prefect_snowflake.database

Module for querying against Snowflake databases.

SnowflakeConnector

Bases: DatabaseBlock

Block used to manage connections with Snowflake.

Upon instantiating, a connection is created and maintained for the life of the object until the close method is called.

It is recommended to use this block as a context manager, which will automatically close the engine and its connections when the context is exited.

It is also recommended that this block is loaded and consumed within a single task or flow because if the block is passed across separate tasks and flows, the state of the block's connection and cursor will be lost.

Parameters:

Name	Type	Description	Default
credentials		The credentials to authenticate with Snowflake.	required
database		The name of the default database to use.	required
warehouse		The name of the default warehouse to use.	required
schema		The name of the default schema to use; this attribute is accessible through SnowflakeConnector(...).schema_.	required
fetch_size		The number of rows to fetch at a time.	required
poll_frequency_s		The number of seconds before checking query.	required

Examples:

Load stored Snowflake connector as a context manager:

from prefect_snowflake.database import SnowflakeConnector

snowflake_connector = SnowflakeConnector.load("BLOCK_NAME")

Insert data into database and fetch results.

from prefect_snowflake.database import SnowflakeConnector

with SnowflakeConnector.load("BLOCK_NAME") as conn:
    conn.execute(
        "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
    )
    conn.execute_many(
        "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
        seq_of_parameters=[
            {"name": "Ford", "address": "Highway 42"},
            {"name": "Unknown", "address": "Space"},
            {"name": "Me", "address": "Myway 88"},
        ],
    )
    results = conn.fetch_all(
        "SELECT * FROM customers WHERE address = %(address)s",
        parameters={"address": "Space"}
    )
    print(results)

Source code in prefect_snowflake/database.py

class SnowflakeConnector(DatabaseBlock):
    """
    Block used to manage connections with Snowflake.

    Upon instantiating, a connection is created and maintained for the life of
    the object until the close method is called.

    It is recommended to use this block as a context manager, which will automatically
    close the engine and its connections when the context is exited.

    It is also recommended that this block is loaded and consumed within a single task
    or flow because if the block is passed across separate tasks and flows,
    the state of the block's connection and cursor will be lost.

    Args:
        credentials: The credentials to authenticate with Snowflake.
        database: The name of the default database to use.
        warehouse: The name of the default warehouse to use.
        schema: The name of the default schema to use;
            this attribute is accessible through `SnowflakeConnector(...).schema_`.
        fetch_size: The number of rows to fetch at a time.
        poll_frequency_s: The number of seconds before checking query.

    Examples:
        Load stored Snowflake connector as a context manager:
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        snowflake_connector = SnowflakeConnector.load("BLOCK_NAME")
        ```

        Insert data into database and fetch results.
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        with SnowflakeConnector.load("BLOCK_NAME") as conn:
            conn.execute(
                "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
            )
            conn.execute_many(
                "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                seq_of_parameters=[
                    {"name": "Ford", "address": "Highway 42"},
                    {"name": "Unknown", "address": "Space"},
                    {"name": "Me", "address": "Myway 88"},
                ],
            )
            results = conn.fetch_all(
                "SELECT * FROM customers WHERE address = %(address)s",
                parameters={"address": "Space"}
            )
            print(results)
        ```
    """  # noqa

    _block_type_name = "Snowflake Connector"
    _logo_url = "https://cdn.sanity.io/images/3ugk85nk/production/bd359de0b4be76c2254bd329fe3a267a1a3879c2-250x250.png"  # noqa
    _documentation_url = "https://prefecthq.github.io/prefect-snowflake/database/#prefect_snowflake.database.SnowflakeConnector"  # noqa
    _description = "Perform data operations against a Snowflake database."

    credentials: SnowflakeCredentials = Field(
        default=..., description="The credentials to authenticate with Snowflake."
    )
    database: str = Field(
        default=..., description="The name of the default database to use."
    )
    warehouse: str = Field(
        default=..., description="The name of the default warehouse to use."
    )
    schema_: str = Field(
        default=...,
        alias="schema",
        description="The name of the default schema to use.",
    )
    fetch_size: int = Field(
        default=1, description="The default number of rows to fetch at a time."
    )
    poll_frequency_s: int = Field(
        default=1,
        title="Poll Frequency [seconds]",
        description=(
            "The number of seconds between checking query "
            "status for long running queries."
        ),
    )

    _connection: Optional[SnowflakeConnection] = None
    _unique_cursors: Dict[str, SnowflakeCursor] = None

    def get_connection(self, **connect_kwargs: Any) -> SnowflakeConnection:
        """
        Returns an authenticated connection that can be
        used to query from Snowflake databases.

        Args:
            **connect_kwargs: Additional arguments to pass to
                `snowflake.connector.connect`.

        Returns:
            The authenticated SnowflakeConnection.

        Examples:
            ```python
            from prefect_snowflake.credentials import SnowflakeCredentials
            from prefect_snowflake.database import SnowflakeConnector

            snowflake_credentials = SnowflakeCredentials(
                account="account",
                user="user",
                password="password",
            )
            snowflake_connector = SnowflakeConnector(
                database="database",
                warehouse="warehouse",
                schema="schema",
                credentials=snowflake_credentials
            )
            with snowflake_connector.get_connection() as connection:
                ...
            ```
        """
        if self._connection is not None:
            return self._connection

        connect_params = {
            "database": self.database,
            "warehouse": self.warehouse,
            "schema": self.schema_,
        }
        connection = self.credentials.get_client(**connect_kwargs, **connect_params)
        self._connection = connection
        self.logger.info("Started a new connection to Snowflake.")
        return connection

    def _start_connection(self):
        """
        Starts Snowflake database connection.
        """
        self.get_connection()
        if self._unique_cursors is None:
            self._unique_cursors = {}

    def _get_cursor(
        self,
        inputs: Dict[str, Any],
        cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    ) -> Tuple[bool, SnowflakeCursor]:
        """
        Get a Snowflake cursor.

        Args:
            inputs: The inputs to generate a unique hash, used to decide
                whether a new cursor should be used.
            cursor_type: The class of the cursor to use when creating a
                Snowflake cursor.

        Returns:
            Whether a cursor is new and a Snowflake cursor.
        """
        self._start_connection()

        input_hash = hash_objects(inputs)
        if input_hash is None:
            raise RuntimeError(
                f"We were not able to hash your inputs, {inputs!r}, "
                "which resulted in an unexpected data return; "
                "please open an issue with a reproducible example."
            )
        if input_hash not in self._unique_cursors.keys():
            new_cursor = self._connection.cursor(cursor_type)
            self._unique_cursors[input_hash] = new_cursor
            return True, new_cursor
        else:
            existing_cursor = self._unique_cursors[input_hash]
            return False, existing_cursor

    async def _execute_async(self, cursor: SnowflakeCursor, inputs: Dict[str, Any]):
        """Helper method to execute operations asynchronously."""
        response = await run_sync_in_worker_thread(cursor.execute_async, **inputs)
        self.logger.info(
            f"Executing the operation, {inputs['command']!r}, asynchronously; "
            f"polling for the result every {self.poll_frequency_s} seconds."
        )

        query_id = response["queryId"]
        while self._connection.is_still_running(
            await run_sync_in_worker_thread(
                self._connection.get_query_status_throw_if_error, query_id
            )
        ):
            await asyncio.sleep(self.poll_frequency_s)
        await run_sync_in_worker_thread(cursor.get_results_from_sfqid, query_id)

    def reset_cursors(self) -> None:
        """
        Tries to close all opened cursors.

        Examples:
            Reset the cursors to refresh cursor position.
            ```python
            from prefect_snowflake.database import SnowflakeConnector

            with SnowflakeConnector.load("BLOCK_NAME") as conn:
                conn.execute(
                    "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
                )
                conn.execute_many(
                    "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                    seq_of_parameters=[
                        {"name": "Ford", "address": "Highway 42"},
                        {"name": "Unknown", "address": "Space"},
                        {"name": "Me", "address": "Myway 88"},
                    ],
                )
                print(conn.fetch_one("SELECT * FROM customers"))  # Ford
                conn.reset_cursors()
                print(conn.fetch_one("SELECT * FROM customers"))  # should be Ford again
            ```
        """  # noqa
        if not self._unique_cursors:
            self.logger.info("There were no cursors to reset.")
            return

        input_hashes = tuple(self._unique_cursors.keys())
        for input_hash in input_hashes:
            cursor = self._unique_cursors.pop(input_hash)
            try:
                cursor.close()
            except Exception as exc:
                self.logger.warning(
                    f"Failed to close cursor for input hash {input_hash!r}: {exc}"
                )
        self.logger.info("Successfully reset the cursors.")

    def fetch_one(
        self,
        operation: str,
        parameters: Optional[Dict[str, Any]] = None,
        cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
        **execute_kwargs: Any,
    ) -> Tuple[Any]:
        """
        Fetch a single result from the database.
        Repeated calls using the same inputs to *any* of the fetch methods of this
        block will skip executing the operation again, and instead,
        return the next set of results from the previous execution,
        until the reset_cursors method is called.

        Args:
            operation: The SQL query or other operation to be executed.
            parameters: The parameters for the operation.
            cursor_type: The class of the cursor to use when creating a Snowflake cursor.
            **execute_kwargs: Additional options to pass to `cursor.execute_async`.

        Returns:
            A tuple containing the data returned by the database,
                where each row is a tuple and each column is a value in the tuple.

