superset2/tests/integration_tests/fixtures/birth_names_dashboard.py

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from typing import Any, Dict, List, Optional

import pandas as pd
import pytest
from pandas import DataFrame
from sqlalchemy import DateTime, String

from superset import ConnectorRegistry, db
from superset.connectors.sqla.models import SqlaTable
from superset.models.core import Database
from superset.models.dashboard import Dashboard
from superset.models.slice import Slice
from superset.utils.core import get_example_database, get_example_default_schema
from tests.common.example_data_generator.birth_names.birth_names_generator_factory import (
    BirthNamesGeneratorFactory,
)
from tests.integration_tests.dashboard_utils import create_table_metadata
from tests.integration_tests.test_app import app

BIRTH_NAMES_TBL_NAME = "birth_names"


@pytest.fixture(scope="session")
def load_birth_names_data():
    with app.app_context():
        database = get_example_database()
        df = _get_dataframe(database)
        dtype = {
            "ds": DateTime if database.backend != "presto" else String(255),
            "gender": String(16),
            "state": String(10),
            "name": String(255),
        }

        df.to_sql(
            BIRTH_NAMES_TBL_NAME,
            database.get_sqla_engine(),
            if_exists="replace",
            chunksize=500,
            dtype=dtype,
            index=False,
            method="multi",
            schema=get_example_default_schema(),
        )
    yield
    with app.app_context():
        engine = get_example_database().get_sqla_engine()
        engine.execute("DROP TABLE IF EXISTS birth_names")


@pytest.fixture()
def load_birth_names_dashboard_with_slices(load_birth_names_data):
    with app.app_context():
        dash_id_to_delete, slices_ids_to_delete = _create_dashboards()
        yield
        _cleanup(dash_id_to_delete, slices_ids_to_delete)


@pytest.fixture(scope="module")
def load_birth_names_dashboard_with_slices_module_scope(load_birth_names_data):
    with app.app_context():
        dash_id_to_delete, slices_ids_to_delete = _create_dashboards()
        yield
        _cleanup(dash_id_to_delete, slices_ids_to_delete)


def _create_dashboards():
    table = _create_table(
        table_name=BIRTH_NAMES_TBL_NAME,
        database=get_example_database(),
        fetch_values_predicate="123 = 123",
    )

    from superset.examples.birth_names import create_dashboard, create_slices

    slices, _ = create_slices(table, admin_owner=False)
    dash = create_dashboard(slices)
    slices_ids_to_delete = [slice.id for slice in slices]
    dash_id_to_delete = dash.id
    return dash_id_to_delete, slices_ids_to_delete


def _create_table(
    table_name: str, database: "Database", fetch_values_predicate: Optional[str] = None,
):
    table = create_table_metadata(
        table_name=table_name,
        database=database,
        fetch_values_predicate=fetch_values_predicate,
    )
    from superset.examples.birth_names import _add_table_metrics, _set_table_metadata

    _set_table_metadata(table, database)
    _add_table_metrics(table)
    db.session.commit()
    return table


def _cleanup(dash_id: int, slices_ids: List[int]) -> None:
    schema = get_example_default_schema()

    table_id = (
        db.session.query(SqlaTable)
        .filter_by(table_name="birth_names", schema=schema)
        .one()
        .id
    )
    datasource = ConnectorRegistry.get_datasource("table", table_id, db.session)
    columns = [column for column in datasource.columns]
    metrics = [metric for metric in datasource.metrics]

    for column in columns:
        db.session.delete(column)
    for metric in metrics:
        db.session.delete(metric)

    dash = db.session.query(Dashboard).filter_by(id=dash_id).first()

    db.session.delete(dash)
    for slice_id in slices_ids:
        db.session.query(Slice).filter_by(id=slice_id).delete()
    db.session.commit()


def _get_dataframe(database: Database) -> DataFrame:
    data = _get_birth_names_data()
    df = pd.DataFrame.from_dict(data)
    if database.backend == "presto":
        df.ds = df.ds.dt.strftime("%Y-%m-%d %H:%M:%S")
    return df


def _get_birth_names_data() -> List[Dict[Any, Any]]:
    return list(BirthNamesGeneratorFactory.make().generate())