in progress

Signed-off-by: John Andersen <johnandersenpdx@gmail.com>

docs/arch/0004-DataFlow-as-Class.rst

@@ -122,6 +122,21 @@ which takes
         return new_fn
 
 
+    def config_to_new_fn(
+        new_fn: Callable,
+    ) -> Callable:
+        # The function which will be in charge of running the dataflow
+        # We will fixup it's method signature using inspect.
+        def func_run_dataflow(self, *args, **kwargs):
+            return self._func_run_dataflow(*args, **kwargs)
+
+        func_run_dataflow = gen_fn(args)
+
+        # {'a': int}
+        return func_run_dataflow
+
+
+
     records = [
         dffml.Record("a", data={"features": {"one": 42}}),
         dffml.Record("b", data={"features": {"one": 420}}),
@@ -137,15 +152,56 @@ which takes
 
 
     class DataFlowClass:
-        pass
-
-
-    @classmethod
-    def _add_dataflow_method(cls, methods):
-        pass
-
-
-    dffml.DataFlow._add_dataflow_method = _add_dataflow_method
+        @classmethod
+        def _add_dataflow_method(cls, name, config: RunCMDConfig):
+            """
+            @config
+            class RunCMDConfig:
+                dataflow: str = field(
+                    "File containing exported DataFlow", required=True,
+                )
+                configloader: BaseConfigLoader = field(
+                    "ConfigLoader to use for importing DataFlow", default=None,
+                )
+                sources: Sources = FIELD_SOURCES
+                caching: List[str] = field(
+                    "Skip running DataFlow if a record already contains these features",
+                    default_factory=lambda: [],
+                )
+                no_update: bool = field(
+                    "Update record with sources", default=False,
+                )
+                no_echo: bool = field(
+                    "Do not echo back records", default=False,
+                )
+                no_strict: bool = field(
+                    "Do not exit on operation exceptions, just log errors", default=False,
+                )
+                orchestrator: BaseOrchestrator = field(
+                    "Orchestrator", default=MemoryOrchestrator,
+                )
+                inputs: List[str] = field(
+                    "Other inputs to add under each ctx (record's key will "
+                    + "be used as the context)",
+                    action=ParseInputsAction,
+                    default_factory=lambda: [],
+                )
+                record_def: str = field(
+                    "Definition to be used for record.key."
+                    + "If set, record.key will be added to the set of inputs "
+                    + "under each context (which is also the record's key)",
+                    default=False,
+                )
+            """
+            setattr(
+                cls,
+                name,
+                config_to_new_fn(
+                    name,
+                    config,
+                    dataflow,
+                )
+            )
 
 
     # TODO Implement calling lambda's defined within config field metadata
@@ -206,7 +262,7 @@ which takes
         )
         # Check if we need to set config object for __init__ as CONFIG to
         # support DFFML plugin classes
-        plugin_cls = dffml.DataFlow.as_class(
+        plugin_cls = cls.as_class(
             name,
             dataflow,
             config_cls,
@@ -320,8 +376,8 @@ which takes
         dbm_source_dataflow,
         DBMSourceConfig,
         {
-            "record": (
-                dffml.DataFlow(
+            "record": {
+                "dataflow": dffml.DataFlow(
                     dffml.GetSingle,
                     seed=[
                         dffml.Input(
@@ -330,7 +386,7 @@ which takes
                         ),
                     ],
                 ),
-            ),
+            },
         }
     )