        Examples:
            Fetch one row from the database where address is Space.
            ```python
            from prefect_snowflake.database import SnowflakeConnector

            with SnowflakeConnector.load("BLOCK_NAME") as conn:
                conn.execute(
                    "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
                )
                conn.execute_many(
                    "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                    seq_of_parameters=[
                        {"name": "Ford", "address": "Highway 42"},
                        {"name": "Unknown", "address": "Space"},
                        {"name": "Me", "address": "Myway 88"},
                    ],
                )
                result = conn.fetch_one(
                    "SELECT * FROM customers WHERE address = %(address)s",
                    parameters={"address": "Space"}
                )
                print(result)
            ```
        """  # noqa
        inputs = dict(
            command=operation,
            params=parameters,
            **execute_kwargs,
        )
        new, cursor = self._get_cursor(inputs, cursor_type=cursor_type)
        if new:
            self.execute(
                operation, parameters, cursor_type=cursor_type, **execute_kwargs
            )
        self.logger.debug("Preparing to fetch a row.")
        return cursor.fetchone()

    async def fetch_one_async(
        self,
        operation: str,
        parameters: Optional[Dict[str, Any]] = None,
        cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
        **execute_kwargs: Any,
    ) -> Tuple[Any]:
        """
        Fetch a single result from the database asynchronously.
        Repeated calls using the same inputs to *any* of the fetch methods of this
        block will skip executing the operation again, and instead,
        return the next set of results from the previous execution,
        until the reset_cursors method is called.

        Args:
            operation: The SQL query or other operation to be executed.
            parameters: The parameters for the operation.
            cursor_type: The class of the cursor to use when creating a Snowflake cursor.
            **execute_kwargs: Additional options to pass to `cursor.execute_async`.

        Returns:
            A tuple containing the data returned by the database,
                where each row is a tuple and each column is a value in the tuple.

        Examples:
            Fetch one row from the database where address is Space.
            ```python
            from prefect_snowflake.database import SnowflakeConnector

            with SnowflakeConnector.load("BLOCK_NAME") as conn:
                conn.execute(
                    "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
                )
                conn.execute_many(
                    "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                    seq_of_parameters=[
                        {"name": "Ford", "address": "Highway 42"},
                        {"name": "Unknown", "address": "Space"},
                        {"name": "Me", "address": "Myway 88"},
                    ],
                )
                result = await conn.fetch_one_async(
                    "SELECT * FROM customers WHERE address = %(address)s",
                    parameters={"address": "Space"}
                )
                print(result)
            ```
        """  # noqa
        inputs = dict(
            command=operation,
            params=parameters,
            **execute_kwargs,
        )
        new, cursor = self._get_cursor(inputs, cursor_type=cursor_type)
        if new:
            await self._execute_async(cursor, inputs)
        self.logger.debug("Preparing to fetch a row.")
        result = await run_sync_in_worker_thread(cursor.fetchone)
        return result

    def fetch_many(
        self,
        operation: str,
        parameters: Optional[Sequence[Dict[str, Any]]] = None,
        size: Optional[int] = None,
        cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
        **execute_kwargs: Any,
    ) -> List[Tuple[Any]]:
        """
        Fetch a limited number of results from the database.
        Repeated calls using the same inputs to *any* of the fetch methods of this
        block will skip executing the operation again, and instead,
        return the next set of results from the previous execution,
        until the reset_cursors method is called.

        Args:
            operation: The SQL query or other operation to be executed.
            parameters: The parameters for the operation.
            size: The number of results to return; if None or 0, uses the value of
                `fetch_size` configured on the block.
            cursor_type: The class of the cursor to use when creating a Snowflake cursor.
            **execute_kwargs: Additional options to pass to `cursor.execute_async`.

        Returns:
            A list of tuples containing the data returned by the database,
                where each row is a tuple and each column is a value in the tuple.

        Examples:
            Repeatedly fetch two rows from the database where address is Highway 42.
            ```python
            from prefect_snowflake.database import SnowflakeConnector

            with SnowflakeConnector.load("BLOCK_NAME") as conn:
                conn.execute(
                    "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
                )
                conn.execute_many(
                    "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                    seq_of_parameters=[
                        {"name": "Marvin", "address": "Highway 42"},
                        {"name": "Ford", "address": "Highway 42"},
                        {"name": "Unknown", "address": "Highway 42"},
                        {"name": "Me", "address": "Highway 42"},
                    ],
                )
                result = conn.fetch_many(
                    "SELECT * FROM customers WHERE address = %(address)s",
                    parameters={"address": "Highway 42"},
                    size=2
                )
                print(result)  # Marvin, Ford
                result = conn.fetch_many(
                    "SELECT * FROM customers WHERE address = %(address)s",
                    parameters={"address": "Highway 42"},
                    size=2
                )
                print(result)  # Unknown, Me
            ```
        """  # noqa
        inputs = dict(
            command=operation,
            params=parameters,
            **execute_kwargs,
        )
        new, cursor = self._get_cursor(inputs, cursor_type)
        if new:
            self.execute(cursor, inputs)
        size = size or self.fetch_size
        self.logger.debug(f"Preparing to fetch {size} rows.")
        return cursor.fetchmany(size=size)

    async def fetch_many_async(
        self,
        operation: str,
        parameters: Optional[Sequence[Dict[str, Any]]] = None,
        size: Optional[int] = None,
        cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
        **execute_kwargs: Any,
    ) -> List[Tuple[Any]]:
        """
        Fetch a limited number of results from the database asynchronously.
        Repeated calls using the same inputs to *any* of the fetch methods of this
        block will skip executing the operation again, and instead,
        return the next set of results from the previous execution,
        until the reset_cursors method is called.

        Args:
            operation: The SQL query or other operation to be executed.
            parameters: The parameters for the operation.
            size: The number of results to return; if None or 0, uses the value of
                `fetch_size` configured on the block.
            cursor_type: The class of the cursor to use when creating a Snowflake cursor.
            **execute_kwargs: Additional options to pass to `cursor.execute_async`.

        Returns:
            A list of tuples containing the data returned by the database,
                where each row is a tuple and each column is a value in the tuple.

        Examples:
            Repeatedly fetch two rows from the database where address is Highway 42.
            ```python
            from prefect_snowflake.database import SnowflakeConnector

            with SnowflakeConnector.load("BLOCK_NAME") as conn:
                conn.execute(
                    "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
                )
                conn.execute_many(
                    "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                    seq_of_parameters=[
                        {"name": "Marvin", "address": "Highway 42"},
                        {"name": "Ford", "address": "Highway 42"},
                        {"name": "Unknown", "address": "Highway 42"},
                        {"name": "Me", "address": "Highway 42"},
                    ],
                )
                result = conn.fetch_many(
                    "SELECT * FROM customers WHERE address = %(address)s",
                    parameters={"address": "Highway 42"},
                    size=2
                )
                print(result)  # Marvin, Ford
                result = conn.fetch_many(
                    "SELECT * FROM customers WHERE address = %(address)s",
                    parameters={"address": "Highway 42"},
                    size=2
                )
                print(result)  # Unknown, Me
            ```
        """  # noqa
        inputs = dict(
            command=operation,
            params=parameters,
            **execute_kwargs,
        )
        new, cursor = self._get_cursor(inputs, cursor_type)
        if new:
            await self._execute_async(cursor, inputs)
        size = size or self.fetch_size
        self.logger.debug(f"Preparing to fetch {size} rows.")
        result = await run_sync_in_worker_thread(cursor.fetchmany, size=size)
        return result

    def fetch_all(
        self,
        operation: str,
        parameters: Optional[Dict[str, Any]] = None,
        cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
        **execute_kwargs: Any,
    ) -> List[Tuple[Any]]:
        """
        Fetch all results from the database.
        Repeated calls using the same inputs to *any* of the fetch methods of this
        block will skip executing the operation again, and instead,
        return the next set of results from the previous execution,
        until the reset_cursors method is called.

        Args:
            operation: The SQL query or other operation to be executed.
            parameters: The parameters for the operation.
            cursor_type: The class of the cursor to use when creating a Snowflake cursor.
            **execute_kwargs: Additional options to pass to `cursor.execute_async`.

        Returns:
            A list of tuples containing the data returned by the database,
                where each row is a tuple and each column is a value in the tuple.

        """  # noqa
        inputs = dict(
            command=operation,
            params=parameters,
            **execute_kwargs,
        )
        new, cursor = self._get_cursor(inputs, cursor_type)
        if new:
            self.execute(
                operation, parameters, cursor_type=cursor_type, **execute_kwargs
            )
        self.logger.debug("Preparing to fetch all rows.")
        return cursor.fetchall()

    async def fetch_all_async(
        self,
        operation: str,
        parameters: Optional[Dict[str, Any]] = None,
        cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
        **execute_kwargs: Any,
    ) -> List[Tuple[Any]]:
        """
        Fetch all results from the database.
        Repeated calls using the same inputs to *any* of the fetch methods of this
        block will skip executing the operation again, and instead,
        return the next set of results from the previous execution,
        until the reset_cursors method is called.

        Args:
            operation: The SQL query or other operation to be executed.
            parameters: The parameters for the operation.
            cursor_type: The class of the cursor to use when creating a Snowflake cursor.
            **execute_kwargs: Additional options to pass to `cursor.execute_async`.

        Returns:
            A list of tuples containing the data returned by the database,
                where each row is a tuple and each column is a value in the tuple.

