Removing Tensorstore Dependency

.pre-commit-config.yaml

@@ -1,4 +1,5 @@
-- repo: https://github.com/pre-commit/mirrors-yapf
-  rev: '5441be1'  # Use the sha / tag you want to point at
-  hooks:
-  - id: yapf
+repos:
+  - repo: https://github.com/pre-commit/mirrors-yapf
+    rev: '5441be1'  # Use the sha / tag you want to point at
+    hooks:
+      - id: yapf

setup.cfg

@@ -34,7 +34,6 @@ install_requires =
     qtpy
     scipy
     scikit-image
-    tensorstore
     toolz
     zarr
 
@@ -53,6 +52,7 @@ testing =
     coverage
     pytest
     pytest-cov
+    tensorstore
     pytest-qt
     napari[pyqt5]
 

setup.py

@@ -5,6 +5,4 @@
 # https://github.com/pypa/setuptools_scm
 use_scm = {"write_to": "src/zarpaint/_version.py"}
 
-setup(
-        use_scm_version=use_scm,
-        )
+setup(use_scm_version=use_scm,)

src/zarpaint/__init__.py

@@ -17,6 +17,5 @@
         'set_axis_labels',
         'watershed_split',
         'add_points_3d_with_alt_click',
-        'zarr_tensorstore'
         'copy_data',
         ]

src/zarpaint/_main.py

@@ -1,7 +1,6 @@
 import argparse
 import ast
 import sys
-
 from ._zarpaint import correct_labels
 
 parser = argparse.ArgumentParser(

src/zarpaint/_normalize.py

@@ -1,36 +1,37 @@
 import numpy as np
 
 _np_uints = {
-    8: np.uint8,
-    16: np.uint16,
-    32: np.uint32,
-    64: np.uint64,
-}
+        8: np.uint8,
+        16: np.uint16,
+        32: np.uint32,
+        64: np.uint64,
+        }
 
 _np_ints = {
-    8: np.int8,
-    16: np.int16,
-    32: np.int32,
-    64: np.int64,
-}
+        8: np.int8,
+        16: np.int16,
+        32: np.int32,
+        64: np.int64,
+        }
 
 _np_floats = {
-    16: np.float16,
-    32: np.float32,
-    64: np.float64,
-}
+        16: np.float16,
+        32: np.float32,
+        64: np.float64,
+        }
 
 _np_complex = {
-    64: np.complex64,
-    128: np.complex128,
-}
+        64: np.complex64,
+        128: np.complex128,
+        }
 
 _np_kinds = {
-    'uint': _np_uints,
-    'int': _np_ints,
-    'float': _np_floats,
-    'complex': _np_complex,
-}
+        'uint': _np_uints,
+        'int': _np_ints,
+        'float': _np_floats,
+        'complex': _np_complex,
+        }
+
 
 def _normalize_str_by_bit_depth(dtype_str, kind):
     if not any(str.isdigit(c) for c in dtype_str):  # Python 'int' or 'float'
@@ -47,6 +48,7 @@ def _normalize_str_by_bit_depth(dtype_str, kind):
     if '64' in dtype_str:
         return bit_dict[64]
 
+
 def normalize_dtype(dtype_spec):
     """Return a proper NumPy type given ~any duck array dtype.
     Parameters

src/zarpaint/_tests/test_copy_data.py

@@ -5,9 +5,12 @@
 from zarpaint import open_tensorstore
 import zarr
 
+
 def test_copy_data(make_napari_viewer):
     viewer = make_napari_viewer()
-    labels_layer1 = viewer.add_labels(np.random.randint(0, 2**23, size=(10, 20, 30)))
+    labels_layer1 = viewer.add_labels(
+            np.random.randint(0, 2**23, size=(10, 20, 30))
+            )
     labels_layer2 = viewer.add_labels(np.zeros((2, 10, 20, 30), dtype=int))
     viewer.dims.set_point(axis=0, value=1)
     widget = copy_data()
@@ -18,8 +21,14 @@ def test_copy_data(make_napari_viewer):
 
 def test_copy_data_tensorstore(make_napari_viewer, tmp_path):
     viewer = make_napari_viewer()
-    labels_layer1 = viewer.add_labels(np.random.randint(0, 2**23, size=(10, 20, 30)))
-    array2 = open_tensorstore(tmp_path/"example.zarr", shape=(2, 10, 20, 30), chunks=(1, 1, 20, 30))
+    labels_layer1 = viewer.add_labels(
+            np.random.randint(0, 2**23, size=(10, 20, 30))
+            )
+    array2 = open_tensorstore(
+            tmp_path / "example.zarr",
+            shape=(2, 10, 20, 30),
+            chunks=(1, 1, 20, 30)
+            )
     labels_layer2 = viewer.add_labels(array2)
     viewer.dims.set_point(axis=0, value=1)
     widget = copy_data()
@@ -30,14 +39,16 @@ def test_copy_data_tensorstore(make_napari_viewer, tmp_path):
 
