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schema=self.schema_name, + ) + self.logger.info("Hard delete: %s", self.config.get("hard_delete")) if self.config["hard_delete"] is True: - connection.execute( - sqlalchemy.text( - f'DELETE FROM "{self.schema_name}"."{self.table_name}" ' - f"WHERE {self.version_column_name} <= {new_version} " - f"OR {self.version_column_name} IS NULL" + delete_stmt = sqlalchemy.delete(target_table).where( + sqlalchemy.or_( + target_table.c[self.version_column_name].is_(None), + target_table.c[self.version_column_name] <= new_version, ) ) + connection.execute(delete_stmt) return if not self.connector.column_exists( @@ -366,15 +374,25 @@ def activate_version(self, new_version: int) -> None: connection=connection, ) # Need to deal with the case where data doesn't exist for the version column - query = sqlalchemy.text( - f'UPDATE "{self.schema_name}"."{self.table_name}"\n' - f"SET {self.soft_delete_column_name} = :deletedate \n" - f"WHERE {self.version_column_name} < :version " - f"OR {self.version_column_name} IS NULL \n" - f" AND {self.soft_delete_column_name} IS NULL\n" - ) - query = query.bindparams( - bindparam("deletedate", value=deleted_at, type_=datetime_type), - bindparam("version", value=new_version, type_=integer_type), + update_stmt = ( + update(target_table) + .values( + { + target_table.c[self.soft_delete_column_name]: bindparam( + "deletedate" + ) + } + ) + .where( + sqlalchemy.and_( + sqlalchemy.or_( + target_table.c[self.version_column_name] + < bindparam("version"), + target_table.c[self.version_column_name].is_(None), + ), + target_table.c[self.soft_delete_column_name].is_(None), + ) + ) ) - connection.execute(query) + bind_params = {"deletedate": deleted_at, "version": new_version} + connection.execute(update_stmt, bind_params) From 937cb8a08bb7603f32778ee40dd82a8b71700a51 Mon Sep 17 00:00:00 2001 From: Sebastian Smiley <46581584+sebastianswms@users.noreply.github.com> Date: Mon, 27 Nov 2023 16:53:26 -0500 Subject: [PATCH 4/7] fix: add test for 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diff --git a/target_postgres/tests/data_files/multiple_schema_messages.singer b/target_postgres/tests/data_files/multiple_schema_messages.singer new file mode 100644 index 00000000..76fa1ec9 --- /dev/null +++ b/target_postgres/tests/data_files/multiple_schema_messages.singer @@ -0,0 +1,12 @@ +{"type": "SCHEMA", "stream": "test_multiple_schema_messages", "key_properties": ["id"], "schema": {"required": ["id"], "type": "object", "properties": {"id": {"type": "integer"}, "metric": {"type": "integer"}}}} +{"type": "SCHEMA", "stream": "test_multiple_schema_messages", "key_properties": ["id"], "schema": {"required": ["id"], "type": "object", "properties": {"id": {"type": "integer"}, "metric": {"type": "integer"}}}} +{"type": "SCHEMA", "stream": "test_multiple_schema_messages", "key_properties": ["id"], "schema": {"required": ["id"], "type": "object", "properties": {"id": {"type": "integer"}, "metric": {"type": "integer"}}}} +{"type": "SCHEMA", "stream": "test_multiple_schema_messages", "key_properties": ["id"], "schema": {"required": ["id"], "type": "object", "properties": {"id": {"type": "integer"}, "metric": {"type": "integer"}}}} +{"type": "RECORD", "stream": "test_multiple_schema_messages", "record": {"id": 1, "metric": 100}} +{"type": "RECORD", "stream": "test_multiple_schema_messages", "record": {"id": 2, "metric": 200}} +{"type": "RECORD", "stream": "test_multiple_schema_messages", "record": {"id": 3, "metric": 