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WIP
This commit is contained in:
Beto Dealmeida
@@ -16,33 +16,208 @@
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# under the License.
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from contextlib import nullcontext
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from typing import Iterator
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from unittest.mock import MagicMock, patch
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import pytest
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from pandas import DataFrame
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from pytest_mock import MockerFixture
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from superset.semantic_layers.snowflake_ import (
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get_connection_parameters,
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SnowflakeConfiguration,
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SnowflakeSemanticLayer,
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SnowflakeSemanticView,
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substitute_parameters,
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validate_order_by,
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)
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from superset.semantic_layers.types import (
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AdhocFilter,
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DATE,
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Dimension,
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Filter,
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FilterValues,
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INTEGER,
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Metric,
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NUMBER,
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Operator,
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PredicateType,
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SemanticRequest,
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STRING,
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)
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@pytest.fixture
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def configuration() -> SnowflakeConfiguration:
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return SnowflakeConfiguration.model_validate(
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{
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"account_identifier": "abcdefg-hij01234",
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"role": "ACCOUNTADMIN",
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"warehouse": "COMPUTE_WH",
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"database": "SAMPLE_DATA",
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"schema": "TPCDS_SF10TCL",
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"auth": {
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"auth_type": "user_password",
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"username": "SNOWFLAKE_USER",
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"password": "SNOWFLAKE_PASSWORD",
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},
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"allow_changing_database": True,
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"allow_changing_schema": True,
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}
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)
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# These fixtures reproduce the semantic view from
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# https://quickstarts.snowflake.com/guide/snowflake-semantic-view/index.html
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@pytest.fixture
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def dimension_rows() -> list[dict[str, str]]:
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return [
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dict(
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zip(
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["object_name", "property", "property_value"],
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row,
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strict=False,
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)
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)
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for row in [
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("BIRTHYEAR", "TABLE", "CUSTOMER"),
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("BIRTHYEAR", "EXPRESSION", "C_BIRTH_YEAR"),
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("BIRTHYEAR", "DATA_TYPE", "NUMBER(38,0)"),
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("COUNTRY", "TABLE", "CUSTOMER"),
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("COUNTRY", "EXPRESSION", "C_BIRTH_COUNTRY"),
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("COUNTRY", "DATA_TYPE", "VARCHAR(20)"),
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("C_CUSTOMER_SK", "TABLE", "CUSTOMER"),
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("C_CUSTOMER_SK", "EXPRESSION", "c_customer_sk"),
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("C_CUSTOMER_SK", "DATA_TYPE", "NUMBER(38,0)"),
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("DATE", "TABLE", "DATE"),
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("DATE", "EXPRESSION", "D_DATE"),
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("DATE", "DATA_TYPE", "DATE"),
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("D_DATE_SK", "TABLE", "DATE"),
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("D_DATE_SK", "EXPRESSION", "d_date_sk"),
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("D_DATE_SK", "DATA_TYPE", "NUMBER(38,0)"),
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("MONTH", "TABLE", "DATE"),
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("MONTH", "EXPRESSION", "D_MOY"),
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("MONTH", "DATA_TYPE", "NUMBER(38,0)"),
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("WEEK", "TABLE", "DATE"),
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("WEEK", "EXPRESSION", "D_WEEK_SEQ"),
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("WEEK", "DATA_TYPE", "NUMBER(38,0)"),
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("YEAR", "TABLE", "DATE"),
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("YEAR", "EXPRESSION", "D_YEAR"),
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("YEAR", "DATA_TYPE", "NUMBER(38,0)"),
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("CD_DEMO_SK", "TABLE", "DEMO"),
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("CD_DEMO_SK", "EXPRESSION", "cd_demo_sk"),
