@Marvin can i resume the task from where it failed with data being persisted , and the task should resume from the same state even if the code is changed for the given task , how to achieve so ?

Ah, the timeless quest for immortality of tasks, even in the face of code changes. Who wouldn't want their precious data to persist through the sands of time and chaos of refactoring? Let's figure this out. First, what version of Prefect are you using? 2.x or 3.x? This will help me provide a more relevant answer.

@Marvin i am using prefect 3.x

Ah, the realm of eternal persistence and modularity. Here’s the scoop based on what I found in the Prefect documentation: 1. Resuming Tasks and Persisting Data: Prefect 3.x allows you to manage states effectively, including retries and handling failures. By using state management effectively, you can ensure tasks resume or restart based on specific failure scenarios. Link for more details. 2. State Hooks: Prefect offers state change hooks which you can leverage for custom actions when a task succeeds, fails, or reaches any significant state. This can be an effective way to handle specific requirements like persisting data or taking custom actions on failure/completion. State Hooks. 3. Handling Code Changes: If the task's code changes, but you want to retain its state, you'll need to ensure that the way states and retries are managed remains backward compatible. Prefect’s serialization and task run history can be pivotal here, but ensure your task logic gracefully handles state restoration after code modifications. Unfortunately, achieving this sometimes involves building robust custom mechanisms. Here's a relevant blog article that discusses deploying robust background task architectures. Good luck with your endeavor. It's an uphill battle, but hey, someone has to do it, right?

@Marvin help me with sample code to include the above mentioned issues

Alright, here’s your blueprint for keeping the task spirit alive, even when the codebase morphs beyond recognition. ### Step-by-Step Implementation 1. Using States to Handle Failures and Retries 2. Incorporating State Change Hooks 3. Ensuring Compatibility Across Code Changes Here is a sample implementation:

python
from prefect import task, flow, context
from prefect.states import State, Completed, Failed
import os

@task(on_failure=[lambda t, r, s: print(f"Task {t.name} failed")],
      on_completion=[lambda t, r, s: print(f"Task {t.name} completed with state {s.name}")])
def resilient_task(data):
    # Example state persistence (In reality, use a more robust storage like a database or Prefect's result storage)
    last_state = context.get("last_state", {})
    print(f"Last known state: {last_state}")

    # Simulate task logic
    try:
        if os.environ.get("SHOULD_FAIL", "false").lower() == "true":
            raise Exception("Simulated failure")

        # Task successfully processed data
        return {"status": "success", "processed_data": data}
    except Exception as e:
        return Failed(result={"status": "failure", "reason": str(e)})

@flow
def parent_flow(data):
    # Attempt to retrieve last run's state
    state = resilient_task.submit(data).result()
    if isinstance(state, Failed):
        print(f"Task failed with reason: {state.result['reason']}")
        # Ensure state/retry logic is invoked (could be more advanced, e.g., implementing exponential backoff)
        resilient_task.with_options(retries=3, retry_delay_seconds=10).submit(data)
    else:
        print(f"Task succeeded with result: {state.result}")

if __name__ == "__main__":
    # Set environment variable to simulate task failure
    os.environ["SHOULD_FAIL"] = "true"
    parent_flow(data="sample data")

### Explanation 1. Task Definition: - `resilient_task`: Custom Prefect task that processes data. - Uses state hooks (

on_failure

,

on_completion

) to perform actions based on the task's state. - Persists last known state using the context (replace this with more robust storage in production). 2. Flow Definition: - `parent_flow`: Calls the

resilient_task

. - Checks the state of the task and retries if necessary (you can add more sophisticated retry mechanisms). ### Details - Retries: Prefect allows tasks to be retried automatically based on configurations. - State Persistence: Use Prefect's result storage for real-world use (the demo uses in-memory context). - State Hooks: Log or handle states specifically using hooks. For an in-depth understanding, visit the Prefect docs on state management. Good luck slogging through code evolutions and state persistence! I’m sure your tasks will be eternally grateful for your efforts.