300}} +{"type": "SCHEMA", "stream": "test_multiple_schema_messages", "key_properties": ["id"], "schema": {"required": ["id"], "type": "object", "properties": {"id": {"type": "integer"}, "metric": {"type": "integer"}}}} +{"type": "SCHEMA", "stream": "test_multiple_schema_messages", "key_properties": ["id"], "schema": {"required": ["id"], "type": "object", "properties": {"id": {"type": "integer"}, "metric": {"type": "integer"}}}} +{"type": "RECORD", "stream": "test_multiple_schema_messages", "record": {"id": 4, "metric": 400}} +{"type": "RECORD", "stream": "test_multiple_schema_messages", "record": {"id": 5, "metric": 500}} +{"type": "RECORD", "stream": "test_multiple_schema_messages", "record": {"id": 6, "metric": 600}} diff --git a/target_postgres/tests/test_standard_target.py b/target_postgres/tests/test_standard_target.py index 4a5068b7..06dd7c56 100644 --- a/target_postgres/tests/test_standard_target.py +++ b/target_postgres/tests/test_standard_target.py @@ -264,6 +264,20 @@ def test_multiple_state_messages(postgres_target): singer_file_to_target(file_name, postgres_target) +# TODO test that data is correct +def test_multiple_schema_messages(postgres_target, caplog): + """Test multiple identical schema messages. + + Multiple schema messages with the same schema should not cause 'schema has changed' + logging statements. See: https://github.com/MeltanoLabs/target-postgres/issues/124 + + Caplog docs: https://docs.pytest.org/en/latest/how-to/logging.html#caplog-fixture + """ + file_name = "multiple_schema_messages.singer" + singer_file_to_target(file_name, postgres_target) + assert "Schema has changed for stream" not in caplog.text + + def test_relational_data(postgres_target): engine = create_engine(postgres_target) file_name = "user_location_data.singer" From 840181e9e0a1eb33604eddc7fab248a406b28524 Mon Sep 17 00:00:00 2001 From: Sebastian Smiley <46581584+sebastianswms@users.noreply.github.com> Date: Mon, 27 Nov 2023 17:01:44 -0500 Subject: [PATCH 5/7] feat: Verify data in tests (row count and first row) (#215) Implement a method to verify data in tests. Currently only checks the total number of rows in a table and the data in the first row. I believe this provides good test coverage while keeping things manageable. Closes #16 --- target_postgres/tests/test_standard_target.py | 219 +++++++++++------- 1 file changed, 132 insertions(+), 87 deletions(-) diff --git a/target_postgres/tests/test_standard_target.py b/target_postgres/tests/test_standard_target.py index 06dd7c56..086b0242 100644 --- a/target_postgres/tests/test_standard_target.py +++ b/target_postgres/tests/test_standard_target.py @@ -4,6 +4,7 @@ import io import uuid from contextlib import redirect_stdout +from decimal import Decimal from pathlib import Path import jsonschema @@ -116,6 +117,57 @@ def remove_metadata_columns(row: dict) -> dict: return new_row +def verify_data( + target: TargetPostgres, + table_name: str, + number_of_rows: int = 1, + primary_key: str | None = None, + check_data: dict | list[dict] | None = None, +): + """Checks whether the data in a table matches a provided data sample. + + Args: + target: The target to obtain a database connection from. + full_table_name: The schema and table name of the table to check data for. + primary_key: The primary key of the table. + number_of_rows: The expected number of rows that should be in the table. + check_data: A dictionary representing the full contents of the first row in the + table, as determined by lowest primary_key value, or else a list of + dictionaries representing every row in the table. + """ + engine = create_engine(target) + full_table_name = f"{target.config['default_target_schema']}.