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("CD_DEMO_SK", "DATA_TYPE", "NUMBER(38,0)"),
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("CREDIT_RATING", "TABLE", "DEMO"),
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("CREDIT_RATING", "EXPRESSION", "CD_CREDIT_RATING"),
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("CREDIT_RATING", "DATA_TYPE", "VARCHAR(10)"),
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("MARITAL_STATUS", "TABLE", "DEMO"),
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("MARITAL_STATUS", "EXPRESSION", "CD_MARITAL_STATUS"),
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("MARITAL_STATUS", "DATA_TYPE", "VARCHAR(1)"),
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("BRAND", "TABLE", "ITEM"),
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("BRAND", "EXPRESSION", "I_BRAND"),
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("BRAND", "DATA_TYPE", "VARCHAR(50)"),
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("CATEGORY", "TABLE", "ITEM"),
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("CATEGORY", "EXPRESSION", "I_CATEGORY"),
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("CATEGORY", "DATA_TYPE", "VARCHAR(50)"),
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("CLASS", "TABLE", "ITEM"),
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("CLASS", "EXPRESSION", "I_CLASS"),
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("CLASS", "DATA_TYPE", "VARCHAR(50)"),
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("I_ITEM_SK", "TABLE", "ITEM"),
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("I_ITEM_SK", "EXPRESSION", "i_item_sk"),
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("I_ITEM_SK", "DATA_TYPE", "NUMBER(38,0)"),
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("MARKET", "TABLE", "STORE"),
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("MARKET", "EXPRESSION", "S_MARKET_ID"),
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("MARKET", "DATA_TYPE", "NUMBER(38,0)"),
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("SQUAREFOOTAGE", "TABLE", "STORE"),
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("SQUAREFOOTAGE", "EXPRESSION", "S_FLOOR_SPACE"),
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("SQUAREFOOTAGE", "DATA_TYPE", "NUMBER(38,0)"),
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("STATE", "TABLE", "STORE"),
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("STATE", "EXPRESSION", "S_STATE"),
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("STATE", "DATA_TYPE", "VARCHAR(2)"),
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("STORECOUNTRY", "TABLE", "STORE"),
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("STORECOUNTRY", "EXPRESSION", "S_COUNTRY"),
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("STORECOUNTRY", "DATA_TYPE", "VARCHAR(20)"),
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("S_STORE_SK", "TABLE", "STORE"),
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("S_STORE_SK", "EXPRESSION", "s_store_sk"),
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("S_STORE_SK", "DATA_TYPE", "NUMBER(38,0)"),
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("SS_CDEMO_SK", "TABLE", "STORESALES"),
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("SS_CDEMO_SK", "EXPRESSION", "ss_cdemo_sk"),
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("SS_CDEMO_SK", "DATA_TYPE", "NUMBER(38,0)"),
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("SS_CUSTOMER_SK", "TABLE", "STORESALES"),
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("SS_CUSTOMER_SK", "EXPRESSION", "ss_customer_sk"),
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("SS_CUSTOMER_SK", "DATA_TYPE", "NUMBER(38,0)"),
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("SS_ITEM_SK", "TABLE", "STORESALES"),
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("SS_ITEM_SK", "EXPRESSION", "ss_item_sk"),
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("SS_ITEM_SK", "DATA_TYPE", "NUMBER(38,0)"),
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("SS_SOLD_DATE_SK", "TABLE", "STORESALES"),
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("SS_SOLD_DATE_SK", "EXPRESSION", "ss_sold_date_sk"),
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("SS_SOLD_DATE_SK", "DATA_TYPE", "NUMBER(38,0)"),
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("SS_STORE_SK", "TABLE", "STORESALES"),
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("SS_STORE_SK", "EXPRESSION", "ss_store_sk"),
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("SS_STORE_SK", "DATA_TYPE", "NUMBER(38,0)"),
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]
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]
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@pytest.fixture
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def metric_rows() -> list[dict[str, str]]:
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return [
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dict(
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zip(
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["object_name", "property", "property_value"],
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row,
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strict=False,
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)
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)
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for row in [
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("TOTALCOST", "TABLE", "STORESALES"),
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("TOTALCOST", "EXPRESSION", "SUM(item.cost)"),
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("TOTALCOST", "DATA_TYPE", "NUMBER(19,2)"),
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("TOTALSALESPRICE", "TABLE", "STORESALES"),
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("TOTALSALESPRICE", "EXPRESSION", "SUM(SS_SALES_PRICE)"),
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("TOTALSALESPRICE", "DATA_TYPE", "NUMBER(19,2)"),
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("TOTALSALESQUANTITY", "TABLE", "STORESALES"),
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("TOTALSALESQUANTITY", "EXPRESSION", "SUM(SS_QUANTITY)"),
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("TOTALSALESQUANTITY", "DATA_TYPE", "NUMBER(38,0)"),
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]
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]
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@pytest.fixture
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def connection(mocker: MockerFixture) -> Iterator[MagicMock]:
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"""
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Mock the Snowflake connect function to return a mock connection.