 def test_copy_data_zarr(make_napari_viewer, tmp_path):
     viewer = make_napari_viewer()
-    labels_layer1 = viewer.add_labels(np.random.randint(0, 2**23, size=(10, 20, 30)))
+    labels_layer1 = viewer.add_labels(
+            np.random.randint(0, 2**23, size=(10, 20, 30))
+            )
     array2 = zarr.open(
-                str(tmp_path/"example.zarr"),
-                mode='w',
-                shape=(2, 10, 20, 30),
-                dtype=np.uint32,
-                chunks=(1, 1, 20, 30),
-                )
+            str(tmp_path / "example.zarr"),
+            mode='w',
+            shape=(2, 10, 20, 30),
+            dtype=np.uint32,
+            chunks=(1, 1, 20, 30),
+            )
     labels_layer2 = viewer.add_labels(array2)
     viewer.dims.set_point(axis=0, value=1)
     widget = copy_data()

src/zarpaint/_tests/test_reader.py

@@ -3,6 +3,7 @@
 import zarr
 import numpy as np
 
+
 def test_reader_pass(tmp_path):
     """
     Test that the reader is able to open a test file
@@ -11,22 +12,33 @@ def test_reader_pass(tmp_path):
     test_file = zarr_tensorstore(new_path)
     assert test_file is None
 
+
 def test_reader_return_callable(tmp_path):
     """
     Test the the reader returns a valid funciton when opening a file
-    """ 
+    """
     example_zarr_folder = tmp_path / 'example.zarr'
-    z1 = zarr.open_array(example_zarr_folder, mode='w', shape=(10000, 10000), chunks=(1000, 1000), dtype='i4', fill_value=0)
+    z1 = zarr.open_array(
+            example_zarr_folder,
+            mode='w',
+            shape=(10000, 10000),
+            chunks=(1000, 1000),
+            dtype='i4',
+            fill_value=0
+            )
     res = zarr_tensorstore(example_zarr_folder)
     assert callable(res)
-
+
+
 def test_reader_can_read_and_write_to_file(tmp_path):
     """
     Creates a zarr file, writes random data to it, then saves the file. Once saved, the file is then 
     reopened and the data is compared.
     """
     example_zarr_folder = tmp_path / 'example.zarr'
-    z1 = zarr.open_array(example_zarr_folder, mode='w', shape=(100, 100), chunks=(100, 100))
+    z1 = zarr.open_array(
+            example_zarr_folder, mode='w', shape=(100, 100), chunks=(100, 100)
+            )
     z1[:] = np.random.rand(100, 100)
 
     reader_func = zarr_tensorstore(example_zarr_folder)
@@ -36,5 +48,5 @@ def test_reader_can_read_and_write_to_file(tmp_path):
     assert len(layers) == 1
 
     layer_info = layers[0]
-    assert isinstance(layer_info, Tuple) 
+    assert isinstance(layer_info, Tuple)
     np.testing.assert_allclose(np.asarray(layer_info[0]), z1)

src/zarpaint/_zarpaint.py

@@ -3,7 +3,6 @@
 import ast
 import os
 import yaml
-
 from magicgui import magic_factory
 import dask.array as da
 import napari
@@ -63,7 +62,7 @@ def open_tensorstore(labels_file: pathlib.Path, *, shape=None, chunks=None):
                 dtype=np.uint32,
                 chunks=chunks,
                 )
-    # read some of the metadata for tensorstore driver from file
+    # read some metadata for tensorstore driver from file
     labels_temp = zarr.open(str(labels_file), mode='r')
     metadata = {
             'dtype': labels_temp.dtype.str,
@@ -120,10 +119,8 @@ def create_labels(
     else:  # use default
         chunks = (1,) * (source_image.ndim - 2) + (128, 128)
 
-    layer_data = open_tensorstore(
-            labels_file,
-            shape=source_image.data.shape,
-            chunks=chunks,
+    layer_data = zarr.open(
+            labels_file, shape=source_image.data.shape, chunks=chunks
             )
     layer_type = 'labels'
     layer_metadata = {

src/zarpaint/napari.yaml

@@ -17,9 +17,6 @@ contributions:
   - id: zarpaint.watershed_split
     title: Split With Watershed…
     python_name: zarpaint:watershed_split
-  - id: zarpaint.get_reader
-    title: Get Reader
-    python_name: zarpaint:zarr_tensorstore
   - id: zarpaint.copy_data
     title: Copy Data…
     python_name: zarpaint:copy_data

src/zarpaint/reader.py

@@ -1,13 +1,11 @@
 from __future__ import annotations
-
+import zarr
 import os
 import pathlib
-from ._zarpaint import open_tensorstore, open_ts_meta
+from ._zarpaint import open_ts_meta
 
 
 def zarr_tensorstore(path: str | pathlib.Path):
     if (str(path).endswith('.zarr') and os.path.isdir(path)
                 and '.zarray' in os.listdir(path)):
-        return lambda path: [
-                (open_tensorstore(path), open_ts_meta(path), 'labels')
-                ]
+        return lambda path: [(zarr.open(path), open_ts_meta(path), 'labels')]