feat: Add filters and columns arguments to read_gbq for enhanced data querying

bigframes/pandas/__init__.py

@@ -59,6 +59,7 @@
 import third_party.bigframes_vendored.pandas.core.reshape.encoding as vendored_pandas_encoding
 import third_party.bigframes_vendored.pandas.core.reshape.merge as vendored_pandas_merge
 import third_party.bigframes_vendored.pandas.core.reshape.tile as vendored_pandas_tile
+import third_party.bigframes_vendored.pandas.io.gbq as vendored_pandas_gbq
 
 
 # Include method definition so that the method appears in our docs for
@@ -486,6 +487,8 @@ def read_gbq(
     index_col: Iterable[str] | str = (),
     col_order: Iterable[str] = (),
     max_results: Optional[int] = None,
+    columns: Iterable[str] = (),
+    filters: vendored_pandas_gbq.FiltersType = (),
 ) -> bigframes.dataframe.DataFrame:
     _set_default_session_location_if_possible(query_or_table)
     return global_session.with_default_session(
@@ -494,6 +497,8 @@ def read_gbq(
         index_col=index_col,
         col_order=col_order,
         max_results=max_results,
+        columns=columns,
+        filters=filters,
     )
 
 

bigframes/session/__init__.py

@@ -284,9 +284,13 @@ def read_gbq(
         index_col: Iterable[str] | str = (),
         col_order: Iterable[str] = (),
         max_results: Optional[int] = None,
+        columns: Iterable[str] = (),
+        filters: third_party_pandas_gbq.FiltersType = (),
         # Add a verify index argument that fails if the index is not unique.
     ) -> dataframe.DataFrame:
         # TODO(b/281571214): Generate prompt to show the progress of read_gbq.
+        query_or_table = self._filters_to_query(query_or_table, columns, filters)
+
         if _is_query(query_or_table):
             return self._read_gbq_query(
                 query_or_table,
@@ -307,6 +311,80 @@ def read_gbq(
                 api_name="read_gbq",
             )
 
+    def _filters_to_query(self, query_or_table, columns, filters):
+        """Convert filters to query"""
+        if len(filters) == 0 and len(columns) == 0:
+            return query_or_table
+
+        sub_query = (
+            f"({query_or_table})" if _is_query(query_or_table) else query_or_table
+        )
+
+        select_clause = "SELECT " + (
+            ", ".join(f"`{column}`" for column in columns) if columns else "*"
+        )
+
+        where_clause = ""
+        if filters:
+            valid_operators = {
+                "in": "IN",
+                "not in": "NOT IN",
+                "==": "=",
+                ">": ">",
+                "<": "<",
+                ">=": ">=",
+                "<=": "<=",
+                "!=": "!=",
+            }
+
+            if (
+                isinstance(filters, Iterable)
+                and isinstance(filters[0], Tuple)
+                and (len(filters[0]) == 0 or not isinstance(filters[0][0], Tuple))
+            ):
+                filters = [filters]
+
+            or_expressions = []
+            for group in filters:
+                if not isinstance(group, Iterable):
+                    raise ValueError(
+                        f"Filter group should be a iterable, {group} is not valid."
+                    )
+
+                and_expressions = []
+                for filter_item in group:
+                    if not isinstance(filter_item, tuple) or (len(filter_item) != 3):
+                        raise ValueError(
+                            f"Filter condition should be a tuple of length 3, {filter_item} is not valid."
+                        )
+
+                    column, operator, value = filter_item
+
+                    if not isinstance(column, str):
+                        raise ValueError(
+                            f"Column name should be a string, but received '{column}' of type {type(column).__name__}."
+                        )
+
+                    if operator not in valid_operators:
+                        raise ValueError(f"Operator {operator} is not valid.")
+
+                    operator = valid_operators[operator]
+
+                    if operator in ["IN", "NOT IN"]:
+                        value_list = ", ".join([repr(v) for v in value])
+                        expression = f"`{column}` {operator} ({value_list})"
+                    else:
+                        expression = f"`{column}` {operator} {repr(value)}"
+                    and_expressions.append(expression)
+
+                or_expressions.append(" AND ".join(and_expressions))
+
+            if or_expressions:
+                where_clause = " WHERE " + " OR ".join(or_expressions)
+
+        full_query = f"{select_clause} FROM {sub_query} AS sub{where_clause}"
+        return full_query
+
     def _query_to_destination(
         self,
         query: str,