{table_name}" + with engine.connect() as connection: + if primary_key is not None and check_data is not None: + if isinstance(check_data, dict): + result = connection.execute( + sqlalchemy.text( + f"SELECT * FROM {full_table_name} ORDER BY {primary_key}" + ) + ) + assert result.rowcount == number_of_rows + result_dict = remove_metadata_columns(result.first()._asdict()) + assert result_dict == check_data + elif isinstance(check_data, list): + result = connection.execute( + sqlalchemy.text( + f"SELECT * FROM {full_table_name} ORDER BY {primary_key}" + ) + ) + assert result.rowcount == number_of_rows + result_dict = [ + remove_metadata_columns(row._asdict()) for row in result.all() + ] + assert result_dict == check_data + else: + raise ValueError("Invalid check_data - not dict or list of dicts") + else: + result = connection.execute( + sqlalchemy.text(f"SELECT COUNT(*) FROM {full_table_name}") + ) + assert result.first()[0] == number_of_rows + + def test_sqlalchemy_url_config(postgres_config_no_ssl): """Be sure that passing a sqlalchemy_url works @@ -230,10 +282,11 @@ def test_special_chars_in_attributes(postgres_target): singer_file_to_target(file_name, postgres_target) -# TODO test that data is correctly set def test_optional_attributes(postgres_target): file_name = "optional_attributes.singer" singer_file_to_target(file_name, postgres_target) + row = {"id": 1, "optional": "This is optional"} + verify_data(postgres_target, "test_optional_attributes", 4, "id", row) def test_schema_no_properties(postgres_target): @@ -256,12 +309,25 @@ def test_large_numeric_primary_key(postgres_target): def test_schema_updates(postgres_target): file_name = "schema_updates.singer" singer_file_to_target(file_name, postgres_target) + row = { + "id": 1, + "a1": Decimal("101"), + "a2": "string1", + "a3": None, + "a4": None, + "a5": None, + "a6": None, + } + verify_data(postgres_target, "test_schema_updates", 6, "id", row) -# TODO test that data is correct def test_multiple_state_messages(postgres_target): file_name = "multiple_state_messages.singer" singer_file_to_target(file_name, postgres_target) + row = {"id": 1, "metric": 100} + verify_data(postgres_target, "test_multiple_state_messages_a", 6, "id", row) + row = {"id": 1, "metric": 110} + verify_data(postgres_target, "test_multiple_state_messages_b", 6, "id", row) # TODO test that data is correct @@ -279,88 +345,65 @@ def test_multiple_schema_messages(postgres_target, caplog): def test_relational_data(postgres_target): - engine = create_engine(postgres_target) file_name = "user_location_data.singer" singer_file_to_target(file_name, postgres_target) file_name = "user_location_upsert_data.singer" singer_file_to_target(file_name, postgres_target) - schema_name = postgres_target.config["default_target_schema"] + users = [ + {"id": 1, "name": "Johny"}, + {"id": 2, "name": "George"}, + {"id": 3, "name": "Jacob"}, + {"id": 4, "name": "Josh"}, + {"id": 5, "name": "Jim"}, + {"id": 8, "name": "Thomas"}, + {"id": 12, "name": "Paul"}, + {"id": 13, "name": "Mary"}, + ] + locations = [ + {"id": 1, "name": "Philly"}, + {"id": 2, "name": "NY"}, + {"id": 3, "name": "San Francisco"}, + {"id": 6, "name": "Colorado"}, + {"id": 8, "name": "Boston"}, + ] + user_in_location = [ + { + "id": 1, + "user_id": 1, + "location_id": 4, + "info": {"weather": "rainy", "mood": "sad"}, + }, + { + "id": 2, + "user_id": 2, + "location_id": 3, + "info": {"weather": "sunny", "mood": "satisfied"}, + }, + { + "id": 3, + "user_id": 1, + "location_id": 3, + "info": {"weather": "sunny", "mood": "happy"}, + }, + { + "id": 6, + "user_id": 3, + "location_id": 2, + "info": {"weather": "sunny", "mood": "happy"}, + }, + { + "id": 14, + "user_id": 4, + "location_id": 1, + "info": {"weather": "cloudy", "mood": "ok"}, + }, + ] - with engine.connect() as connection: - expected_test_users = [ - {"id": 1, "name": "Johny"}, - {"id": 2, "name": "George"}, - {"id": 3, "name": "Jacob"}, - {"id": 4, "name": "Josh"}, - {"id": 5, "name": "Jim"}, - {"id": 8, "name": "Thomas"}, - {"id": 