# ask-ai

Joram Sbrisny

02/21/2024, 8:37 PM
@Scout: How i can generate dynamicly assets


02/21/2024, 8:37 PM
Creating dynamic assets in Dagster can be approached in a couple of ways, depending on what you mean by "dynamic." If you're referring to assets that are created based on varying conditions or inputs during runtime, Dagster provides mechanisms to handle such scenarios. 1. Dynamic Partitions: If you need to create new partitions for an asset based on dynamic conditions such as the arrival of new data files, you can use a
. This allows you to define a partition set where the partitions are not known ahead of time and can be added or removed dynamically. Here's an example from the documentation:
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python     from dagster import DynamicPartitionsDefinition, asset      images_partitions_def = DynamicPartitionsDefinition(name="images")      @asset(partitions_def=images_partitions_def)     def images(context):         ...
In this case, you can use a sensor to detect the presence of new data and trigger a run for the new partition. 2. Dynamic Output: If you have a scenario where an asset computation might result in a dynamic number of outputs, you can use
within your ops. However, this is more relevant to the execution of ops within a job and not directly related to the creation of assets. It's important to note that while Dagster supports dynamic partitioning, the creation of entirely new assets dynamically (i.e., defining new asset functions or classes at runtime) is not a pattern that is explicitly supported according to the documentation. Instead, Dagster encourages the use of partitions to handle dynamic datasets within a single asset definition. If you need further guidance on how to implement dynamic assets for your specific use case, please provide more details, and I can help you navigate the documentation to find the most suitable solution.