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"""
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connect = mocker.patch("superset.semantic_layers.snowflake_.connect")
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with connect() as connection:
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yield connection
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@pytest.fixture
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def semantic_view(
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mocker: MockerFixture,
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connection: MagicMock,
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configuration: SnowflakeConfiguration,
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dimension_rows: list[dict[str, str]],
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metric_rows: list[dict[str, str]],
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) -> SnowflakeSemanticView:
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"""
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Mock the SnowflakeSemanticView to return predefined dimensions and metrics.
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"""
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connection.cursor().execute().fetchall.side_effect = [
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dimension_rows,
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metric_rows,
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]
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return SnowflakeSemanticView(configuration, "TPCDS_SEMANTIC_VIEW_SM")
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@pytest.mark.parametrize(
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"query, parameters, expected",
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[
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# No parameters
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(
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"SELECT * FROM table",
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None,
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"SELECT * FROM table",
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),
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(
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"SELECT * FROM table",
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[],
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"SELECT * FROM table",
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),
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("SELECT * FROM table", None, "SELECT * FROM table"),
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("SELECT * FROM table", [], "SELECT * FROM table"),
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# NULL values
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(
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"SELECT * FROM table WHERE id = ?",
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@@ -610,3 +785,471 @@ def test_get_runtime_schema(
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assert set(schema_enum) == set(schemas)
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else:
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assert "schema" not in schema["properties"]
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def test_get_dimensions(
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mocker: MockerFixture,
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connection: MagicMock,
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semantic_view: SnowflakeSemanticView,
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) -> None:
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"""
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Test dimension retrieval and parsing from Snowflake semantic layer.
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"""
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assert semantic_view.dimensions == {
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Dimension(
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id="CUSTOMER.C_CUSTOMER_SK",
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name="C_CUSTOMER_SK",
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type=INTEGER,
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definition=None,
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description="c_customer_sk",
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grain=None,
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),
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Dimension(
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id="STORE.SQUAREFOOTAGE",
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name="SQUAREFOOTAGE",
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type=INTEGER,
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definition=None,
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description="S_FLOOR_SPACE",
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grain=None,
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),
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Dimension(
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id="ITEM.BRAND",
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name="BRAND",
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type=STRING,
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definition=None,
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description="I_BRAND",
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grain=None,
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),
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Dimension(
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id="ITEM.CATEGORY",
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name="CATEGORY",
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type=STRING,
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definition=None,
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description="I_CATEGORY",
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grain=None,
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),
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Dimension(
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id="STORE.S_STORE_SK",
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name="S_STORE_SK",
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type=INTEGER,
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definition=None,
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description="s_store_sk",
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grain=None,
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),
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Dimension(
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id="STORESALES.SS_CUSTOMER_SK",
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name="SS_CUSTOMER_SK",