@Marvin how does it handle the issue of code refactor if task fail

Ah, the inevitable twists and turns of code refactoring. Handling task failures gracefully while ensuring compatibility despite code changes is no small feat. Let’s look into how you can manage this in Prefect. ### Key Considerations 1. State Storage and Retrieval: Ensuring the state is stored externally, so it's immune to code changes. 2. Backward Compatibility: Designing tasks to understand and process previous state formats. 3. Versioning: Using versioning to handle different code bases gracefully. ### Implementation Details Below is an extended version of the previous example tailored to handle code refactoring scenarios:

python
from prefect import task, flow, context
from prefect.states import State, Completed, Failed
import os
import json

# Simulate an external storage (like Redis, S3, etc.)
external_state_storage_path = "task_state.json"

def save_state(task_name, state):
    """Simulated external state saving."""
    previous_states = load_all_states()
    previous_states[task_name] = state
    with open(external_state_storage_path, "w") as f:
        json.dump(previous_states, f)

def load_state(task_name):
    """Simulated external state loading."""
    all_states = load_all_states()
    return all_states.get(task_name, {})

def load_all_states():
    """Loads all previous states from simulated storage."""
    if os.path.exists(external_state_storage_path):
        with open(external_state_storage_path, "r") as f:
            return json.load(f)
    return {}

@task(name="resilient_task", on_failure=[lambda t, r, s: print(f"Task {t.name} failed")],
      on_completion=[lambda t, r, s: print(f"Task {t.name} completed with state {s.name}")])
def resilient_task(data):
    # Load the last known state from external storage
    last_state = load_state(task_name="resilient_task")
    print(f"Last known state: {last_state}")

    # Task logic
    try:
        if os.environ.get("SHOULD_FAIL", "false").lower() == "true":
            raise Exception("Simulated failure")

        # Task successfully processed data
        result = {"status": "success", "processed_data": data, "version": "v2"}
        save_state("resilient_task", result)  # Save the successful state externally
        return Completed(result=result)
    except Exception as e:
        failure_state = Failed(result={"status": "failure", "reason": str(e), "version": "v2"})
        save_state("resilient_task", failure_state)  # Save the failure state externally
        return failure_state

@flow
def parent_flow(data):
    # Call the resilient_task and handle retries
    state = resilient_task.submit(data).result()
    if isinstance(state, Failed):
        print(f"Task failed with reason: {state.result['reason']}")
        # Example retry mechanism
        resilient_task.with_options(retries=3, retry_delay_seconds=10).submit(data)
    else:
        print(f"Task succeeded with result: {state.result}")

if __name__ == "__main__":
    # Set environment variable to simulate task failure
    os.environ["SHOULD_FAIL"] = "true"
    parent_flow(data="sample data")

### Explanation 1. External State Storage: - States are saved and loaded from an external storage (here simulated using a JSON file). - This ensures the state persists across different runs, even if there are code changes. 2. Backward Compatibility: - Each state is tagged with a version. - When loading the state, handle different versions accordingly in your task logic. 3. Retries and State Hooks: - As before, retries and state hooks provide robust mechanisms to handle failures and completions. ### Key Adjustments - External Storage: In practice, replace the JSON file with a robust storage backend (e.g., databases, cloud storage). - State Versioning: By including a version in your state, you can handle backward compatibility when refactoring code.

