@Marvin generate a demo flow where a 5 tasks are being called concurrently. Then 5 other tasks are being called with the result of the first tasks. Once a task is started, their follow up task must also be started.

To create a flow in Prefect 3.x where tasks are executed concurrently and follow-up tasks depend on their predecessors, you can utilize the

@flow

and

@task

decorators. Here's a concise example that aligns with your requirements:

python
from prefect import flow, task
from prefect.futures import PrefectFuture

@task
def initial_task(task_id: int) -> str:
    return f"Result from task {task_id}"

@task
def follow_up_task(result: str) -> None:
    print(f"Processing {result}")

@flow
def concurrent_flow():
    # Start initial tasks concurrently
    initial_results = [initial_task.submit(i) for i in range(5)]

    # Start follow-up tasks as soon as their corresponding initial task completes
    follow_up_results = [follow_up_task.submit(result) for result in initial_results]

# Execute the flow
if __name__ == "__main__":
    concurrent_flow()

### Explanation: 1. Task Execution: The

initial_task

produces a result, which is then immediately consumed by

follow_up_task

. 2. Concurrency: The

.submit()

method is used to execute tasks concurrently. 3. Dependencies: Each

follow_up_task

waits for its corresponding

initial_task

to complete, ensuring that tasks are executed in pairs. For more details on task concurrency and dependencies in Prefect 3.x, refer to the Prefect documentation.

@Marvin alter the code so that the follow up task will still launch even if the inital task failed. In the initial task, a custom exception can be thrown that has an added data component. The follow up task uses either the result of a completed inital task or the data of the exception in case the initial task failed

To ensure that the follow-up task executes even if the initial task fails, you can define a custom exception with additional data and handle it appropriately. Here's how you can modify your flow:

python
from prefect import flow, task
from prefect.exceptions import PrefectException

class CustomTaskException(PrefectException):
    def __init__(self, message: str, data: str):
        super().__init__(message)
        self.data = data

@task
def initial_task(task_id: int) -> str:
    if task_id % 2 == 0:  # Simulate failure for demonstration
        raise CustomTaskException("Task failed", data=f"Data from task {task_id}")
    return f"Result from task {task_id}"

@task
def follow_up_task(result_or_exception_data: str) -> None:
    print(f"Processing {result_or_exception_data}")

@flow
def concurrent_flow():
    initial_results = []
    for i in range(5):
        try:
            result = initial_task.submit(i).result()
        except CustomTaskException as e:
            result = e.data
        initial_results.append(result)

    follow_up_results = [follow_up_task.submit(result) for result in initial_results]

# Execute the flow
if __name__ == "__main__":
    concurrent_flow()

### Key Points: - Custom Exception:

CustomTaskException

includes a

data

attribute to store additional information. - Error Handling: The

try-except

block in the flow handles exceptions, allowing the flow to continue and use the

data

from the exception. - Task Execution: The follow-up task uses either the result of a successful task or the exception's data. This approach ensures that the follow-up tasks are executed regardless of the initial task's success, using the exception's data if necessary.

@Marvin when running your latest code snippet, the initial tasks are no longer starting concurrently

To ensure that the initial tasks start concurrently, you can submit all tasks first and then handle the results or exceptions. Here's the corrected approach:

python
from prefect import flow, task
from prefect.exceptions import PrefectException
from prefect.futures import PrefectFuture

class CustomTaskException(PrefectException):
    def __init__(self, message: str, data: str):
        super().__init__(message)
        self.data = data

@task
def initial_task(task_id: int) -> str:
    if task_id % 2 == 0:  # Simulate failure for demonstration
        raise CustomTaskException("Task failed", data=f"Data from task {task_id}")
    return f"Result from task {task_id}"

@task
def follow_up_task(result_or_exception_data: str) -> None:
    print(f"Processing {result_or_exception_data}")

@flow
def concurrent_flow():
    # Submit all initial tasks concurrently
    initial_futures = [initial_task.submit(i) for i in range(5)]

    # Process results or exceptions
    for future in initial_futures:
        try:
            result = future.result()
        except CustomTaskException as e:
            result = e.data

        # Submit follow-up task
        follow_up_task.submit(result)

# Execute the flow
if __name__ == "__main__":
    concurrent_flow()

### Explanation: - Concurrent Execution: All initial tasks are submitted first using

.submit()

, ensuring they run concurrently. - Result Handling: After submission, results or exceptions are handled in a loop. - Follow-up Task Submission: Follow-up tasks are submitted immediately after handling the result or exception of each initial task. This ensures that the initial tasks execute concurrently, and follow-up tasks are initiated as soon as their corresponding initial task completes.

