tidy

Author: alimanfoo

zarr/attrs.py

@@ -113,11 +113,13 @@ def put(self, d):
         self._write_op(self._put_nosync, d)
 
     def _put_nosync(self, d):
-        s = json.dumps(d, indent=4, sort_keys=True, ensure_ascii=True, separators=(',', ': '))
+        s = json.dumps(d, indent=4, sort_keys=True, ensure_ascii=True,
+                       separators=(',', ': '))
         self.store[self.key] = s.encode('ascii')
         if self.cache:
             self._cached_asdict = d
 
+    # noinspection PyMethodOverriding
     def update(self, *args, **kwargs):
         """Update the values of several attributes in a single operation."""
         self._write_op(self._update_nosync, *args, **kwargs)

zarr/convenience.py

@@ -54,7 +54,7 @@ def open(store, mode='a', **kwargs):
         >>> zr = zarr.open(store, mode='r')  # open existing array read-only
         >>> zr
         <zarr.core.Array (100,) int32 read-only>
-        >>> gw = zarr.open(store, mode='w')  # open new group, overwriting any previous data
+        >>> gw = zarr.open(store, mode='w')  # open new group, overwriting previous data
         >>> gw
         <zarr.hierarchy.Group '/'>
         >>> ga = zarr.open(store, mode='a')  # open existing group for reading and writing
@@ -97,8 +97,8 @@ def open(store, mode='a', **kwargs):
 
 
 def save_array(store, arr, **kwargs):
-    """Convenience function to save a NumPy array to the local file system, following a similar
-    API to the NumPy save() function.
+    """Convenience function to save a NumPy array to the local file system, following a
+    similar API to the NumPy save() function.
 
     Parameters
     ----------
@@ -152,7 +152,8 @@ def save_group(store, *args, **kwargs):
 
     Examples
     --------
-    Save several arrays to a directory on the file system (uses a :class:`DirectoryStore`)::
+    Save several arrays to a directory on the file system (uses a
+    :class:`DirectoryStore`):
 
         >>> import zarr
         >>> import numpy as np
@@ -333,17 +334,18 @@ def load(store):
     Returns
     -------
     out
-        If the store contains an array, out will be a numpy array. If the store contains a group,
-        out will be a dict-like object where keys are array names and values are numpy arrays.
+        If the store contains an array, out will be a numpy array. If the store contains
+        a group, out will be a dict-like object where keys are array names and values
+        are numpy arrays.
 
     See Also
     --------
     save, savez
 
     Notes
     -----
-    If loading data from a group of arrays, data will not be immediately loaded into memory.
-    Rather, arrays will be loaded into memory as they are requested.
+    If loading data from a group of arrays, data will not be immediately loaded into
+    memory. Rather, arrays will be loaded into memory as they are requested.
 
     """
     # handle polymorphic store arg

zarr/creation.py

@@ -80,13 +80,14 @@ def create(shape, chunks=True, dtype=None, compressor='default',
     Create an array with different some different configuration options::
 
         >>> from numcodecs import Blosc
+        >>> compressor = Blosc(cname='zstd', clevel=1, shuffle=Blosc.BITSHUFFLE)
         >>> z = zarr.create((10000, 10000), chunks=(1000, 1000), dtype='i1', order='F',
-        ...                 compressor=Blosc(cname='zstd', clevel=1, shuffle=Blosc.BITSHUFFLE))
+        ...                 compressor=compressor)
         >>> z
         <zarr.core.Array (10000, 10000) int8>
 
-    To create an array with object dtype requires a filter that can handle Python object encoding,
-    e.g., `MsgPack` or `Pickle` from `numcodecs`::
+    To create an array with object dtype requires a filter that can handle Python object
+    encoding, e.g., `MsgPack` or `Pickle` from `numcodecs`::
 
         >>> from numcodecs import MsgPack
         >>> z = zarr.create((10000, 10000), chunks=(1000, 1000), dtype=object,

zarr/errors.py

@@ -61,6 +61,6 @@ def err_too_many_indices(selection, shape):
 
 
 def err_vindex_invalid_selection(selection):
-    raise IndexError('unsupported selection type for vectorized indexing; only coordinate '
-                     'selection (tuple of integer arrays) and mask selection (single '
-                     'Boolean array) are supported; got {!r}'.format(selection))
+    raise IndexError('unsupported selection type for vectorized indexing; only '
+                     'coordinate selection (tuple of integer arrays) and mask selection '
+                     '(single Boolean array) are supported; got {!r}'.format(selection))

zarr/hierarchy.py

@@ -708,6 +708,7 @@ def require_groups(self, *names):
         """Convenience method to require multiple groups in a single call."""
         return tuple(self.require_group(name) for name in names)
 
+    # noinspection PyIncorrectDocstring
     def create_dataset(self, name, **kwargs):
         """Create an array.
 
@@ -977,7 +978,8 @@ def move(self, source, dest):
         dest = self._item_path(dest)
 
         # Check that source exists.
-        if not (contains_array(self._store, source) or contains_group(self._store, source)):
+        if not (contains_array(self._store, source) or
+                contains_group(self._store, source)):
             raise ValueError('The source, "%s", does not exist.' % source)
         if contains_array(self._store, dest) or contains_group(self._store, dest):
             raise ValueError('The dest, "%s", already exists.' % dest)

zarr/indexing.py

@@ -54,8 +54,10 @@ def normalize_integer_selection(dim_sel, dim_len):
     return dim_sel
 
 
-ChunkDimProjection = collections.namedtuple('ChunkDimProjection',
-                                            ('dim_chunk_ix', 'dim_chunk_sel', 'dim_out_sel'))
+ChunkDimProjection = collections.namedtuple(
+    'ChunkDimProjection',
+    ('dim_chunk_ix', 'dim_chunk_sel', 'dim_out_sel')
+)
 """A mapping from chunk to output array for a single dimension.
 
 Parameters
@@ -149,7 +151,8 @@ def __iter__(self):
                 dim_chunk_sel_stop = self.stop - dim_offset
 
             dim_chunk_sel = slice(dim_chunk_sel_start, dim_chunk_sel_stop, self.step)
-            dim_chunk_nitems = ceildiv((dim_chunk_sel_stop - dim_chunk_sel_start), self.step)
+            dim_chunk_nitems = ceildiv((dim_chunk_sel_stop - dim_chunk_sel_start),
+                                       self.step)
             dim_out_sel = slice(dim_out_offset, dim_out_offset + dim_chunk_nitems)
 
             yield ChunkDimProjection(dim_chunk_ix, dim_chunk_sel, dim_out_sel)
@@ -211,11 +214,13 @@ def ensure_tuple(v):
     return v
 
 
-ChunkProjection = collections.namedtuple('ChunkProjection',
-                                         ('chunk_coords', 'chunk_selection', 'out_selection'))
-"""A mapping of items from chunk to output array. Can be used to extract items from the chunk
-array for loading into an output array. Can also be used to extract items from a value array for
-setting/updating in a chunk array.
+ChunkProjection = collections.namedtuple(
+    'ChunkProjection',
+    ('chunk_coords', 'chunk_selection', 'out_selection')
+)
+"""A mapping of items from chunk to output array. Can be used to extract items from the 
+chunk array for loading into an output array. Can also be used to extract items from a 
+value array for setting/updating in a chunk array.
 
 Parameters
 ----------
@@ -264,7 +269,8 @@ def __init__(self, selection, array):
 
         # setup per-dimension indexers
         dim_indexers = []
-        for dim_sel, dim_len, dim_chunk_len in zip(selection, array._shape, array._chunks):
+        for dim_sel, dim_len, dim_chunk_len in \
+                zip(selection, array._shape, array._chunks):
 
             if is_integer(dim_sel):
                 dim_indexer = IntDimIndexer(dim_sel, dim_len, dim_chunk_len)
@@ -273,8 +279,9 @@ def __init__(self, selection, array):
                 dim_indexer = SliceDimIndexer(dim_sel, dim_len, dim_chunk_len)
 
             else:
-                raise IndexError('unsupported selection item for basic indexing; expected integer '
-                                 'or slice, got {!r}'.format(type(dim_sel)))
+                raise IndexError('unsupported selection item for basic indexing; '
+                                 'expected integer or slice, got {!r}'
+                                 .format(type(dim_sel)))
 
             dim_indexers.append(dim_indexer)
 
@@ -300,7 +307,8 @@ def __init__(self, dim_sel, dim_len, dim_chunk_len):
 
         # check number of dimensions
         if not is_bool_array(dim_sel, 1):
-            raise IndexError('Boolean arrays in an orthogonal selection must 1-dimensional only')
+            raise IndexError('Boolean arrays in an orthogonal selection must '
+                             'be 1-dimensional only')
 
