Yes, you can pass variables to the

@materialize

decorator in several ways. Let me show you with some examples:

python
from prefect import materialize

# Basic usage with static parameters
@materialize(asset="my-asset")
def my_function():
    return "result"

# Using variables for asset names
asset_name = "dynamic-asset"
@materialize(asset=asset_name)
def dynamic_asset_function():
    return "result"

# Multiple assets
asset_list = ["asset1", "asset2"]
@materialize(*asset_list)
def multi_asset_function():
    return "result"

# With additional task configuration
task_config = {"retries": 3, "retry_delay_seconds": 60}
@materialize(asset="my-asset", **task_config)
def configured_function():
    return "result"

The

@materialize

decorator accepts: 1. Asset names as strings or

Asset

objects 2. Any valid task configuration parameters (like retries, tags, etc.) You can mix and match these parameters as needed, and they can all be variables rather than static values. This makes it very flexible for dynamic asset creation and configuration. For more details about working with assets, you can check out the assets documentation.

Ah, now I understand what you're trying to achieve! You want to determine the asset's location dynamically at runtime. Here's how you can do it:

python
from prefect import materialize
from functools import partial

def create_asset(location):
    # Create a new decorator with the runtime location
    runtime_materialize = materialize(asset=location)
    
    # Use this decorator on your function
    @runtime_materialize
    def my_function():
        return "some result"
    
    return my_function()

# Use it like this:
result = create_asset("my/dynamic/location")

Or, if you prefer a class-based approach:

python
from prefect import materialize

class DynamicAssetCreator:
    def process_data(self, location):
        # Create and apply the decorator at runtime
        @materialize(asset=location)
        def _process():
            return "processed data"
        
        return _process()

# Use it like this:
processor = DynamicAssetCreator()
result = processor.process_data("path/to/my/asset")

The key point is that instead of using the decorator syntax (

@materialize

), we're creating the decorator at runtime when we know the location and then immediately applying it to our function. This pattern is particularly useful when: - The asset location depends on runtime parameters - You're creating assets programmatically based on user input - You need to generate multiple assets with different locations in a loop Just remember that each time you call the function, it will create a new materialized asset at the specified location.