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<@ULVA73B9P> Show me a basic example of how I can ...
# ask-marvin
k
@Marvin Show me a basic example of how I can use the SqlAlchemyConnector block to connect to a SQL database and execute a query. Assume I already have the query string stored in 
extract_query
and I want to use 
pandas.read_sql
.
m
To connect to a SQL database using the 
SqlAlchemyConnector
block in Prefect and execute a query with 
pandas.read_sql
, you'll need to follow these steps. Here's a basic example assuming you're using Prefect 3.x: 1. Install the 
prefect-sqlalchemy
package if you haven't already. This package provides the necessary blocks and integrations for SQLAlchemy.
Copy code
bash
    pip install prefect-sqlalchemy
2. Register the block types in the Prefect environment. This step ensures that the 
SqlAlchemyConnector
is available for use. 3. Save your database credentials to a block using Prefect's UI or code. You need to have a block saved to use the 
load
method. 4. Load the block and execute the query. Here's a code snippet to demonstrate this:
Copy code
python
    from prefect import flow
    from prefect_sqlalchemy import SqlAlchemyConnector
    import pandas as pd

    @flow
    def execute_sql_query():
        # Load the SqlAlchemyConnector block
        connector = SqlAlchemyConnector.load("your-connector-block-name")

        # Use the connector to execute a query
        with connector.get_connection() as engine:
            df = pd.read_sql("SELECT * FROM your_table", con=engine)
        
        print(df)

    execute_sql_query()
In this example, replace 
"your-connector-block-name"
with the name of your saved block and 
"SELECT * FROM your_table"
with your actual query stored in 
extract_query
. For more details, you can refer to the Prefect SQLAlchemy integration documentation.
k
@Marvin Is 
DatabaseCredentials
still valid to use instead of 
SqlAlchemyConnector
?
m
The 
DatabaseCredentials
block isn't explicitly mentioned in the latest Prefect 3.x documentation, which suggests that it may not be the recommended approach for managing database connections in this version. Instead, the 
SqlAlchemyConnector
block is highlighted as the primary means to connect to databases using SQLAlchemy. The 
SqlAlchemyConnector
block is designed to encapsulate the connection logic and credentials management, making it more suitable for modern Prefect workflows. It allows you to load credentials and establish connections seamlessly within your Prefect flows. For more details, you can refer to the Prefect SQLAlchemy integration documentation. If you have existing workflows using 
DatabaseCredentials
, it might be worth exploring how to migrate to the 
SqlAlchemyConnector
for better compatibility and support with Prefect 3.x.
k
@Marvin Please explain this error message and how I can fix it:
Copy code
Error encountered when computing cache key - result will not be persisted.
Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 347, in compute_key
    return hash_objects(hashed_inputs, raise_on_failure=True)
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\utilities\hashing.py", line 89, in hash_objects
    raise HashError(msg)
prefect.exceptions.HashError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\task_engine.py", line 161, in compute_transaction_key
    key = self.task.cache_policy.compute_key(
        task_ctx=task_run_context,
        inputs=self.parameters or {},
        flow_parameters=parameters or {},
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 188, in compute_key
    policy_key = policy.compute_key(
        task_ctx=task_ctx,
    ...<2 lines>...
        **kwargs,
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 357, in compute_key
    raise ValueError(msg) from exc
ValueError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object

This often occurs when task inputs contain objects that cannot be cached like locks, file handles, or other system resources.

To resolve this, you can:
  1. Exclude these arguments by defining a custom `cache_key_fn`
  2. Disable caching by passing `cache_policy=NO_CACHE`
m
Your message was too long by 56 tokens...
k
Please explain this error message and how I can fix it:
Copy code
Error encountered when computing cache key - result will not be persisted.
Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 347, in compute_key
    return hash_objects(hashed_inputs, raise_on_failure=True)
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\utilities\hashing.py", line 89, in hash_objects
    raise HashError(msg)
prefect.exceptions.HashError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\task_engine.py", line 161, in compute_transaction_key
    key = self.task.cache_policy.compute_key(
        task_ctx=task_run_context,
        inputs=self.parameters or {},
        flow_parameters=parameters or {},
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 188, in compute_key
    policy_key = policy.compute_key(
        task_ctx=task_ctx,
    ...<2 lines>...
        **kwargs,
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 357, in compute_key
    raise ValueError(msg) from exc
ValueError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object

This often occurs when task inputs contain objects that cannot be cached like locks, file handles, or other system resources.
@Marvin Please explain this error message and how I can fix it:
Copy code
Error encountered when computing cache key - result will not be persisted.
Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 347, in compute_key
    return hash_objects(hashed_inputs, raise_on_failure=True)
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\utilities\hashing.py", line 89, in hash_objects
    raise HashError(msg)
prefect.exceptions.HashError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\task_engine.py", line 161, in compute_transaction_key
    key = self.task.cache_policy.compute_key(
        task_ctx=task_run_context,
        inputs=self.parameters or {},
        flow_parameters=parameters or {},
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 188, in compute_key
    policy_key = policy.compute_key(
        task_ctx=task_ctx,
    ...<2 lines>...
        **kwargs,
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 357, in compute_key
    raise ValueError(msg) from exc
ValueError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object

This often occurs when task inputs contain objects that cannot be cached like locks, file handles, or other system resources.