        Examples:
            Fetch all rows from the database where address is Highway 42.
            ```python
            from prefect_snowflake.database import SnowflakeConnector

            with SnowflakeConnector.load("BLOCK_NAME") as conn:
                await conn.execute_async(
                    "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
                )
                await conn.execute_many_async(
                    "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                    seq_of_parameters=[
                        {"name": "Marvin", "address": "Highway 42"},
                        {"name": "Ford", "address": "Highway 42"},
                        {"name": "Unknown", "address": "Highway 42"},
                        {"name": "Me", "address": "Myway 88"},
                    ],
                )
                result = await conn.fetch_all_async(
                    "SELECT * FROM customers WHERE address = %(address)s",
                    parameters={"address": "Highway 42"},
                )
                print(result)  # Marvin, Ford, Unknown
            ```
        """  # noqa
        inputs = dict(
            command=operation,
            params=parameters,
            **execute_kwargs,
        )
        new, cursor = self._get_cursor(inputs, cursor_type)
        if new:
            await self._execute_async(cursor, inputs)
        self.logger.debug("Preparing to fetch all rows.")
        result = await run_sync_in_worker_thread(cursor.fetchall)
        return result

    def execute(
        self,
        operation: str,
        parameters: Optional[Dict[str, Any]] = None,
        cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
        **execute_kwargs: Any,
    ) -> None:
        """
        Executes an operation on the database. This method is intended to be used
        for operations that do not return data, such as INSERT, UPDATE, or DELETE.
        Unlike the fetch methods, this method will always execute the operation
        upon calling.

        Args:
            operation: The SQL query or other operation to be executed.
            parameters: The parameters for the operation.
            cursor_type: The class of the cursor to use when creating a Snowflake cursor.
            **execute_kwargs: Additional options to pass to `cursor.execute_async`.

        Examples:
            Create table named customers with two columns, name and address.
            ```python
            from prefect_snowflake.database import SnowflakeConnector

            with SnowflakeConnector.load("BLOCK_NAME") as conn:
                conn.execute(
                    "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
                )
            ```
        """  # noqa
        self._start_connection()

        inputs = dict(
            command=operation,
            params=parameters,
            **execute_kwargs,
        )
        with self._connection.cursor(cursor_type) as cursor:
            run_coro_as_sync(self._execute_async(cursor, inputs))
        self.logger.info(f"Executed the operation, {operation!r}.")

    async def execute_async(
        self,
        operation: str,
        parameters: Optional[Dict[str, Any]] = None,
        cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
        **execute_kwargs: Any,
    ) -> None:
        """
        Executes an operation on the database. This method is intended to be used
        for operations that do not return data, such as INSERT, UPDATE, or DELETE.
        Unlike the fetch methods, this method will always execute the operation
        upon calling.

        Args:
            operation: The SQL query or other operation to be executed.
            parameters: The parameters for the operation.
            cursor_type: The class of the cursor to use when creating a Snowflake cursor.
            **execute_kwargs: Additional options to pass to `cursor.execute_async`.

        Examples:
            Create table named customers with two columns, name and address.
            ```python
            from prefect_snowflake.database import SnowflakeConnector

            with SnowflakeConnector.load("BLOCK_NAME") as conn:
                conn.execute(
                    "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
                )
            ```
        """  # noqa
        self._start_connection()

        inputs = dict(
            command=operation,
            params=parameters,
            **execute_kwargs,
        )
        with self._connection.cursor(cursor_type) as cursor:
            await run_sync_in_worker_thread(cursor.execute, **inputs)
        self.logger.info(f"Executed the operation, {operation!r}.")

    def execute_many(
        self,
        operation: str,
        seq_of_parameters: List[Dict[str, Any]],
    ) -> None:
        """
        Executes many operations on the database. This method is intended to be used
        for operations that do not return data, such as INSERT, UPDATE, or DELETE.
        Unlike the fetch methods, this method will always execute the operations
        upon calling.

        Args:
            operation: The SQL query or other operation to be executed.
            seq_of_parameters: The sequence of parameters for the operation.

        Examples:
            Create table and insert three rows into it.
            ```python
            from prefect_snowflake.database import SnowflakeConnector

            with SnowflakeConnector.load("BLOCK_NAME") as conn:
                conn.execute(
                    "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
                )
                conn.execute_many(
                    "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                    seq_of_parameters=[
                        {"name": "Marvin", "address": "Highway 42"},
                        {"name": "Ford", "address": "Highway 42"},
                        {"name": "Unknown", "address": "Space"},
                    ],
                )
            ```
        """  # noqa
        self._start_connection()

        inputs = dict(
            command=operation,
            seqparams=seq_of_parameters,
        )
        with self._connection.cursor() as cursor:
            cursor.executemany(**inputs)
        self.logger.info(
            f"Executed {len(seq_of_parameters)} operations off {operation!r}."
        )

    async def execute_many_async(
        self,
        operation: str,
        seq_of_parameters: List[Dict[str, Any]],
    ) -> None:
        """
        Executes many operations on the database. This method is intended to be used
        for operations that do not return data, such as INSERT, UPDATE, or DELETE.
        Unlike the fetch methods, this method will always execute the operations
        upon calling.

        Args:
            operation: The SQL query or other operation to be executed.
            seq_of_parameters: The sequence of parameters for the operation.

        Examples:
            Create table and insert three rows into it.
            ```python
            from prefect_snowflake.database import SnowflakeConnector

            with SnowflakeConnector.load("BLOCK_NAME") as conn:
                conn.execute(
                    "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
                )
                conn.execute_many(
                    "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                    seq_of_parameters=[
                        {"name": "Marvin", "address": "Highway 42"},
                        {"name": "Ford", "address": "Highway 42"},
                        {"name": "Unknown", "address": "Space"},
                    ],
                )
            ```
        """  # noqa
        self._start_connection()

        inputs = dict(
            command=operation,
            seqparams=seq_of_parameters,
        )
        with self._connection.cursor() as cursor:
            await run_sync_in_worker_thread(cursor.executemany, **inputs)
        self.logger.info(
            f"Executed {len(seq_of_parameters)} operations off {operation!r}."
        )

    def close(self):
        """
        Closes connection and its cursors.
        """
        try:
            self.reset_cursors()
        finally:
            if self._connection is None:
                self.logger.info("There was no connection open to be closed.")
                return
            self._connection.close()
            self._connection = None
            self.logger.info("Successfully closed the Snowflake connection.")

    def __enter__(self):
        """
        Start a connection upon entry.
        """
        return self

    def __exit__(self, *args):
        """
        Closes connection and its cursors upon exit.
        """
        self.close()

    def __getstate__(self):
        """Allows block to be pickled and dumped."""
        data = self.__dict__.copy()
        data.update({k: None for k in {"_connection", "_unique_cursors"}})
        return data

    def __setstate__(self, data: dict):
        """Reset connection and cursors upon loading."""
        self.__dict__.update(data)
        self._start_connection()

__enter__()

Start a connection upon entry.

Source code in prefect_snowflake/database.py

def __enter__(self):
    """
    Start a connection upon entry.
    """
    return self

__exit__(*args)

Closes connection and its cursors upon exit.

Source code in prefect_snowflake/database.py

def __exit__(self, *args):
    """
    Closes connection and its cursors upon exit.
    """
    self.close()

__getstate__()

Allows block to be pickled and dumped.

Source code in prefect_snowflake/database.py

def __getstate__(self):
    """Allows block to be pickled and dumped."""
    data = self.__dict__.copy()
    data.update({k: None for k in {"_connection", "_unique_cursors"}})
    return data

__setstate__(data)

Reset connection and cursors upon loading.

Source code in prefect_snowflake/database.py

def __setstate__(self, data: dict):
    """Reset connection and cursors upon loading."""
    self.__dict__.update(data)
    self._start_connection()

close()

Closes connection and its cursors.

Source code in prefect_snowflake/database.py

def close(self):
    """
    Closes connection and its cursors.
    """
    try:
        self.reset_cursors()
    finally:
        if self._connection is None:
            self.logger.info("There was no connection open to be closed.")
            return
        self._connection.close()
        self._connection = None
        self.logger.info("Successfully closed the Snowflake connection.")

execute(operation, parameters=None, cursor_type=SnowflakeCursor, **execute_kwargs)

Executes an operation on the database. This method is intended to be used for operations that do not return data, such as INSERT, UPDATE, or DELETE. Unlike the fetch methods, this method will always execute the operation upon calling.

Parameters:

Name	Type	Description	Default
operation	str	The SQL query or other operation to be executed.	required
parameters	Optional[Dict[str, Any]]	The parameters for the operation.	None
cursor_type	Type[SnowflakeCursor]	The class of the cursor to use when creating a Snowflake cursor.	SnowflakeCursor
**execute_kwargs	Any	Additional options to pass to cursor.execute_async.	{}

Examples:

Create table named customers with two columns, name and address.

from prefect_snowflake.database import SnowflakeConnector

with SnowflakeConnector.load("BLOCK_NAME") as conn:
    conn.execute(
        "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
    )

Source code in prefect_snowflake/database.py

def execute(
    self,
    operation: str,
    parameters: Optional[Dict[str, Any]] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    **execute_kwargs: Any,
) -> None:
    """
    Executes an operation on the database. This method is intended to be used
    for operations that do not return data, such as INSERT, UPDATE, or DELETE.
    Unlike the fetch methods, this method will always execute the operation
    upon calling.

    Args:
        operation: The SQL query or other operation to be executed.
        parameters: The parameters for the operation.
        cursor_type: The class of the cursor to use when creating a Snowflake cursor.
        **execute_kwargs: Additional options to pass to `cursor.execute_async`.

    Examples:
        Create table named customers with two columns, name and address.
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        with SnowflakeConnector.load("BLOCK_NAME") as conn:
            conn.execute(
                "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
            )
        ```
    """  # noqa
    self._start_connection()

    inputs = dict(
        command=operation,
        params=parameters,
        **execute_kwargs,
    )
    with self._connection.cursor(cursor_type) as cursor:
        run_coro_as_sync(self._execute_async(cursor, inputs))
    self.logger.info(f"Executed the operation, {operation!r}.")

execute_async(operation, parameters=None, cursor_type=SnowflakeCursor, **execute_kwargs) async

Executes an operation on the database. This method is intended to be used for operations that do not return data, such as INSERT, UPDATE, or DELETE. Unlike the fetch methods, this method will always execute the operation upon calling.

