fix #540

Signed-off-by: zethson <lukas.heumos@posteo.net>

.flake8

@@ -25,9 +25,9 @@ ignore = # module imported but unused -> required for Scanpys API
          E731,
          # allow I, O, l as variable names -> I is the identity matrix, i, j, k, l is reasonable indexing notation
          E741
- per-file-ignores =
+per-file-ignores =
     # F811 Redefinition of unused name from line, does not play nice with pytest fixtures
-    tests/test*.py: F811
+    anndata/tests/test*.py: F811
     # F821 Undefined name, can't import AnnData or it'd be a circular import
     anndata/compat/_overloaded_dict.py: F821
     # E721 comparing types, but we specifically are checking that we aren't getting subtypes (views)

anndata/_core/views.py

@@ -8,6 +8,7 @@
 from pandas.api.types import is_bool_dtype
 from scipy import sparse
 
+import anndata
 from .access import ElementRef
 from ..logging import anndata_logger as logger
 from ..compat import ZappyArray
@@ -44,7 +45,7 @@ class _ViewMixin(_SetItemMixin):
     def __init__(
         self,
         *args,
-        view_args: Tuple["anndata.AnnData", str, Tuple[str, ...]] = None,
+        view_args: Tuple[anndata.AnnData, str, Tuple[str, ...]] = None,
         **kwargs,
     ):
         if view_args is not None:

anndata/_io/read.py

@@ -18,7 +18,7 @@
 except ImportError as e:  # noqa: F841
 
     def read_zarr(*_, **__):
-        raise e
+        raise e  # noqa: F821  TODO: There might be a better way to go about this
 
 
 def read_csv(

anndata/_io/write.py

@@ -19,7 +19,7 @@
 except ImportError as e:  # noqa: F841  # TODO: Is there a better way?
 
     def write_zarr(*_, **__):
-        raise e
+        raise e  # noqa: F821  # TODO: Fix together with import Error handling
 
 
 logger = get_logger(__name__)

anndata/compat/__init__.py

@@ -9,7 +9,7 @@
 import pandas as pd
 
 from ._overloaded_dict import _overloaded_uns, OverloadedDict
-from .._core.index import _subset
+from .._core.index import _subset, Index1D
 
 # try importing zarr, dask, and zappy
 from packaging import version
@@ -194,7 +194,7 @@ def _find_sparse_matrices(d: Mapping, n: int, keys: tuple, paths: list):
     return paths
 
 
-def _slice_uns_sparse_matrices(uns: MutableMapping, oidx: "Index1d", orig_n_obs: int):
+def _slice_uns_sparse_matrices(uns: MutableMapping, oidx: Index1D, orig_n_obs: int):
     """slice sparse spatrices of n_obs × n_obs in self.uns"""
     if isinstance(oidx, slice) and len(range(*oidx.indices(orig_n_obs))) == orig_n_obs:
         return uns  # slice of entire dimension is a no-op

anndata/tests/helpers.py

@@ -1,6 +1,6 @@
 from functools import singledispatch, wraps
 from string import ascii_letters
-from typing import Tuple
+from typing import Tuple, Collection, Type
 from collections.abc import Mapping
 import warnings
 
@@ -68,9 +68,9 @@ def gen_adata(
     X_dtype=np.float32,
     # obs_dtypes,
     # var_dtypes,
-    obsm_types: "Collection[Type]" = (sparse.csr_matrix, np.ndarray, pd.DataFrame),
-    varm_types: "Collection[Type]" = (sparse.csr_matrix, np.ndarray, pd.DataFrame),
-    layers_types: "Collection[Type]" = (sparse.csr_matrix, np.ndarray, pd.DataFrame),
+    obsm_types: Collection[Type] = (sparse.csr_matrix, np.ndarray, pd.DataFrame),
+    varm_types: Collection[Type] = (sparse.csr_matrix, np.ndarray, pd.DataFrame),
+    layers_types: Collection[Type] = (sparse.csr_matrix, np.ndarray, pd.DataFrame),
 ) -> AnnData:
     """\
     Helper function to generate a random AnnData for testing purposes.

anndata/tests/test_concatenate.py

@@ -3,6 +3,7 @@
 from itertools import chain, product
 from functools import partial
 import warnings
+from typing import List, Callable, Any
 
 import numpy as np
 from numpy import ma
@@ -796,7 +797,7 @@ def map_values(mapping, path, key, old_parent, new_parent, new_items):
     return ret
 
 
-def permute_nested_values(dicts: "List[dict]", gen_val: "Callable[[int], Any]"):
+def permute_nested_values(dicts: List[dict], gen_val: Callable[[int], Any]):
     """
     This function permutes the values of a nested mapping, for testing that out merge
     method work regardless of the values types.