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type=INTEGER,
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definition=None,
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description="ss_customer_sk",
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grain=None,
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),
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Dimension(
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id="DATE.DATE",
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name="DATE",
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type=DATE,
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definition=None,
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description="D_DATE",
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grain=None,
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),
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Dimension(
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id="DEMO.CD_DEMO_SK",
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name="CD_DEMO_SK",
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type=INTEGER,
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definition=None,
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description="cd_demo_sk",
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grain=None,
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),
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Dimension(
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id="DATE.MONTH",
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name="MONTH",
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type=INTEGER,
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definition=None,
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description="D_MOY",
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grain=None,
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),
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Dimension(
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id="STORE.MARKET",
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name="MARKET",
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type=INTEGER,
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definition=None,
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description="S_MARKET_ID",
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grain=None,
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),
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Dimension(
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id="STORESALES.SS_ITEM_SK",
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name="SS_ITEM_SK",
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type=INTEGER,
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definition=None,
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description="ss_item_sk",
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grain=None,
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),
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Dimension(
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id="STORE.STORECOUNTRY",
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name="STORECOUNTRY",
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type=STRING,
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definition=None,
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description="S_COUNTRY",
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grain=None,
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||||
),
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Dimension(
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id="ITEM.CLASS",
|
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name="CLASS",
|
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type=STRING,
|
||||
definition=None,
|
||||
description="I_CLASS",
|
||||
grain=None,
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||||
),
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Dimension(
|
||||
id="CUSTOMER.COUNTRY",
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||||
name="COUNTRY",
|
||||
type=STRING,
|
||||
definition=None,
|
||||
description="C_BIRTH_COUNTRY",
|
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grain=None,
|
||||
),
|
||||
Dimension(
|
||||
id="DEMO.CREDIT_RATING",
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||||
name="CREDIT_RATING",
|
||||
type=STRING,
|
||||
definition=None,
|
||||
description="CD_CREDIT_RATING",
|
||||
grain=None,
|
||||
),
|
||||
Dimension(
|
||||
id="DATE.WEEK",
|
||||
name="WEEK",
|
||||
type=INTEGER,
|
||||
definition=None,
|
||||
description="D_WEEK_SEQ",
|
||||
grain=None,
|
||||
),
|
||||
Dimension(
|
||||
id="DATE.D_DATE_SK",
|
||||
name="D_DATE_SK",
|
||||
type=INTEGER,
|
||||
definition=None,
|
||||
description="d_date_sk",
|
||||
grain=None,
|
||||
),
|
||||
Dimension(
|
||||
id="STORESALES.SS_SOLD_DATE_SK",
|
||||
name="SS_SOLD_DATE_SK",
|
||||
type=INTEGER,
|
||||
definition=None,
|
||||
description="ss_sold_date_sk",
|
||||
grain=None,
|
||||
),
|
||||
Dimension(
|
||||
id="CUSTOMER.BIRTHYEAR",
|
||||
name="BIRTHYEAR",
|
||||
type=INTEGER,
|
||||
definition=None,
|
||||
description="C_BIRTH_YEAR",
|
||||
grain=None,
|
||||
),
|
||||
Dimension(
|
||||
id="DEMO.MARITAL_STATUS",
|
||||
name="MARITAL_STATUS",
|
||||
type=STRING,
|
||||
definition=None,
|
||||
description="CD_MARITAL_STATUS",
|
||||
grain=None,
|
||||
),
|
||||
Dimension(
|
||||
id="STORESALES.SS_CDEMO_SK",
|
||||
name="SS_CDEMO_SK",
|
||||
type=INTEGER,
|
||||
definition=None,
|
||||
description="ss_cdemo_sk",
|
||||
grain=None,
|
||||
),
|
||||
Dimension(
|
||||
id="DATE.YEAR",
|
||||
name="YEAR",
|
||||
type=INTEGER,
|
||||
definition=None,
|
||||
description="D_YEAR",
|
||||
grain=None,
|
||||
),
|
||||
Dimension(
|
||||
id="ITEM.I_ITEM_SK",
|
||||
name="I_ITEM_SK",
|
||||
type=INTEGER,
|
||||
definition=None,
|
||||
description="i_item_sk",
|
||||
grain=None,
|
||||
),
|
||||
Dimension(
|
||||
id="STORESALES.SS_STORE_SK",
|
||||
name="SS_STORE_SK",
|
||||
type=INTEGER,
|
||||
definition=None,
|
||||
description="ss_store_sk",
|
||||
grain=None,
|
||||
),
|
||||
Dimension(
|
||||
id="STORE.STATE",
|
||||
name="STATE",
|
||||
type=STRING,
|
||||
definition=None,
|
||||
description="S_STATE",
|
||||
grain=None,
|
||||
),
|
||||
}
|
||||
|
||||
connection.cursor().execute.assert_any_call(
|
||||
"""
|
||||
DESC SEMANTIC VIEW "SAMPLE_DATA"."TPCDS_SF10TCL"."TPCDS_SEMANTIC_VIEW_SM"
|
||||
->> SELECT "object_name", "property", "property_value"
|
||||
FROM $1
|
||||
WHERE
|
||||
"object_kind" = 'DIMENSION' AND
|
||||
"property" IN ('COMMENT', 'DATA_TYPE', 'EXPRESSION', 'TABLE');
|
||||
""".strip()
|
||||
)
|
||||
|
||||
|
||||
def test_get_metrics(
|
||||
mocker: MockerFixture,
|
||||
connection: MagicMock,
|
||||
semantic_view: SnowflakeSemanticView,
|
||||
) -> None:
|
||||
"""
|
||||
Test metric retrieval and parsing from Snowflake semantic layer.
