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<@ULVA73B9P> if there a way that I can use: ```imp...
# ask-marvin
r
@Marvin if there a way that I can use:
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import logging

logger = logging.getLogger(__name__)
instead of
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from prefect import  get_run_logger
logger = get_run_logger()
I want to write my code in standard way and not to be coupled with prefect, for example when I am writing libraries
m
To use standard logging with Prefect without relying on 
get_run_logger
, you can integrate Prefect task functionality without changing existing logging mechanisms. Here's a way to do it: 1. Wrap existing functions with a custom decorator that injects Prefect functionality as needed. 2. Use standard 
logging.getLogger
 within those functions. ### Example: Let’s modify the way you use the logger in your functions to be more Prefect-friendly, but still maintain standard logging practices:
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python
import logging
from prefect import flow, task

# Standard logging setup
logger = logging.getLogger(__name__)
logging.basicConfig(level=<http://logging.INFO|logging.INFO>)

# Wrapping the function in a Prefect task
@task
def add(a, b):
    <http://logger.info|logger.info>(f"Sum: {a + b}")
    return a + b

# Example flow
@flow
def run_flow():
    add(3, 4)

if __name__ == "__main__":
    run_flow()
### Explanation: 1. Standard Logging: You set up the logger as you normally would. 2. @task Decorator: Use Prefect's 
@task
decorator to convert your function into a task. 3. Run as a Flow: Define and run the flow normally. ### Why This Works: - You continue using the standard 
logging
library. - Prefect tasks and flows integrate seamlessly through decorators without modifying your logging logic. - This makes your code modular and not tightly coupled with Prefect, enabling reusability in different contexts. For further details, reference issues and discussions: - GitHub Issue: Create a wrapper to run pre-existing functions as Tasks - Prefect Documentation: Unfortunately, an error occurred while accessing specific links, but check Tasks and Logging Prefect Docs for the latest info. If you have more detailed questions or need additional customization, feel free to ask!
r
@Marvin when I am doing it, I don't see anything of my custom in the log when running the flow
m
It appears you're facing issues with integrating the standard logging library with Prefect, as your custom log messages are not appearing as expected when you run the flow. There are a few known issues and some proposed workarounds that might help you resolve this. ### Workaround Solutions 1. Use 
PREFECT_LOGGING_EXTRA_LOGGERS
Configuration: Prefect allows you to capture logs from additional loggers by configuring 
PREFECT_LOGGING_EXTRA_LOGGERS
. This should help in bringing in logs from your custom logger to Prefect's logging system.
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python
   from prefect.settings import PREFECT_LOGGING_EXTRA_LOGGERS, update_current_profile

   # Update the Prefect profile to include the custom logger
   update_current_profile({PREFECT_LOGGING_EXTRA_LOGGERS: "your_custom_logger"})
2. Custom Logging within Prefect Tasks: Prefect might not automatically pick up logs from custom loggers without additional setup. To ensure your custom logs are properly registered, consider adding an explicit 
StreamHandler
and setting up the logger within the Prefect context. Here's an example setup:
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python
   import logging
   from prefect import flow, task
   from prefect.settings import PREFECT_LOGGING_EXTRA_LOGGERS, update_current_profile

   # Update the Prefect profile to include your custom logger
   update_current_profile({PREFECT_LOGGING_EXTRA_LOGGERS: "your_custom_logger"})

   # Standard logging setup
   custom_logger = logging.getLogger("your_custom_logger")
   console_handler = logging.StreamHandler()
   console_handler.setLevel(<http://logging.INFO|logging.INFO>)
   custom_logger.addHandler(console_handler)

   @task
   def add(a, b):
       <http://custom_logger.info|custom_logger.info>(f"Adding {a} and {b}")
       result = a + b
       <http://custom_logger.info|custom_logger.info>(f"Result: {result}")
       return result

