feat: Added custom query support for PostgreSQL

README.md

@@ -277,8 +277,7 @@ page provides few examples of how this tool can be used to run custom query vali
 
 #### Custom Query Row Validations 
 
-(Note: Custom query row validation is currently only supported for BigQuery, Teradata, SQL Server, and
-Impala/Hive. Struct and array data types are not currently supported.)
+(Note: Custom query row validation is currently only supported for BigQuery, Teradata, SQL Server, PostgreSQL and Impala/Hive. Struct and array data types are not currently supported.)
 
 Below is the command syntax for row validations. In order to run row level
 validations you need to pass `--hash` flag which will specify the fields

data_validation/clients.py

@@ -23,6 +23,7 @@
 import pandas
 import third_party.ibis.ibis_addon.datatypes
 import third_party.ibis.ibis_addon.base_sqlalchemy.alchemy
+import third_party.ibis.ibis_postgres.client
 from google.cloud import bigquery
 from ibis.backends.mysql.client import MySQLClient
 from ibis.backends.pandas.client import PandasClient

third_party/ibis/ibis_postgres/client.py

@@ -0,0 +1,111 @@
+# Copyright 2022 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# from ibis.backends.postgres.client import PostgreSQLClient
+import ibis.expr.datatypes as dt
+import ibis.expr.schema as sch
+from ibis import util
+from ibis.backends.postgres.client import PostgreSQLClient
+
+def _get_schema_using_query(self, query: str) -> sch.Schema:
+    raw_name = util.guid()
+    name = self.con.dialect.identifier_preparer.quote_identifier(raw_name)
+    type_info_sql = f"""\
+SELECT
+attname,
+format_type(atttypid, atttypmod) AS type
+FROM pg_attribute
+WHERE attrelid = {raw_name!r}::regclass
+AND attnum > 0
+AND NOT attisdropped
+ORDER BY attnum
+"""
+    with self.con.connect() as con:
+        con.execute(f"CREATE TEMPORARY VIEW {name} AS {query}")
+        try:
+            type_info = con.execute(type_info_sql).fetchall()
+        finally:
+            con.execute(f"DROP VIEW {name}")
+    tuples = [(col, self._get_type(typestr)) for col, typestr in type_info]
+    return sch.Schema.from_tuples(tuples)
+
+def _get_type(self,typestr: str) -> dt.DataType:
+    _type_mapping = {
+    # "boolean": dt.bool,
+    "boolean": dt.boolean,
+    "boolean[]": dt.Array(dt.boolean),
+    "bytea": dt.binary,
+    "bytea[]": dt.Array(dt.binary),
+    "character(1)": dt.string,
+    "character(1)[]": dt.Array(dt.string),
+    "bigint": dt.int64,
+    "bigint[]": dt.Array(dt.int64),
+    "smallint": dt.int16,
+    "smallint[]": dt.Array(dt.int16),
+    "integer": dt.int32,
+    "integer[]": dt.Array(dt.int32),
+    "text": dt.string,
+    "text[]": dt.Array(dt.string),
+    "json": dt.json,
+    "json[]": dt.Array(dt.json),
+    "point": dt.point,
+    "point[]": dt.Array(dt.point),
+    "polygon": dt.polygon,
+    "polygon[]": dt.Array(dt.polygon),
+    "line": dt.linestring,
+    "line[]": dt.Array(dt.linestring),
+    "real": dt.float32,
+    "real[]": dt.Array(dt.float32),
+    "double precision": dt.float64,
+    "double precision[]": dt.Array(dt.float64),
+    "macaddr8": dt.macaddr,
+    "macaddr8[]": dt.Array(dt.macaddr),
+    "macaddr": dt.macaddr,
+    "macaddr[]": dt.Array(dt.macaddr),
+    "inet": dt.inet,
+    "inet[]": dt.Array(dt.inet),
+    "character": dt.string,
+    "character[]": dt.Array(dt.string),
+    "character varying": dt.string,
+    "character varying[]": dt.Array(dt.string),
+    "date": dt.date,
+    "date[]": dt.Array(dt.date),
+    "time without time zone": dt.time,
+    "time without time zone[]": dt.Array(dt.time),
+    "timestamp without time zone": dt.timestamp,
+    "timestamp without time zone[]": dt.Array(dt.timestamp),
+    "timestamp with time zone": dt.Timestamp("UTC"),
+    "timestamp with time zone[]": dt.Array(dt.Timestamp("UTC")),
+    "interval": dt.interval,
+    "interval[]": dt.Array(dt.interval),
+    # NB: this isn"t correct, but we try not to fail
+    "time with time zone": "time",
+    "numeric": dt.float64,
+    "numeric[]": dt.Array(dt.float64),
+    "uuid": dt.uuid,
+    "uuid[]": dt.Array(dt.uuid),
+    "jsonb": dt.jsonb,
+    "jsonb[]": dt.Array(dt.jsonb),
+    "geometry": dt.geometry,
+    "geometry[]": dt.Array(dt.geometry),
+    "geography": dt.geography,
+    "geography[]": dt.Array(dt.geography),
+    }
+    try:
+        return _type_mapping[typestr]
+    except KeyError:
+        return 
+
+PostgreSQLClient._get_schema_using_query = _get_schema_using_query
+PostgreSQLClient._get_type = _get_type