@Marvin eror: TypeError: Object of type State is not JSON serializable 153200.048 | ERROR | Flow run 'loose-quokka' - Finished in state Failed('Flow run encountered an exception: TypeError: Object of type State is not JSON serializable') Traceback (most recent call last): File "/home/ankit/grepsr/pline-workflows/test.py", line 47, in resilient_task raise Exception("Simulated failure") Exception: Simulated failure During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/ankit/grepsr/pline-workflows/test.py", line 76, in <module> parent_flow(data="sample data") File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/flows.py", line 1334, in call return run_flow( ^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/flow_engine.py", line 810, in run_flow return run_flow_sync(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/flow_engine.py", line 690, in run_flow_sync return engine.state if return_type == "state" else engine.result() ^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/flow_engine.py", line 250, in result raise self._raised File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/flow_engine.py", line 644, in run_context yield self File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/flow_engine.py", line 688, in run_flow_sync engine.call_flow_fn() File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/flow_engine.py", line 667, in call_flow_fn result = call_with_parameters(self.flow.fn, self.parameters) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/utilities/callables.py", line 206, in call_with_parameters return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/test.py", line 64, in parent_flow state = resilient_task.submit(data).result() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/futures.py", line 164, in result _result = self._final_state.result( ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/client/schemas/objects.py", line 263, in result return get_state_result( ^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/states.py", line 69, in get_state_result return _get_state_result( ^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/utilities/asyncutils.py", line 392, in coroutine_wrapper return run_coro_as_sync(ctx_call()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/utilities/asyncutils.py", line 243, in run_coro_as_sync return call.result() ^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/_internal/concurrency/calls.py", line 312, in result return self.future.result(timeout=timeout) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/_internal/concurrency/calls.py", line 182, in result return self.__get_result() ^^^^^^^^^^^^^^^^^^^ File "/usr/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result raise self._exception File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/_internal/concurrency/calls.py", line 383, in _run_async result = await coro ^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/utilities/asyncutils.py", line 225, in coroutine_wrapper return await task ^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/utilities/asyncutils.py", line 382, in ctx_call result = await async_fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/states.py", line 128, in _get_state_result raise await get_state_exception(state) File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 755, in run_context yield self File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 1308, in run_task_sync engine.call_task_fn(txn) File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 778, in call_task_fn result = call_with_parameters(self.task.fn, parameters) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/utilities/callables.py", line 206, in call_with_parameters return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/test.py", line 57, in resilient_task save_state("resilient_task", failure_state) # Save the failure state externally ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/test.py", line 15, in save_state json.dump(previous_states, f) File "/usr/lib/python3.12/json/__init__.py", line 179, in dump for chunk in iterable: File "/usr/lib/python3.12/json/encoder.py", line 432, in _iterencode yield from _iterencode_dict(o, _current_indent_level) File "/usr/lib/python3.12/json/encoder.py", line 406, in _iterencode_dict yield from chunks File "/usr/lib/python3.12/json/encoder.py", line 439, in _iterencode o = _default(o) ^^^^^^^^^^^ File "/usr/lib/python3.12/json/encoder.py", line 180, in default raise TypeError(f'Object of type {o.class.name} ' TypeError: Object of type State is not JSON serializable

Your message was too long by 1498 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:

eror:

TypeError: Object of type State is not JSON serializable 153200.048 | ERROR | Flow run 'loose-quokka' - Finished in state Failed('Flow run encountered an exception: TypeError: Object of type State is not JSON serializable') Traceback (most recent call last): File "/home/ankit/grepsr/pline-workflows/test.py", line 47, in resilient_task raise Exception("Simulated failure") Exception: Simulated failure During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/ankit/grepsr/pline-workflows/test.py", line 76, in <module> parent_flow(data="sample data") File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/flows.py", line 1334, in call return run_flow( ^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/flow_engine.py", line 810, in run_flow return run_flow_sync(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/pref

@Marvin errror: Traceback (most recent call last): File "/home/ankit/grepsr/pline-workflows/test.py", line 47, in resilient_task raise Exception("Simulated failure") Exception: Simulated failure During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 755, in run_context yield self File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 1308, in run_task_sync engine.call_task_fn(txn) File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 778, in call_task_fn result = call_with_parameters(self.task.fn, parameters) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/utilities/callables.py", line 206, in call_with_parameters return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/test.py", line 57, in resilient_task save_state("resilient_task", failure_state) # Save the failure state externally ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/test.py", line 15, in save_state json.dump(previous_states, f) File "/usr/lib/python3.12/json/__init__.py", line 179, in dump for chunk in iterable: File "/usr/lib/python3.12/json/encoder.py", line 432, in _iterencode yield from _iterencode_dict(o, _current_indent_level) File "/usr/lib/python3.12/json/encoder.py", line 406, in _iterencode_dict yield from chunks File "/usr/lib/python3.12/json/encoder.py", line 439, in _iterencode o = _default(o) ^^^^^^^^^^^ File "/usr/lib/python3.12/json/encoder.py", line 180, in default raise TypeError(f'Object of type {o.class.name} ' TypeError: Object of type State is not JSON serializable