   @flow
   def run_flow():
       add(3, 4)

   if __name__ == "__main__":
       run_flow()
### Known Issues and References - Duplicate Logs: There are known issues with Prefect causing duplicate logs when using custom loggers. This might happen if Prefect interferes with the logger configuration. - See GitHub Issue: Duplicated local logs from prefect. - Log Streaming: If you're interested in streaming logs directly: - See GitHub Issue: Option to stream flow run logs. By applying the 
PREFECT_LOGGING_EXTRA_LOGGERS
configuration and ensuring proper logger setup within your Prefect job, you should be able to get your custom logs into Prefect's logging system effectively.
r
@Marvin I will try to ask again, I would like to do the following:
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import logging
logger = logging.getLogger(__name__)
logger.setLevel(<http://logging.INFO|logging.INFO>)

@task(log_prints=True, persist_result=True)
def load_features_folder_to_temp_table(ctx: Context, features_uri) -> str:
    <http://logger.info|logger.info>('Loading features to temp table')
    return ""
And see the logs in the console and in prefect ui
m
To use standard logging with the standard 
logging.getLogger
while ensuring your logs appear in both the console and the Prefect UI, you can follow the steps below. This involves setting up your logger correctly and using the 
log_prints
parameter in the Prefect task decorator. Here's how you can do it: ### Setup 1. Configure Logger: Set up the logger to send logs to the console. 2. Task Definition: Use the 
log_prints
parameter in your Prefect task. ### Code Example
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python
import logging
from prefect import flow, task

# Configure the logger
logger = logging.getLogger(__name__)
logger.setLevel(<http://logging.INFO|logging.INFO>)
console_handler = logging.StreamHandler()
console_handler.setLevel(<http://logging.INFO|logging.INFO>)
logger.addHandler(console_handler)

@task(log_prints=True)  # Ensures the logs are captured and shown in Prefect UI
def load_features_folder_to_temp_table(features_uri):
    <http://logger.info|logger.info>('Loading features to temp table')
    return "Loading complete"

@flow
def run_flow():
    load_features_folder_to_temp_table("<s3://bucket/path>")

if __name__ == "__main__":
    run_flow()
### Explanation 1. Logger Configuration: - Create a logger with 
logging.getLogger(__name__)
to ensure the logs are associated with your current module. - Set the logging level to 
INFO
or any level of your choice. - Attach a 
StreamHandler
to the logger to output logs to the console. 2. Prefect Task: - Use the 
@task(log_prints=True)
decorator to ensure print statements and logger outputs are captured by Prefect and shown in the UI. 3. Prefect Flow: - Define and run the flow as usual. ### Additional Notes - This setup ensures that the logs generated by 
<http://logger.info|logger.info>()
are displayed in both the console and the Prefect UI. - Ensure you import necessary modules like 
flow
and 
task
from Prefect. By following these steps, you should see your custom logs in both the console and the Prefect UI. If you need further customization or encounter specific issues, feel free to ask!
r
@Marvin didn't work
m
If the standard logging with 
logging.getLogger
is not appearing in the Prefect UI when you set 
log_prints=True
, it's possible that the integration might have some nuances. Below are some steps and another example to help you achieve this. ### Another Comprehensive Example This example ensures that both console outputs and Prefect UI logs show messages from 
logging.getLogger
.
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python
import logging
from prefect import flow, task
from prefect.context import get_run_context

# Configure the logger
logger = logging.getLogger(__name__)
logger.setLevel(<http://logging.INFO|logging.INFO>)
console_handler = logging.StreamHandler()
console_handler.setLevel(<http://logging.INFO|logging.INFO>)
logger.addHandler(console_handler)

@task(log_prints=True)
def load_features_folder_to_temp_table(features_uri):
    <http://logger.info|logger.info>('Loading features to temp table')
    return "Loading complete"

@flow
def run_flow():
    load_features_folder_to_temp_table("<s3://bucket/path>")

