Fix loading checks from a delta table with special characters

src/databricks/labs/dqx/checks_storage.py

@@ -23,7 +23,7 @@
 from sqlalchemy.schema import CreateSchema
 from sqlalchemy.dialects.postgresql import JSONB
 from sqlalchemy.exc import DatabaseError, ProgrammingError, OperationalError, IntegrityError
-
+from urllib.parse import quote
 
 import yaml
 from pyspark.sql import SparkSession
@@ -107,7 +107,8 @@ def load(self, config: TableChecksStorageConfig) -> list[dict]:
             NotFound: if the table does not exist in the workspace
         """
         logger.info(f"Loading quality rules (checks) from table '{config.location}'")
-        if not self.ws.tables.exists(config.location).table_exists:
+        api_ready_location = quote(config.location.replace("`", ""))
+        if not self.ws.tables.exists(api_ready_location).table_exists:
             raise NotFound(f"Checks table {config.location} does not exist in the workspace")
         rules_df = self.spark.read.table(config.location)
         return serialize_checks_from_dataframe(rules_df, run_config_name=config.run_config_name) or []

tests/integration/test_save_and_load_checks_from_table.py

@@ -76,6 +76,17 @@ def test_load_checks_when_checks_table_does_not_exist(ws, make_schema, make_rand
         config = TableChecksStorageConfig(location=table_name)
         engine.load_checks(config=config)
 
+def test_load_checks_with_special_characters_in_table_name(ws, make_schema, make_random, spark):
+    catalog_name = TEST_CATALOG
+    schema_name = make_schema(catalog_name=catalog_name).name
+    table_name = f"`{catalog_name}`.`{schema_name}`.`table-with-special_chars$#{make_random(5)}`"
+
+    engine = DQEngine(ws, spark)
+    config = TableChecksStorageConfig(location=table_name, run_config_name="default")
+    engine.save_checks(INPUT_CHECKS, config=config)
+    checks = engine.load_checks(config=config)
+    assert checks == EXPECTED_CHECKS, "Checks were not loaded correctly."
+
 
 def test_save_and_load_checks_from_table(ws, make_schema, make_random, spark):
     catalog_name = TEST_CATALOG