12, "name": "Paul"}, - {"id": 13, "name": "Mary"}, - ] - - full_table_name = f"{schema_name}.test_users" - result = connection.execute( - sqlalchemy.text(f"SELECT * FROM {full_table_name} ORDER BY id") - ) - result_dict = [remove_metadata_columns(row._asdict()) for row in result.all()] - assert result_dict == expected_test_users - - expected_test_locations = [ - {"id": 1, "name": "Philly"}, - {"id": 2, "name": "NY"}, - {"id": 3, "name": "San Francisco"}, - {"id": 6, "name": "Colorado"}, - {"id": 8, "name": "Boston"}, - ] - - full_table_name = f"{schema_name}.test_locations" - result = connection.execute( - sqlalchemy.text(f"SELECT * FROM {full_table_name} ORDER BY id") - ) - result_dict = [remove_metadata_columns(row._asdict()) for row in result.all()] - assert result_dict == expected_test_locations - - expected_test_user_in_location = [ - { - "id": 1, - "user_id": 1, - "location_id": 4, - "info": {"weather": "rainy", "mood": "sad"}, - }, - { - "id": 2, - "user_id": 2, - "location_id": 3, - "info": {"weather": "sunny", "mood": "satisfied"}, - }, - { - "id": 3, - "user_id": 1, - "location_id": 3, - "info": {"weather": "sunny", "mood": "happy"}, - }, - { - "id": 6, - "user_id": 3, - "location_id": 2, - "info": {"weather": "sunny", "mood": "happy"}, - }, - { - "id": 14, - "user_id": 4, - "location_id": 1, - "info": {"weather": "cloudy", "mood": "ok"}, - }, - ] - - full_table_name = f"{schema_name}.test_user_in_location" - result = connection.execute( - sqlalchemy.text(f"SELECT * FROM {full_table_name} ORDER BY id") - ) - result_dict = [remove_metadata_columns(row._asdict()) for row in result.all()] - assert result_dict == expected_test_user_in_location + verify_data(postgres_target, "test_users", 8, "id", users) + verify_data(postgres_target, "test_locations", 5, "id", locations) + verify_data(postgres_target, "test_user_in_location", 5, "id", user_in_location) def test_no_primary_keys(postgres_target): @@ -369,9 +412,7 @@ def test_no_primary_keys(postgres_target): table_name = "test_no_pk" full_table_name = postgres_target.config["default_target_schema"] + "." + table_name with engine.connect() as connection, connection.begin(): - result = connection.execute( - sqlalchemy.text(f"DROP TABLE IF EXISTS {full_table_name}") - ) + connection.execute(sqlalchemy.text(f"DROP TABLE IF EXISTS {full_table_name}")) file_name = f"{table_name}.singer" singer_file_to_target(file_name, postgres_target) @@ -384,10 +425,7 @@ def test_no_primary_keys(postgres_target): file_name = f"{table_name}_append.singer" singer_file_to_target(file_name, postgres_target) - # Will populate us with 22 records, we run this twice - with engine.connect() as connection: - result = connection.execute(sqlalchemy.text(f"SELECT * FROM {full_table_name}")) - assert result.rowcount == 16 + verify_data(postgres_target, table_name, 16) def test_no_type(postgres_target): @@ -395,19 +433,20 @@ def test_no_type(postgres_target): singer_file_to_target(file_name, postgres_target) -# TODO test that data is correct def test_duplicate_records(postgres_target): file_name = "duplicate_records.singer" singer_file_to_target(file_name, postgres_target) + row = {"id": 1, "metric": 100} + verify_data(postgres_target, "test_duplicate_records", 2, "id", row) -# TODO test that data is correct def test_array_data(postgres_target): file_name = "array_data.singer" singer_file_to_target(file_name, postgres_target) + row = {"id": 1, "fruits": ["apple", "orange", "pear"]} + verify_data(postgres_target, "test_carts", 4, "id", row) -# TODO test that data is correct def test_encoded_string_data(postgres_target): """ We removed NUL characters from the original encoded_strings.singer as postgres doesn't allow them. @@ -420,6 +459,12 @@ def