if __name__ == "__main__":
    run_flow()
#### Key Points 1. Prefect Settings Adjustment: Ensure 
PREFECT_LOGGING_EXTRA_LOGGERS
is set if required. This setting can help Prefect capture logs from custom loggers.
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python
    from prefect.settings import PREFECT_LOGGING_EXTRA_LOGGERS, update_current_profile
    update_current_profile({PREFECT_LOGGING_EXTRA_LOGGERS: "your_custom_logger"})
2. 
log_prints=True
Parameter: This ensures that any 
print
statements within the task function are logged by Prefect and visible in the Prefect UI. ### Known Issues and Workarounds From the GitHub issues and pull requests, a few important notes: - Logging with 
log_prints
: The 
log_prints
feature is designed to capture print statements but it should normally pick up standard logging statements as well. - Stacklevel Adjustments: If the logs don't show the correct function names or details, you might need to tweak logging levels or configuration. ### Additional Debugging It's a good practice to verify that the logger is configured correctly and the logs are being captured as expected: 1. Standalone Logger Test:
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python
    <http://logger.info|logger.info>("This is a standalone test message")
2. Prefect Logger Integration: Using 
get_run_context()
to ensure Prefect context is being respected:
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python
    @task(log_prints=True)
    def load_features_folder_to_temp_table(features_uri):
        ctx = get_run_context()
        <http://ctx.logger.info|ctx.logger.info>("Loading features to temp table")
        <http://logger.info|logger.info>('Loading features to temp table')  # Both should log
        return "Loading complete"

    @flow
    def run_flow():
        load_features_folder_to_temp_table("<s3://bucket/path>")

    if __name__ == "__main__":
        run_flow()
### Resources - GitHub Issues: - Verbose logs due to log_prints capturing non-std prints - Improve @flow(log_prints=True) to include appropriate stacklevel - Example Task with Persisted Result These changes and checks should help ensure that your logging integrates smoothly with Prefect, and your logs are visible both in the console and the Prefect UI.
r
@Marvin
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@task(log_prints=True, persist_result=True)
def load_features_folder_to_temp_table(ctx: Context, features_uri) -> str:
    print('Loading features to temp table')
I tried the following and still I don't see anything in the log
m
Let's ensure that your setup captures logs both in the console and the Prefect UI. There could be multiple reasons why logs aren't appearing as expected. Here’s a refined setup to help achieve this: ### Comprehensive Example First, use 
print()
to see if basic logging works. If 
print()
works, then you will know the issue is specific to 
logging.getLogger
.
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python
import logging
from prefect import flow, task

# Configure standard logger
logger = logging.getLogger(__name__)
logger.setLevel(<http://logging.INFO|logging.INFO>)
console_handler = logging.StreamHandler()
console_handler.setLevel(<http://logging.INFO|logging.INFO>)
logger.addHandler(console_handler)

# Ensure the message is in the log
@task(log_prints=True, persist_result=True)
def load_features_folder_to_temp_table(features_uri):
    print('Logging with print statement: Loading features to temp table')
    <http://logger.info|logger.info>('Logging with <http://logger.info|logger.info>: Loading features to temp table')
    return "Features loaded"

@flow
def run_flow():
    load_features_folder_to_temp_table("<s3://bucket/path>")

if __name__ == "__main__":
    run_flow()
### Detailed Explanation 1. Logger Configuration: - Set up the logger as described. - Attach a 
StreamHandler
to ensure logs are output to the console. 2. Task with 
log_prints=True
: - Use both 
print()
and 
<http://logger.info|logger.info>()
inside the task to see which gets captured. 3. Flow Definition: - Define and run the flow to trigger the task. ### Debugging Steps 1. Standalone Log Test: Before adding to Prefect, ensure the logger works:
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python
   <http://logger.info|logger.info>("Standalone log test message")
2. Verbosity and Logging Levels: Double-check the logging level and verbosity:
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python
   import os
   os.environ["PREFECT_LOGGING_LEVEL"] = "INFO"
3. Additional Debugging Inside Task: Add more print statements to troubleshoot if 
log_prints=True
works:
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python
   @task(log_prints=True, persist_result=True)
   def load_features_folder_to_temp_table(features_uri):
       print('Starting task...')
       <http://logger.info|logger.info>('Using logger inside the task.')
       print('Task completed.')
### Prefect Settings Profiling (Optional) Make sure the custom logger is included in Prefect's logging:
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python
from prefect.settings import PREFECT_LOGGING_EXTRA_LOGGERS, update_current_profile

