[docs] - Graph-backed asset examples (#8339)

docs/content/concepts/assets/software-defined-assets.mdx

@@ -236,6 +236,64 @@ graph_asset = AssetsDefinition.from_graph(store_slack_files_in_sql)
 
 **Note**: All output assets must be selected when using a graph-backed asset to create a job. Dagster will select all graph output automatically upon creating a job.
 
+#### Defining basic dependencies
+
+The `from_graph` attribute on the `AssetsDefinition` object infers upstream and downstream asset dependencies from the graph definition provided. In the most simple case when the graph returns a singular output, Dagster infers the name of the graph to be the outputted asset key.
+
+In the example below, Dagster creates an asset with key `middle_asset` from the `middle_asset` graph. Just like assets defined via <PyObject object="asset" decorator />, each argument to the decorated graph function is an upstream asset name. `middle_asset` depends on `upstream_asset`, and `downstream_asset` depends on `middle_asset`.
+
+```python file=/concepts/assets/graph_backed_asset.py startafter=start_basic_dependencies endbefore=end_basic_dependencies
+@asset
+def upstream_asset():
+    return 1
+
+
+@graph
+def middle_asset(upstream_asset):
+    return add_one(upstream_asset)
+
+
+middle_asset = AssetsDefinition.from_graph(middle_asset)
+
+
+@asset
+def downstream_asset(middle_asset):
+    return middle_asset + 1
+```
+
+When your graph returns multiple outputs, Dagster infers each output name to be the outputted asset key. In the below example, `two_assets_graph` accepts `upstream_asset` and outputs two assets, `first_asset` and `second_asset`.
+
+```python file=/concepts/assets/graph_backed_asset.py startafter=start_basic_dependencies_2 endbefore=end_basic_dependencies_2
+@graph(out={"first_asset": GraphOut(), "second_asset": GraphOut()})
+def two_assets_graph(upstream_asset):
+    one, two = two_outputs(upstream_asset)
+    return {"first_asset": one, "second_asset": two}
+
+
+two_assets = AssetsDefinition.from_graph(two_assets_graph)
+```
+
+#### Defining explicit dependencies
+
+You can also define dependencies for graph-backed assets explicitly via the `asset_keys_by_input_name` and `asset_keys_by_output_name` arguments to `from_graph`:
+
+```python file=/concepts/assets/graph_backed_asset.py startafter=start_explicit_dependencies endbefore=end_explicit_dependencies
+@graph(out={"one": GraphOut(), "two": GraphOut()})
+def return_one_and_two(zero):
+    one, two = two_outputs(zero)
+    return {"one": one, "two": two}
+
+
+explicit_deps_asset = AssetsDefinition.from_graph(
+    return_one_and_two,
+    asset_keys_by_input_name={"zero": AssetKey("upstream_asset")},
+    asset_keys_by_output_name={
+        "one": AssetKey("asset_one"),
+        "two": AssetKey("asset_two"),
+    },
+)
+```
+
 ### Asset context
 
 Since a software-defined asset contains an op, all the typical functionality of an op - like the use of [resources](/concepts/resources) and [configuration](#asset-configuration) - is available to an asset. Supplying the `context` parameter provides access to system information for the op, for example:

examples/docs_snippets/docs_snippets/concepts/assets/graph_backed_asset.py

@@ -2,7 +2,20 @@
 
 from pandas import DataFrame
 
-from dagster import AssetGroup, AssetsDefinition, ResourceDefinition, graph, op
+from dagster import (
+    AssetGroup,
+    AssetKey,
+    AssetsDefinition,
+    GraphOut,
+    Out,
+    Output,
+    ResourceDefinition,
+    asset,
+    build_assets_job,
+    graph,
+    op,
+    repository,
+)
 
 
 def create_db_connection():
@@ -48,3 +61,89 @@ def store_slack_files_in_sql():
     [graph_asset],
     resource_defs={"slack": ResourceDefinition.hardcoded_resource(slack_mock)},
 ).build_job("store_slack_files")
+
+
+@op
+def add_one(input_num):
+    return input_num + 1
+
+
+# start_basic_dependencies
+
+
+@asset
+def upstream_asset():
+    return 1
+
+
+@graph
+def middle_asset(upstream_asset):
+    return add_one(upstream_asset)
+
+
+middle_asset = AssetsDefinition.from_graph(middle_asset)
+
+
+@asset
+def downstream_asset(middle_asset):
+    return middle_asset + 1
+
+
+# end_basic_dependencies
+
+basic_deps_job = build_assets_job(
+    "basic_deps_job", [upstream_asset, middle_asset, downstream_asset]
+)
+
+
+@op(out={"one": Out(), "two": Out()})
+def two_outputs(upstream):
+    yield Output(output_name="one", value=upstream)
+    yield Output(output_name="two", value=upstream)
+
+
+# start_basic_dependencies_2
+
+
+@graph(out={"first_asset": GraphOut(), "second_asset": GraphOut()})
+def two_assets_graph(upstream_asset):
+    one, two = two_outputs(upstream_asset)
+    return {"first_asset": one, "second_asset": two}
+
+
+two_assets = AssetsDefinition.from_graph(two_assets_graph)
+
+# end_basic_dependencies_2
+
+second_basic_deps_job = build_assets_job(
+    "second_basic_deps_job", [upstream_asset, two_assets]
+)
+
+# start_explicit_dependencies
+
+
+@graph(out={"one": GraphOut(), "two": GraphOut()})
+def return_one_and_two(zero):
+    one, two = two_outputs(zero)
+    return {"one": one, "two": two}
+
+
+explicit_deps_asset = AssetsDefinition.from_graph(
+    return_one_and_two,
+    asset_keys_by_input_name={"zero": AssetKey("upstream_asset")},
+    asset_keys_by_output_name={
+        "one": AssetKey("asset_one"),
+        "two": AssetKey("asset_two"),
+    },
+)
+
+# end_explicit_dependencies
+
+explicit_deps_job = build_assets_job(
+    "explicit_deps_job", [upstream_asset, explicit_deps_asset]
+)
+
+
+@repository
+def my_repo():
+    return [basic_deps_job, store_slack_files, second_basic_deps_job, explicit_deps_job]