Support for complex params

src/databricks/sqlalchemy/__init__.py

@@ -1,4 +1,10 @@
 from databricks.sqlalchemy.base import DatabricksDialect
-from databricks.sqlalchemy._types import TINYINT, TIMESTAMP, TIMESTAMP_NTZ
+from databricks.sqlalchemy._types import (
+    TINYINT,
+    TIMESTAMP,
+    TIMESTAMP_NTZ,
+    DatabricksArray,
+    DatabricksMap,
+)
 
-__all__ = ["TINYINT", "TIMESTAMP", "TIMESTAMP_NTZ"]
+__all__ = ["TINYINT", "TIMESTAMP", "TIMESTAMP_NTZ", "DatabricksArray", "DatabricksMap"]

src/databricks/sqlalchemy/_types.py

@@ -5,6 +5,7 @@
 import sqlalchemy
 from sqlalchemy.engine.interfaces import Dialect
 from sqlalchemy.ext.compiler import compiles
+from sqlalchemy.types import TypeDecorator, UserDefinedType
 
 from databricks.sql.utils import ParamEscaper
 
@@ -321,3 +322,46 @@ class TINYINT(sqlalchemy.types.TypeDecorator):
 @compiles(TINYINT, "databricks")
 def compile_tinyint(type_, compiler, **kw):
     return "TINYINT"
+
+
+class DatabricksArray(UserDefinedType):
+    """
+    A custom array type that can wrap any other SQLAlchemy type.
+
+    Examples:
+        DatabricksArray(String)         -> ARRAY<STRING>
+        DatabricksArray(Integer)        -> ARRAY<INT>
+        DatabricksArray(CustomType)     -> ARRAY<CUSTOM_TYPE>
+    """
+
+    def __init__(self, item_type):
+        self.item_type = item_type() if isinstance(item_type, type) else item_type
+
+
+@compiles(DatabricksArray, "databricks")
+def compile_databricks_array(type_, compiler, **kw):
+    inner = compiler.process(type_.item_type, **kw)
+
+    return f"ARRAY<{inner}>"
+
+
+class DatabricksMap(UserDefinedType):
+    """
+    A custom map type that can wrap any other SQLAlchemy types for both key and value.
+
+    Examples:
+        DatabricksMap(String, String)         -> MAP<STRING,STRING>
+        DatabricksMap(Integer, String)        -> MAP<INT,STRING>
+        DatabricksMap(String, DatabricksArray(Integer)) -> MAP<STRING,ARRAY<INT>>
+    """
+
+    def __init__(self, key_type, value_type):
+        self.key_type = key_type() if isinstance(key_type, type) else key_type
+        self.value_type = value_type() if isinstance(value_type, type) else value_type
+
+
+@compiles(DatabricksMap, "databricks")
+def compile_databricks_map(type_, compiler, **kw):
+    key_type = compiler.process(type_.key_type, **kw)
+    value_type = compiler.process(type_.value_type, **kw)
+    return f"MAP<{key_type},{value_type}>"

tests/test_local/test_ddl.py

@@ -1,12 +1,13 @@
 import pytest
-from sqlalchemy import Column, MetaData, String, Table, create_engine
+from sqlalchemy import Column, MetaData, String, Table, Numeric, Integer, create_engine
 from sqlalchemy.schema import (
     CreateTable,
     DropColumnComment,
     DropTableComment,
     SetColumnComment,
     SetTableComment,
 )
+from databricks.sqlalchemy import DatabricksArray, DatabricksMap
 
