Add type-aware serializers

Author: andystaples

azure/functions/_durable_functions.py

@@ -1,9 +1,23 @@
 # Copyright (c) Microsoft Corporation. All rights reserved.
 # Licensed under the MIT License.
 
-from typing import Union
+import json
+import logging
+import os
+import sys
+from typing import Any, Callable, Optional, Union
+
 from . import _abc
-from importlib import import_module
+
+logger = logging.getLogger(__name__)
+
+_STRICT_ENV_VAR = "AZURE_FUNCTIONS_DURABLE_STRICT_TYPING"
+_TRUTHY = frozenset({"1", "true", "yes"})
+_LEGACY_KEYS = frozenset({"__class__", "__module__", "__data__"})
+
+
+def _is_strict_mode() -> bool:
+    return os.environ.get(_STRICT_ENV_VAR, "").strip().lower() in _TRUTHY
 
 
 # Utilities
@@ -46,33 +60,52 @@ def _serialize_custom_object(obj):
 def _deserialize_custom_object(obj: dict) -> object:
     """Deserialize a user-defined object from JSON.
 
-    Deserializes a dictionary encoding a custom object,
-    if it contains class metadata suggesting that it should be
-    decoded further.
+    Reconstructs a custom object from a dictionary that carries the
+    ``{"__class__", "__module__", "__data__"}`` envelope produced by
+    :func:`_serialize_custom_object`.  The class is resolved by looking
+    up ``__module__`` in :data:`sys.modules`; modules are never imported
+    on demand.
 
-    Parameters:
+    Parameters
     ----------
-    obj: dict
-        Dictionary object that potentially encodes a custom class
+    obj : dict
+        Dictionary that potentially encodes a custom class.
 
-    Returns:
-    --------
+    Returns
+    -------
     object
-        Either the original `obj` dictionary or the custom object it encoded
+        Either the original ``obj`` dictionary (if it is not an
+        envelope) or the reconstructed custom object.
 
-    Exceptions
-    ----------
+    Raises
+    ------
+    ValueError
+        If the declared module is not present in ``sys.modules``.
+    AttributeError
+        If the declared module is loaded but does not define the
+        declared class.
     TypeError
-        If the decoded object does not contain a `from_json` function
+        If the resolved class does not expose a ``from_json`` function.
     """
     if ("__class__" in obj) and ("__module__" in obj) and ("__data__" in obj):
         class_name = obj.pop("__class__")
         module_name = obj.pop("__module__")
         obj_data = obj.pop("__data__")
 
-        # Importing the clas
-        module = import_module(module_name)
-        class_ = getattr(module, class_name)
+        # Resolve the class from already-loaded modules; this function
+        # does not import modules on demand.
+        module = sys.modules.get(module_name)
+        if module is None:
+            raise ValueError(
+                f"cannot deserialize custom object: module "
+                f"{module_name!r} is not loaded in sys.modules"
+            )
+        class_ = getattr(module, class_name, None)
+        if class_ is None:
+            raise AttributeError(
+                f"cannot deserialize custom object: class {class_name!r} "
+                f"not found in module {module_name!r}"
+            )
 
         if not hasattr(class_, "from_json"):
             raise TypeError(f"class {type(obj)} does not expose a `from_json` "
@@ -83,6 +116,179 @@ def _deserialize_custom_object(obj: dict) -> object:
     return obj
 
