@Marvin How can I interact with the cache Results manually from an interactive Python session?

It seems like I had a technical hiccup while trying to determine the latest Prefect version and searching the documentation. I'll now search the appropriate Prefect 2.x and 3.x documentation for guidance on interacting with cached Results manually. Let's see how Prefect handles cached Results across different versions. To manually interact with cache results in an interactive Python session using Prefect, you'll need to understand how Prefect manages caching and apply some specific techniques outlined in the Prefect documentation. ### Prefect 2.x - Caching and Refreshing: In Prefect 2.x, task results are cached in memory during a flow run and persisted based on the

PREFECT_LOCAL_STORAGE_PATH

setting. Caching is limited to flows with access to that storage path. - Manual Cache Key: You can define a custom cache key function to alter caching behavior. Here’s an example:

python
  def cache_within_flow_run(context, parameters):
      return f"{context.task_run.flow_run_id}-{task_input_hash(context, parameters)}"

  @task(cache_key_fn=cache_within_flow_run)
  def cached_task():
      print('running an expensive operation')
      return 42

- Refreshing Cache: To refresh the cache and force a task to update its data, use the

refresh_cache

option:

python
  def static_cache_key(context, parameters):
      return "static cache key"

  @task(cache_key_fn=static_cache_key, refresh_cache=True)
  def caching_task():
      return random.random()

### Prefect 3.x - Task Caching: In Prefect 3.x, caching involves tasks entering a

Completed

state without re-running the defined code, based on inputs, code definition, and flow/task run ID. - Cache Key: Customize the cache key similarly to Prefect 2.x using attributes like input and run IDs for idempotency. - Refresh Cache: Use

refresh_cache

to ignore existing cache and rerun tasks. You can also set

PREFECT_TASKS_REFRESH_CACHE=true

to refresh caches for all tasks globally. - Example:

python
  import random

  def static_cache_key(context, parameters):
      return "static cache key"

  @task(cache_key_fn=static_cache_key, refresh_cache=True)
  def caching_task():
      return random.random()

Links to Prefect documentation: - Prefect 2.x: Prefect 2.x Caching - Prefect 3.x: Prefect 3.x Caching These examples and explanations should help you to interact with and manage cached results in an interactive Python session using Prefect. If you have specific use cases or need more detailed guidance, feel free to ask!

And how does prefect load a cached Result?

The "RolledBack" status in Prefect typically relates to transaction management within flow and task executions. Here's how it is generally understood in the context of Prefect: ### Prefect 3.x - Transactional Context: Prefect transactions involve multiple stages, including staging, committing, and rolling back. If any error occurs after data has been staged but before it’s committed, the transaction is rolled back. This means that any staged changes are discarded, and the task or transaction is effectively undone. - Commit and Rollback: Transactions can either: - Commit: Successfully complete and apply all changes. - Rollback: Encounter an error and revert all changes back to the original state. Such a rollback typically happens after an error is detected during the transaction, affecting the parent transaction and any subtransactions. This ensures that the system's state remains consistent even if individual operations fail. You can refer to some detailed documentation on Prefect 3.x handling of transactions here: Prefect 3.x Transactions. ### Prefect 2.x I could not find direct references to the "RolledBack" status in the Prefect 2.x documentation through my search. Prefect 2.x documentation might handle this through different terminologies or within a broader explanation of task retries or state management. If you'd like more targeted help or have specific use cases or logs indicating a "RolledBack" state, feel free to provide additional context!