 
 class DDLTestBase:
@@ -94,3 +95,20 @@ def test_alter_table_drop_comment(self, table_with_comment):
         stmt = DropTableComment(table_with_comment)
         output = self.compile(stmt)
         assert output == "COMMENT ON TABLE martin IS NULL"
+
+
+class TestTableComplexTypeDDL(DDLTestBase):
+    @pytest.fixture(scope="class")
+    def metadata(self) -> MetaData:
+        metadata = MetaData()
+        col1 = Column("array_array_string", DatabricksArray(DatabricksArray(String)))
+        col2 = Column("map_string_string", DatabricksMap(String, String))
+        table = Table("complex_type", metadata, col1, col2)
+        return metadata
+
+    def test_create_table_with_complex_type(self, metadata):
+        stmt = CreateTable(metadata.tables["complex_type"])
+        output = self.compile(stmt)
+
+        assert "array_array_string ARRAY<ARRAY<STRING>>" in output
+        assert "map_string_string MAP<STRING,STRING>" in output

tests/test_local/test_parsing.py

@@ -9,7 +9,28 @@
     get_comment_from_dte_output,
     DatabricksSqlAlchemyParseException,
 )
+from sqlalchemy import (
+    BigInteger,
+    Boolean,
+    Date,
+    DateTime,
+    Integer,
+    Numeric,
+    String,
+    Time,
+    Uuid,
+)
+
+from databricks.sqlalchemy import (
+    DatabricksArray,
+    TIMESTAMP,
+    TINYINT,
+    DatabricksMap,
+    TIMESTAMP_NTZ,
+)
+from databricks.sqlalchemy import DatabricksDialect
 
+dialect = DatabricksDialect()
 
 # These are outputs from DESCRIBE TABLE EXTENDED
 @pytest.mark.parametrize(
@@ -158,3 +179,66 @@ def test_filter_dict_by_value(match, output):
 
 def test_get_comment_from_dte_output():
     assert get_comment_from_dte_output(FMT_SAMPLE_DT_OUTPUT) == "some comment"
+
+
+def get_databricks_non_compound_types():
+    return [
+        Integer,
+        String,
+        Boolean,
+        Date,
+        DateTime,
+        Time,
+        Uuid,
+        Numeric,
+        TINYINT,
+        TIMESTAMP,
+        TIMESTAMP_NTZ,
+        BigInteger
+    ]
+
+
+@pytest.mark.parametrize("internal_type", get_databricks_non_compound_types())
+def test_array_parsing(internal_type):
+    array_type = DatabricksArray(internal_type())
+
+    actual_parsed = array_type.compile(dialect=dialect)
+    expected_parsed = "ARRAY<{}>".format(internal_type().compile(dialect=dialect))
+    assert actual_parsed == expected_parsed
+
+
+@pytest.mark.parametrize("internal_type_1", get_databricks_non_compound_types())
+@pytest.mark.parametrize("internal_type_2", get_databricks_non_compound_types())
+def test_map_parsing(internal_type_1, internal_type_2):
+    map_type = DatabricksMap(internal_type_1(), internal_type_2())
+
+    actual_parsed = map_type.compile(dialect=dialect)
+    expected_parsed = "MAP<{},{}>".format(
+        internal_type_1().compile(dialect=dialect),
+        internal_type_2().compile(dialect=dialect),
+    )
+    assert actual_parsed == expected_parsed
+
+
+@pytest.mark.parametrize("internal_type", get_databricks_non_compound_types())
+def test_multilevel_array_type_parsing(internal_type):
+    array_type = DatabricksArray(DatabricksArray(DatabricksArray(internal_type())))
+
+    actual_parsed = array_type.compile(dialect=dialect)
+    expected_parsed = "ARRAY<ARRAY<ARRAY<{}>>>".format(
+        internal_type().compile(dialect=dialect)
+    )
+    assert actual_parsed == expected_parsed
+
+
+@pytest.mark.parametrize("internal_type", get_databricks_non_compound_types())
+def test_multilevel_map_type_parsing(internal_type):
+    map_type = DatabricksMap(
+        String, DatabricksMap(String, DatabricksMap(String, internal_type()))
+    )
+
+    actual_parsed = map_type.compile(dialect=dialect)
+    expected_parsed = "MAP<STRING,MAP<STRING,MAP<STRING,{}>>>".format(
+        internal_type().compile(dialect=dialect)
+    )
+    assert actual_parsed == expected_parsed