adding pickle support, fix #40

pydantic/main.py

@@ -64,7 +64,6 @@ def __new__(mcs, name, bases, namespace):
             for ann_name, ann_type in annotations.items():
                 if ann_name.startswith('_'):
                     continue
-                print(ann_type)
                 fields[ann_name] = Field.infer(
                     name=ann_name,
                     value=...,
@@ -93,7 +92,7 @@ class BaseModel(metaclass=MetaModel):
     __slots__ = '__values__',
 
     def __init__(self, **data):
-        object.__setattr__(self, '__values__', self._process_values(data))
+        self.__setstate__(self._process_values(data))
 
     def __getattr__(self, name):
         try:
@@ -108,6 +107,12 @@ def __setattr__(self, name, value):
             raise TypeError(f'"{self.__class__.__name__}" is immutable and does not support item assignment')
         self.__values__[name] = value
 
+    def __getstate__(self):
+        return self.__values__
+
+    def __setstate__(self, state):
+        object.__setattr__(self, '__values__', state)
+
     def values(self, *, include: Set[str]=None, exclude: Set[str]=set()) -> Dict[str, Any]:
         """
         Get a dict of the values processed by the model, optionally specifying which fields to include or exclude.
@@ -126,16 +131,16 @@ def construct(cls, **values):
         data. Chances are you don't want to use this method directly.
         """
         m = cls.__new__(cls)
-        object.__setattr__(m, '__values__', values)
+        m.__setstate__(values)
         return m
 
     def copy(self, *, include: Set[str]=None, exclude: Set[str]=None, update: Dict[str, Any]=None):
         """
         Duplicate a model, optionally choose which fields to include, exclude and change
         :param include: fields to include in new model.
         :param exclude: fields to exclude from new model, as with values this takes precedence over include
-        :param update: values to changed/update in the new model. Note: the data is not validated before creating
-            the new model, so you should trust this data.
+        :param update: values to change/add in the new model. Note: the data is not validated before creating
+            the new model: you should trust this data.
         :return: new model instance
         """
         if include is None and exclude is None and update is None:

tests/test_construction.py

@@ -1,10 +1,12 @@
+import pickle
+
 import pytest
 
 from pydantic import BaseModel
 
 
 class Model(BaseModel):
-    a: float
+    a: float = ...
     b: int = 10
 
 
@@ -83,3 +85,24 @@ def test_copy_update():
     assert set(m.values().keys()) == set(m2.values().keys()) == {'a', 'b', 'c', 'd'}
 
     assert m != m2
+
+
+def test_simple_pickle():
+    m = Model(a='24')
+    b = pickle.dumps(m)
+    m2 = pickle.loads(b)
+    assert m.a == m2.a == 24
+    assert m.b == m2.b == 10
+    assert m == m2
+    assert m is not m2
+    assert tuple(m) == (('a', 24.0), ('b', 10))
+    assert tuple(m2) == (('a', 24.0), ('b', 10))
+
+
+def test_recursive_pickle():
+    m = ModelTwo(a=24, d=Model(a='123.45'))
+    m2 = pickle.loads(pickle.dumps(m))
+    assert m == m2
+
+    assert m.d.a == 123.45
+    assert m2.d.a == 123.45