To resolve this, you can:
  1. Exclude these arguments by defining a custom `cache_key_fn`
  2. Disable caching by passing `cache_policy=NO_CACHE`
m
Your message was too long by 56 tokens...
k
Please explain this error message and how I can fix it:
Copy code
Error encountered when computing cache key - result will not be persisted.
Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 347, in compute_key
    return hash_objects(hashed_inputs, raise_on_failure=True)
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\utilities\hashing.py", line 89, in hash_objects
    raise HashError(msg)
prefect.exceptions.HashError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\task_engine.py", line 161, in compute_transaction_key
    key = self.task.cache_policy.compute_key(
        task_ctx=task_run_context,
        inputs=self.parameters or {},
        flow_parameters=parameters or {},
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 188, in compute_key
    policy_key = policy.compute_key(
        task_ctx=task_ctx,
    ...<2 lines>...
        **kwargs,
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 357, in compute_key
    raise ValueError(msg) from exc
ValueError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object

This often occurs when task inputs contain objects that cannot be cached like locks, file handles, or other system resources.
@Marvin Please explain this error message and how I can fix it:
Copy code
Error encountered when computing cache key - result will not be persisted.
Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 347, in compute_key
    return hash_objects(hashed_inputs, raise_on_failure=True)
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\utilities\hashing.py", line 89, in hash_objects
    raise HashError(msg)
prefect.exceptions.HashError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\task_engine.py", line 161, in compute_transaction_key
    key = self.task.cache_policy.compute_key(
        task_ctx=task_run_context,
        inputs=self.parameters or {},
        flow_parameters=parameters or {},
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 188, in compute_key
    policy_key = policy.compute_key(
        task_ctx=task_ctx,
    ...<2 lines>...
        **kwargs,
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 357, in compute_key
    raise ValueError(msg) from exc
ValueError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object

This often occurs when task inputs contain objects that cannot be cached like locks, file handles, or other system resources.
m
Your message was too long by 17 tokens...
k
@Marvin Please explain this error message and how I can fix it:
Copy code
Error encountered when computing cache key - result will not be persisted.
Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 347, in compute_key
    return hash_objects(hashed_inputs, raise_on_failure=True)
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\utilities\hashing.py", line 89, in hash_objects
    raise HashError(msg)
prefect.exceptions.HashError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\task_engine.py", line 161, in compute_transaction_key
    key = self.task.cache_policy.compute_key(
        task_ctx=task_run_context,
        inputs=self.parameters or {},
        flow_parameters=parameters or {},
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 188, in compute_key
    policy_key = policy.compute_key(
        task_ctx=task_ctx,
    ...<2 lines>...
        **kwargs,
    )
  File "C:\Users\kaleb.king\Documents\GitHub\Data-Warehouse\venv\prefect\Lib\site-packages\prefect\cache_policies.py", line 357, in compute_key
    raise ValueError(msg) from exc
ValueError: Unable to create hash - objects could not be serialized.
  JSON error: Unable to serialize unknown type: <class 'snowflake.connector.cursor.SnowflakeCursor'>
  Pickle error: cannot pickle '_thread.lock' object
m
The error message you're encountering indicates that Prefect is unable to serialize a 
SnowflakeCursor
object for caching purposes. This is due to the cursor containing elements that are not serializable, such as a 
_thread.lock
object. Here's how you can address this issue: 1. Avoid Passing Non-Serializable Objects: Ensure that non-serializable objects like database cursors are not passed as parameters to tasks or used in a way that requires serialization. Prefect attempts to cache task inputs and outputs, so anything that cannot be serialized will cause issues. 2. Extract Data Before Passing: If you need to use data from a 
SnowflakeCursor
, extract the data into a serializable format (e.g., a list or a Pandas DataFrame) before passing it to tasks. For example, execute the query and fetch the results into a DataFrame:
Copy code
python
    import pandas as pd

    # Assuming `cursor` is your SnowflakeCursor
    df = pd.DataFrame.from_records(cursor.fetchall(), columns=[desc[0] for desc in cursor.description])
3. Disable Caching for Specific Tasks: If caching is not essential for certain tasks, you can disable it by setting the task's cache policy to 
None
. 4. Custom Serialization: If you need to pass complex objects, consider implementing custom serialization logic, but this can be complex and is generally not recommended for cursors or similar objects. For more information on Prefect's caching and serialization, you might want to explore the Prefect documentation on caching and the Prefect Snowflake integration.
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