwargs)
    elif ext in pandas_ext:
        return pd.read_csv(filename, **kwargs)
    elif ext in adata_ext:
        return anndata.read(filename, **kwargs)
    else:
        raise ValueError('"{}" does not end on a valid extension.\n'
                         'Please, provide one of the available extensions.\n{}\n'
                         .format(filename, numpy_ext | pandas_ext))