Jason Gofford
02/27/2024, 3:43 PMScout
02/27/2024, 3:43 PMAssetSelection
API provided by Dagster. This API allows you to create complex selections of assets using various methods, including selecting by key prefixes. To select assets with a specific key prefix, you can use the AssetSelection.key_prefixes
method. Here's an example from the documentation: python # match any asset key where the first segment is equal to "a" or "b" # e.g. AssetKey(["a", "b", "c"]) would match, but AssetKey(["abc"]) would not. AssetSelection.key_prefixes("a", "b") # match any asset key where the first two segments are ["a", "b"] or ["a", "c"] AssetSelection.key_prefixes(["a", "b"], ["a", "c"])
When creating a job, you can use the define_asset_job
function and pass the AssetSelection
as the selection
parameter. Here's an example of how you might define a job that selects assets with a particular key prefix: python from dagster import define_asset_job, AssetSelection # Assuming "my_prefix" is the key prefix for the assets you want to select my_asset_selection = AssetSelection.key_prefixes("my_prefix") my_job = define_asset_job( name="my_asset_job", selection=my_asset_selection )
This job will include all assets (both SourceAssets and normal Assets) that have the specified key prefix. Keep in mind that the assets must be included in the assets argument of the Definitions
object that this job is included on. Please note that the exact syntax and methods may vary depending on the version of Dagster you are using, and you should refer to the latest documentation for the most accurate and up-to-date information.Jason Gofford
02/27/2024, 3:45 PMScout
02/27/2024, 3:45 PMAssetSelection.keys
method to explicitly list out the asset keys for each batch. This method allows you to select assets by their full keys, which can include the key prefix and any additional components that make the keys unique for each batch. Here's an example of how you might define separate jobs for each batch of assets: python from dagster import define_asset_job, AssetSelection # Define the asset keys for each batch batch_a_keys = [AssetKey(["my_prefix", "specific_identifier_for_batch_a", ...]), ...] batch_b_keys = [AssetKey(["my_prefix", "specific_identifier_for_batch_b", ...]), ...] batch_c_keys = [AssetKey(["my_prefix", "specific_identifier_for_batch_c", ...]), ...] # Create AssetSelections for each batch batch_a_selection = AssetSelection.keys(*batch_a_keys) batch_b_selection = AssetSelection.keys(*batch_b_keys) batch_c_selection = AssetSelection.keys(*batch_c_keys) # Define jobs for each batch batch_a_job = define_asset_job( name="batch_a_job", selection=batch_a_selection ) batch_b_job = define_asset_job( name="batch_b_job", selection=batch_b_selection ) batch_c_job = define_asset_job( name="batch_c_job", selection=batch_c_selection )
In this example, specific_identifier_for_batch_a
, specific_identifier_for_batch_b
, and specific_identifier_for_batch_c
would be the unique parts of the asset keys that differentiate between the batches A, B, and C, respectively. This approach assumes that you have a clear way to distinguish between the assets in each batch based on their keys. If the batches are not distinguishable by key alone, you may need to use additional metadata or naming conventions to create your selections. Remember to check the latest Dagster documentation for the most accurate and up-to-date information on how to use AssetSelection
and related APIs.Jason Gofford
02/27/2024, 3:47 PMScout
02/27/2024, 3:48 PMAssetSelection
API. The selection mechanisms provided by Dagster typically involve specifying exact asset keys or using prefixes, rather than performing substring matches. However, if you want to select all asset keys that start with a specific substring within a given key prefix, you would typically need to manually construct a list of those asset keys based on your naming conventions and then use that list to define your job. Here's a conceptual example of how you might do this: python from dagster import define_asset_job, AssetSelection, repository from my_assets_module import assets # Assuming this is where your assets are defined # Assuming "my/prefix" is the key prefix and "stock" is the substring you're looking for prefix = "my/prefix" substring = "stock" # Manually construct a list of asset keys that match the criteria matching_asset_keys = [ asset.key for asset in assets if asset.key.to_string().startswith(f"{prefix}/{substring}") ] # Create an AssetSelection for the matching assets matching_assets_selection = AssetSelection.keys(*matching_asset_keys) # Define a job for the matching assets matching_assets_job = define_asset_job( name="matching_assets_job", selection=matching_assets_selection ) @repository def my_repository(): return [matching_assets_job] + assets
In this example, you would need to have a list of all your assets imported from my_assets_module
. You would then filter this list to include only those assets whose keys start with the desired prefix and substring. The resulting list of asset keys is used to create an AssetSelection
for the job. Please note that this approach requires you to have access to the asset definitions in order to inspect their keys. If your assets are dynamically generated or if you have a large number of assets, you might need a more dynamic approach to generate the list of matching asset keys. Always refer to the latest Dagster documentation to check for any updates or new features that might provide additional selection mechanisms that could simplify this process.Jason Gofford
02/27/2024, 4:08 PMScout
02/27/2024, 4:08 PMAssetSelection
is used to select assets for inclusion in a job, and it operates on asset keys. However, if you're encountering an AttributeError
, it suggests that the objects you're iterating over do not have a key
attribute, which means they might not be asset instances as expected. To select assets based on a substring match within a given key prefix, you would need to ensure that you're working with the correct asset objects that have the key
