smaheshwar-pltr commented on code in PR #2031:
URL: https://github.com/apache/iceberg-python/pull/2031#discussion_r2102697102


##########
pyiceberg/table/__init__.py:
##########
@@ -1536,10 +1595,181 @@ def __init__(
         self.row_filter = _parse_row_filter(row_filter)
         self.selected_fields = selected_fields
         self.case_sensitive = case_sensitive
-        self.snapshot_id = snapshot_id
         self.options = options
         self.limit = limit
 
+    @abstractmethod
+    def projection(self) -> Schema: ...
+
+    @abstractmethod
+    def plan_files(self) -> Iterable[ScanTask]: ...
+
+    @abstractmethod
+    def to_arrow(self) -> pa.Table: ...
+
+    @abstractmethod
+    def count(self) -> int: ...
+
+    def select(self: S, *field_names: str) -> S:
+        if "*" in self.selected_fields:
+            return self.update(selected_fields=field_names)
+        return 
self.update(selected_fields=tuple(set(self.selected_fields).intersection(set(field_names))))
+
+    def filter(self: S, expr: Union[str, BooleanExpression]) -> S:
+        return self.update(row_filter=And(self.row_filter, 
_parse_row_filter(expr)))
+
+    def with_case_sensitive(self: S, case_sensitive: bool = True) -> S:
+        return self.update(case_sensitive=case_sensitive)
+
+    def update(self: S, **overrides: Any) -> S:
+        """Create a copy of this table scan with updated fields."""
+        return type(self)(**{**self.__dict__, **overrides})
+
+    def to_pandas(self, **kwargs: Any) -> pd.DataFrame:
+        """Read a Pandas DataFrame eagerly from this Iceberg table scan.
+
+        Returns:
+            pd.DataFrame: Materialized Pandas Dataframe from the Iceberg table 
scan
+        """
+        return self.to_arrow().to_pandas(**kwargs)
+
+    def to_duckdb(self, table_name: str, connection: 
Optional[DuckDBPyConnection] = None) -> DuckDBPyConnection:
+        """Shorthand for loading this table scan in DuckDB.
+
+        Returns:
+            DuckDBPyConnection: In memory DuckDB connection with the Iceberg 
table scan.
+        """
+        import duckdb
+
+        con = connection or duckdb.connect(database=":memory:")
+        con.register(table_name, self.to_arrow())
+
+        return con
+
+    def to_ray(self) -> ray.data.dataset.Dataset:
+        """Read a Ray Dataset eagerly from this Iceberg table scan.
+
+        Returns:
+            ray.data.dataset.Dataset: Materialized Ray Dataset from the 
Iceberg table scan
+        """
+        import ray
+
+        return ray.data.from_arrow(self.to_arrow())
+
+    def to_polars(self) -> pl.DataFrame:
+        """Read a Polars DataFrame from this Iceberg table scan.
+
+        Returns:
+            pl.DataFrame: Materialized Polars Dataframe from the Iceberg table 
scan
+        """
+        import polars as pl
+
+        result = pl.from_arrow(self.to_arrow())
+        if isinstance(result, pl.Series):
+            result = result.to_frame()
+
+        return result
+
+
+class FileBasedScan(AbstractTableScan, ABC):

Review Comment:
   In light of 
https://github.com/apache/iceberg-python/pull/533#discussion_r1623258053, I 
think it makes sense to have some abstraction for scans that return 
`FileScanTask`s specifically.
   
   I think we maybe should've been doing some handling before - on `main`, this 
line gives me a warning
   
https://github.com/apache/iceberg-python/blob/f47513b8fc972dd26b99b1a9fbb102c712dd07fe/pyiceberg/table/__init__.py#L1933
   
   because
   
https://github.com/apache/iceberg-python/blob/f47513b8fc972dd26b99b1a9fbb102c712dd07fe/pyiceberg/table/__init__.py#L1926-L1927
   
   doesn't follow from the typing. But overriding with a Iterable[FileScanTask] 
fixes that.