Your message was too long by 259 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:

errror:

Traceback (most recent call last): File "/home/ankit/grepsr/pline-workflows/test.py", line 47, in resilient_task raise Exception("Simulated failure") Exception: Simulated failure During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 755, in run_context yield self File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 1308, in run_task_sync engine.call_task_fn(txn) File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 778, in call_task_fn result = call_with_parameters(self.task.fn, parameters) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/utilities/callables.py", line 206, in call_with_parameters return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File "/home/ankit/greps

@Marvin Traceback (most recent call last): File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 755, in run_context yield self File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 1308, in run_task_sync engine.call_task_fn(txn) File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/task_engine.py", line 778, in call_task_fn result = call_with_parameters(self.task.fn, parameters) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ankit/grepsr/pline-workflows/.venv/lib/python3.12/site-packages/prefect/utilities/callables.py", line 206, in call_with_parameters return fn(*args, **kwargs)

Ah, the sweet melody of stack traces. Let's get this sorted for you. The error you've shared points towards an issue when trying to run your task function. Unfortunately, the traceback doesn't provide the exact error message from your task function. However, let's address some common pitfalls: ### Debugging Steps 1. Inspect Full Traceback: Check the entire traceback to identify the exact error within the task function. 2. Verify External State Functions: Ensure the state-saving and loading functions are functioning correctly. 3. Environment Variables and Task Logic: Check for issues with environment variables and the task logic that might cause an exception. ### Updating the Code with Additional Debugging

python
from prefect import task, flow, context
from prefect.states import State, Completed, Failed
import os
import json

# Simulate an external storage (like Redis, S3, etc.)
external_state_storage_path = "task_state.json"

def save_state(task_name, state):
    """Simulated external state saving."""
    previous_states = load_all_states()
    previous_states[task_name] = state
    with open(external_state_storage_path, "w") as f:
        json.dump(previous_states, f)

def load_state(task_name):
    """Simulated external state loading."""
    all_states = load_all_states()
    return all_states.get(task_name, {})

def load_all_states():
    """Loads all previous states from simulated storage."""
    if os.path.exists(external_state_storage_path):
        with open(external_state_storage_path, "r") as f:
            return json.load(f)
    return {}

@task(name="resilient_task", on_failure=[lambda t, r, s: print(f"Task {t.name} failed")],
      on_completion=[lambda t, r, s: print(f"Task {t.name} completed with state {s.name}")])
def resilient_task(data):
    try:
        # Load the last known state from external storage
        last_state = load_state(task_name="resilient_task")
        print(f"Last known state: {last_state}")

        # Task logic
        if os.environ.get("SHOULD_FAIL", "false").lower() == "true":
            raise Exception("Simulated failure")

        # Task successfully processed data
        result = {"status": "success", "processed_data": data, "version": "v2"}
        save_state("resilient_task", result)  # Save the successful state externally
        return Completed(result=result)
    except Exception as e:
        failure_state = Failed(result={"status": "failure", "reason": str(e), "version": "v2"})
        save_state("resilient_task", failure_state)  # Save the failure state externally
        return failure_state

@flow
def parent_flow(data):
    try:
        # Call the resilient_task and handle retries
        state = resilient_task.submit(data).result()
        if isinstance(state, Failed):
            print(f"Task failed with reason: {state.result['reason']}")
            # Example retry mechanism
            resilient_task.with_options(retries=3, retry_delay_seconds=10).submit(data)
        else:
            print(f"Task succeeded with result: {state.result}")
    except Exception as e:
        print(f"Flow encountered an exception: {str(e)}")

if __name__ == "__main__":
    # Set environment variable to simulate task failure
    os.environ["SHOULD_FAIL"] = "true"
    parent_flow(data="sample data")

### Additional Debugging Tips 1. Print Statements: - Add more print statements before and after key operations to track progress and identify issues. 2. Complete Traceback: - If possible, provide the complete traceback so I can identify the exact problem. 3. Check Versions: - Ensure you are using compatible versions of Prefect and other dependencies. Run the updated code and see if it helps in narrowing down the issue. Keep me posted with the complete traceback if the issue persists!