attribute. Here's a revised conceptual approach that assumes you have a list of asset keys: python from dagster import define_asset_job, AssetSelection, repository, AssetKey from my_assets_module import assets # Assuming this is where your assets are defined # Assuming "my/prefix" is the key prefix and "stock" is the substring you're looking for prefix = "my/prefix" substring = "stock" # Manually construct a list of asset keys that match the criteria matching_asset_keys = [ AssetKey([*asset.key.path, asset.key.to_string().split("/")[-1]]) for asset in assets if asset.key.to_string().startswith(f"{prefix}/{substring}") ] # Create an AssetSelection for the matching assets matching_assets_selection = AssetSelection.keys(*matching_asset_keys) # Define a job for the matching assets matching_assets_job = define_asset_job( name="matching_assets_job", selection=matching_assets_selection ) @repository def my_repository(): return [matching_assets_job] + assets
In this revised example, we're iterating over a list of asset instances (assumed to be provided by my_assets_module.assets
) and checking if their keys match the desired pattern. The AssetKey
is constructed from the path of the existing asset key, and we're using the to_string()
method to get the string representation of the key for substring matching. Please ensure that the assets
variable actually contains asset instances with a key
attribute. If assets
is not a list of asset instances, you would need to adjust the code to correctly reference the asset keys. If you continue to encounter issues, please ensure that you are using the correct version of Dagster and that you are following the latest documentation for asset selection and job definition. If the problem persists, it may be helpful to provide more context or a specific code example that is causing the error, so that I can give you more accurate guidance.Jason Gofford
02/27/2024, 4:11 PMAssetSelection.key_prefixes(key_prefix)
and then, on the output of that match, match on the substring. Add this into your example.Scout
02/27/2024, 4:11 PMAssetSelection.key_prefixes
method to get the initial selection and then filter that selection further based on the substring. Here's how you could implement this: python from dagster import define_asset_job, AssetSelection, repository, AssetKey from my_assets_module import assets # Assuming this is where your assets are defined # Define the key prefix and the substring you're looking for key_prefix = "my/prefix" substring = "stock" # Step 1: Select assets based on the key prefix initial_selection = AssetSelection.key_prefixes(key_prefix) # Step 2: Further filter the initial selection based on the substring matching_asset_keys = [ asset.key for asset in assets if initial_selection.has_asset_key(asset.key) and asset.key.to_string().split("/")[-1].startswith(substring) ] # Create an AssetSelection for the matching assets matching_assets_selection = AssetSelection.keys(*matching_asset_keys) # Define a job for the matching assets matching_assets_job = define_asset_job( name="matching_assets_job", selection=matching_assets_selection ) @repository def my_repository(): return [matching_assets_job] + assets
In this example, initial_selection
is an AssetSelection
object that includes all assets with the specified key prefix. Then, we iterate over the list of assets and check if each asset is included in the initial_selection
and if its last key component starts with the specified substring. Please note that this example assumes that assets
is a list of asset instances that have a key
attribute, and that initial_selection.has_asset_key(asset.key)
is a method that checks if a given AssetKey
is part of the selection. The AssetSelection
API may not have a has_asset_key
method, so you would need to implement the logic to check if an asset key is part of the initial selection based on your specific use case and the version of Dagster you are using. Always refer to the latest Dagster documentation to ensure that you are using the correct methods and APIs for your version of Dagster. If the functionality you need is not available, you may need to implement custom logic to achieve the desired asset selection.Jason Gofford
02/27/2024, 4:24 PMAssetSelection.key_prefixes(key_prefix)
selection, how do I subsequently filter the matched keys to only include those that have the "stock" prefix. Provide me a full worked example.Scout
02/27/2024, 4:24 PMAssetSelection.key_prefixes(key_prefix)
method allows you to select assets that match a given key prefix. To subsequently filter the matched keys to only include those that have an additional "stock" prefix, you would need to manually iterate over the assets and filter them based on the asset key's string representation. Here's a full worked example of how you might achieve this: python from dagster import AssetKey, define_asset_job, AssetSelection, repository from my_assets_module import assets # Assuming this is where your assets are defined # Define the key prefix key_prefix = "my/prefix" # Step 1: Select assets based on the key prefix initial_selection = AssetSelection.key_prefixes(key_prefix) # Step 2: Further filter the initial selection based on the "stock" prefix matching_asset_keys = [ asset.key for asset in assets if asset.key.to_string().startswith(f"{key_prefix}/stock") ] # Create an AssetSelection for the matching assets matching_assets_selection = AssetSelection.keys(*matching_asset_keys) # Define a job for the matching assets matching_assets_job = define_asset_job( name="stock_assets_job", selection=matching_assets_selection ) @repository def my_repository(): return [matching_assets_job] + assets
In this example, initial_selection
is not directly used to filter the assets. Instead, we use a list comprehension to iterate over the assets
and select those whose keys start with the combination of key_prefix
and the additional "stock" prefix. The AssetKey.to_string()
method is used to get the string representation of the asset key, which is then checked for the desired prefix pattern. Please note that this example assumes that assets
is a list of asset instances that have a key
attribute. If assets
is not a list of asset instances, or if the assets are defined in a way that does not allow direct iteration, you would need to adjust the code accordingly. Remember to refer to the latest Dagster documentation to ensure that you are using the correct methods and APIs for your version of Dagster. If the functionality you need is not available, you may need to implement custom logic to achieve the desired asset selection.Jason Gofford
02/27/2024, 7:10 PMScout
02/27/2024, 7:10 PMpython # In module foo_assets.py from dagster import asset @asset(key_prefix="foo") def load_data(): # logic for loading data in the context of "foo" ... # In module bar_assets.py from dagster import asset @asset(key_prefix="bar") def load_data(): # logic for loading data in the context of "bar" ...
