CLN: annotate and de-nest write_array (#30012)

Author: jbrockmendel

pandas/io/pytables.py

@@ -40,6 +40,7 @@
     is_list_like,
     is_timedelta64_dtype,
 )
+from pandas.core.dtypes.generic import ABCExtensionArray
 from pandas.core.dtypes.missing import array_equivalent
 
 from pandas import (
@@ -54,7 +55,7 @@
     concat,
     isna,
 )
-from pandas._typing import FrameOrSeries
+from pandas._typing import ArrayLike, FrameOrSeries
 from pandas.core.arrays.categorical import Categorical
 import pandas.core.common as com
 from pandas.core.computation.pytables import PyTablesExpr, maybe_expression
@@ -2960,7 +2961,7 @@ def read_index_node(
         data = node[start:stop]
         # If the index was an empty array write_array_empty() will
         # have written a sentinel. Here we relace it with the original.
-        if "shape" in node._v_attrs and self._is_empty_array(node._v_attrs.shape):
+        if "shape" in node._v_attrs and np.prod(node._v_attrs.shape) == 0:
             data = np.empty(node._v_attrs.shape, dtype=node._v_attrs.value_type,)
         kind = _ensure_decoded(node._v_attrs.kind)
         name = None
@@ -3006,25 +3007,27 @@ def read_index_node(
 
         return index
 
-    def write_array_empty(self, key: str, value):
+    def write_array_empty(self, key: str, value: ArrayLike):
         """ write a 0-len array """
 
         # ugly hack for length 0 axes
         arr = np.empty((1,) * value.ndim)
         self._handle.create_array(self.group, key, arr)
-        getattr(self.group, key)._v_attrs.value_type = str(value.dtype)
-        getattr(self.group, key)._v_attrs.shape = value.shape
+        node = getattr(self.group, key)
+        node._v_attrs.value_type = str(value.dtype)
+        node._v_attrs.shape = value.shape
 
-    def _is_empty_array(self, shape) -> bool:
-        """Returns true if any axis is zero length."""
-        return any(x == 0 for x in shape)
+    def write_array(self, key: str, value: ArrayLike, items: Optional[Index] = None):
+        # TODO: we only have one test that gets here, the only EA
+        #  that gets passed is DatetimeArray, and we never have
+        #  both self._filters and EA
+        assert isinstance(value, (np.ndarray, ABCExtensionArray)), type(value)
 
-    def write_array(self, key: str, value, items=None):
         if key in self.group:
             self._handle.remove_node(self.group, key)
 
         # Transform needed to interface with pytables row/col notation
-        empty_array = self._is_empty_array(value.shape)
+        empty_array = value.size == 0
         transposed = False
 
         if is_categorical_dtype(value):
@@ -3039,29 +3042,29 @@ def write_array(self, key: str, value, items=None):
                 value = value.T
                 transposed = True
 
+        atom = None
         if self._filters is not None:
-            atom = None
             try:
                 # get the atom for this datatype
                 atom = _tables().Atom.from_dtype(value.dtype)
             except ValueError:
                 pass
 
-            if atom is not None:
-                # create an empty chunked array and fill it from value
-                if not empty_array:
-                    ca = self._handle.create_carray(
-                        self.group, key, atom, value.shape, filters=self._filters
-                    )
-                    ca[:] = value
-                    getattr(self.group, key)._v_attrs.transposed = transposed
+        if atom is not None:
+            # We only get here if self._filters is non-None and
+            #  the Atom.from_dtype call succeeded
 
-                else:
-                    self.write_array_empty(key, value)
+            # create an empty chunked array and fill it from value
+            if not empty_array:
+                ca = self._handle.create_carray(
+                    self.group, key, atom, value.shape, filters=self._filters
+                )
+                ca[:] = value
 
-                return
+            else:
+                self.write_array_empty(key, value)
 
-        if value.dtype.type == np.object_:
+        elif value.dtype.type == np.object_:
 
             # infer the type, warn if we have a non-string type here (for
             # performance)
@@ -3071,35 +3074,30 @@ def write_array(self, key: str, value, items=None):
             elif inferred_type == "string":
                 pass
             else:
-                try:
-                    items = list(items)
-                except TypeError:
-                    pass
                 ws = performance_doc % (inferred_type, key, items)
                 warnings.warn(ws, PerformanceWarning, stacklevel=7)
 
             vlarr = self._handle.create_vlarray(self.group, key, _tables().ObjectAtom())
             vlarr.append(value)
+
+        elif empty_array:
+            self.write_array_empty(key, value)
+        elif is_datetime64_dtype(value.dtype):
+            self._handle.create_array(self.group, key, value.view("i8"))
+            getattr(self.group, key)._v_attrs.value_type = "datetime64"
+        elif is_datetime64tz_dtype(value.dtype):
+            # store as UTC
+            # with a zone
+            self._handle.create_array(self.group, key, value.asi8)
+
+            node = getattr(self.group, key)
+            node._v_attrs.tz = _get_tz(value.tz)
+            node._v_attrs.value_type = "datetime64"
+        elif is_timedelta64_dtype(value.dtype):
+            self._handle.create_array(self.group, key, value.view("i8"))
+            getattr(self.group, key)._v_attrs.value_type = "timedelta64"
         else:
-            if empty_array:
-                self.write_array_empty(key, value)
-            else:
-                if is_datetime64_dtype(value.dtype):
-                    self._handle.create_array(self.group, key, value.view("i8"))
-                    getattr(self.group, key)._v_attrs.value_type = "datetime64"
-                elif is_datetime64tz_dtype(value.dtype):
-                    # store as UTC
-                    # with a zone
-                    self._handle.create_array(self.group, key, value.asi8)
-
-                    node = getattr(self.group, key)
-                    node._v_attrs.tz = _get_tz(value.tz)
-                    node._v_attrs.value_type = "datetime64"
-                elif is_timedelta64_dtype(value.dtype):
-                    self._handle.create_array(self.group, key, value.view("i8"))
-                    getattr(self.group, key)._v_attrs.value_type = "timedelta64"
-                else:
-                    self._handle.create_array(self.group, key, value)
+            self._handle.create_array(self.group, key, value)
 
         getattr(self.group, key)._v_attrs.transposed = transposed