[FOR DISCUSSION] Automatically capture params on object construction

tmp.py

@@ -0,0 +1,76 @@
+from typing import Any, Dict, Type
+import inspect
+
+
+def get_arg_params(argument: Any, annotation: Type) -> Any:
+    existing_params = getattr(argument, '_params', None)
+    if existing_params is not None:
+        return existing_params
+    elif annotation in {float, int}:
+        return argument
+    else:
+        # There are several more cases to handle here if we want to actually do this, but not *that*
+        # many more.  We just have to cover all base python types.  Unions might be tricky to figure
+        # out, but should still be doable.  This logic basically mirrors what we do when creating
+        # objects in FromParams, we're just going the other way.
+        raise ValueError()
+
+
+def get_params(init, *args, **kwargs) -> Dict[str, Any]:
+    signature = inspect.signature(init)
+    parameters = dict(signature.parameters)
+    # need some fancy logic here to match *args and **kwargs with the parametrs.  It's deterministic
+    # and doable, but more than I want to write right now.  The below is a quick and dirty first
+    # pass.  Oh, hmm, super classes and **kwargs _inside_ the __init__ method make this more tricky,
+    # but still doable.
+    arg_list = list(args)
+    saved_params = {}
+    for param_name, param in parameters.items():
+        if param_name == "self":
+            continue
+        if param_name in kwargs:
+            argument = kwargs.pop(param_name)
+        else:
+            argument = arg_list.pop(0)
+        argument_params = get_arg_params(argument, param.annotation)
+        saved_params[param_name] = argument_params
+    return saved_params
+
+
+class Meta(type):
+    def __new__(mcs, name, bases, namespace, **kwargs):
+        new_cls = super(Meta, mcs).__new__(mcs, name, bases, namespace, **kwargs)
+        user_init = new_cls.__init__
+        def __init__(self, *args, **kwargs):
+            self._params = get_params(user_init, *args, **kwargs)
+            user_init(self, *args, **kwargs)
+        setattr(new_cls, '__init__', __init__)
+        return new_cls
+
+
+class FromParams(metaclass=Meta):
+    pass
+
+
+class Gaussian(FromParams):
+    def __init__(self, mean: float, variance: float):
+        self.mean = mean
+        self.variance = variance
+
+
+class NestedGaussian(FromParams):
+    def __init__(self, gaussian: Gaussian, alpha: float):
+        self.gaussian = gaussian
+        self.alpha = alpha
+
+
+g = Gaussian(1.3, 2.3)
+print(g._params)
+# {'mean': 1.3, 'variance': 2.3}
+g = Gaussian(mean=1.8, variance=4.3)
+print(g._params)
+# {'mean': 1.8, 'variance': 4.3}
+
+n = NestedGaussian(Gaussian(mean=1.8, variance=4.3), alpha=.01)
+print(n._params)
+# {'gaussian': {'mean': 1.8, 'variance': 4.3}, 'alpha': 0.01}