# Update current profile to include the custom logger
update_current_profile({PREFECT_LOGGING_EXTRA_LOGGERS: __name__})
### Resources Reference the GitHub issues if the problem persists: - Task with Persisted Result - Verbose logs with log_prints By following this setup and debugging each step individually, you should be able to identify why the logs are not appearing as expected and ensure they are visible both in the console and the Prefect UI. If further issues arise, feel free to ask!
r
@Marvin I tried to use 
print()
and it doesn't work
m
If using 
print()
statements within a Prefect task with 
log_prints=True
is still not showing up in the logs, let's take a more detailed approach to ensure everything is configured correctly. ### Detailed Step-by-Step Approach 1. Ensure logger and Prefect are working properly: First, verify that the logger itself is working outside of any Prefect context.
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python
import logging

# Configure the logger
logger = logging.getLogger("custom_logger")
logger.setLevel(<http://logging.INFO|logging.INFO>)
console_handler = logging.StreamHandler()
console_handler.setLevel(<http://logging.INFO|logging.INFO>)
logger.addHandler(console_handler)

# Test the logger
<http://logger.info|logger.info>('Standalone logging test')
2. Minimal Prefect Task and Flow Setup: Use a very minimal setup to ensure that logs are being captured correctly.
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python
import logging
from prefect import flow, task

# Configure the logger
logger = logging.getLogger("custom_logger")
logger.setLevel(<http://logging.INFO|logging.INFO>)
console_handler = logging.StreamHandler()
console_handler.setLevel(<http://logging.INFO|logging.INFO>)
logger.addHandler(console_handler)

@task(log_prints=True)
def load_features_folder_to_temp_table():
    print('Logging with print statement: Loading features to temp table')
    <http://logger.info|logger.info>('Logging with <http://logger.info|logger.info>: Loading features to temp table')
    return "Features loaded"

@flow
def run_flow():
    load_features_folder_to_temp_table()

if __name__ == "__main__":
    run_flow()
3. Check Environment Settings: Ensure that the logging level is set correctly in your environment. Prefect might have its own logging settings overriding your configurations.
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python
import os

os.environ["PREFECT_LOGGING_LEVEL"] = "INFO"
4. Prefect Settings: Configure Prefect to ensure it captures extra loggers if necessary.
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python
from prefect.settings import PREFECT_LOGGING_EXTRA_LOGGERS, update_current_profile

update_current_profile({PREFECT_LOGGING_EXTRA_LOGGERS: "custom_logger"})
5. Full Example with Debugging: Integrate all of these steps in a single example to ensure that every part is functioning as expected.
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python
import logging
import os
from prefect import task, flow
from prefect.settings import PREFECT_LOGGING_EXTRA_LOGGERS, update_current_profile

# Environment configuration for logging
os.environ["PREFECT_LOGGING_LEVEL"] = "INFO"

# Configure Prefect logging for custom logger if necessary
update_current_profile({PREFECT_LOGGING_EXTRA_LOGGERS: "__main__"})

# Configure the logger
logger = logging.getLogger("custom_logger")
logger.setLevel(<http://logging.INFO|logging.INFO>)
console_handler = logging.StreamHandler()
console_handler.setLevel(<http://logging.INFO|logging.INFO>)
logger.addHandler(console_handler)

@task(log_prints=True)
def load_features_folder_to_temp_table():
    print('Logging with print statement: Loading features to temp table')
    <http://logger.info|logger.info>('Logging with <http://logger.info|logger.info>: Loading features to temp table')
    return "Features loaded"

@flow
def run_flow():
    load_features_folder_to_temp_table()

if __name__ == "__main__":
    # Standalone test
    <http://logger.info|logger.info>('Standalone logging test outside Prefect')

    # Run Prefect flow
    run_flow()
### Troubleshooting Checklist 1. Standalone Test: Confirm that your logger works independently of Prefect. 2. Task Logging: Ensure the 
@task(log_prints=True)
decorator is correctly applied. 3. Flow Execution: Verify that the flow runs and that there are no suppressed exceptions. 4. Environment Setup: Make sure environments variables and Prefect profiles are correctly set up.
By following these detailed steps and confirming each part independently, you should be able to diagnose why the logs are not showing up in both the console and the Prefect UI. If any part doesn't work as expected, it pinpoints precisely where the issue might be for easier debugging.
r
@Marvin I followed it step by step. 
print()
us to work, but 
<http://logging.info|logging.info>
appears in the console log but not int prefect UI
m
If 
print()
statements are showing up in the Prefect UI but 
<http://logging.info|logging.info>()
is only appearing in the console, the issue might be with how Prefect captures logs from custom loggers. Prefect's log capture mechanics might need some fine-tuning to handle logs from 
logging.getLogger
properly. Let's try focusing on ensuring that Prefect's logging configuration captures your custom logger's output. ### Step-by-Step Configuration 1. Logger Configuration: Make sure your logger is correctly configured. 2. Logging to Prefect UI: Modify the Prefect logging configuration to capture your custom logger. ### Example
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python
import logging
from prefect import flow, task
from prefect import context
from prefect.settings import PREFECT_LOGGING_EXTRA_LOGGERS, update_current_profile