In this example, even though both functions are named load_data
, they are distinguished by their key prefixes, "foo" and "bar". When you refer to these assets in Dagster, you would use their full asset keys, which include the key prefix, such as foo/load_data
and bar/load_data
. This allows you to have a clear organizational structure for your assets and avoid naming collisions, even when the underlying function names are the same. It's important to use the full asset key, including the prefix, when selecting or referring to these assets in your Dagster code to ensure that the correct asset is being addressed.Jason Gofford
02/27/2024, 7:14 PMScout
02/27/2024, 7:14 PMprint_table
for both the foo
and bar
namespaces, linking them to their respective load_data
upstream assets: python # In module foo_assets.py from dagster import asset, AssetIn @asset(key_prefix="foo") def load_data(): # logic for loading data in the context of "foo" ... @asset( key_prefix="foo", ins={"load_data_input": AssetIn(key="foo/load_data")} ) def print_table(load_data_input): # logic for printing the table in the context of "foo" print(load_data_input) # In module bar_assets.py from dagster import asset, AssetIn @asset(key_prefix="bar") def load_data(): # logic for loading data in the context of "bar" ... @asset( key_prefix="bar", ins={"load_data_input": AssetIn(key="bar/load_data")} ) def print_table(load_data_input): # logic for printing the table in the context of "bar" print(load_data_input)
In this example, the print_table
asset in the foo_assets.py
module is linked to the foo/load_data
asset by specifying the full asset key in the AssetIn
object. Similarly, the print_table
asset in the bar_assets.py
module is linked to the bar/load_data
asset. By using the full asset keys with prefixes, you ensure that each print_table
asset is connected to the correct load_data
asset within its namespace. This allows you to have multiple assets with the same name across different namespaces without any ambiguity about their dependencies.Jason Gofford
02/27/2024, 7:16 PMScout
02/27/2024, 7:16 PMAssetIn
can be specified with a list of strings rather than a single string to represent the hierarchical structure of the asset key. This is useful when you have multi-component asset keys that represent hierarchical namespaces, similar to paths in a filesystem. Here's how you can specify the AssetIn
with a list for the print_table
assets in both the foo
and bar
namespaces: python # In module foo_assets.py from dagster import asset, AssetIn @asset(key_prefix="foo") def load_data(): # logic for loading data in the context of "foo" ... @asset( key_prefix="foo", ins={"load_data_input": AssetIn(key=["foo", "load_data"])} ) def print_table(load_data_input): # logic for printing the table in the context of "foo" print(load_data_input) # In module bar_assets.py from dagster import asset, AssetIn @asset(key_prefix="bar") def load_data(): # logic for loading data in the context of "bar" ... @asset( key_prefix="bar", ins={"load_data_input": AssetIn(key=["bar", "load_data"])} ) def print_table(load_data_input): # logic for printing the table in the context of "bar" print(load_data_input)
In this example, the AssetIn
objects for load_data_input
are specified using lists of strings: ["foo", "load_data"]
and ["bar", "load_data"]
. These lists represent the hierarchical structure of the asset keys, ensuring that the print_table
assets are correctly linked to their respective load_data
upstream assets within the foo
and bar
namespaces.Jason Gofford
02/27/2024, 7:26 PMScout
02/27/2024, 7:26 PMkey_prefix
parameter in the same way that normal assets defined with the @asset
decorator do. SourceAssets are typically defined with a specific key
that represents the asset's identity in the asset catalog. However, you can manually include a prefix in the key of a SourceAsset by specifying it as part of the asset key. Here's an example of how you might define a SourceAsset with a prefix: python from dagster import SourceAsset, AssetKey source_asset_with_prefix = SourceAsset( key=AssetKey(["my_prefix", "source_asset_name"]), # ... other parameters ... )
In this example, source_asset_with_prefix
is a SourceAsset with a key that includes the prefix "my_prefix" as the first component of the asset key. If you want to apply a key prefix to multiple SourceAssets programmatically, you would need to construct the AssetKey for each SourceAsset with the desired prefix as part of its key. Please refer to the latest Dagster documentation to check for any updates or changes to the handling of SourceAssets and key prefixes after my knowledge cutoff date.