Merge pull request #68 from alfred82santa/feature/performance-tests

Added performace test, BlobField and slots for models

.env

@@ -0,0 +1 @@
+[email protected]

dirty_models/base.py

@@ -11,6 +11,9 @@ class BaseData():
     """
     Base class for data inside dirty model
     """
+
+    __slots__ = []
+
     _locked = None
     _read_only = None
     _parent = None

dirty_models/fields.py

@@ -452,3 +452,7 @@ def __init__(self, model_class=None, **kwargs):
 
     def convert_value(self, value):
         return self._model_class(data=value, field_type=self.field_type)
+
+
+class BlobField(BaseField):
+    pass

performance/__init__.py

@@ -0,0 +1,32 @@
+from datetime import datetime, timedelta
+from sys import setrecursionlimit
+from functools import reduce
+
+
+class Runner:
+
+    def __init__(self, config):
+        self.config = config
+
+    def run(self):
+        setrecursionlimit(9999999)
+
+        result = {}
+        for label, data in self.config.items():
+            test = data['test_class'](**data['params'])
+            test.prepare()
+            result_test = []
+            print ('{0} start'.format(label))
+            for i in range(data.get('repeats', 1)):
+                print ('{0}: iteration no. {1} start'.format(label, i))
+                time_start = datetime.now()
+                test.run()
+                time_stop = datetime.now()
+                elapsed = time_stop - time_start
+                print ('{0}: iteration no. {1} => {2}'.format(label, i, str(elapsed)))
+                result_test.append(elapsed)
+            total = reduce(lambda acc, x: acc + x, result_test, timedelta())
+            print ('{0} => {1}'.format(label, str(total)))
+            result[label] = {'results': result_test, 'total': total}
+
+        return result

performance/blobfield.py

@@ -0,0 +1,25 @@
+'''
+Created on 15/09/2014
+
+:author: alfred
+'''
+from dirty_models.models import BaseModel
+from dirty_models.fields import BlobField
+from performance.dynamicmodel import create_dict
+
+
+class FakeDynModel(BaseModel):
+    fake_data = BlobField()
+
+
+class BlobFieldPerformance:
+
+    def __init__(self, depth=5, children_count=5):
+        self.depth = depth
+        self.children_count = children_count
+
+    def prepare(self):
+        self.data = create_dict(self.depth, self.children_count)
+
+    def run(self):
+        return FakeDynModel(data={'fake_data': self.data})

performance/dynamicmodel.py

@@ -0,0 +1,31 @@
+'''
+Created on 15/09/2014
+
+:author: alfred
+'''
+from dirty_models.models import DynamicModel, BaseModel
+from dirty_models.fields import ModelField
+
+
+def create_dict(depth=5, children_count=5):
+    if depth > 0:
+        return {'test_{0}'.format(i): create_dict(depth - 1, children_count) for i in range(children_count)}
+    else:
+        return 'top'
+
+
+class FakeDynModel(BaseModel):
+    fake_data = ModelField(model_class=DynamicModel)
+
+
+class DynamicModelPerformance:
+
+    def __init__(self, depth=5, children_count=5):
+        self.depth = depth
+        self.children_count = children_count
+
+    def prepare(self):
+        self.data = create_dict(self.depth, self.children_count)
+
+    def run(self):
+        return FakeDynModel(data={'fake_data': self.data})

performancerunner.py

@@ -0,0 +1,21 @@
+'''
+Created on 15/09/2014
+
+:author: alfred
+'''
+from performance import Runner
+from performance.dynamicmodel import DynamicModelPerformance
+from performance.blobfield import BlobFieldPerformance
+
+config = {'DynamicModel': {'test_class': DynamicModelPerformance,
+                           'repeats': 5,
+                           'params': {'depth': 6, 'children_count': 6}},
+          'BlobField': {'test_class': BlobFieldPerformance,
+                           'repeats': 5,
+                           'params': {'depth': 6, 'children_count': 6}}}
+
+if __name__ == '__main__':
+
+    runner = Runner(config)
+
+    print(runner.run())