test_encoded_string_data(postgres_target): file_name = "encoded_strings.singer" singer_file_to_target(file_name, postgres_target) + row = {"id": 1, "info": "simple string 2837"} + verify_data(postgres_target, "test_strings", 11, "id", row) + row = {"id": 1, "info": {"name": "simple", "value": "simple string 2837"}} + verify_data(postgres_target, "test_strings_in_objects", 11, "id", row) + row = {"id": 1, "strings": ["simple string", "απλή συμβολοσειρά", "简单的字串"]} + verify_data(postgres_target, "test_strings_in_arrays", 6, "id", row) def test_tap_appl(postgres_target): From d59fb44b59fd67b7e1ecae64d4d1dd45451e8a20 Mon Sep 17 00:00:00 2001 From: Sebastian Smiley <46581584+sebastianswms@users.noreply.github.com> Date: Tue, 28 Nov 2023 14:11:46 -0500 Subject: [PATCH 6/7] feat: Refactor for a more efficient prepare_table() (#228) Refactor code in prepare_table() to drastically reduce database queries required from O(n) db queries to O(1) db queries, where n is the number of columns in the table. This change improves test_reserved_keywords() running time and closes #142 Running `time poetry run pytest -k 'test_reserved_keywords'` on main branch gave me an average running time of 33.441 seconds across three runs: ``` real 0m33.539s user 0m21.294s sys 0m0.531s real 0m33.300s user 0m21.272s sys 0m0.472s real 0m33.484s user 0m21.337s sys 0m0.503s ``` Running `time poetry run pytest -k 'test_reserved_keywords'` after my changes gave me an average running time of 1.271 seconds across three runs: ``` real 0m1.232s user 0m1.005s sys 0m0.056s real 0m1.299s user 0m1.018s sys 0m0.105s real 0m1.281s user 0m1.024s sys 0m0.082s ``` --- target_postgres/connector.py | 36 +++++++++++++++++++++++++++++------- 1 file changed, 29 insertions(+), 7 deletions(-) diff --git a/target_postgres/connector.py b/target_postgres/connector.py index b50e1cae..09554d59 100644 --- a/target_postgres/connector.py +++ b/target_postgres/connector.py @@ -118,13 +118,24 @@ def prepare_table( # type: ignore[override] table = meta.tables[ full_table_name ] # So we don't mess up the casing of the Table reference + + columns = self.get_table_columns( + schema_name=cast(str, schema_name), + table_name=table_name, + connection=connection, + ) + for property_name, property_def in schema["properties"].items(): + column_object = None + if property_name in columns: + column_object = columns[property_name] self.prepare_column( schema_name=cast(str, schema_name), table=table, column_name=property_name, sql_type=self.to_sql_type(property_def), connection=connection, + column_object=column_object, ) return meta.tables[full_table_name] @@ -366,6 +377,7 @@ def prepare_column( # type: ignore[override] column_name: str, sql_type: sqlalchemy.types.TypeEngine, connection: sqlalchemy.engine.Connection, + column_object: sqlalchemy.Column | None = None, ) -> None: """Adapt target table to provided schema if possible. @@ -376,7 +388,11 @@ def prepare_column( # type: ignore[override] sql_type: the SQLAlchemy type. connection: the database connection. """ - if not self.column_exists(table.fullname, column_name, connection=connection): + column_exists = column_object is not None or self.column_exists( + table.fullname, column_name, connection=connection + ) + + if not column_exists: self._create_empty_column( # We should migrate every function to use sqlalchemy.Table # instead of having to know what the function wants @@ -394,6 +410,7 @@ def prepare_column( # type: ignore[override] column_name=column_name, sql_type=sql_type, connection=connection, + column_object=column_object, ) def _create_empty_column( # type: ignore[override] @@ -466,6 +483,7 @@ def _adapt_column_type( # type: ignore[override] column_name: str, sql_type: sqlalchemy.types.TypeEngine, connection: sqlalchemy.engine.Connection, + column_object: sqlalchemy.Column | None, ) -> None: """Adapt table column type to support the new JSON schema type. @@ -477,12 +495,16 @@ def _adapt_column_type( # type: ignore[override] Raises: NotImplementedError: if altering columns is not supported. """ - current_type: sqlalchemy.types.TypeEngine = self._get_column_type( - schema_name=schema_name, - table_name=table_name, - column_name=column_name, - connection=connection, - ) + current_type: sqlalchemy.types.TypeEngine + if column_object is not None: + current_type = t.cast(sqlalchemy.types.TypeEngine, column_object.type) + else: + current_type = self._get_column_type( + schema_name=schema_name, + table_name=table_name, + column_name=column_name, + connection=connection, + ) # remove collation if present and save it current_type_collation = self.remove_collation(current_type) From 8262aeb2258c6284fba8e6299de6ef3d629f32c7 Mon Sep 17 00:00:00 2001 From: Sebastian Smiley <46581584+sebastianswms@users.noreply.github.com> Date: Tue, 28 Nov 2023 14:20:34 -0500 Subject: [PATCH 7/7] doc: Datatype documentation (#234) README update that lists each postgres and jsonschema type and how target-postgres maps between them. Based on prior discussion, this is all that's desired right now in-terms of #13 and #106, although this doesn't full address either. --- README.md | 66 +++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 66 insertions(+) diff --git a/README.md b/README.md index 2e0a2ae5..a1b48c33 100644 --- a/README.md +++ b/README.md @@ -149,3 +149,69 @@ meltano invoke target-postgres --version See the [dev guide](https://sdk.meltano.com/en/latest/dev_guide.html) for more instructions on how to use the Meltano SDK to develop your own Singer taps and targets. + +## Data Types + +The below table shows how this tap will map between jsonschema datatypes and Postgres datatypes. + +| jsonschema | Postgres | +|--------------------------------|-----------------------------------------| +| integer | bigint | +| UNSUPPORTED | bigserial | +| UNSUPPORTED | bit [ (n) ] | +| UNSUPPORTED | bit varying [ (n) ] | +| boolean | boolean | +| UNSUPPORTED | box | +| UNSUPPORTED | bytea | +| UNSUPPORTED | character [ (n) ] | +| UNSUPPORTED | character varying [ (n) ] | +| UNSUPPORTED | cidr | +| UNSUPPORTED | circle | +| string with format="date" | date | +| UNSUPPORTED | double precision | +| UNSUPPORTED | inet | +| UNSUPPORTED | integer | +| UNSUPPORTED | interval [ fields ] [ (p) ] | +| UNSUPPORTED | json | +| array; object | jsonb | +| UNSUPPORTED | line | +| UNSUPPORTED | lseg | +| UNSUPPORTED | macaddr | +| UNSUPPORTED | macaddr8 | +| UNSUPPORTED | money | +| number | numeric [ (p, s) ] | +| UNSUPPORTED | path | +| UNSUPPORTED | pg_lsn | +| UNSUPPORTED | pg_snapshot | +| UNSUPPORTED | point | +| UNSUPPORTED | polygon | +| UNSUPPORTED | real | +| UNSUPPORTED | smallint | +| UNSUPPORTED | smallserial | +| UNSUPPORTED | serial | +| string without format; untyped | text | +| string with format="time" | time [ (p) ] [ without time zone ] | +| UNSUPPORTED | time [ (p) ] with time zone | +| string with format="date-time" | timestamp [ (p) ] [ without time zone ] | +| UNSUPPORTED | timestamp [ (p) ] with time zone | +| UNSUPPORTED | tsquery | +| UNSUPPORTED | tsvector | +| UNSUPPORTED | txid_snapshot | +| UNSUPPORTED | uuid | +| UNSUPPORTED | xml | + +Note that while object types are mapped directly to jsonb, array types are mapped to a jsonb array. + +If a column has multiple jsonschema types, the following order is using to order Postgres types, from highest priority to lowest priority. +- ARRAY(JSONB) +- JSONB +- TEXT +- TIMESTAMP +- DATETIME +- DATE +- TIME +- DECIMAL +- BIGINT +- INTEGER +- BOOLEAN +- NOTYPE