superset2/superset/utils/mock_data.py

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# to you under the Apache License, Version 2.0 (the
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#
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import decimal
import logging
import os
import random
import string
import sys
from collections.abc import Iterator
from datetime import date, datetime, time, timedelta
from typing import Any, Callable, cast, Optional, TypedDict
from uuid import uuid4

import sqlalchemy.sql.sqltypes
import sqlalchemy_utils
from flask_appbuilder import Model
from sqlalchemy import Column, inspect, MetaData, Table as DBTable
from sqlalchemy.dialects import postgresql
from sqlalchemy.sql import func
from sqlalchemy.sql.visitors import VisitableType

from superset import db
from superset.sql.parse import Table
from superset.utils import json

logger = logging.getLogger(__name__)


class ColumnInfo(TypedDict):
    name: str
    type: VisitableType
    nullable: bool
    default: Optional[Any]
    autoincrement: str
    primary_key: int


example_column = {
    "name": "id",
    "type": sqlalchemy.sql.sqltypes.INTEGER(),
    "nullable": False,
    "default": None,
    "autoincrement": "auto",
    "primary_key": 1,
}


MINIMUM_DATE = date(1900, 1, 1)
MAXIMUM_DATE = date.today()
days_range = (MAXIMUM_DATE - MINIMUM_DATE).days


def get_type_generator(  # pylint: disable=too-many-return-statements,too-many-branches  # noqa: C901
    sqltype: sqlalchemy.sql.sqltypes,
) -> Callable[[], Any]:
    if isinstance(sqltype, sqlalchemy.dialects.mysql.types.TINYINT):
        return lambda: random.choice([0, 1])  # noqa: S311

    if isinstance(
        sqltype, (sqlalchemy.sql.sqltypes.INTEGER, sqlalchemy.sql.sqltypes.Integer)
    ):
        return lambda: random.randrange(2147483647)  # noqa: S311

    if isinstance(sqltype, sqlalchemy.sql.sqltypes.BIGINT):
        return lambda: random.randrange(sys.maxsize)  # noqa: S311

    if isinstance(
        sqltype, (sqlalchemy.sql.sqltypes.VARCHAR, sqlalchemy.sql.sqltypes.String)
    ):
        length = random.randrange(sqltype.length or 255)  # noqa: S311
        length = max(8, length)  # for unique values
        length = min(100, length)  # for FAB perms
        return lambda: "".join(random.choices(string.ascii_letters, k=length))  # noqa: S311

    if isinstance(
        sqltype, (sqlalchemy.sql.sqltypes.TEXT, sqlalchemy.sql.sqltypes.Text)
    ):
        length = random.randrange(65535)  # noqa: S311
        # "practicality beats purity"
        length = max(length, 2048)
        return lambda: "".join(random.choices(string.ascii_letters, k=length))  # noqa: S311

    if isinstance(
        sqltype, (sqlalchemy.sql.sqltypes.BOOLEAN, sqlalchemy.sql.sqltypes.Boolean)
    ):
        return lambda: random.choice([True, False])  # noqa: S311

    if isinstance(
        sqltype, (sqlalchemy.sql.sqltypes.FLOAT, sqlalchemy.sql.sqltypes.REAL)
    ):
        return lambda: random.uniform(-sys.maxsize, sys.maxsize)  # noqa: S311

    if isinstance(sqltype, sqlalchemy.sql.sqltypes.DATE):
        return lambda: MINIMUM_DATE + timedelta(days=random.randrange(days_range))  # noqa: S311

    if isinstance(sqltype, sqlalchemy.sql.sqltypes.TIME):
        return lambda: time(
            random.randrange(24),  # noqa: S311
            random.randrange(60),  # noqa: S311
            random.randrange(60),  # noqa: S311
        )

    if isinstance(
        sqltype,
        (
            sqlalchemy.sql.sqltypes.TIMESTAMP,
            sqlalchemy.sql.sqltypes.DATETIME,
            sqlalchemy.sql.sqltypes.DateTime,
        ),
    ):
        return lambda: datetime.fromordinal(MINIMUM_DATE.toordinal()) + timedelta(
            seconds=random.randrange(days_range * 86400)  # noqa: S311
        )

    if isinstance(sqltype, sqlalchemy.sql.sqltypes.Numeric):
        # since decimal is used in some models to store time, return a value that
        # is a reasonable timestamp
        return lambda: decimal.Decimal(datetime.now().timestamp() * 1000)

    if isinstance(sqltype, sqlalchemy.sql.sqltypes.JSON):
        return lambda: {
            "".join(random.choices(string.ascii_letters, k=8)): random.randrange(65535)  # noqa: S311
            for _ in range(10)
        }

    if isinstance(
        sqltype,
        (
            sqlalchemy.sql.sqltypes.BINARY,
            sqlalchemy_utils.types.encrypted.encrypted_type.EncryptedType,
        ),
    ):
        length = random.randrange(sqltype.length or 255)  # noqa: S311
        return lambda: os.urandom(length)