tests/unit/session/test_session.py

@@ -57,3 +57,60 @@ def test_session_init_fails_with_no_project():
                 credentials=mock.Mock(spec=google.auth.credentials.Credentials)
             )
         )
+
+
+@pytest.mark.parametrize(
+    ("query_or_table", "columns", "filters", "expected_output"),
+    [
+        pytest.param(
+            """SELECT
+                rowindex,
+                string_col,
+            FROM `test_table` AS t
+            """,
+            [],
+            [("rowindex", "<", 4), ("string_col", "==", "Hello, World!")],
+            """SELECT * FROM (SELECT
+                rowindex,
+                string_col,
+            FROM `test_table` AS t
+            ) AS sub WHERE `rowindex` < 4 AND `string_col` = 'Hello, World!'""",
+            id="query_input",
+        ),
+        pytest.param(
+            "test_table",
+            [],
+            [("date_col", ">", "2022-10-20")],
+            "SELECT * FROM test_table AS sub WHERE `date_col` > '2022-10-20'",
+            id="table_input",
+        ),
+        pytest.param(
+            "test_table",
+            ["row_index", "string_col"],
+            [
+                (("rowindex", "not in", [0, 6]),),
+                (("string_col", "in", ["Hello, World!", "こんにちは"]),),
+            ],
+            (
+                "SELECT `row_index`, `string_col` FROM test_table AS sub WHERE "
+                "`rowindex` NOT IN (0, 6) OR `string_col` IN ('Hello, World!', "
+                "'こんにちは')"
+            ),
+            id="or_operation",
+        ),
+        pytest.param(
+            "test_table",
+            [],
+            ["date_col", ">", "2022-10-20"],
+            None,
+            marks=pytest.mark.xfail(
+                raises=ValueError,
+            ),
+            id="raise_error",
+        ),
+    ],
+)
+def test_read_gbq_with_filters(query_or_table, columns, filters, expected_output):
+    session = resources.create_bigquery_session()
+    query = session._filters_to_query(query_or_table, columns, filters)
+    assert query == expected_output

third_party/bigframes_vendored/pandas/io/gbq.py

@@ -3,10 +3,13 @@
 
 from __future__ import annotations
 
-from typing import Iterable, Optional
+from typing import Any, Iterable, Literal, Optional, Tuple, Union
 
 from bigframes import constants
 
+FilterType = Tuple[str, Literal["in", "not in", "<", "<=", "==", "!=", ">=", ">"], Any]
+FiltersType = Iterable[Union[FilterType, Iterable[FilterType]]]
+
 
 class GBQIOMixin:
     def read_gbq(
@@ -16,6 +19,8 @@ def read_gbq(
         index_col: Iterable[str] | str = (),
         col_order: Iterable[str] = (),
         max_results: Optional[int] = None,
+        columns: Iterable[str] = (),
+        filters: FiltersType = (),
     ):
         """Loads a DataFrame from BigQuery.
 
@@ -70,6 +75,21 @@ def read_gbq(
             <BLANKLINE>
             [2 rows x 3 columns]
 
+        Reading data with `columns` and `filters` parameters:
+
+            >>> columns = ['pitcherFirstName', 'pitcherLastName', 'year', 'pitchSpeed']
+            >>> filters = [('year', '==', 2016), ('pitcherFirstName', 'in', ['John', 'Doe'])]
+            >>> df = bpd.read_gbq(
+            ...             "bigquery-public-data.baseball.games_wide",
+            ...             columns=columns,
+            ...             filters=filters,
+            ...         )
+            >>> df.head(1)
+                     pitcherFirstName	pitcherLastName     year	pitchSpeed
+            0	                 John	         Axford	    2016            98
+            <BLANKLINE>
+            [1 rows x 4 columns]
+
         Args:
             query_or_table (str):
                 A SQL string to be executed or a BigQuery table to be read. The
@@ -83,6 +103,16 @@ def read_gbq(
             max_results (Optional[int], default None):
                 If set, limit the maximum number of rows to fetch from the
                 query results.
+            columns (Iterable[str], default ()): If not empty, only these columns
+                will be read from table.
+            filters (Iterable[Union[Tuple, Iterable[Tuple]]], default ()): To
+                filter out data. Filter syntax: [[(column, op, val), …],…] where
+                op is [==, >, >=, <, <=, !=, in, not in]. The innermost tuples
+                are transposed into a set of filters applied through an AND
+                operation. The outer Iterable combines these sets of filters
+                through an OR operation. A single Iterable of tuples can also
+                be used, meaning that no OR operation between set of filters
+                is to be conducted.
 
         Returns:
             bigframes.dataframe.DataFrame: A DataFrame representing results of the query or table.