checkpoint

src/hdmf/build/classgenerator.py

@@ -1,7 +1,6 @@
 from copy import deepcopy
 from datetime import datetime, date
 from collections.abc import Callable
-import types as tp
 
 import numpy as np
 
@@ -88,11 +87,8 @@ def generate_class(self, **kwargs):
                              + str(e)
                              + " Please define that type before defining '%s'." % name)
         cls = ExtenderMeta(data_type, tuple(bases), classdict)
+        cls.post_init_method = post_init_method
 
-        if post_init_method is not None:
-            cls.post_init_method = tp.MethodType(post_init_method, cls) # set as bounded method
-        else:
-            cls.post_init_method = post_init_method # set to None
         return cls
 
 
@@ -358,7 +354,6 @@ def __init__(self, **kwargs):
             if self.post_init_method is not None:
                 self.post_init_method(**original_kwargs)
 
-
         classdict['__init__'] = __init__
 
 
@@ -433,6 +428,7 @@ def set_init(cls, classdict, bases, docval_args, not_inherited_fields, name):
             def __init__(self, **kwargs):
                 # store the values passed to init for each MCI attribute so that they can be added
                 # after calling __init__
+                original_kwargs = dict(kwargs)
                 new_kwargs = list()
                 for field_clsconf in classdict['__clsconf__']:
                     attr_name = field_clsconf['attr']
@@ -460,5 +456,8 @@ def __init__(self, **kwargs):
                     add_method = getattr(self, new_kwarg['add_method_name'])
                     add_method(new_kwarg['value'])
 
+                if self.post_init_method is not None:
+                    self.post_init_method(**original_kwargs)
+
             # override __init__
             classdict['__init__'] = __init__

tests/unit/build_tests/test_classgenerator.py

@@ -84,22 +84,6 @@ def test_no_generators(self):
 
 class TestPostInitGetClass(TestCase):
     def setUp(self):
-        # self.bar_spec = GroupSpec(
-        #     doc='A test group specification with a data type',
-        #     data_type_def='Bar',
-        #     datasets=[
-        #         DatasetSpec(
-        #             doc='a dataset',
-        #             dtype='int',
-        #             name='data',
-        #             attributes=[AttributeSpec(name='attr1', doc='an integer attribute', dtype='int')]
-        #         )
-        #     ])
-        # specs = [self.bar_spec]
-        # containers = {'Bar': Bar}
-        # from hdmf.common import get_type_map
-        # self.type_map = get_type_map()
-        # self.spec_catalog = self.type_map.namespace_catalog.get_namespace(CORE_NAMESPACE).catalog
         spec = GroupSpec(
             doc='A test group specification with a data type',
             data_type_def='Baz',
@@ -132,7 +116,7 @@ def post_init_method(self, **kwargs):
         cls = self.type_map.get_dt_container_cls('Baz', CORE_NAMESPACE, post_init_method)
 
         with self.assertRaises(ValueError):
-            instance = cls(name='instance', attr1=9)
+            cls(name='instance', attr1=9)
 
 class TestDynamicContainer(TestCase):