prefect_snowflake.database
Module for querying against Snowflake databases.
Classes
SnowflakeConnector (DatabaseBlock)
pydantic-model
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 |
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(
"We were not able to hash your inputs, "
"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.")
@sync_compatible
async 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:
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
@sync_compatible
async def fetch_many(
self,
operation: str,
parameters: Optional[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:
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
@sync_compatible
async 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.
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:
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": "Myway 88"},
],
)
result = conn.fetch_all(
"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
@sync_compatible
async 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:
await run_sync_in_worker_thread(cursor.execute, **inputs)
self.logger.info(f"Executed the operation, {operation!r}.")
@sync_compatible
async 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:
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()
Attributes
credentials: SnowflakeCredentials
pydantic-field
required
The credentials to authenticate with Snowflake.
database: str
pydantic-field
required
The name of the default database to use.
fetch_size: int
pydantic-field
The default number of rows to fetch at a time.
poll_frequency_s: int
pydantic-field
The number of seconds between checking query status for long running queries.
schema_: str
pydantic-field
required
The name of the default schema to use.
warehouse: str
pydantic-field
required
The name of the default warehouse to use.
Methods
__enter__
special
Start a connection upon entry.
Source code in prefect_snowflake/database.py
def __enter__(self):
"""
Start a connection upon entry.
"""
return self
__exit__
special
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__
special
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
__json_encoder__
special
staticmethod
partial(func, args, *keywords) - new function with partial application of the given arguments and keywords.
__setstate__
special
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
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[snowflake.connector.cursor.SnowflakeCursor] |
The class of the cursor to use when creating a Snowflake cursor. |
<class 'snowflake.connector.cursor.SnowflakeCursor'> |
**execute_kwargs |
Any |
Additional options to pass to |
{} |
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
@sync_compatible
async 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:
await run_sync_in_worker_thread(cursor.execute, **inputs)
self.logger.info(f"Executed the operation, {operation!r}.")
execute_many
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
@sync_compatible
async 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:
await run_sync_in_worker_thread(cursor.executemany, **inputs)
self.logger.info(
f"Executed {len(seq_of_parameters)} operations off {operation!r}."
)
fetch_all
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[snowflake.connector.cursor.SnowflakeCursor] |
The class of the cursor to use when creating a Snowflake cursor. |
<class 'snowflake.connector.cursor.SnowflakeCursor'> |
**execute_kwargs |
Any |
Additional options to pass to |
{} |
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:
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": "Myway 88"},
],
)
result = conn.fetch_all(
"SELECT * FROM customers WHERE address = %(address)s",
parameters={"address": "Highway 42"},
)
print(result) # Marvin, Ford, Unknown
Source code in prefect_snowflake/database.py
@sync_compatible
async 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.
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:
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": "Myway 88"},
],
)
result = conn.fetch_all(
"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
async
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[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
|
None |
cursor_type |
Type[snowflake.connector.cursor.SnowflakeCursor] |
The class of the cursor to use when creating a Snowflake cursor. |
<class 'snowflake.connector.cursor.SnowflakeCursor'> |
**execute_kwargs |
Any |
Additional options to pass to |
{} |
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
@sync_compatible
async def fetch_many(
self,
operation: str,
parameters: Optional[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:
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
async
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[snowflake.connector.cursor.SnowflakeCursor] |
The class of the cursor to use when creating a Snowflake cursor. |
<class 'snowflake.connector.cursor.SnowflakeCursor'> |
**execute_kwargs |
Any |
Additional options to pass to |
{} |
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
@sync_compatible
async 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:
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
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
|
{} |
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.")
Functions
snowflake_multiquery
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[snowflake.connector.cursor.SnowflakeCursor] |
The type of database cursor to use for the query. |
<class 'snowflake.connector.cursor.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 |
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(
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
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[snowflake.connector.cursor.SnowflakeCursor] |
The type of database cursor to use for the query. |
<class 'snowflake.connector.cursor.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 |
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(
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
async
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[snowflake.connector.cursor.SnowflakeCursor] |
The type of database cursor to use for the query. |
<class 'snowflake.connector.cursor.SnowflakeCursor'> |
Returns:
| Type | Description |
|---|---|
List[Tuple[Any]] |
The output of |
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://afile.csv @mystage;",
snowflake_connector,
)
return result
snowflake_query_sync_flow()
Source code in prefect_snowflake/database.py
@task
async 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://afile.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