diff --git a/guide/README.md b/guide/README.md
index b209c2ec6..a094592c6 100644
--- a/guide/README.md
+++ b/guide/README.md
@@ -58,6 +58,24 @@ Rabit provides different reduction operators, for example,  if you change ```op:
 the reduction operation will be a summation, and the result will become ```a = {1, 3, 5}```.
 You can also run the example with different processes by setting -n to different values.
 
+In order to make the library available for a wider range of developers, we decided to provide a python wrapper to our C++ code. Developers can now program rabit applications in Python! The same example as before can be found in [basic.py](basic.py):
+
+```python
+import numpy as np
+import rabit
+rabit.init()
+n = 3
+rank = rabit.get_rank()
+a = np.zeros(n)
+for i in xrange(n):
+    a[i] = rank + i
+    
+print '@node[%d] before-allreduce: a=%s' % (rank, str(a))
+a = rabit.allreduce(a, rabit.MAX)
+print '@node[%d] after-allreduce: a=%s' % (rank, str(a))
+rabit.finalize()
+```
+
 Broadcast is another method provided by rabit besides Allreduce. This function allows one node to broadcast its
 local data to all other nodes. The following code in [broadcast.cc](broadcast.cc) broadcasts a string from
 node 0 to all other nodes.
@@ -85,6 +103,22 @@ The following command starts the program with three worker processes.
 ```
 Besides strings, rabit also allows to broadcast constant size array and vectors.
 
+The counterpart in python can be found in [broadcast.py](broadcast.py). Here is a snippet so that you can get a better sense of how simple is to use the wrapper:
+
+```python
+import rabit
+rabit.init()
+n = 3
+rank = rabit.get_rank()
+s = None
+if rank == 0:
+    s = {'hello world':100, 2:3}
+print '@node[%d] before-broadcast: s=\"%s\"' % (rank, str(s))
+s = rabit.broadcast(s, 0)
+print '@node[%d] after-broadcast: s=\"%s\"' % (rank, str(s))
+rabit.finalize()
+```
+
 Common Use Case
 =====
 Many distributed machine learning algorithms involve splitting the data into different nodes,
@@ -266,13 +300,4 @@ recovered node fetches its latest checkpoint and the results of
 Allreduce/Broadcast calls after the checkpoint from some alive nodes.
 
 This is just a conceptual introduction to rabit's fault tolerance model. The actual implementation is more sophisticated,
-and can deal with more complicated cases such as multiple nodes failure and node failure during recovery phase.
-
-Python Wrapper
-=====
-In order to make the library available for a wider range of developers, we decided to provide a python wrapper to our C++ code.
-
-Developers can now program rabit applications in Python! We provide a couple of examples:
-
-* [./basic.py](./basic.py) : [./basic.cc](./basic.cc) counterpart, explained above.
-* [./broadcast.py](./broadcast.py) : [./broadcast.cc](./broadcast.cc) counterpart, explained above.
+and can deal with more complicated cases such as multiple nodes failure and node failure during recovery phase.
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