feat: read_gbq_table supports LIKE as a operator in filters (#454)

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Fixes internal issue 330149095
 🦕

Author: tswast

bigframes/session/__init__.py

@@ -318,6 +318,7 @@ def _to_query(
             valid_operators: Mapping[third_party_pandas_gbq.FilterOps, str] = {
                 "in": "IN",
                 "not in": "NOT IN",
+                "LIKE": "LIKE",
                 "==": "=",
                 ">": ">",
                 "<": "<",

tests/system/small/test_session.py

@@ -327,6 +327,18 @@ def test_read_gbq_twice_with_same_timestamp(session, penguins_table_id):
     assert df3 is not None
 
 
+def test_read_gbq_table_clustered_with_filter(session: bigframes.Session):
+    df = session.read_gbq_table(
+        "bigquery-public-data.cloud_storage_geo_index.landsat_index",
+        filters=[[("sensor_id", "LIKE", "OLI%")], [("sensor_id", "LIKE", "%TIRS")]],  # type: ignore
+        columns=["sensor_id"],
+    )
+    sensors = df.groupby(["sensor_id"]).agg("count").to_pandas(ordered=False)
+    assert "OLI" in sensors.index
+    assert "TIRS" in sensors.index
+    assert "OLI_TIRS" in sensors.index
+
+
 def test_read_gbq_wildcard(session: bigframes.Session):
     df = session.read_gbq("bigquery-public-data.noaa_gsod.gsod193*")
     assert df.shape == (348485, 32)

third_party/bigframes_vendored/pandas/io/gbq.py

@@ -7,7 +7,7 @@
 
 from bigframes import constants
 
-FilterOps = Literal["in", "not in", "<", "<=", "==", "!=", ">=", ">"]
+FilterOps = Literal["in", "not in", "<", "<=", "==", "!=", ">=", ">", "LIKE"]
 FilterType = Tuple[str, FilterOps, Any]
 FiltersType = Union[Iterable[FilterType], Iterable[Iterable[FilterType]]]
 
@@ -112,7 +112,7 @@ def read_gbq(
                 query results.
             filters (Union[Iterable[FilterType], Iterable[Iterable[FilterType]]], default ()): To
                 filter out data. Filter syntax: [[(column, op, val), …],…] where
-                op is [==, >, >=, <, <=, !=, in, not in]. The innermost tuples
+                op is [==, >, >=, <, <=, !=, in, not in, LIKE]. 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