it works!

Author: jreback

pandas/hashtable.pyx

@@ -28,7 +28,6 @@ PyDateTime_IMPORT
 cdef extern from "Python.h":
     int PySlice_Check(object)
 
-
 def list_to_object_array(list obj):
     '''
     Convert list to object ndarray. Seriously can't believe I had to write this
@@ -108,14 +107,12 @@ cdef class Int64Vector(Vector):
 
     cdef inline void append(self, int64_t x) nogil:
 
-        with nogil:
-
-            if self.needs_resize():
-                with gil:
-                    self.resize()
+        if self.needs_resize():
+            with gil:
+                self.resize()
 
-            self.data[self.n] = x
-            self.n += 1
+        self.data[self.n] = x
+        self.n += 1
 
 cdef class Float64Vector(Vector):
 

vb_suite/gil.py

@@ -8,15 +8,15 @@
 from pandas.util.testing import test_parallel
 
 N = 1000000
-ngroups = 100
+ngroups = 1000
 
 def get_test_data(ngroups=100, n=N):
     unique_groups = range(ngroups)
-    arr = np.asarray(np.tile(unique_groups, n / ngroups), dtype=object)
+    arr = np.asarray(np.tile(unique_groups, n / ngroups), dtype='int64')
 
     if len(arr) < n:
         arr = np.asarray(list(arr) + unique_groups[:n - len(arr)],
-                         dtype=object)
+                         dtype='int64')
 
     random.shuffle(arr)
     return arr
@@ -26,10 +26,8 @@ def get_test_data(ngroups=100, n=N):
                 'data1' : np.random.randn(N),
                 'data2' : np.random.randn(N)})
 
-grp = df.groupby('key1')['data1']
-
 def f():
-    grp.sum()
+    df.groupby('key1')['data1'].sum()
 
 # run consecutivily
 def g2():