Parameters:

Name	Type	Description	Default
operation	str	The SQL query or other operation to be executed.	required
parameters	Optional[Dict[str, Any]]	The parameters for the operation.	None
cursor_type	Type[SnowflakeCursor]	The class of the cursor to use when creating a Snowflake cursor.	SnowflakeCursor
**execute_kwargs	Any	Additional options to pass to cursor.execute_async.	{}

Examples:

Create table named customers with two columns, name and address.

from prefect_snowflake.database import SnowflakeConnector

with SnowflakeConnector.load("BLOCK_NAME") as conn:
    conn.execute(
        "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
    )

Source code in prefect_snowflake/database.py

async def execute_async(
    self,
    operation: str,
    parameters: Optional[Dict[str, Any]] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    **execute_kwargs: Any,
) -> None:
    """
    Executes an operation on the database. This method is intended to be used
    for operations that do not return data, such as INSERT, UPDATE, or DELETE.
    Unlike the fetch methods, this method will always execute the operation
    upon calling.

    Args:
        operation: The SQL query or other operation to be executed.
        parameters: The parameters for the operation.
        cursor_type: The class of the cursor to use when creating a Snowflake cursor.
        **execute_kwargs: Additional options to pass to `cursor.execute_async`.

    Examples:
        Create table named customers with two columns, name and address.
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        with SnowflakeConnector.load("BLOCK_NAME") as conn:
            conn.execute(
                "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
            )
        ```
    """  # noqa
    self._start_connection()

    inputs = dict(
        command=operation,
        params=parameters,
        **execute_kwargs,
    )
    with self._connection.cursor(cursor_type) as cursor:
        await run_sync_in_worker_thread(cursor.execute, **inputs)
    self.logger.info(f"Executed the operation, {operation!r}.")

execute_many(operation, seq_of_parameters)

Executes many operations on the database. This method is intended to be used for operations that do not return data, such as INSERT, UPDATE, or DELETE. Unlike the fetch methods, this method will always execute the operations upon calling.

Parameters:

Name	Type	Description	Default
operation	str	The SQL query or other operation to be executed.	required
seq_of_parameters	List[Dict[str, Any]]	The sequence of parameters for the operation.	required

Examples:

Create table and insert three rows into it.

from prefect_snowflake.database import SnowflakeConnector

with SnowflakeConnector.load("BLOCK_NAME") as conn:
    conn.execute(
        "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
    )
    conn.execute_many(
        "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
        seq_of_parameters=[
            {"name": "Marvin", "address": "Highway 42"},
            {"name": "Ford", "address": "Highway 42"},
            {"name": "Unknown", "address": "Space"},
        ],
    )

Source code in prefect_snowflake/database.py

def execute_many(
    self,
    operation: str,
    seq_of_parameters: List[Dict[str, Any]],
) -> None:
    """
    Executes many operations on the database. This method is intended to be used
    for operations that do not return data, such as INSERT, UPDATE, or DELETE.
    Unlike the fetch methods, this method will always execute the operations
    upon calling.

    Args:
        operation: The SQL query or other operation to be executed.
        seq_of_parameters: The sequence of parameters for the operation.

    Examples:
        Create table and insert three rows into it.
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        with SnowflakeConnector.load("BLOCK_NAME") as conn:
            conn.execute(
                "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
            )
            conn.execute_many(
                "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                seq_of_parameters=[
                    {"name": "Marvin", "address": "Highway 42"},
                    {"name": "Ford", "address": "Highway 42"},
                    {"name": "Unknown", "address": "Space"},
                ],
            )
        ```
    """  # noqa
    self._start_connection()

    inputs = dict(
        command=operation,
        seqparams=seq_of_parameters,
    )
    with self._connection.cursor() as cursor:
        cursor.executemany(**inputs)
    self.logger.info(
        f"Executed {len(seq_of_parameters)} operations off {operation!r}."
    )

execute_many_async(operation, seq_of_parameters) async

Executes many operations on the database. This method is intended to be used for operations that do not return data, such as INSERT, UPDATE, or DELETE. Unlike the fetch methods, this method will always execute the operations upon calling.

Parameters:

Name	Type	Description	Default
operation	str	The SQL query or other operation to be executed.	required
seq_of_parameters	List[Dict[str, Any]]	The sequence of parameters for the operation.	required

Examples:

Create table and insert three rows into it.

from prefect_snowflake.database import SnowflakeConnector

with SnowflakeConnector.load("BLOCK_NAME") as conn:
    conn.execute(
        "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
    )
    conn.execute_many(
        "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
        seq_of_parameters=[
            {"name": "Marvin", "address": "Highway 42"},
            {"name": "Ford", "address": "Highway 42"},
            {"name": "Unknown", "address": "Space"},
        ],
    )

Source code in prefect_snowflake/database.py

async def execute_many_async(
    self,
    operation: str,
    seq_of_parameters: List[Dict[str, Any]],
) -> None:
    """
    Executes many operations on the database. This method is intended to be used
    for operations that do not return data, such as INSERT, UPDATE, or DELETE.
    Unlike the fetch methods, this method will always execute the operations
    upon calling.

    Args:
        operation: The SQL query or other operation to be executed.
        seq_of_parameters: The sequence of parameters for the operation.

    Examples:
        Create table and insert three rows into it.
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        with SnowflakeConnector.load("BLOCK_NAME") as conn:
            conn.execute(
                "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
            )
            conn.execute_many(
                "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                seq_of_parameters=[
                    {"name": "Marvin", "address": "Highway 42"},
                    {"name": "Ford", "address": "Highway 42"},
                    {"name": "Unknown", "address": "Space"},
                ],
            )
        ```
    """  # noqa
    self._start_connection()

    inputs = dict(
        command=operation,
        seqparams=seq_of_parameters,
    )
    with self._connection.cursor() as cursor:
        await run_sync_in_worker_thread(cursor.executemany, **inputs)
    self.logger.info(
        f"Executed {len(seq_of_parameters)} operations off {operation!r}."
    )

fetch_all(operation, parameters=None, cursor_type=SnowflakeCursor, **execute_kwargs)

Fetch all results from the database. Repeated calls using the same inputs to any of the fetch methods of this block will skip executing the operation again, and instead, return the next set of results from the previous execution, until the reset_cursors method is called.

Parameters:

Name	Type	Description	Default
operation	str	The SQL query or other operation to be executed.	required
parameters	Optional[Dict[str, Any]]	The parameters for the operation.	None
cursor_type	Type[SnowflakeCursor]	The class of the cursor to use when creating a Snowflake cursor.	SnowflakeCursor
**execute_kwargs	Any	Additional options to pass to cursor.execute_async.	{}

Returns:

Type	Description
List[Tuple[Any]]	A list of tuples containing the data returned by the database, where each row is a tuple and each column is a value in the tuple.

Source code in prefect_snowflake/database.py

def fetch_all(
    self,
    operation: str,
    parameters: Optional[Dict[str, Any]] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    **execute_kwargs: Any,
) -> List[Tuple[Any]]:
    """
    Fetch all results from the database.
    Repeated calls using the same inputs to *any* of the fetch methods of this
    block will skip executing the operation again, and instead,
    return the next set of results from the previous execution,
    until the reset_cursors method is called.

    Args:
        operation: The SQL query or other operation to be executed.
        parameters: The parameters for the operation.
        cursor_type: The class of the cursor to use when creating a Snowflake cursor.
        **execute_kwargs: Additional options to pass to `cursor.execute_async`.

    Returns:
        A list of tuples containing the data returned by the database,
            where each row is a tuple and each column is a value in the tuple.

    """  # noqa
    inputs = dict(
        command=operation,
        params=parameters,
        **execute_kwargs,
    )
    new, cursor = self._get_cursor(inputs, cursor_type)
    if new:
        self.execute(
            operation, parameters, cursor_type=cursor_type, **execute_kwargs
        )
    self.logger.debug("Preparing to fetch all rows.")
    return cursor.fetchall()

fetch_all_async(operation, parameters=None, cursor_type=SnowflakeCursor, **execute_kwargs) async

Fetch all results from the database. Repeated calls using the same inputs to any of the fetch methods of this block will skip executing the operation again, and instead, return the next set of results from the previous execution, until the reset_cursors method is called.

Parameters:

Name	Type	Description	Default
operation	str	The SQL query or other operation to be executed.	required
parameters	Optional[Dict[str, Any]]	The parameters for the operation.	None
cursor_type	Type[SnowflakeCursor]	The class of the cursor to use when creating a Snowflake cursor.	SnowflakeCursor
**execute_kwargs	Any	Additional options to pass to cursor.execute_async.	{}

Returns:

Type	Description
List[Tuple[Any]]	A list of tuples containing the data returned by the database, where each row is a tuple and each column is a value in the tuple.

Examples:

Fetch all rows from the database where address is Highway 42.

from prefect_snowflake.database import SnowflakeConnector

with SnowflakeConnector.load("BLOCK_NAME") as conn:
    await conn.execute_async(
        "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
    )
    await conn.execute_many_async(
        "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
        seq_of_parameters=[
            {"name": "Marvin", "address": "Highway 42"},
            {"name": "Ford", "address": "Highway 42"},
            {"name": "Unknown", "address": "Highway 42"},
            {"name": "Me", "address": "Myway 88"},
        ],
    )
    result = await conn.fetch_all_async(
        "SELECT * FROM customers WHERE address = %(address)s",
        parameters={"address": "Highway 42"},
    )
    print(result)  # Marvin, Ford, Unknown

Source code in prefect_snowflake/database.py

async def fetch_all_async(
    self,
    operation: str,
    parameters: Optional[Dict[str, Any]] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    **execute_kwargs: Any,
) -> List[Tuple[Any]]:
    """
    Fetch all results from the database.
    Repeated calls using the same inputs to *any* of the fetch methods of this
    block will skip executing the operation again, and instead,
    return the next set of results from the previous execution,
    until the reset_cursors method is called.

    Args:
        operation: The SQL query or other operation to be executed.
        parameters: The parameters for the operation.
        cursor_type: The class of the cursor to use when creating a Snowflake cursor.
        **execute_kwargs: Additional options to pass to `cursor.execute_async`.

    Returns:
        A list of tuples containing the data returned by the database,
            where each row is a tuple and each column is a value in the tuple.

    Examples:
        Fetch all rows from the database where address is Highway 42.
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        with SnowflakeConnector.load("BLOCK_NAME") as conn:
            await conn.execute_async(
                "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
            )
            await conn.execute_many_async(
                "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                seq_of_parameters=[
                    {"name": "Marvin", "address": "Highway 42"},
                    {"name": "Ford", "address": "Highway 42"},
                    {"name": "Unknown", "address": "Highway 42"},
                    {"name": "Me", "address": "Myway 88"},
                ],
            )
            result = await conn.fetch_all_async(
                "SELECT * FROM customers WHERE address = %(address)s",
                parameters={"address": "Highway 42"},
            )
            print(result)  # Marvin, Ford, Unknown
        ```
    """  # noqa
    inputs = dict(
        command=operation,
        params=parameters,
        **execute_kwargs,
    )
    new, cursor = self._get_cursor(inputs, cursor_type)
    if new:
        await self._execute_async(cursor, inputs)
    self.logger.debug("Preparing to fetch all rows.")
    result = await run_sync_in_worker_thread(cursor.fetchall)
    return result

fetch_many(operation, parameters=None, size=None, cursor_type=SnowflakeCursor, **execute_kwargs)

Fetch a limited number of results from the database. Repeated calls using the same inputs to any of the fetch methods of this block will skip executing the operation again, and instead, return the next set of results from the previous execution, until the reset_cursors method is called.

Parameters:

Name	Type	Description	Default
operation	str	The SQL query or other operation to be executed.	required
parameters	Optional[Sequence[Dict[str, Any]]]	The parameters for the operation.	None
size	Optional[int]	The number of results to return; if None or 0, uses the value of fetch_size configured on the block.	None
cursor_type	Type[SnowflakeCursor]	The class of the cursor to use when creating a Snowflake cursor.	SnowflakeCursor
**execute_kwargs	Any	Additional options to pass to cursor.execute_async.	{}

Returns:

Type	Description
List[Tuple[Any]]	A list of tuples containing the data returned by the database, where each row is a tuple and each column is a value in the tuple.

Examples:

Repeatedly fetch two rows from the database where address is Highway 42.

from prefect_snowflake.database import SnowflakeConnector

with SnowflakeConnector.load("BLOCK_NAME") as conn:
    conn.execute(
        "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
    )
    conn.execute_many(
        "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
        seq_of_parameters=[
            {"name": "Marvin", "address": "Highway 42"},
            {"name": "Ford", "address": "Highway 42"},
            {"name": "Unknown", "address": "Highway 42"},
            {"name": "Me", "address": "Highway 42"},
        ],
    )
    result = conn.fetch_many(
        "SELECT * FROM customers WHERE address = %(address)s",
        parameters={"address": "Highway 42"},
        size=2
    )
    print(result)  # Marvin, Ford
    result = conn.fetch_many(
        "SELECT * FROM customers WHERE address = %(address)s",
        parameters={"address": "Highway 42"},
        size=2
    )
    print(result)  # Unknown, Me

Source code in prefect_snowflake/database.py

def fetch_many(
    self,
    operation: str,
    parameters: Optional[Sequence[Dict[str, Any]]] = None,
    size: Optional[int] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    **execute_kwargs: Any,
) -> List[Tuple[Any]]:
    """
    Fetch a limited number of results from the database.
    Repeated calls using the same inputs to *any* of the fetch methods of this
    block will skip executing the operation again, and instead,
    return the next set of results from the previous execution,
    until the reset_cursors method is called.

    Args:
        operation: The SQL query or other operation to be executed.
        parameters: The parameters for the operation.
        size: The number of results to return; if None or 0, uses the value of
            `fetch_size` configured on the block.
        cursor_type: The class of the cursor to use when creating a Snowflake cursor.
        **execute_kwargs: Additional options to pass to `cursor.execute_async`.

    Returns:
        A list of tuples containing the data returned by the database,
            where each row is a tuple and each column is a value in the tuple.

    Examples:
        Repeatedly fetch two rows from the database where address is Highway 42.
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        with SnowflakeConnector.load("BLOCK_NAME") as conn:
            conn.execute(
                "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
            )
            conn.execute_many(
                "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                seq_of_parameters=[
                    {"name": "Marvin", "address": "Highway 42"},
                    {"name": "Ford", "address": "Highway 42"},
                    {"name": "Unknown", "address": "Highway 42"},
                    {"name": "Me", "address": "Highway 42"},
                ],
            )
            result = conn.fetch_many(
                "SELECT * FROM customers WHERE address = %(address)s",
                parameters={"address": "Highway 42"},
                size=2
            )
            print(result)  # Marvin, Ford
            result = conn.fetch_many(
                "SELECT * FROM customers WHERE address = %(address)s",
                parameters={"address": "Highway 42"},
                size=2
            )
            print(result)  # Unknown, Me
        ```
    """  # noqa
    inputs = dict(
        command=operation,
        params=parameters,
        **execute_kwargs,
    )
    new, cursor = self._get_cursor(inputs, cursor_type)
    if new:
        self.execute(cursor, inputs)
    size = size or self.fetch_size
    self.logger.debug(f"Preparing to fetch {size} rows.")
    return cursor.fetchmany(size=size)

fetch_many_async(operation, parameters=None, size=None, cursor_type=SnowflakeCursor, **execute_kwargs) async

Fetch a limited number of results from the database asynchronously. Repeated calls using the same inputs to any of the fetch methods of this block will skip executing the operation again, and instead, return the next set of results from the previous execution, until the reset_cursors method is called.

Parameters:

Name	Type	Description	Default
operation	str	The SQL query or other operation to be executed.	required
parameters	Optional[Sequence[Dict[str, Any]]]	The parameters for the operation.	None
size	Optional[int]	The number of results to return; if None or 0, uses the value of fetch_size configured on the block.	None
cursor_type	Type[SnowflakeCursor]	The class of the cursor to use when creating a Snowflake cursor.	SnowflakeCursor
**execute_kwargs	Any	Additional options to pass to cursor.execute_async.	{}

Returns:

Type	Description
List[Tuple[Any]]	A list of tuples containing the data returned by the database, where each row is a tuple and each column is a value in the tuple.

Examples:

Repeatedly fetch two rows from the database where address is Highway 42.

from prefect_snowflake.database import SnowflakeConnector

with SnowflakeConnector.load("BLOCK_NAME") as conn:
    conn.execute(
        "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
    )
    conn.execute_many(
        "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
        seq_of_parameters=[
            {"name": "Marvin", "address": "Highway 42"},
            {"name": "Ford", "address": "Highway 42"},
            {"name": "Unknown", "address": "Highway 42"},
            {"name": "Me", "address": "Highway 42"},
        ],
    )
    result = conn.fetch_many(
        "SELECT * FROM customers WHERE address = %(address)s",
        parameters={"address": "Highway 42"},
        size=2
    )
    print(result)  # Marvin, Ford
    result = conn.fetch_many(
        "SELECT * FROM customers WHERE address = %(address)s",
        parameters={"address": "Highway 42"},
        size=2
    )
    print(result)  # Unknown, Me

Source code in prefect_snowflake/database.py

async def fetch_many_async(
    self,
    operation: str,
    parameters: Optional[Sequence[Dict[str, Any]]] = None,
    size: Optional[int] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    **execute_kwargs: Any,
) -> List[Tuple[Any]]:
    """
    Fetch a limited number of results from the database asynchronously.
    Repeated calls using the same inputs to *any* of the fetch methods of this
    block will skip executing the operation again, and instead,
    return the next set of results from the previous execution,
    until the reset_cursors method is called.

    Args:
        operation: The SQL query or other operation to be executed.
        parameters: The parameters for the operation.
        size: The number of results to return; if None or 0, uses the value of
            `fetch_size` configured on the block.
        cursor_type: The class of the cursor to use when creating a Snowflake cursor.
        **execute_kwargs: Additional options to pass to `cursor.execute_async`.

    Returns:
        A list of tuples containing the data returned by the database,
            where each row is a tuple and each column is a value in the tuple.

    Examples:
        Repeatedly fetch two rows from the database where address is Highway 42.
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        with SnowflakeConnector.load("BLOCK_NAME") as conn:
            conn.execute(
                "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
            )
            conn.execute_many(
                "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                seq_of_parameters=[
                    {"name": "Marvin", "address": "Highway 42"},
                    {"name": "Ford", "address": "Highway 42"},
                    {"name": "Unknown", "address": "Highway 42"},
                    {"name": "Me", "address": "Highway 42"},
                ],
            )
            result = conn.fetch_many(
                "SELECT * FROM customers WHERE address = %(address)s",
                parameters={"address": "Highway 42"},
                size=2
            )
            print(result)  # Marvin, Ford
            result = conn.fetch_many(
                "SELECT * FROM customers WHERE address = %(address)s",
                parameters={"address": "Highway 42"},
                size=2
            )
            print(result)  # Unknown, Me
        ```
    """  # noqa
    inputs = dict(
        command=operation,
        params=parameters,
        **execute_kwargs,
    )
    new, cursor = self._get_cursor(inputs, cursor_type)
    if new:
        await self._execute_async(cursor, inputs)
    size = size or self.fetch_size
    self.logger.debug(f"Preparing to fetch {size} rows.")
    result = await run_sync_in_worker_thread(cursor.fetchmany, size=size)
    return result

fetch_one(operation, parameters=None, cursor_type=SnowflakeCursor, **execute_kwargs)

Fetch a single result from the database. Repeated calls using the same inputs to any of the fetch methods of this block will skip executing the operation again, and instead, return the next set of results from the previous execution, until the reset_cursors method is called.

Parameters:

Name	Type	Description	Default
operation	str	The SQL query or other operation to be executed.	required
parameters	Optional[Dict[str, Any]]	The parameters for the operation.	None
cursor_type	Type[SnowflakeCursor]	The class of the cursor to use when creating a Snowflake cursor.	SnowflakeCursor
**execute_kwargs	Any	Additional options to pass to cursor.execute_async.	{}

Returns:

Type	Description
Tuple[Any]	A tuple containing the data returned by the database, where each row is a tuple and each column is a value in the tuple.

Examples:

Fetch one row from the database where address is Space.

from prefect_snowflake.database import SnowflakeConnector

with SnowflakeConnector.load("BLOCK_NAME") as conn:
    conn.execute(
        "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
    )
    conn.execute_many(
        "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
        seq_of_parameters=[
            {"name": "Ford", "address": "Highway 42"},
            {"name": "Unknown", "address": "Space"},
            {"name": "Me", "address": "Myway 88"},
        ],
    )
    result = conn.fetch_one(
        "SELECT * FROM customers WHERE address = %(address)s",
        parameters={"address": "Space"}
    )
    print(result)

Source code in prefect_snowflake/database.py

def fetch_one(
    self,
    operation: str,
    parameters: Optional[Dict[str, Any]] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    **execute_kwargs: Any,
) -> Tuple[Any]:
    """
    Fetch a single result from the database.
    Repeated calls using the same inputs to *any* of the fetch methods of this
    block will skip executing the operation again, and instead,
    return the next set of results from the previous execution,
    until the reset_cursors method is called.

    Args:
        operation: The SQL query or other operation to be executed.
        parameters: The parameters for the operation.
        cursor_type: The class of the cursor to use when creating a Snowflake cursor.
        **execute_kwargs: Additional options to pass to `cursor.execute_async`.

    Returns:
        A tuple containing the data returned by the database,
            where each row is a tuple and each column is a value in the tuple.

    Examples:
        Fetch one row from the database where address is Space.
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        with SnowflakeConnector.load("BLOCK_NAME") as conn:
            conn.execute(
                "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
            )
            conn.execute_many(
                "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                seq_of_parameters=[
                    {"name": "Ford", "address": "Highway 42"},
                    {"name": "Unknown", "address": "Space"},
                    {"name": "Me", "address": "Myway 88"},
                ],
            )
            result = conn.fetch_one(
                "SELECT * FROM customers WHERE address = %(address)s",
                parameters={"address": "Space"}
            )
            print(result)
        ```
    """  # noqa
    inputs = dict(
        command=operation,
        params=parameters,
        **execute_kwargs,
    )
    new, cursor = self._get_cursor(inputs, cursor_type=cursor_type)
    if new:
        self.execute(
            operation, parameters, cursor_type=cursor_type, **execute_kwargs
        )
    self.logger.debug("Preparing to fetch a row.")
    return cursor.fetchone()

fetch_one_async(operation, parameters=None, cursor_type=SnowflakeCursor, **execute_kwargs) async

Fetch a single result from the database asynchronously. Repeated calls using the same inputs to any of the fetch methods of this block will skip executing the operation again, and instead, return the next set of results from the previous execution, until the reset_cursors method is called.

Parameters:

Name	Type	Description	Default
operation	str	The SQL query or other operation to be executed.	required
parameters	Optional[Dict[str, Any]]	The parameters for the operation.	None
cursor_type	Type[SnowflakeCursor]	The class of the cursor to use when creating a Snowflake cursor.	SnowflakeCursor
**execute_kwargs	Any	Additional options to pass to cursor.execute_async.	{}

Returns:

Type	Description
Tuple[Any]	A tuple containing the data returned by the database, where each row is a tuple and each column is a value in the tuple.

Examples:

Fetch one row from the database where address is Space.

from prefect_snowflake.database import SnowflakeConnector

with SnowflakeConnector.load("BLOCK_NAME") as conn:
    conn.execute(
        "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
    )
    conn.execute_many(
        "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
        seq_of_parameters=[
            {"name": "Ford", "address": "Highway 42"},
            {"name": "Unknown", "address": "Space"},
            {"name": "Me", "address": "Myway 88"},
        ],
    )
    result = await conn.fetch_one_async(
        "SELECT * FROM customers WHERE address = %(address)s",
        parameters={"address": "Space"}
    )
    print(result)

Source code in prefect_snowflake/database.py

async def fetch_one_async(
    self,
    operation: str,
    parameters: Optional[Dict[str, Any]] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    **execute_kwargs: Any,
) -> Tuple[Any]:
    """
    Fetch a single result from the database asynchronously.
    Repeated calls using the same inputs to *any* of the fetch methods of this
    block will skip executing the operation again, and instead,
    return the next set of results from the previous execution,
    until the reset_cursors method is called.

    Args:
        operation: The SQL query or other operation to be executed.
        parameters: The parameters for the operation.
        cursor_type: The class of the cursor to use when creating a Snowflake cursor.
        **execute_kwargs: Additional options to pass to `cursor.execute_async`.

    Returns:
        A tuple containing the data returned by the database,
            where each row is a tuple and each column is a value in the tuple.

    Examples:
        Fetch one row from the database where address is Space.
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        with SnowflakeConnector.load("BLOCK_NAME") as conn:
            conn.execute(
                "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
            )
            conn.execute_many(
                "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                seq_of_parameters=[
                    {"name": "Ford", "address": "Highway 42"},
                    {"name": "Unknown", "address": "Space"},
                    {"name": "Me", "address": "Myway 88"},
                ],
            )
            result = await conn.fetch_one_async(
                "SELECT * FROM customers WHERE address = %(address)s",
                parameters={"address": "Space"}
            )
            print(result)
        ```
    """  # noqa
    inputs = dict(
        command=operation,
        params=parameters,
        **execute_kwargs,
    )
    new, cursor = self._get_cursor(inputs, cursor_type=cursor_type)
    if new:
        await self._execute_async(cursor, inputs)
    self.logger.debug("Preparing to fetch a row.")
    result = await run_sync_in_worker_thread(cursor.fetchone)
    return result

get_connection(**connect_kwargs)

Returns an authenticated connection that can be used to query from Snowflake databases.

Parameters:

Name	Type	Description	Default
**connect_kwargs	Any	Additional arguments to pass to snowflake.connector.connect.	{}

Returns:

Type	Description
SnowflakeConnection	The authenticated SnowflakeConnection.

Examples:

from prefect_snowflake.credentials import SnowflakeCredentials
from prefect_snowflake.database import SnowflakeConnector

snowflake_credentials = SnowflakeCredentials(
    account="account",
    user="user",
    password="password",
)
snowflake_connector = SnowflakeConnector(
    database="database",
    warehouse="warehouse",
    schema="schema",
    credentials=snowflake_credentials
)
with snowflake_connector.get_connection() as connection:
    ...

Source code in prefect_snowflake/database.py

def get_connection(self, **connect_kwargs: Any) -> SnowflakeConnection:
    """
    Returns an authenticated connection that can be
    used to query from Snowflake databases.

    Args:
        **connect_kwargs: Additional arguments to pass to
            `snowflake.connector.connect`.

    Returns:
        The authenticated SnowflakeConnection.

    Examples:
        ```python
        from prefect_snowflake.credentials import SnowflakeCredentials
        from prefect_snowflake.database import SnowflakeConnector

        snowflake_credentials = SnowflakeCredentials(
            account="account",
            user="user",
            password="password",
        )
        snowflake_connector = SnowflakeConnector(
            database="database",
            warehouse="warehouse",
            schema="schema",
            credentials=snowflake_credentials
        )
        with snowflake_connector.get_connection() as connection:
            ...
        ```
    """
    if self._connection is not None:
        return self._connection

    connect_params = {
        "database": self.database,
        "warehouse": self.warehouse,
        "schema": self.schema_,
    }
    connection = self.credentials.get_client(**connect_kwargs, **connect_params)
    self._connection = connection
    self.logger.info("Started a new connection to Snowflake.")
    return connection

reset_cursors()

Tries to close all opened cursors.

Examples:

Reset the cursors to refresh cursor position.

from prefect_snowflake.database import SnowflakeConnector

with SnowflakeConnector.load("BLOCK_NAME") as conn:
    conn.execute(
        "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
    )
    conn.execute_many(
        "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
        seq_of_parameters=[
            {"name": "Ford", "address": "Highway 42"},
            {"name": "Unknown", "address": "Space"},
            {"name": "Me", "address": "Myway 88"},
        ],
    )
    print(conn.fetch_one("SELECT * FROM customers"))  # Ford
    conn.reset_cursors()
    print(conn.fetch_one("SELECT * FROM customers"))  # should be Ford again

Source code in prefect_snowflake/database.py

def reset_cursors(self) -> None:
    """
    Tries to close all opened cursors.