# Update Prefect profile to include the custom logger
update_current_profile({PREFECT_LOGGING_EXTRA_LOGGERS: "custom_logger"})

# Configure the logger
logger = logging.getLogger("custom_logger")
logger.setLevel(<http://logging.INFO|logging.INFO>)
console_handler = logging.StreamHandler()
console_handler.setLevel(<http://logging.INFO|logging.INFO>)
logger.addHandler(console_handler)

@task(log_prints=True)
def load_features_folder_to_temp_table():
    print('Logging with print statement: Loading features to temp table')
    
    <http://logger.info|logger.info>('Logging with <http://logger.info|logger.info>: Loading features to temp table')
    
    # Explicitly logging using Prefect's logging
    context.get_run_context().<http://logger.info|logger.info>('Prefect context logger: Loading features to temp table')
    
    return "Features loaded"

@flow
def run_flow():
    load_features_folder_to_temp_table()

if __name__ == "__main__":
    # Standalone test
    <http://logger.info|logger.info>('Standalone logging test outside Prefect')

    # Run Prefect flow
    run_flow()
### Detailed Breakdown 1. Update Prefect Profile: Make sure Prefect's profile includes your custom logger.
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python
   from prefect.settings import PREFECT_LOGGING_EXTRA_LOGGERS, update_current_profile
   update_current_profile({PREFECT_LOGGING_EXTRA_LOGGERS: "custom_logger"})
2. Configure the Logger: Set up your custom logger as desired.
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python
   logger = logging.getLogger("custom_logger")
   logger.setLevel(<http://logging.INFO|logging.INFO>)
   console_handler = logging.StreamHandler()
   console_handler.setLevel(<http://logging.INFO|logging.INFO>)
   logger.addHandler(console_handler)
3. Task Definition with Prefect Context Logger: Use the Prefect context logger to ensure proper log capture.
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python
   @task(log_prints=True)
   def load_features_folder_to_temp_table():
       print('Logging with print statement: Loading features to temp table')

       <http://logger.info|logger.info>('Logging with <http://logger.info|logger.info>: Loading features to temp table')

       # Explicitly logging using Prefect's logging
       context_logger = context.get_run_context().logger
       <http://context_logger.info|context_logger.info>('Prefect context logger: Loading features to temp table')

       return "Features loaded"
4. Run the Flow: Execute your flow and verify the logs in Prefect UI.
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python
   @flow
   def run_flow():
       load_features_folder_to_temp_table()

   if __name__ == "__main__":
       # Standalone test
       <http://logger.info|logger.info>('Standalone logging test outside Prefect')

       # Run Prefect flow
       run_flow()
### Additional Debugging Tips 1. Logging Configuration in Prefect Settings: Check if 
PREFECT_LOGGING_EXTRA_LOGGERS
properly includes the custom logger:
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python
   from prefect.settings import PREFECT_LOGGING_EXTRA_LOGGERS, update_current_profile
   update_current_profile({PREFECT_LOGGING_EXTRA_LOGGERS: "custom_logger"})
2. Verify Prefect Environment Settings: Make sure Prefect has the correct logging configuration:
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python
   import os
   os.environ["PREFECT_LOGGING_LEVEL"] = "INFO"
3. Check Prefect Logs in UI: Make sure you’re inspecting the logs correctly in the Prefect UI, as sometimes they might be categorized differently.
This setup should ensure Prefect captures logs from both 
print()
and 
logging.getLogger
. If issues persist, it might be worth reviewing the logs at another level or consulting Prefect support for deeper configuration validation.
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