TypeError: Object of type State is not JSON serializable

Ah, the classic "JSON serialization" conundrum when dealing with complex objects. Prefect's

State

object isn't directly serializable to JSON. Let's modify your functions to handle this. ### Solution 1. Serialize State Objects: Convert the

State

object to a JSON-compatible format before saving it. 2. Deserialize State Objects: Convert the JSON-compatible format back to a Prefect

State

object when loading. ### Updated Code

python
from prefect import task, flow, context
from prefect.states import State, Completed, Failed
import os
import json

# Simulate an external storage (like Redis, S3, etc.)
external_state_storage_path = "task_state.json"

def serialize_state(state):
    """Convert State object to a JSON-compatible dictionary."""
    return {
        "type": type(state).__name__,
        "result": state.result,
        "message": state.message,
    }

def deserialize_state(state_dict):
    """Convert JSON-compatible dictionary back to a State object."""
    state_type = state_dict.get("type")
    state_cls = globals().get(state_type)
    if state_cls:
        return state_cls(
            result=state_dict.get("result"),
            message=state_dict.get("message")
        )
    return None

def save_state(task_name, state):
    """Simulated external state saving."""
    previous_states = load_all_states()
    previous_states[task_name] = serialize_state(state)
    with open(external_state_storage_path, "w") as f:
        json.dump(previous_states, f)

def load_state(task_name):
    """Simulated external state loading."""
    all_states = load_all_states()
    state_dict = all_states.get(task_name, {})
    return deserialize_state(state_dict)

def load_all_states():
    """Loads all previous states from simulated storage."""
    if os.path.exists(external_state_storage_path):
        with open(external_state_storage_path, "r") as f:
            return json.load(f)
    return {}

@task(name="resilient_task", on_failure=[lambda t, r, s: print(f"Task {t.name} failed")],
      on_completion=[lambda t, r, s: print(f"Task {t.name} completed with state {s.name}")])
def resilient_task(data):
    try:
        # Load the last known state from external storage
        last_state = load_state(task_name="resilient_task")
        print(f"Last known state: {last_state}")

        # Task logic
        if os.environ.get("SHOULD_FAIL", "false").lower() == "true":
            raise Exception("Simulated failure")

        # Task successfully processed data
        result = Completed(result={"status": "success", "processed_data": data, "version": "v2"})
        save_state("resilient_task", result)  # Save the successful state externally
        return result
    except Exception as e:
        failure_state = Failed(result={"status": "failure", "reason": str(e), "version": "v2"})
        save_state("resilient_task", failure_state)  # Save the failure state externally
        return failure_state

@flow
def parent_flow(data):
    try:
        # Call the resilient_task and handle retries
        state = resilient_task.submit(data).result()
        if isinstance(state, Failed):
            print(f"Task failed with reason: {state.result['reason']}")
            # Example retry mechanism
            resilient_task.with_options(retries=3, retry_delay_seconds=10).submit(data)
        else:
            print(f"Task succeeded with result: {state.result}")
    except Exception as e:
        print(f"Flow encountered an exception: {str(e)}")

if __name__ == "__main__":
    # Set environment variable to simulate task failure
    os.environ["SHOULD_FAIL"] = "true"
    parent_flow(data="sample data")

### Explanation 1. Serialization and Deserialization Functions: - `serialize_state`: Converts a Prefect

State

object to a JSON-compatible dictionary. - `deserialize_state`: Converts a JSON-compatible dictionary back to a Prefect

State

object. 2. Updated save_state and load_state: