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# marvin-in-the-wild

Mitch

06/12/2024, 1:29 AM

@Marvin What is the recommended way to add breakpoints and view variables while debugging flow code locally?

Marvin

06/12/2024, 1:29 AM

To add breakpoints and view variables while debugging your Prefect flow code locally, here are some recommended steps: 1. Using built-in Python debugging tools: You can use traditional debugging tools such as

pdb

(Python Debugger) or IDE-specific breakpoints.

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python
    import pdb

    @task
    def my_task():
        x = 10
        pdb.set_trace()  # This will add a breakpoint
        return x * 10

    with Flow("debug-flow") as flow:
        result = my_task()

2. Running flows locally: Make sure to run your flows locally for a smoother debugging experience. Prefect allows you to run flows directly without interacting with the API, which makes local debugging easier.

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python
    if __name__ == "__main__":
        flow.run()

3. Using
flow.run
with agents: Instead of suggesting

prefect agent

, you should use

prefect worker

as agents are deprecated. 4. Viewing variables and task states: Prefect's logging system helps in viewing task states and debugging outputs. You can set up logs within your tasks:

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python
    from prefect import task, flow

    @task
    def my_task():
        x = 10
        <http://prefect.context.logger.info|prefect.context.logger.info>(f"Variable x value: {x}")
        return x * 10

    @flow
    def debug_flow():
        result = my_task()
        <http://prefect.context.logger.info|prefect.context.logger.info>(f"Task result: {result}")
        
    if __name__ == "__main__":
        debug_flow()

5. References: - For more detailed guidance on deploying tasks and debugging, you can check the Prefect's Overriding Job Variables guide. - Additionally, Prefect discusses how to handle local debugging with agents in some GitHub conversations, e.g., using

flow.run(with_backend=True)

for local API testing. If you require more tailored debugging tips for specific issues or setups, feel free to ask!

Mitch

06/12/2024, 1:30 AM

@Marvin Can I use the vscode debugger's breakpoints with deployed flows?

Marvin

06/12/2024, 1:31 AM

Using VSCode's debugger breakpoints directly with deployed flows might not be straightforward, but here's a systematic approach to enable debugging for your Prefect deployments: 1. Local Development: - First, develop and test your flows locally using VSCode's built-in debugger. You can use

pdb

for breakpoints or VSCode's debugging tools. - Example of setting a breakpoint:

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python
    import pdb
    from prefect import flow, task

    @task
    def my_task():
        x = 10
        pdb.set_trace()  # Add breakpoint here
        return x * 10

    @flow
    def debug_flow():
        result = my_task()
        return result

    if __name__ == "__main__":
        debug_flow()

2. Use Prefect Worker for Local Execution: - Ensure to use

prefect worker

for local execution. This helps in running and debugging flows locally. - Example command:

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sh
     prefect worker start

3. Deploying with Infrastructure and Source Control: - If you deploy your flow from a source control repository (like GitHub) or use storage blocks, you can still run and debug using a local setup before deployment. - Documentation link: Prefect Deployment Storage Guide 4. Auto-Update Deployed Code: - Use

flow.serve

to automatically update your deployed flow if changes are made to the codebase. - Example setup from GitHub:

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python
     from prefect import flow
     from prefect.deployments import Deployment
     from prefect.filesystems import GitHub

     @flow
     def my_flow(name: str = "world"):
         print(f"Hello {name}! I'm a flow from a GitHub repo!")

     if __name__ == "__main__":
         deploy = Deployment.build_from_flow(
             flow=my_flow,
             name="my-deployment",
             storage=GitHub.load("demo-repo"),
             entrypoint="example.py:my_flow"
         )
         deploy.apply()

5. Remote Debugging with Logs: - For debugging deployed flows, use Prefect’s logging to check the value of variables and states:

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python
     from prefect import task, flow

     @task(log_prints=True)
     def my_task():
         x = 10
         <http://prefect.context.logger.info|prefect.context.logger.info>(f"Variable x value: {x}")
         return x * 10

     @flow
     def debug_flow():
         result = my_task()
         <http://prefect.context.logger.info|prefect.context.logger.info>(f"Task result: {result}")
         return result

For more intricate debugging involving cloud or remote setups, you may need to configure remote debugging in VSCode by setting up SSH tunnels or using cloud provider debugging tools. References: - Prefect Storage Guide - Upgrading Agents to Workers If you need more detailed steps on any specific part, feel free to ask!