@Marvin can you alter the try_catch so that when the initial task raised the exception, the task result is passed to the wait_for of the follow up task to create a dependency line ?

To create a dependency using the

wait_for

parameter in Prefect, you can pass the

PrefectFuture

of the initial task to the follow-up task. Here's how you can modify the code:

python
from prefect import flow, task
from prefect.exceptions import PrefectException
from prefect.futures import PrefectFuture

class CustomTaskException(PrefectException):
    def __init__(self, message: str, data: str):
        super().__init__(message)
        self.data = data

@task
def initial_task(task_id: int) -> str:
    if task_id % 2 == 0:  # Simulate failure for demonstration
        raise CustomTaskException("Task failed", data=f"Data from task {task_id}")
    return f"Result from task {task_id}"

@task
def follow_up_task(result_or_exception_data: str) -> None:
    print(f"Processing {result_or_exception_data}")

@flow
def concurrent_flow():
    # Submit all initial tasks concurrently
    initial_futures = [initial_task.submit(i) for i in range(5)]

    # Process results or exceptions and create dependencies
    for future in initial_futures:
        try:
            result = future.result()
            follow_up_task.submit(result)
        except CustomTaskException as e:
            # Pass the future to wait_for to ensure dependency even on failure
            follow_up_task.submit(e.data, wait_for=[future])

# Execute the flow
if __name__ == "__main__":
    concurrent_flow()

### Key Changes: - Dependency Management: The

follow_up_task

is submitted with the

wait_for

parameter, which includes the

future

of the initial task. This establishes a dependency line, ensuring the follow-up task waits for the initial task to complete, even if it fails. - Exception Handling: The exception data is used, and the dependency is maintained via

wait_for

. This setup ensures that the follow-up tasks are dependent on their respective initial tasks, maintaining the desired execution order and dependencies.

@Marvin in your current code the follow_up task is no longer started if the initial task fails

To ensure that the follow-up task is executed even when the initial task fails, while maintaining a dependency using

wait_for

, you can handle the exception and still submit the follow-up task. Here's how you can achieve this:

python
from prefect import flow, task
from prefect.exceptions import PrefectException
from prefect.futures import PrefectFuture

class CustomTaskException(PrefectException):
    def __init__(self, message: str, data: str):
        super().__init__(message)
        self.data = data

@task
def initial_task(task_id: int) -> str:
    if task_id % 2 == 0:  # Simulate failure for demonstration
        raise CustomTaskException("Task failed", data=f"Data from task {task_id}")
    return f"Result from task {task_id}"

@task
def follow_up_task(result_or_exception_data: str) -> None:
    print(f"Processing {result_or_exception_data}")

@flow
def concurrent_flow():
    # Submit all initial tasks concurrently
    initial_futures = [initial_task.submit(i) for i in range(5)]

    # Process results or exceptions and create dependencies
    for future in initial_futures:
        result = None
        try:
            result = future.result()
        except CustomTaskException as e:
            result = e.data
        finally:
            # Ensure follow-up task is submitted with a dependency on the initial task
            follow_up_task.submit(result, wait_for=[future])

# Execute the flow
if __name__ == "__main__":
    concurrent_flow()

### Explanation: - Exception Handling: The

try-except-finally

structure ensures that the follow-up task is always submitted, even if the initial task fails. - Dependency Management: The

wait_for

parameter is used to create a dependency, ensuring that the follow-up task waits for the initial task to complete, regardless of its success or failure. - Result Handling: The follow-up task uses either the result of the initial task or the exception data. This approach guarantees that the follow-up task is always executed and maintains the dependency on the initial task.