 
+# ---------------------------------------------------------------------------
+# Public Durable Functions JSON codec
+# ---------------------------------------------------------------------------
+
+
+def df_dumps(value: Any) -> str:
+    """Serialize *value* to a JSON string.
+
+    In **loose mode** (default) this is equivalent to
+    ``json.dumps(value, default=_serialize_custom_object)``: nested
+    custom objects are wrapped recursively in the
+    ``{"__class__", "__module__", "__data__"}`` envelope.
+
+    In **strict mode** (``AZURE_FUNCTIONS_DURABLE_STRICT_TYPING`` set
+    to ``1``, ``true`` or ``yes``) only the top-level custom object is
+    wrapped; its ``__data__`` payload is serialized as plain JSON
+    without a ``default=`` hook.  ``to_json()`` must therefore return
+    a value that is natively JSON-serializable, and ``TypeError`` is
+    raised if any nested value is not.
+    """
+    if _is_strict_mode():
+        if hasattr(value, "to_json"):
+            envelope = _serialize_custom_object(value)
+            return json.dumps(envelope)
+        # Primitive / plain-JSON value -- serialize without default=.
+        return json.dumps(value)
+    return json.dumps(value, default=_serialize_custom_object)
+
+
+def df_loads(s: str, expected_type: Optional[type] = None) -> Any:
+    """Deserialize a JSON string, optionally validating against *expected_type*.
+
+    When *expected_type* is ``None``:
+
+    * **Loose mode** (default) runs
+      ``json.loads(s, object_hook=_deserialize_custom_object)``.  Custom
+      objects whose declaring module is already present in
+      ``sys.modules`` are reconstructed; otherwise ``ValueError`` is
+      raised.
+    * **Strict mode** parses without an ``object_hook``.  A legacy
+      custom-object envelope at the top level raises ``TypeError`` --
+      the caller must supply ``expected_type`` to deserialize custom
+      objects in strict mode.
+
+    When *expected_type* is provided the raw JSON is parsed first
+    (without an ``object_hook``) so the payload can be inspected before
+    any class lookup.  On a class/module mismatch loose mode logs a
+    warning and strict mode raises ``TypeError``.  In loose mode the
+    legacy ``object_hook`` path then runs (so nested custom objects are
+    also reconstructed); in strict mode the matching custom-object
+    payload is reconstructed by calling
+    ``expected_type.from_json(raw["__data__"])`` directly.
+    """
+    if expected_type is not None:
+        return _loads_with_expected_type(s, expected_type)
+
+    if _is_strict_mode():
+        return _loads_strict_no_type(s)
+
+    return json.loads(s, object_hook=_deserialize_custom_object)
+
+
+def _get_serialize_default() -> Optional[Callable]:
+    """Return the ``default`` callback for ``json.dumps``.
+
+    Intended for call sites that build their own ``json.dumps``
+    invocation (e.g. ``OrchestratorState.to_json_string``) and want to
+    honour the active typing mode.  Returns ``_serialize_custom_object``
+    in loose mode and ``None`` in strict mode.
+    """
+    if _is_strict_mode():
+        return None
+    return _serialize_custom_object
+
+
+def _loads_strict_no_type(s: str) -> Any:
+    """Strict-mode deserialization when no *expected_type* is supplied.
+
+    Parses *s* without an ``object_hook``.  Returns the parsed value
+    unchanged for primitive / plain-JSON payloads; raises ``TypeError``
+    if the top-level value is a legacy custom-object envelope.
+    """
+    raw = json.loads(s)
+    if _is_legacy_custom_dict(raw):
+        raise TypeError(
+            "df_loads: strict mode requires expected_type to "
+            "deserialize custom-object payloads, but none was provided. "
+            f"Payload declares {raw['__module__']}.{raw['__class__']}."
+        )
+    return raw
+
+
+def _is_legacy_custom_dict(d: Any) -> bool:
+    """Return True if *d* is a dict with legacy custom-object markers."""
+    return isinstance(d, dict) and _LEGACY_KEYS.issubset(d)
+
+
+def _has_json_protocol(cls: type) -> bool:
+    """Return True iff *cls* exposes callable ``to_json`` and ``from_json``."""
+    return callable(getattr(cls, "to_json", None)) and callable(
+        getattr(cls, "from_json", None)
+    )
+
+
+def _is_compatible(value: Any, expected_type: type) -> bool:
+    """Best-effort ``isinstance`` check that tolerates generic type hints."""
+    try:
+        return isinstance(value, expected_type)
+    except TypeError:
+        # typing constructs like List[int] aren't valid for isinstance.
+        return True
+
+
+def _loads_with_expected_type(s: str, expected_type: type) -> Any:
+    """Parse *s* and validate the result against *expected_type*.
+
+    The raw JSON is parsed without an ``object_hook`` so the payload
+    shape can be inspected before any class lookup.  In strict mode a
+    matching custom-object payload is reconstructed via
+    ``expected_type.from_json``; in loose mode the legacy
+    ``object_hook`` path runs so nested custom objects inside
+    ``__data__`` are also reconstructed.
+    """
+    raw = json.loads(s)
+    strict = _is_strict_mode()
+
+    if _is_legacy_custom_dict(raw):
+        class_name = raw["__class__"]
+        module_name = raw["__module__"]
+        type_matches = (class_name == expected_type.__name__
+                        and module_name == expected_type.__module__)
+
+        if not type_matches:
+            msg = (
+                f"df_loads: payload declares class "
+                f"{module_name}.{class_name} but expected "
+                f"{expected_type.__module__}.{expected_type.__name__}"
+            )
+            if strict:
+                raise TypeError(msg)
+            logger.warning(msg)
+            # Fall through to the object_hook path below.
+
+        if strict:
+            if not _has_json_protocol(expected_type):
+                raise TypeError(
+                    f"df_loads: expected_type "
+                    f"{expected_type.__module__}.{expected_type.__name__} "
+                    f"does not expose from_json"
+                )
+            return expected_type.from_json(raw["__data__"])
+
+        # Loose mode -- use the object_hook path so nested custom
+        # objects inside __data__ are also reconstructed.
+        return json.loads(s, object_hook=_deserialize_custom_object)
+
+    # Primitive / plain-JSON payload -- validate the Python type.
+    if not _is_compatible(raw, expected_type):
+        msg = (
+            f"df_loads: deserialized value ({type(raw).__name__}) is not "
+            f"compatible with expected type {expected_type}"
+        )
+        if strict:
+            raise TypeError(msg)
+        logger.warning(msg)
+
+    if strict:
+        return raw
+    # Loose mode -- use the object_hook path so nested custom objects
+    # inside dicts/lists are reconstructed.
+    return json.loads(s, object_hook=_deserialize_custom_object)
+
+
 class OrchestrationContext(_abc.OrchestrationContext):
     """A durable function orchestration context.
 