    Examples:
        Reset the cursors to refresh cursor position.
        ```python
        from prefect_snowflake.database import SnowflakeConnector

        with SnowflakeConnector.load("BLOCK_NAME") as conn:
            conn.execute(
                "CREATE TABLE IF NOT EXISTS customers (name varchar, address varchar);"
            )
            conn.execute_many(
                "INSERT INTO customers (name, address) VALUES (%(name)s, %(address)s);",
                seq_of_parameters=[
                    {"name": "Ford", "address": "Highway 42"},
                    {"name": "Unknown", "address": "Space"},
                    {"name": "Me", "address": "Myway 88"},
                ],
            )
            print(conn.fetch_one("SELECT * FROM customers"))  # Ford
            conn.reset_cursors()
            print(conn.fetch_one("SELECT * FROM customers"))  # should be Ford again
        ```
    """  # noqa
    if not self._unique_cursors:
        self.logger.info("There were no cursors to reset.")
        return

    input_hashes = tuple(self._unique_cursors.keys())
    for input_hash in input_hashes:
        cursor = self._unique_cursors.pop(input_hash)
        try:
            cursor.close()
        except Exception as exc:
            self.logger.warning(
                f"Failed to close cursor for input hash {input_hash!r}: {exc}"
            )
    self.logger.info("Successfully reset the cursors.")

snowflake_multiquery(queries, snowflake_connector, params=None, cursor_type=SnowflakeCursor, as_transaction=False, return_transaction_control_results=False, poll_frequency_seconds=1)

Executes multiple queries against a Snowflake database in a shared session. Allows execution in a transaction.

Parameters:

Name	Type	Description	Default
queries	List[str]	The list of queries to execute against the database.	required
params	Union[Tuple[Any], Dict[str, Any]]	The params to replace the placeholders in the query.	None
snowflake_connector	SnowflakeConnector	The credentials to use to authenticate.	required
cursor_type	Type[SnowflakeCursor]	The type of database cursor to use for the query.	SnowflakeCursor
as_transaction	bool	If True, queries are executed in a transaction.	False
return_transaction_control_results	bool	Determines if the results of queries controlling the transaction (BEGIN/COMMIT) should be returned.	False
poll_frequency_seconds	int	Number of seconds to wait in between checks for run completion.	1

Returns:

Type	Description
List[List[Tuple[Any]]]	List of the outputs of response.fetchall() for each query.

Examples:

Query Snowflake table with the ID value parameterized.

from prefect import flow
from prefect_snowflake.credentials import SnowflakeCredentials
from prefect_snowflake.database import SnowflakeConnector, snowflake_multiquery


@flow
def snowflake_multiquery_flow():
    snowflake_credentials = SnowflakeCredentials(
        account="account",
        user="user",
        password="password",
    )
    snowflake_connector = SnowflakeConnector(
        database="database",
        warehouse="warehouse",
        schema="schema",
        credentials=snowflake_credentials
    )
    result = snowflake_multiquery(
        ["SELECT * FROM table WHERE id=%{id_param}s LIMIT 8;", "SELECT 1,2"],
        snowflake_connector,
        params={"id_param": 1},
        as_transaction=True
    )
    return result

snowflake_multiquery_flow()

Source code in prefect_snowflake/database.py

@task
def snowflake_multiquery(
    queries: List[str],
    snowflake_connector: SnowflakeConnector,
    params: Union[Tuple[Any], Dict[str, Any]] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    as_transaction: bool = False,
    return_transaction_control_results: bool = False,
    poll_frequency_seconds: int = 1,
) -> List[List[Tuple[Any]]]:
    """
    Executes multiple queries against a Snowflake database in a shared session.
    Allows execution in a transaction.

    Args:
        queries: The list of queries to execute against the database.
        params: The params to replace the placeholders in the query.
        snowflake_connector: The credentials to use to authenticate.
        cursor_type: The type of database cursor to use for the query.
        as_transaction: If True, queries are executed in a transaction.
        return_transaction_control_results: Determines if the results of queries
            controlling the transaction (BEGIN/COMMIT) should be returned.
        poll_frequency_seconds: Number of seconds to wait in between checks for
            run completion.

    Returns:
        List of the outputs of `response.fetchall()` for each query.

    Examples:
        Query Snowflake table with the ID value parameterized.
        ```python
        from prefect import flow
        from prefect_snowflake.credentials import SnowflakeCredentials
        from prefect_snowflake.database import SnowflakeConnector, snowflake_multiquery


        @flow
        def snowflake_multiquery_flow():
            snowflake_credentials = SnowflakeCredentials(
                account="account",
                user="user",
                password="password",
            )
            snowflake_connector = SnowflakeConnector(
                database="database",
                warehouse="warehouse",
                schema="schema",
                credentials=snowflake_credentials
            )
            result = snowflake_multiquery(
                ["SELECT * FROM table WHERE id=%{id_param}s LIMIT 8;", "SELECT 1,2"],
                snowflake_connector,
                params={"id_param": 1},
                as_transaction=True
            )
            return result

        snowflake_multiquery_flow()
        ```
    """
    with snowflake_connector.get_connection() as connection:
        if as_transaction:
            queries.insert(0, BEGIN_TRANSACTION_STATEMENT)
            queries.append(END_TRANSACTION_STATEMENT)

        with connection.cursor(cursor_type) as cursor:
            results = []
            for query in queries:
                response = cursor.execute_async(query, params=params)
                query_id = response["queryId"]
                while connection.is_still_running(
                    connection.get_query_status_throw_if_error(query_id)
                ):
                    sleep(poll_frequency_seconds)
                cursor.get_results_from_sfqid(query_id)
                result = cursor.fetchall()
                results.append(result)

    # cut off results from BEGIN/COMMIT queries
    if as_transaction and not return_transaction_control_results:
        return results[1:-1]
    else:
        return results

snowflake_multiquery_async(queries, snowflake_connector, params=None, cursor_type=SnowflakeCursor, as_transaction=False, return_transaction_control_results=False, poll_frequency_seconds=1) async

Executes multiple queries against a Snowflake database in a shared session. Allows execution in a transaction.

Parameters:

Name	Type	Description	Default
queries	List[str]	The list of queries to execute against the database.	required
params	Union[Tuple[Any], Dict[str, Any]]	The params to replace the placeholders in the query.	None
snowflake_connector	SnowflakeConnector	The credentials to use to authenticate.	required
cursor_type	Type[SnowflakeCursor]	The type of database cursor to use for the query.	SnowflakeCursor
as_transaction	bool	If True, queries are executed in a transaction.	False
return_transaction_control_results	bool	Determines if the results of queries controlling the transaction (BEGIN/COMMIT) should be returned.	False
poll_frequency_seconds	int	Number of seconds to wait in between checks for run completion.	1

Returns:

Type	Description
List[List[Tuple[Any]]]	List of the outputs of response.fetchall() for each query.

Examples:

Query Snowflake table with the ID value parameterized.

from prefect import flow
from prefect_snowflake.credentials import SnowflakeCredentials
from prefect_snowflake.database import SnowflakeConnector, snowflake_multiquery


@flow
def snowflake_multiquery_flow():
    snowflake_credentials = SnowflakeCredentials(
        account="account",
        user="user",
        password="password",
    )
    snowflake_connector = SnowflakeConnector(
        database="database",
        warehouse="warehouse",
        schema="schema",
        credentials=snowflake_credentials
    )
    result = snowflake_multiquery(
        ["SELECT * FROM table WHERE id=%{id_param}s LIMIT 8;", "SELECT 1,2"],
        snowflake_connector,
        params={"id_param": 1},
        as_transaction=True
    )
    return result

snowflake_multiquery_flow()

Source code in prefect_snowflake/database.py

@task
async def snowflake_multiquery_async(
    queries: List[str],
    snowflake_connector: SnowflakeConnector,
    params: Union[Tuple[Any], Dict[str, Any]] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    as_transaction: bool = False,
    return_transaction_control_results: bool = False,
    poll_frequency_seconds: int = 1,
) -> List[List[Tuple[Any]]]:
    """
    Executes multiple queries against a Snowflake database in a shared session.
    Allows execution in a transaction.

    Args:
        queries: The list of queries to execute against the database.
        params: The params to replace the placeholders in the query.
        snowflake_connector: The credentials to use to authenticate.
        cursor_type: The type of database cursor to use for the query.
        as_transaction: If True, queries are executed in a transaction.
        return_transaction_control_results: Determines if the results of queries
            controlling the transaction (BEGIN/COMMIT) should be returned.
        poll_frequency_seconds: Number of seconds to wait in between checks for
            run completion.

    Returns:
        List of the outputs of `response.fetchall()` for each query.

    Examples:
        Query Snowflake table with the ID value parameterized.
        ```python
        from prefect import flow
        from prefect_snowflake.credentials import SnowflakeCredentials
        from prefect_snowflake.database import SnowflakeConnector, snowflake_multiquery


        @flow
        def snowflake_multiquery_flow():
            snowflake_credentials = SnowflakeCredentials(
                account="account",
                user="user",
                password="password",
            )
            snowflake_connector = SnowflakeConnector(
                database="database",
                warehouse="warehouse",
                schema="schema",
                credentials=snowflake_credentials
            )
            result = snowflake_multiquery(
                ["SELECT * FROM table WHERE id=%{id_param}s LIMIT 8;", "SELECT 1,2"],
                snowflake_connector,
                params={"id_param": 1},
                as_transaction=True
            )
            return result

        snowflake_multiquery_flow()
        ```
    """
    with snowflake_connector.get_connection() as connection:
        if as_transaction:
            queries.insert(0, BEGIN_TRANSACTION_STATEMENT)
            queries.append(END_TRANSACTION_STATEMENT)

        with connection.cursor(cursor_type) as cursor:
            results = []
            for query in queries:
                response = cursor.execute_async(query, params=params)
                query_id = response["queryId"]
                while connection.is_still_running(
                    connection.get_query_status_throw_if_error(query_id)
                ):
                    await asyncio.sleep(poll_frequency_seconds)
                cursor.get_results_from_sfqid(query_id)
                result = cursor.fetchall()
                results.append(result)

    # cut off results from BEGIN/COMMIT queries
    if as_transaction and not return_transaction_control_results:
        return results[1:-1]
    else:
        return results

snowflake_query(query, snowflake_connector, params=None, cursor_type=SnowflakeCursor, poll_frequency_seconds=1)

Executes a query against a Snowflake database.