         # check shape
         if dim_sel.shape[0] != dim_len:
@@ -392,7 +400,8 @@ def __init__(self, dim_sel, dim_len, dim_chunk_len, wraparound=True, boundscheck
         # ensure 1d array
         dim_sel = np.asanyarray(dim_sel)
         if not is_integer_array(dim_sel, 1):
-            raise IndexError('integer arrays in an orthogonal selection must be 1-dimensional only')
+            raise IndexError('integer arrays in an orthogonal selection must be '
+                             '1-dimensional only')
 
         # handle wraparound
         if wraparound:
@@ -409,7 +418,8 @@ def __init__(self, dim_sel, dim_len, dim_chunk_len, wraparound=True, boundscheck
         self.nitems = len(dim_sel)
 
         # determine which chunk is needed for each selection item
-        # note: for dense integer selections, the division operation here is the bottleneck
+        # note: for dense integer selections, the division operation here is the
+        # bottleneck
         dim_sel_chunk = dim_sel // dim_chunk_len
 
         # determine order of indices
@@ -520,7 +530,8 @@ def __init__(self, selection, array):
 
         # setup per-dimension indexers
         dim_indexers = []
-        for dim_sel, dim_len, dim_chunk_len in zip(selection, array._shape, array._chunks):
+        for dim_sel, dim_len, dim_chunk_len in \
+                zip(selection, array._shape, array._chunks):
 
             if is_integer(dim_sel):
                 dim_indexer = IntDimIndexer(dim_sel, dim_len, dim_chunk_len)
@@ -535,8 +546,9 @@ def __init__(self, selection, array):
                 dim_indexer = BoolArrayDimIndexer(dim_sel, dim_len, dim_chunk_len)
 
             else:
-                raise IndexError('unsupported selection item for orthogonal indexing; expected '
-                                 'integer, slice, integer array or Boolean array, got {!r}'
+                raise IndexError('unsupported selection item for orthogonal indexing; '
+                                 'expected integer, slice, integer array or Boolean '
+                                 'array, got {!r}'
                                  .format(type(dim_sel)))
 
             dim_indexers.append(dim_indexer)
@@ -563,9 +575,10 @@ def __iter__(self):
             # handle advanced indexing arrays orthogonally
             if self.is_advanced:
 
-                # numpy doesn't support orthogonal indexing directly as yet, so need to work
-                # around via np.ix_. Also np.ix_ does not support a mixture of arrays and slices
-                # or integers, so need to convert slices and integers into ranges.
+                # N.B., numpy doesn't support orthogonal indexing directly as yet,
+                # so need to work around via np.ix_. Also np.ix_ does not support a
+                # mixture of arrays and slices or integers, so need to convert slices
+                # and integers into ranges.
                 chunk_selection = ix_(chunk_selection, self.array._chunks)
 
                 # special case for non-monotonic indices
@@ -623,8 +636,9 @@ def __init__(self, selection, array):
 
         # validation
         if not is_coordinate_selection(selection, array):
-            raise IndexError('invalid coordinate selection; expected one integer (coordinate) '
-                             'array per dimension of the target array, got {!r}'.format(selection))
+            raise IndexError('invalid coordinate selection; expected one integer '
+                             '(coordinate) array per dimension of the target array, '
+                             'got {!r}'.format(selection))
 
         # handle wraparound, boundscheck
         for dim_sel, dim_len in zip(selection, array.shape):
@@ -764,8 +778,8 @@ def check_fields(fields, dtype):
         return dtype
     # check type
     if not isinstance(fields, (str, list, tuple)):
-        raise IndexError("'fields' argument must be a string or list of strings; found {!r}"
-                         .format(type(fields)))
+        raise IndexError("'fields' argument must be a string or list of strings; found "
+                         "{!r}".format(type(fields)))
     if fields:
         if dtype.names is None:
             raise IndexError("invalid 'fields' argument, array does not have any fields")

zarr/meta.py

@@ -139,6 +139,7 @@ def decode_fill_value(v, dtype):
         else:
             return np.array(v, dtype=dtype)[()]
     elif dtype.kind in 'SV':
+        # noinspection PyBroadException
         try:
             v = base64.standard_b64decode(v)
             v = np.array(v, dtype=dtype)[()]