From 7e1509d8fa1ff8f04cee628664c96bcc141edbc9 Mon Sep 17 00:00:00 2001
From: "W. Trevor King" <wking@drexel.edu>
Date: Fri, 4 Jun 2010 11:23:21 -0400
Subject: [PATCH] Added explicit pickle test and fixed curve.Data pickling.

I missunderstood how __reduce__ worked the first time.  Now there's a
doctest proving it works ;).
---
 hooke/curve.py | 42 ++++++++++++++++++++++++++++++++++++++----
 1 file changed, 38 insertions(+), 4 deletions(-)

diff --git a/hooke/curve.py b/hooke/curve.py
index 1b30bfa..146acfa 100644
--- a/hooke/curve.py
+++ b/hooke/curve.py
@@ -60,11 +60,27 @@ class Data (numpy.ndarray):
            [ 20.,  21.]])
     >>> d.info
     {'columns': ['distance (m)', 'force (N)']}
+
+    The information gets passed on to slices.
+
     >>> row_a = d[:,0]
     >>> row_a
     Data([  0.,  10.,  20.])
     >>> row_a.info
     {'columns': ['distance (m)', 'force (N)']}
+
+    The data-type is also pickleable, to ensure we can move it between
+    processes with :class:`multiprocessing.Queue`\s.
+
+    >>> import pickle
+    >>> s = pickle.dumps(d)
+    >>> z = pickle.loads(s)
+    >>> z
+    Data([[  0.,   1.],
+           [ 10.,  11.],
+           [ 20.,  21.]])
+    >>> z.info
+    {'columns': ['distance (m)', 'force (N)']}
     """
     def __new__(subtype, shape, dtype=numpy.float, buffer=None, offset=0,
                 strides=None, order=None, info=None):
@@ -89,11 +105,29 @@ class Data (numpy.ndarray):
         # We do not need to return anything
 
     def __reduce__(self):
-        base_class_state = list(numpy.ndarray.__reduce__(self))
-        own_state = (self.info,)
-        return (base_class_state, own_state)
+        """Collapse an instance for pickling.
+
+        Returns
+        -------
+        reconstruct : callable
+            Called to create the initial version of the object.
+        args : tuple
+            A tuple of arguments for `reconstruct`
+        state : (optional)
+            The state to be passed to __setstate__, if present.
+        iter : iterator (optional)
+            Yielded items will be appended to the reconstructed
+            object.
+        dict : iterator (optional)
+            Yielded (key,value) tuples pushed back onto the
+            reconstructed object.
+        """
+        base_reduce = list(numpy.ndarray.__reduce__(self))
+        # tack our stuff onto ndarray's setstate portion.
+        base_reduce[2] = (base_reduce[2], (self.info,))
+        return tuple(base_reduce)
 
-    def __setstate__(self,state):
+    def __setstate__(self, state):
         base_class_state,own_state = state
         numpy.ndarray.__setstate__(self, base_class_state)
         self.info, = own_state
-- 
2.26.2