sungwy commented on code in PR #931:
URL: https://github.com/apache/iceberg-python/pull/931#discussion_r1761801698


##########
pyiceberg/table/__init__.py:
##########
@@ -456,6 +461,85 @@ def append(self, df: pa.Table, snapshot_properties: 
Dict[str, str] = EMPTY_DICT)
                 for data_file in data_files:
                     append_files.append_data_file(data_file)
 
+    def _build_partition_predicate(self, partition_records: List[Record]) -> 
BooleanExpression:
+        partition_spec = self.table_metadata.spec()
+        schema = self.table_metadata.schema()
+        partition_fields = [schema.find_field(field.source_id).name for field 
in partition_spec.fields]
+
+        expr: BooleanExpression = AlwaysFalse()
+        for partition_record in partition_records:
+            match_partition_expression: BooleanExpression = AlwaysTrue()
+
+            for pos in range(len(partition_fields)):
+                predicate = (
+                    EqualTo(Reference(partition_fields[pos]), 
partition_record[pos])
+                    if partition_record[pos] is not None
+                    else IsNull(Reference(partition_fields[pos]))
+                )
+                match_partition_expression = And(match_partition_expression, 
predicate)
+            expr = Or(expr, match_partition_expression)
+        return expr
+
+    def dynamic_overwrite(self, df: pa.Table, snapshot_properties: Dict[str, 
str] = EMPTY_DICT) -> None:
+        """
+        Shorthand for adding a table dynamic overwrite with a PyArrow table to 
the transaction.
+
+        Args:
+            df: The Arrow dataframe that will be used to overwrite the table
+            snapshot_properties: Custom properties to be added to the snapshot 
summary
+        """
+        try:
+            import pyarrow as pa
+        except ModuleNotFoundError as e:
+            raise ModuleNotFoundError("For writes PyArrow needs to be 
installed") from e
+
+        from pyiceberg.io.pyarrow import _check_pyarrow_schema_compatible, 
_dataframe_to_data_files
+
+        if not isinstance(df, pa.Table):
+            raise ValueError(f"Expected PyArrow table, got: {df}")
+
+        if self.table_metadata.spec().is_unpartitioned():
+            raise ValueError("Cannot apply dynamic overwrite on an 
unpartitioned table.")
+
+        for field in self.table_metadata.spec().fields:
+            if not isinstance(field.transform, IdentityTransform):
+                raise ValueError(
+                    f"For now dynamic overwrite does not support a table with 
non-identity-transform field in the latest partition spec: {field}"
+                )
+
+        downcast_ns_timestamp_to_us = 
Config().get_bool(DOWNCAST_NS_TIMESTAMP_TO_US_ON_WRITE) or False
+        _check_pyarrow_schema_compatible(
+            self.table_metadata.schema(), provided_schema=df.schema, 
downcast_ns_timestamp_to_us=downcast_ns_timestamp_to_us
+        )
+
+        # If dataframe does not have data, there is no need to overwrite
+        if df.shape[0] == 0:
+            return
+
+        append_snapshot_commit_uuid = uuid.uuid4()
+        data_files: List[DataFile] = list(
+            _dataframe_to_data_files(
+                table_metadata=self._table.metadata, 
write_uuid=append_snapshot_commit_uuid, df=df, io=self._table.io
+            )
+        )
+
+        overlapping_partitions = [data_file.partition for data_file in 
data_files]

Review Comment:
   nit: Should we turn this into a set of partitions instead, and run 
`_build_partition_predicate` on a unique set of partition records?
   
   also thought for rename: `partitions_to_overwrite`?



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