Parameters:

Name	Type	Description	Default
query	str	The query to execute against the database.	required
params	Union[Tuple[Any], Dict[str, Any]]	The params to replace the placeholders in the query.	None
snowflake_connector	SnowflakeConnector	The credentials to use to authenticate.	required
cursor_type	Type[SnowflakeCursor]	The type of database cursor to use for the query.	SnowflakeCursor
poll_frequency_seconds	int	Number of seconds to wait in between checks for run completion.	1

Returns:

Type	Description
List[Tuple[Any]]	The output of response.fetchall().

Examples:

Query Snowflake table with the ID value parameterized.

from prefect import flow
from prefect_snowflake.credentials import SnowflakeCredentials
from prefect_snowflake.database import SnowflakeConnector, snowflake_query


@flow
def snowflake_query_flow():
    snowflake_credentials = SnowflakeCredentials(
        account="account",
        user="user",
        password="password",
    )
    snowflake_connector = SnowflakeConnector(
        database="database",
        warehouse="warehouse",
        schema="schema",
        credentials=snowflake_credentials
    )
    result = snowflake_query(
        "SELECT * FROM table WHERE id=%{id_param}s LIMIT 8;",
        snowflake_connector,
        params={"id_param": 1}
    )
    return result

snowflake_query_flow()

Source code in prefect_snowflake/database.py

@task
def snowflake_query(
    query: str,
    snowflake_connector: SnowflakeConnector,
    params: Union[Tuple[Any], Dict[str, Any]] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    poll_frequency_seconds: int = 1,
) -> List[Tuple[Any]]:
    """
    Executes a query against a Snowflake database.

    Args:
        query: The query to execute against the database.
        params: The params to replace the placeholders in the query.
        snowflake_connector: The credentials to use to authenticate.
        cursor_type: The type of database cursor to use for the query.
        poll_frequency_seconds: Number of seconds to wait in between checks for
            run completion.

    Returns:
        The output of `response.fetchall()`.

    Examples:
        Query Snowflake table with the ID value parameterized.
        ```python
        from prefect import flow
        from prefect_snowflake.credentials import SnowflakeCredentials
        from prefect_snowflake.database import SnowflakeConnector, snowflake_query


        @flow
        def snowflake_query_flow():
            snowflake_credentials = SnowflakeCredentials(
                account="account",
                user="user",
                password="password",
            )
            snowflake_connector = SnowflakeConnector(
                database="database",
                warehouse="warehouse",
                schema="schema",
                credentials=snowflake_credentials
            )
            result = snowflake_query(
                "SELECT * FROM table WHERE id=%{id_param}s LIMIT 8;",
                snowflake_connector,
                params={"id_param": 1}
            )
            return result

        snowflake_query_flow()
        ```
    """
    # context manager automatically rolls back failed transactions and closes
    with snowflake_connector.get_connection() as connection:
        with connection.cursor(cursor_type) as cursor:
            response = cursor.execute_async(query, params=params)
            query_id = response["queryId"]
            while connection.is_still_running(
                connection.get_query_status_throw_if_error(query_id)
            ):
                sleep(poll_frequency_seconds)
            cursor.get_results_from_sfqid(query_id)
            result = cursor.fetchall()
    return result

snowflake_query_async(query, snowflake_connector, params=None, cursor_type=SnowflakeCursor, poll_frequency_seconds=1) async

Executes a query against a Snowflake database.

Parameters:

Name	Type	Description	Default
query	str	The query to execute against the database.	required
params	Union[Tuple[Any], Dict[str, Any]]	The params to replace the placeholders in the query.	None
snowflake_connector	SnowflakeConnector	The credentials to use to authenticate.	required
cursor_type	Type[SnowflakeCursor]	The type of database cursor to use for the query.	SnowflakeCursor
poll_frequency_seconds	int	Number of seconds to wait in between checks for run completion.	1

Returns:

Type	Description
List[Tuple[Any]]	The output of response.fetchall().

Examples:

Query Snowflake table with the ID value parameterized.

from prefect import flow
from prefect_snowflake.credentials import SnowflakeCredentials
from prefect_snowflake.database import SnowflakeConnector, snowflake_query


@flow
def snowflake_query_flow():
    snowflake_credentials = SnowflakeCredentials(
        account="account",
        user="user",
        password="password",
    )
    snowflake_connector = SnowflakeConnector(
        database="database",
        warehouse="warehouse",
        schema="schema",
        credentials=snowflake_credentials
    )
    result = snowflake_query(
        "SELECT * FROM table WHERE id=%{id_param}s LIMIT 8;",
        snowflake_connector,
        params={"id_param": 1}
    )
    return result

snowflake_query_flow()

Source code in prefect_snowflake/database.py

@task
async def snowflake_query_async(
    query: str,
    snowflake_connector: SnowflakeConnector,
    params: Union[Tuple[Any], Dict[str, Any]] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
    poll_frequency_seconds: int = 1,
) -> List[Tuple[Any]]:
    """
    Executes a query against a Snowflake database.

    Args:
        query: The query to execute against the database.
        params: The params to replace the placeholders in the query.
        snowflake_connector: The credentials to use to authenticate.
        cursor_type: The type of database cursor to use for the query.
        poll_frequency_seconds: Number of seconds to wait in between checks for
            run completion.

    Returns:
        The output of `response.fetchall()`.

    Examples:
        Query Snowflake table with the ID value parameterized.
        ```python
        from prefect import flow
        from prefect_snowflake.credentials import SnowflakeCredentials
        from prefect_snowflake.database import SnowflakeConnector, snowflake_query


        @flow
        def snowflake_query_flow():
            snowflake_credentials = SnowflakeCredentials(
                account="account",
                user="user",
                password="password",
            )
            snowflake_connector = SnowflakeConnector(
                database="database",
                warehouse="warehouse",
                schema="schema",
                credentials=snowflake_credentials
            )
            result = snowflake_query(
                "SELECT * FROM table WHERE id=%{id_param}s LIMIT 8;",
                snowflake_connector,
                params={"id_param": 1}
            )
            return result

        snowflake_query_flow()
        ```
    """
    # context manager automatically rolls back failed transactions and closes
    with snowflake_connector.get_connection() as connection:
        with connection.cursor(cursor_type) as cursor:
            response = cursor.execute_async(query, params=params)
            query_id = response["queryId"]
            while connection.is_still_running(
                connection.get_query_status_throw_if_error(query_id)
            ):
                await asyncio.sleep(poll_frequency_seconds)
            cursor.get_results_from_sfqid(query_id)
            result = cursor.fetchall()
    return result

snowflake_query_sync(query, snowflake_connector, params=None, cursor_type=SnowflakeCursor)

Executes a query in sync mode against a Snowflake database.

Parameters:

Name	Type	Description	Default
query	str	The query to execute against the database.	required
params	Union[Tuple[Any], Dict[str, Any]]	The params to replace the placeholders in the query.	None
snowflake_connector	SnowflakeConnector	The credentials to use to authenticate.	required
cursor_type	Type[SnowflakeCursor]	The type of database cursor to use for the query.	SnowflakeCursor

Returns:

Type	Description
List[Tuple[Any]]	The output of response.fetchall().

Examples:

Execute a put statement.

from prefect import flow
from prefect_snowflake.credentials import SnowflakeCredentials
from prefect_snowflake.database import SnowflakeConnector, snowflake_query


@flow
def snowflake_query_sync_flow():
    snowflake_credentials = SnowflakeCredentials(
        account="account",
        user="user",
        password="password",
    )
    snowflake_connector = SnowflakeConnector(
        database="database",
        warehouse="warehouse",
        schema="schema",
        credentials=snowflake_credentials
    )
    result = snowflake_query_sync(
        "put file://a_file.csv @mystage;",
        snowflake_connector,
    )
    return result

snowflake_query_sync_flow()

Source code in prefect_snowflake/database.py

@task
def snowflake_query_sync(
    query: str,
    snowflake_connector: SnowflakeConnector,
    params: Union[Tuple[Any], Dict[str, Any]] = None,
    cursor_type: Type[SnowflakeCursor] = SnowflakeCursor,
) -> List[Tuple[Any]]:
    """
    Executes a query in sync mode against a Snowflake database.

    Args:
        query: The query to execute against the database.
        params: The params to replace the placeholders in the query.
        snowflake_connector: The credentials to use to authenticate.
        cursor_type: The type of database cursor to use for the query.

    Returns:
        The output of `response.fetchall()`.

    Examples:
        Execute a put statement.
        ```python
        from prefect import flow
        from prefect_snowflake.credentials import SnowflakeCredentials
        from prefect_snowflake.database import SnowflakeConnector, snowflake_query


        @flow
        def snowflake_query_sync_flow():
            snowflake_credentials = SnowflakeCredentials(
                account="account",
                user="user",
                password="password",
            )
            snowflake_connector = SnowflakeConnector(
                database="database",
                warehouse="warehouse",
                schema="schema",
                credentials=snowflake_credentials
            )
            result = snowflake_query_sync(
                "put file://a_file.csv @mystage;",
                snowflake_connector,
            )
            return result

        snowflake_query_sync_flow()
        ```
    """
    # context manager automatically rolls back failed transactions and closes
    with snowflake_connector.get_connection() as connection:
        with connection.cursor(cursor_type) as cursor:
            cursor.execute(query, params=params)
            result = cursor.fetchall()
    return result