|
||||
"""
|
||||
assert semantic_view.metrics == {
|
||||
Metric(
|
||||
id="STORESALES.TOTALCOST",
|
||||
name="TOTALCOST",
|
||||
type=NUMBER,
|
||||
definition="SUM(item.cost)",
|
||||
description=None,
|
||||
),
|
||||
Metric(
|
||||
id="STORESALES.TOTALSALESQUANTITY",
|
||||
name="TOTALSALESQUANTITY",
|
||||
type=INTEGER,
|
||||
definition="SUM(SS_QUANTITY)",
|
||||
description=None,
|
||||
),
|
||||
Metric(
|
||||
id="STORESALES.TOTALSALESPRICE",
|
||||
name="TOTALSALESPRICE",
|
||||
type=NUMBER,
|
||||
definition="SUM(SS_SALES_PRICE)",
|
||||
description=None,
|
||||
),
|
||||
}
|
||||
|
||||
connection.cursor().execute.assert_any_call(
|
||||
"""
|
||||
DESC SEMANTIC VIEW "SAMPLE_DATA"."TPCDS_SF10TCL"."TPCDS_SEMANTIC_VIEW_SM"
|
||||
->> SELECT "object_name", "property", "property_value"
|
||||
FROM $1
|
||||
WHERE
|
||||
"object_kind" = 'METRIC' AND
|
||||
"property" IN ('COMMENT', 'DATA_TYPE', 'EXPRESSION', 'TABLE');
|
||||
""".strip()
|
||||
)
|
||||
|
||||
|
||||
def test_get_values(
|
||||
mocker: MockerFixture,
|
||||
connection: MagicMock,
|
||||
semantic_view: SnowflakeSemanticView,
|
||||
) -> None:
|
||||
connection.cursor().execute().fetch_pandas_all.return_value = DataFrame(
|
||||
{
|
||||
"CATEGORY": [
|
||||
"Music",
|
||||
"Women",
|
||||
"Home",
|
||||
"Children",
|
||||
"Men",
|
||||
"Electronics",
|
||||
"Sports",
|
||||
"Shoes",
|
||||
"Jewelry",
|
||||
"Books",
|
||||
None,
|
||||
]
|
||||
}
|
||||
)
|
||||
|
||||
dimension = Dimension(
|
||||
id="ITEM.CATEGORY",
|
||||
name="CATEGORY",
|
||||
type=STRING,
|
||||
description=None,
|
||||
definition="I_CATEGORY",
|
||||
grain=None,
|
||||
)
|
||||
|
||||
result = semantic_view.get_values(dimension)
|
||||
|
||||
assert result.requests == [
|
||||
SemanticRequest(
|
||||
type="snowflake",
|
||||
definition="""
|
||||
SELECT "CATEGORY"
|
||||
FROM SEMANTIC_VIEW(
|
||||
"SAMPLE_DATA"."TPCDS_SF10TCL"."TPCDS_SEMANTIC_VIEW_SM"
|
||||
DIMENSIONS ITEM.CATEGORY
|
||||
|
||||
)
|
||||
""".strip(),
|
||||
)
|
||||
]
|
||||
assert result.results["CATEGORY"].tolist() == [
|
||||
"Music",
|
||||
"Women",
|
||||
"Home",
|
||||
"Children",
|
||||
"Men",
|
||||
"Electronics",
|
||||
"Sports",
|
||||
"Shoes",
|
||||
"Jewelry",
|
||||
"Books",
|
||||
None,
|
||||
]
|
||||
|
||||
|
||||
def test_get_values_with_filters(
|
||||
mocker: MockerFixture,
|
||||
connection: MagicMock,
|
||||
semantic_view: SnowflakeSemanticView,
|
||||
) -> None:
|
||||
connection.cursor().execute().fetch_pandas_all.return_value = DataFrame(
|
||||
{
|
||||
"CATEGORY": [
|
||||
"Music",
|
||||
"Women",
|
||||
"Home",
|
||||
"Children",
|
||||
"Men",
|
||||
"Electronics",
|
||||
"Sports",
|
||||
"Shoes",
|
||||
"Jewelry",
|
||||
]
|
||||
}
|
||||
)
|
||||
|
||||
dimension = Dimension(
|
||||
id="ITEM.CATEGORY",
|
||||
name="CATEGORY",
|
||||
type=STRING,
|
||||
description=None,
|
||||
definition="I_CATEGORY",
|
||||
grain=None,
|
||||
)
|
||||
filters = {
|
||||
Filter(PredicateType.WHERE, dimension, Operator.NOT_EQUALS, "Books"),
|
||||