Mitch

06/12/2024, 1:37 AM

@Marvin Is there a way for me to set VSCode breakpoints that show me interactively the lists of variables and let me hop into function or continue running the flow code (LOCALLY)

Marvin

06/12/2024, 1:37 AM

Yes, you can set up VSCode breakpoints for a more interactive debugging experience, allowing you to view variables, step into functions, and continue running your flow code locally. Here's a step-by-step guide to achieving this: ### Step 1: Set Up VSCode for Python Debugging 1. Install the Python extension for VSCode if you haven't already. 2. Create a
launch.json
file in the

.vscode

directory of your project. This file configures the VSCode debugger to run your Python script. ### Step 2: Configure

launch.json

Create or modify the

.vscode/launch.json

file to include a configuration for launching your Prefect flow:

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json
{
  "version": "0.2.0",
  "configurations": [
    {
      "name": "Python: Current File",
      "type": "python",
      "request": "launch",
      "program": "${file}",
      "console": "integratedTerminal"
    }
  ]
}

### Step 3: Add Breakpoints in Your Code Open your Python file and click in the gutter to the left of the line numbers to add breakpoints. Alternatively, you can use the

F9

key to toggle breakpoints. ### Step 4: Example Prefect Flow with Tasks Here’s an example of a Prefect flow with a task where you want to debug using breakpoints:

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python
from prefect import flow, task

@task
def my_task():
    x = 10
    # You can add a breakpoint here by clicking in the gutter in VSCode 
    return x * 10

@flow
def debug_flow():
    result = my_task()
    return result

if __name__ == "__main__":
    debug_flow()

### Step 5: Start Debugging 1. Open the file containing your flow (e.g.,

main.py

). 2. Set breakpoints by clicking on the left gutter in VSCode where you want your code to pause. 3. Press

F5

to start the debugging session. The debugger will pause execution at the breakpoints, and you can now inspect variables, step through code, or continue execution. ### Step 6: Interact with Debugger - Inspect Variables: Hover over variables to see their current values. - Debug Console: Use the Debug Console to evaluate expressions. - Step Controls: Use the controls in the top toolbar to step over, step into, or continue running the code. ### Step 7: Using Debug Controls - Continue (F5): Continue running the program until the next breakpoint. - Step Over (F10): Execute the current line and move to the next line. - Step Into (F11): Step into functions to inspect their execution. - Step Out (Shift+F11): Step out of the current function back to the caller. ### Summary Using VSCode's debugging features allows you to: - Set breakpoints. - View and inspect variable values. - Step through your code line by line. - Evaluate expressions in the debug console. By following the steps above, you can effectively debug your Prefect flow code locally using VSCode. If you have any specific issues or need more detailed guidance on a particular aspect, feel free to ask!

Mitch

06/12/2024, 1:38 AM

@Marvin Will this allow me to actually actually debug flows served with

.serve()

Marvin

06/12/2024, 1:38 AM

Currently, using VSCode's interactive debugging tools directly with flows served via

.serve()

in Prefect isn't officially supported. However, you can still achieve a similar debugging experience by employing the right techniques and configurations. Here’s how you can do it: ### Debugging a Flow Served with

.serve()

1. Initial Local Debugging: - Before deploying your flow using

.serve()

, initially debug your flow locally using breakpoints and VSCode's debugger to ensure that the core functionality is correct. 2. Use Prefect's Logging: - Prefect provides logging capabilities that can be useful for understanding the state of your flow and tasks when running in a served deployment. This will help in logging variable states and understanding flow execution. 3. Breakpoint in Locally Served Flows: - If you want to add breakpoints and step through the code interactively while serving the flow, you can achieve this by adding breakpoints using the

pdb

library and then running the serve command manually in a separate terminal. ### Example Setup #### Step 1: Create Your Flow