##########
pyiceberg/table/__init__.py:
##########
@@ -1536,10 +1595,181 @@ def __init__(
         self.row_filter = _parse_row_filter(row_filter)
         self.selected_fields = selected_fields
         self.case_sensitive = case_sensitive
-        self.snapshot_id = snapshot_id
         self.options = options
         self.limit = limit
 
+    @abstractmethod
+    def projection(self) -> Schema: ...
+
+    @abstractmethod
+    def plan_files(self) -> Iterable[ScanTask]: ...
+
+    @abstractmethod
+    def to_arrow(self) -> pa.Table: ...
+
+    @abstractmethod
+    def count(self) -> int: ...
+
+    def select(self: S, *field_names: str) -> S:
+        if "*" in self.selected_fields:
+            return self.update(selected_fields=field_names)
+        return 
self.update(selected_fields=tuple(set(self.selected_fields).intersection(set(field_names))))
+
+    def filter(self: S, expr: Union[str, BooleanExpression]) -> S:
+        return self.update(row_filter=And(self.row_filter, 
_parse_row_filter(expr)))
+
+    def with_case_sensitive(self: S, case_sensitive: bool = True) -> S:
+        return self.update(case_sensitive=case_sensitive)
+
+    def update(self: S, **overrides: Any) -> S:
+        """Create a copy of this table scan with updated fields."""
+        return type(self)(**{**self.__dict__, **overrides})
+
+    def to_pandas(self, **kwargs: Any) -> pd.DataFrame:
+        """Read a Pandas DataFrame eagerly from this Iceberg table scan.
+
+        Returns:
+            pd.DataFrame: Materialized Pandas Dataframe from the Iceberg table 
scan
+        """
+        return self.to_arrow().to_pandas(**kwargs)
+
+    def to_duckdb(self, table_name: str, connection: 
Optional[DuckDBPyConnection] = None) -> DuckDBPyConnection:
+        """Shorthand for loading this table scan in DuckDB.
+
+        Returns:
+            DuckDBPyConnection: In memory DuckDB connection with the Iceberg 
table scan.
+        """
+        import duckdb
+
+        con = connection or duckdb.connect(database=":memory:")
+        con.register(table_name, self.to_arrow())
+
+        return con
+
+    def to_ray(self) -> ray.data.dataset.Dataset:
+        """Read a Ray Dataset eagerly from this Iceberg table scan.
+
+        Returns:
+            ray.data.dataset.Dataset: Materialized Ray Dataset from the 
Iceberg table scan
+        """
+        import ray
+
+        return ray.data.from_arrow(self.to_arrow())
+
+    def to_polars(self) -> pl.DataFrame:
+        """Read a Polars DataFrame from this Iceberg table scan.
+
+        Returns:
+            pl.DataFrame: Materialized Polars Dataframe from the Iceberg table 
scan
+        """
+        import polars as pl
+
+        result = pl.from_arrow(self.to_arrow())
+        if isinstance(result, pl.Series):
+            result = result.to_frame()
+
+        return result
+
+
+class FileBasedScan(AbstractTableScan, ABC):

Review Comment:
   In light of 
https://github.com/apache/iceberg-python/pull/533#discussion_r1623258053, I 
think it makes sense to have some abstraction for scans that return 
`FileScanTask`s specifically.
   
   I think we maybe should've been doing some handling before - on `main`, this 
line gives me a warning
   
https://github.com/apache/iceberg-python/blob/f47513b8fc972dd26b99b1a9fbb102c712dd07fe/pyiceberg/table/__init__.py#L1933
   
   because
   
https://github.com/apache/iceberg-python/blob/f47513b8fc972dd26b99b1a9fbb102c712dd07fe/pyiceberg/table/__init__.py#L1926-L1927
   
   doesn't follow from the typing. But overriding this return type a 
Iterable[FileScanTask] fixes that, as here.



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