avoid setting column labels in special case of Series(block)

Author: tswast

bigframes/operations/base.py

@@ -84,16 +84,6 @@ def __init__(
                 f"Series constructor only supports copy=True. {constants.FEEDBACK_LINK}"
             )
 
-        if name is DEFAULT:
-            if isinstance(data, blocks.Block):
-                name = data.column_labels[0]
-            elif hasattr(data, "name"):
-                name = getattr(data, "name")
-            elif hasattr(data, "_name"):
-                name = getattr(data, "_name")
-            else:
-                name = None
-
         if isinstance(data, blocks.Block):
             block = data
         elif isinstance(data, SeriesMethods):
@@ -139,6 +129,8 @@ def __init__(
                 idx_cols = idx_block.index_columns
                 block, _ = idx_block.join(block, how="left")
                 block = block.with_index_labels(bf_index.names)
+            if name is not DEFAULT:
+                block = block.with_column_labels([name])
             if dtype:
                 bf_dtype = bigframes.dtypes.bigframes_type(dtype)
                 block = block.multi_apply_unary_op(ops.AsTypeOp(to_type=bf_dtype))
@@ -150,14 +142,14 @@ def __init__(
                 data=data,
                 index=index,  # type:ignore
                 dtype=dtype,  # type:ignore
-                name=name,
+                name=name if name is not DEFAULT else None,
             )
             name = pd_series.name  # type: ignore
             block = read_pandas_func(pd_series)._get_block()  # type:ignore
+            block = block.with_column_labels([name])
 
         assert block is not None
 
-        block = block.with_column_labels([name])
         self._block: blocks.Block = block
 
     @property

bigframes/session/__init__.py

@@ -1829,7 +1829,7 @@ def udf(
         Turning an arbitrary python function into a BigQuery managed python udf:
 
             >>> bq_name = datetime.datetime.now().strftime("bigframes_%Y%m%d%H%M%S%f")
-            >>> @bpd.udf(dataset="bigfranes_testing", name=bq_name)
+            >>> @bpd.udf(dataset="bigfranes_testing", name=bq_name)  # doctest: +SKIP
             ... def minutes_to_hours(x: int) -> float:
             ...     return x/60
 
@@ -1842,8 +1842,8 @@ def udf(
             4    120
             dtype: Int64
 
-            >>> hours = minutes.apply(minutes_to_hours)
-            >>> hours
+            >>> hours = minutes.apply(minutes_to_hours)  # doctest: +SKIP
+            >>> hours  # doctest: +SKIP
             0    0.0
             1    0.5
             2    1.0
@@ -1856,7 +1856,7 @@ def udf(
         packages (optionally with the package version) via `packages` param.
 
             >>> bq_name = datetime.datetime.now().strftime("bigframes_%Y%m%d%H%M%S%f")
-            >>> @bpd.udf(
+            >>> @bpd.udf(  # doctest: +SKIP
             ...     dataset="bigfranes_testing",
             ...     name=bq_name,
             ...     packages=["cryptography"]
@@ -1873,14 +1873,14 @@ def udf(
             ...     return f.encrypt(input.encode()).decode()
 
             >>> names = bpd.Series(["Alice", "Bob"])
-            >>> hashes = names.apply(get_hash)
+            >>> hashes = names.apply(get_hash)  # doctest: +SKIP
 
         You can clean-up the BigQuery functions created above using the BigQuery
         client from the BigQuery DataFrames session:
 
             >>> session = bpd.get_global_session()
-            >>> session.bqclient.delete_routine(minutes_to_hours.bigframes_bigquery_function)
-            >>> session.bqclient.delete_routine(get_hash.bigframes_bigquery_function)
+            >>> session.bqclient.delete_routine(minutes_to_hours.bigframes_bigquery_function)  # doctest: +SKIP
+            >>> session.bqclient.delete_routine(get_hash.bigframes_bigquery_function)  # doctest: +SKIP
 
         Args:
             input_types (type or sequence(type), Optional):