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python
import prefect
from prefect import flow, task

@task
def my_task():
    x = 10
    <http://prefect.context.logger.info|prefect.context.logger.info>(f"Variable x value: {x}")
    return x * 10

@flow(log_prints=True)
def debug_flow():
    result = my_task()
    return result

if __name__ == "__main__":
    # For initial debugging using VSCode
    debug_flow()

#### Step 2: Debug Locally Using

pdb

Add a breakpoint using

pdb

in your task:

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python
import pdb

@task
def my_task():
    x = 10
    pdb.set_trace()  # Add a breakpoint here
    return x * 10

Run your flow in the VSCode debugger to debug interactively. #### Step 3: Serve Your Flow After initial debugging, modify your entry point to serve the flow:

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python
if __name__ == "__main__":
    debug_flow.serve(name="debug-deployment", interval=60)

Run the serve command manually in a terminal:

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bash
python your_flow_file.py

### Use the Debug Console When the flow pauses at the

pdb.set_trace()

breakpoint, you can interact with it using the terminal where you ran the serve command. You can inspect variables, step through the code, and continue execution. ### Summary - Local Debugging: Start by adding breakpoints and debugging locally using VSCode's debugger. - Log Variables: Use Prefect's logging capabilities to log variable states. - Manual Serve with Breakpoints: Add

pdb.set_trace()

breakpoints and run the serve command manually for interactive debugging. Using these steps, you can achieve an interactive debugging experience for flows served with

.serve()

while leveraging VSCode's powerful debugging features. References: - Prefect Concepts - Flows - Prefect Cloud - Connecting If you have more specific needs or run into issues, feel free to ask for further assistance!

Marvin

06/13/2024, 8:28 PM

Using VSCode's interactive debugging tools directly with flows served using

flow.serve

is not officially supported. Here are the challenges and potential workarounds: ### Challenges: 1. Interactive Debugging: When using

.serve()

, the flow is continuously monitored and initiated by Prefect's infrastructure, making it difficult to attach a debugger like VSCode's interactive debugger. 2. Concurrency: Flows executing in a served environment might have different lifecycles and execution contexts than those run directly for debugging purposes. ### Workarounds: 1. Use
pdb
for Local Interaction: You can still use

pdb

to insert breakpoints and manually run

flow.serve()

in a local terminal. 2. Prefect Logging: Logging can be essential for tracking variable states and task outputs when debugging indirectly via

flow.serve()

. ### Example: #### Step 1: Define Flow with

pdb

Breakpoints Add breakpoints using

pdb

and inspect the variables:

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python
import pdb
from prefect import flow, task

@task
def my_task():
    x = 10
    pdb.set_trace()  # Add breakpoint here
    return x * 10

@flow(log_prints=True)
def debug_flow():
    result = my_task()
    return result

if __name__ == "__main__":
    # Use .serve() to continuously monitor and serve the flow
    debug_flow.serve(name="debug-deployment", interval=60)

#### Step 2: Run the Flow with

pdb

1. Open a Terminal: Open a separate terminal window. 2. Run Your Script: Execute your script that contains

flow.serve()

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sh
python your_flow_file.py

3. Interact with pdb: When execution hits

pdb.set_trace()

, the process pauses, and you can interact with it using the terminal. - Inspect variables. - Step through the code. - Continue execution.

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sh
> /path/to/your_script.py(8)my_task()
-> return x * 10
(Pdb) print(x)
10
(Pdb) n
> /path/to/your_script.py(12)debug_flow()
-> result = my_task()
...

# Continue execution
(Pdb) c

### Alternative: Locally Debug Before Serving It's always advisable to thoroughly debug the flow locally before wrapping it with `.serve()`:

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python
if __name__ == "__main__":
    # For local debugging
    debug_flow()

This allows you to use VSCode’s interactive debugger fully: 1. Set breakpoints by clicking in the left margin. 2. Run the debugger with

F5

. 3. Inspect variables, step through the code line by line, and evaluate expressions in the Debug Console. ### Key Takeaways - Direct Interaction: Full VSCode interaction with served flows isn't straightforward due to the nature of

.serve()

. - Use pdb: Utilize

pdb

for local, interactive debugging before deploying with

.serve()

. - Logging: Heavily rely on Prefect's logging to trace execution when debugging served flows. If you run into specific issues or have further questions, please let me know!