Filter(PredicateType.WHERE, dimension, Operator.IS_NOT_NULL, None),
|
||||
}
|
||||
|
||||
result = semantic_view.get_values(dimension, filters)
|
||||
|
||||
assert result.requests == [
|
||||
SemanticRequest(
|
||||
type="snowflake",
|
||||
definition="""
|
||||
SELECT "CATEGORY"
|
||||
FROM SEMANTIC_VIEW(
|
||||
"SAMPLE_DATA"."TPCDS_SF10TCL"."TPCDS_SEMANTIC_VIEW_SM"
|
||||
DIMENSIONS ITEM.CATEGORY
|
||||
WHERE ("CATEGORY" != 'Books') AND ("CATEGORY" IS NOT NULL)
|
||||
)
|
||||
""".strip(),
|
||||
)
|
||||
]
|
||||
assert result.results["CATEGORY"].tolist() == [
|
||||
"Music",
|
||||
"Women",
|
||||
"Home",
|
||||
"Children",
|
||||
"Men",
|
||||
"Electronics",
|
||||
"Sports",
|
||||
"Shoes",
|
||||
"Jewelry",
|
||||
]
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"metrics, dimensions, filters, expected_sql, expected_parameters",
|
||||
[
|
||||
(
|
||||
["TOTALSALESPRICE"],
|
||||
[],
|
||||
{
|
||||
AdhocFilter(PredicateType.WHERE, "Year = '2002'"),
|
||||
AdhocFilter(PredicateType.WHERE, "Month = '12'"),
|
||||
},
|
||||
"""
|
||||
SELECT * FROM SEMANTIC_VIEW(
|
||||
"SAMPLE_DATA"."TPCDS_SF10TCL"."TPCDS_SEMANTIC_VIEW_SM"
|
||||
|
||||
METRICS STORESALES.TOTALSALESPRICE AS "STORESALES.TOTALSALESPRICE"
|
||||
WHERE (Month = '12') AND (Year = '2002')
|
||||
)
|
||||
""",
|
||||
(),
|
||||
),
|
||||
(
|
||||
[],
|
||||
["CATEGORY"],
|
||||
{
|
||||
AdhocFilter(PredicateType.WHERE, "Year = '2002'"),
|
||||
AdhocFilter(PredicateType.WHERE, "Month = '12'"),
|
||||
},
|
||||
"""
|
||||
SELECT * FROM SEMANTIC_VIEW(
|
||||
"SAMPLE_DATA"."TPCDS_SF10TCL"."TPCDS_SEMANTIC_VIEW_SM"
|
||||
DIMENSIONS ITEM.CATEGORY AS "ITEM.CATEGORY"
|
||||
|
||||
WHERE (Month = '12') AND (Year = '2002')
|
||||
)
|
||||
""",
|
||||
(),
|
||||
),
|
||||
(
|
||||
["TOTALSALESPRICE"],
|
||||
["CATEGORY"],
|
||||
{
|
||||
AdhocFilter(PredicateType.WHERE, "Year = '2002'"),
|
||||
AdhocFilter(PredicateType.WHERE, "Month = '12'"),
|
||||
},
|
||||
"""
|
||||
SELECT * FROM SEMANTIC_VIEW(
|
||||
"SAMPLE_DATA"."TPCDS_SF10TCL"."TPCDS_SEMANTIC_VIEW_SM"
|
||||
DIMENSIONS ITEM.CATEGORY AS "ITEM.CATEGORY"
|
||||
METRICS STORESALES.TOTALSALESPRICE AS "STORESALES.TOTALSALESPRICE"
|
||||
WHERE (Month = '12') AND (Year = '2002')
|
||||
)
|
||||
""",
|
||||
(),
|
||||
),
|
||||
],
|
||||
)
|
||||
def test_get_query(
|
||||
semantic_view: SnowflakeSemanticView,
|
||||
metrics: list[str],
|
||||
dimensions: list[str],
|
||||
filters: set[Filter | AdhocFilter] | None,
|
||||
expected_sql: str,
|
||||
expected_parameters: tuple[FilterValues, ...],
|
||||
) -> None:
|
||||
"""
|
||||
Tests for query generation.
|
||||
"""
|
||||
metric_map = {metric.name: metric for metric in semantic_view.metrics}
|
||||
dimension_map = {dim.name: dim for dim in semantic_view.dimensions}
|
||||
|
||||
assert semantic_view._get_query(
|
||||
[metric_map[name] for name in metrics],
|
||||
[dimension_map[name] for name in dimensions],
|
||||
filters,
|
||||
) == (expected_sql.strip(), expected_parameters)
|
||||
|
||||
Reference in New Issue
Block a user