    if isinstance(sqltype, sqlalchemy_utils.types.uuid.UUIDType):
        return uuid4

    if isinstance(sqltype, postgresql.base.UUID):
        return lambda: str(uuid4())

    if isinstance(sqltype, sqlalchemy.sql.sqltypes.BLOB):
        length = random.randrange(sqltype.length or 255)  # noqa: S311
        return lambda: os.urandom(length)

    logger.warning(
        "Unknown type %s. Please add it to `get_type_generator`.", type(sqltype)
    )
    return lambda: b"UNKNOWN TYPE"


def add_data(
    columns: Optional[list[ColumnInfo]],
    num_rows: int,
    table_name: str,
    append: bool = True,
) -> None:
    """
    Generate synthetic data for testing migrations and features.

    If the table already exists `columns` can be `None`.

    :param Optional[List[ColumnInfo]] columns: list of column names and types to create
    :param int num_rows: how many rows to generate and insert
    :param str table_name: name of table, will be created if it doesn't exist
    :param bool append: if the table already exists, append data or replace?
    """
    # pylint: disable=import-outside-toplevel
    from superset.utils.database import get_example_database  # noqa: PLC0415

    database = get_example_database()
    table_exists = database.has_table(Table(table_name))

    with database.get_sqla_engine() as engine:
        if columns is None:
            if not table_exists:
                raise Exception(  # pylint: disable=broad-exception-raised
                    f"The table {table_name} does not exist. To create it you need to "
                    "pass a list of column names and types."
                )

            inspector = inspect(engine)
            columns = inspector.get_columns(table_name)

        # create table if needed
        column_objects = get_column_objects(columns)
        metadata = MetaData()
        table = DBTable(table_name, metadata, *column_objects)
        metadata.create_all(engine)

        if not append:
            engine.execute(table.delete())

        data = generate_data(columns, num_rows)
        engine.execute(table.insert(), data)


def get_column_objects(columns: list[ColumnInfo]) -> list[Column]:
    out = []
    for column in columns:
        kwargs = cast(dict[str, Any], column.copy())
        kwargs["type_"] = kwargs.pop("type")
        out.append(Column(**kwargs))
    return out


def generate_data(columns: list[ColumnInfo], num_rows: int) -> list[dict[str, Any]]:
    keys = [column["name"] for column in columns]
    return [
        dict(zip(keys, row, strict=False))
        for row in zip(
            *[generate_column_data(column, num_rows) for column in columns],
            strict=False,
        )
    ]


def generate_column_data(column: ColumnInfo, num_rows: int) -> list[Any]:
    gen = get_type_generator(column["type"])
    return [gen() for _ in range(num_rows)]


def add_sample_rows(model: type[Model], count: int) -> Iterator[Model]:
    """
    Add entities of a given model.

    :param Model model: a Superset/FAB model
    :param int count: how many entities to generate and insert
    """
    inspector = inspect(model)

    # select samples to copy relationship values
    relationships = inspector.relationships.items()
    samples = db.session.query(model).limit(count).all() if relationships else []

    max_primary_key: Optional[int] = None
    for i in range(count):
        sample = samples[i % len(samples)] if samples else None
        kwargs = {}
        for column in inspector.columns.values():
            # for primary keys, keep incrementing
            if column.primary_key:
                if max_primary_key is None:
                    max_primary_key = (
                        db.session.query(func.max(getattr(model, column.name))).scalar()
                        or 0
                    )
                max_primary_key += 1
                kwargs[column.name] = max_primary_key

            # if the column has a foreign key, copy the value from an existing entity
            elif column.foreign_keys:
                if sample:
                    kwargs[column.name] = getattr(sample, column.name)
                else:
                    kwargs[column.name] = get_valid_foreign_key(column)

            # should be an enum but it's not
            elif column.name == "datasource_type":
                kwargs[column.name] = "table"

            # otherwise, generate a random value based on the type
            else:
                kwargs[column.name] = generate_value(column)

        entity = model(**kwargs)
        yield entity


def get_valid_foreign_key(column: Column) -> Any:
    foreign_key = list(column.foreign_keys)[0]
    table_name, column_name = foreign_key.target_fullname.split(".", 1)
    return db.engine.execute(f"SELECT {column_name} FROM {table_name} LIMIT 1").scalar()  # noqa: S608


def generate_value(column: Column) -> Any:
    if hasattr(column.type, "enums"):
        return random.choice(column.type.enums)  # noqa: S311

    json_as_string = "json" in column.name.lower() and isinstance(
        column.type, sqlalchemy.sql.sqltypes.Text
    )
    type_ = sqlalchemy.sql.sqltypes.JSON() if json_as_string else column.type
    value = get_type_generator(type_)()
    if json_as_string:
        value = json.dumps(value)
    return value