feat: add to_dicts

fixes #9185

Author: NickCrews

Diff for: ibis/backends/__init__.py

@@ -586,6 +586,44 @@ def to_delta(
         with expr.to_pyarrow_batches(params=params) as batch_reader:
             write_deltalake(path, batch_reader, **kwargs)
 
+    @util.experimental
+    def to_dicts(
+        self, expr: ir.Table, *, chunk_size: int = 1_000_000
+    ) -> Iterable[dict[str, Any]]:
+        """Iterate through each row as a `dict` of column_name -> value.
+
+        Parameters
+        ----------
+        expr
+            The ibis expression to materialize as an iterable of row dictionaries.
+        chunk_size
+            We materialize the results in chunks of this size, to keep memory usage under control.
+            Larger values probably will be faster but consume more memory.
+
+        Returns
+        -------
+        Iterable[dict[str, Any]]
+            An iterator of dictionaries, each representing a row in the table.
+
+        Examples
+        --------
+        >>> t = ibis.memtable({"i": [1, 2, 3], "s": ["a", "b", "c"]})
+        >>> list(t.to_dicts())
+        [{'i': 1, 's': 'a'}, {'i': 2, 's': 'b'}, {'i': 3, 's': 'c'}]
+
+        Single Columns are returned as dictionaries with a single key:
+
+        >>> column = t.i
+        >>> list(column.to_dicts())
+        [{'i': 1}, {'i': 2}, {'i': 3}]
+
+        See Also
+        --------
+        [`Column.to_list`](./expression-generic.qmd##ibis.expr.types.generic.Column.to_list)
+        """
+        for batch in self.to_pyarrow_batches(expr, chunk_size=chunk_size):
+            yield from batch.to_pylist()
+
     @util.experimental
     def to_json(
         self,

Diff for: ibis/backends/tests/test_export.py

@@ -350,6 +350,24 @@ def test_table_to_csv(tmp_path, backend, awards_players):
     backend.assert_frame_equal(awards_players.to_pandas(), df)
 
 
+@pytest.mark.parametrize("chunk_size", [1, 1000])
+def test_to_dicts(con, chunk_size):
+    t = ibis.memtable({"i": [1, 2, 3], "s": ["a", "b", "c"]})
+    t = con.create_table("to_dicts_table", t, overwrite=True)
+
+    result = list(t.to_dicts(chunk_size=chunk_size))
+    expected = [{"i": 1, "s": "a"}, {"i": 2, "s": "b"}, {"i": 3, "s": "c"}]
+    assert result == expected
+
+    result = list(t.limit(0).to_dicts(chunk_size=chunk_size))
+    expected = []
+    assert result == expected
+
+    result = list(t.i.to_dicts(chunk_size=chunk_size))
+    expected = [{"i": 1}, {"i": 2}, {"i": 3}]
+    assert result == expected
+
+
 @pytest.mark.notimpl(
     [
         "athena",

Diff for: ibis/expr/types/core.py

@@ -20,7 +20,7 @@
 from ibis.util import experimental
 
 if TYPE_CHECKING:
-    from collections.abc import Iterator, Mapping
+    from collections.abc import Iterable, Iterator, Mapping
     from pathlib import Path
 
     import pandas as pd
@@ -771,6 +771,41 @@ def to_delta(
         """
         self._find_backend(use_default=True).to_delta(self, path, **kwargs)
 
+    @experimental
+    def to_dicts(self, *, chunk_size: int = 1_000_000) -> Iterable[dict[str, Any]]:
+        """Iterate through each row as a `dict` of column_name -> value.
+
+        Parameters
+        ----------
+        chunk_size
+            We materialize the results in chunks of this size, to keep memory usage under control.
+            Larger values probably will be faster but consume more memory.
+
+        Returns
+        -------
+        Iterable[dict[str, Any]]
+            An iterator of dictionaries, each representing a row in the table.
+
+        Examples
+        --------
+        >>> t = ibis.memtable({"i": [1, 2, 3], "s": ["a", "b", "c"]})
+        >>> list(t.to_dicts())
+        [{'i': 1, 's': 'a'}, {'i': 2, 's': 'b'}, {'i': 3, 's': 'c'}]
+
+        Single Columns are returned as dictionaries with a single key:
+
+        >>> column = t.i
+        >>> list(column.to_dicts())
+        [{'i': 1}, {'i': 2}, {'i': 3}]
+
+        See Also
+        --------
+        [`Column.to_list`](./expression-generic.qmd##ibis.expr.types.generic.Column.to_list)
+        """
+        return self._find_backend(use_default=True).to_dicts(
+            self, chunk_size=chunk_size
+        )
+
     @experimental
     def to_json(
         self,