Mitch

06/13/2024, 8:30 PM

@Marvin is there a way to interact with VSCode's interactive debugger while wrapping the code with .server()? Possibly by attaching to the running process?

Marvin

06/13/2024, 8:31 PM

Yes, it is possible to interact with VSCode's interactive debugger with flows wrapped with

.serve()

by attaching the debugger to the running process. This approach allows you to set breakpoints, inspect variables, and step through the code. Here’s how you can achieve this: ### Step-by-Step Guide 1. Configure VSCode for Remote Debugging: - Install the

ptvsd

package (Python Tools for Visual Studio Debugging). You can do this with the following command:

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sh
     pip install ptvsd

2. Update Your Flow Script: - Add the

ptvsd

setup to your script to enable the remote debugger. This will listen for VSCode to attach.

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python
    import ptvsd
    from prefect import flow, task

    # Enable ptvsd on the script entry point
    ptvsd.enable_attach(address=('localhost', 5678), redirect_output=True)
    print("Waiting for debugger attach...")
    ptvsd.wait_for_attach()

    @task
    def my_task():
        x = 10
        # Add a breakpoint here in your code
        return x * 10

    @flow(log_prints=True)
    def debug_flow():
        result = my_task()
        return result

    if __name__ == "__main__":
        debug_flow.serve(name="debug-deployment", interval=60)

3. Set Up VSCode to Attach to the Process: - Configure the

launch.json

in the

.vscode

folder to attach to the running process:

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json
     {
       "version": "0.2.0",
       "configurations": [
         {
           "name": "Python: Attach",
           "type": "python",
           "request": "attach",
           "connect": {
             "host": "localhost",
             "port": 5678
           },
           "justMyCode": true
         }
       ]
     }

4. Run Your Script: - Start your script in a terminal:

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sh
     python your_flow_file.py

- Ensure that the output shows "Waiting for debugger attach..." 5. Attach the VSCode Debugger: - Open VSCode. - Go to the Debug panel. - Select the "Python: Attach" configuration. - Click the green play button or press

F5

. 6. Set Breakpoints and Debug: - You can now set breakpoints in your code within VSCode. - The debugger will stop at these breakpoints, and you can inspect variables, step through the code, etc. ### Example Flow Script Here's a full example to reiterate the above steps:

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python
import ptvsd
from prefect import flow, task

# Enable ptvsd on the script entry point
ptvsd.enable_attach(address=('localhost', 5678), redirect_output=True)
print("Waiting for debugger attach...")
ptvsd.wait_for_attach()

@task
def my_task():
    x = 10
    # Add a breakpoint here in your code
    return x * 10

@flow(log_prints=True)
def debug_flow():
    result = my_task()
    return result

if __name__ == "__main__":
    debug_flow.serve(name="debug-deployment", interval=60)

### Launch Configuration (launch.json)

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json
{
  "version": "0.2.0",
  "configurations": [
    {
      "name": "Python: Attach",
      "type": "python",
      "request": "attach",
      "connect": {
        "host": "localhost",
        "port": 5678
      },
      "justMyCode": true
    }
  ]
}

### Conclusion By following these steps, you can interactively debug your Prefect flows wrapped with

.serve()

using VSCode's powerful interactive debugger. This setup leverages remote debugging via the

ptvsd

library, allowing you to attach to a running process and take full advantage of VSCode's debugging capabilities. If you encounter any issues or need further assistance, feel free to ask!

Mitch

06/13/2024, 8:40 PM

@Marvin Thank you, this was a good answer

Marvin

06/13/2024, 8:40 PM

You're welcome! I'm glad to hear that it was helpful. If you have any more questions or need further assistance with Prefect, debugging, or anything else related to Python and software development, feel free to reach out. Happy coding!

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