unblock needed casts

Author: TrevorBergeron

bigframes/operations/generic_ops.py

@@ -85,6 +85,10 @@
             dtypes.TIMESTAMP_DTYPE,
             dtypes.INT_DTYPE,
         ),
+        (
+            dtypes.TIMEDELTA_DTYPE,
+            dtypes.INT_DTYPE,
+        ),
         (
             dtypes.STRING_DTYPE,
             dtypes.INT_DTYPE,
@@ -132,6 +136,10 @@
             dtypes.BOOL_DTYPE,
         ),
         # String casts
+        (
+            dtypes.BYTES_DTYPE,
+            dtypes.STRING_DTYPE,
+        ),
         (
             dtypes.BOOL_DTYPE,
             dtypes.STRING_DTYPE,
@@ -164,6 +172,11 @@
             dtypes.JSON_DTYPE,
             dtypes.STRING_DTYPE,
         ),
+        # bytes casts
+        (
+            dtypes.STRING_DTYPE,
+            dtypes.BYTES_DTYPE,
+        ),
         # decimal casts
         (
             dtypes.STRING_DTYPE,

bigframes/session/polars_executor.py

@@ -105,12 +105,12 @@ def execute(
         if not self._can_execute(plan):
             return None
         # Note: Ignoring ordered flag, as just executing totally ordered is fine.
-        try:
-            lazy_frame: pl.LazyFrame = self._compiler.compile(
-                array_value.ArrayValue(plan).node
-            )
-        except Exception:
-            return None
+        # try:
+        lazy_frame: pl.LazyFrame = self._compiler.compile(
+            array_value.ArrayValue(plan).node
+        )
+        # except Exception:
+        #    return None
         if peek is not None:
             lazy_frame = lazy_frame.limit(peek)
         pa_table = lazy_frame.collect().to_arrow()

tests/system/small/test_series.py

@@ -3685,8 +3685,12 @@ def test_astype_numeric_to_int(scalars_df_index, scalars_pandas_df_index):
     column = "numeric_col"
     to_type = "Int64"
     bf_result = scalars_df_index[column].astype(to_type).to_pandas()
-    # Round to the nearest whole number to avoid TypeError
-    pd_result = scalars_pandas_df_index[column].round(0).astype(to_type)
+    # Truncate to int to avoid TypeError
+    pd_result = (
+        scalars_pandas_df_index[column]
+        .apply(lambda x: None if pd.isna(x) else math.trunc(x))
+        .astype(to_type)
+    )
     pd.testing.assert_series_equal(bf_result, pd_result)