azure/functions/durable_functions.py

@@ -92,10 +92,20 @@ def decode(cls,
 
         # Durable functions extension always returns a string of json
         # See durable functions library's call_activity_task docs
+        #
+        # Strict-mode caveat: when the AZURE_FUNCTIONS_DURABLE_STRICT_TYPING
+        # environment variable is set, df_loads requires an `expected_type`
+        # to deserialize custom-object envelopes.  The worker's converter
+        # dispatch does not currently forward the activity function's
+        # parameter type annotation to `decode`, so we have nothing to
+        # pass here -- a strict-mode payload carrying a custom-object
+        # envelope will surface as TypeError below and be re-raised as
+        # ValueError.  Plumbing `expected_type` through `InConverter.decode`
+        # is tracked as future work in the spec (see
+        # spec-functions-sdk-df-serialization.md, section 6).
         if data_type in ['string', 'json']:
             try:
-                callback = _durable_functions._deserialize_custom_object
-                result = json.loads(data.value, object_hook=callback)
+                result = _durable_functions.df_loads(data.value)
             except json.JSONDecodeError:
                 # String failover if the content is not json serializable
                 result = data.value
@@ -113,8 +123,7 @@ def decode(cls,
     def encode(cls, obj: typing.Any, *,
                expected_type: typing.Optional[type]) -> meta.Datum:
         try:
-            callback = _durable_functions._serialize_custom_object
-            result = json.dumps(obj, default=callback)
+            result = _durable_functions.df_dumps(obj)
         except TypeError as e:
             raise ValueError(
                 f'activity trigger output must be json serializable ({obj})') from e