change docs/examples refs to be just examples

this closes  #3915

docs/source/attic/parallel_task_old.rst

@@ -74,7 +74,7 b' The actual results are stored in a dictionary, ``tr.results``, and a namespace o'
 
 That should cover the basics of running simple Tasks.  There are several more powerful things the user can do with Tasks covered later.  The most useful probably being using a ``MutiEngineClient`` interface to initialize all the engines with the import dependencies necessary to run the user's Tasks.
 
-There are many options for running and managing Tasks. The best way to learn further about the ``Task`` interface is to study the examples in ``docs/examples``. If the user do so and learn a lots about this interface, we encourage the user to expand this documentation about the ``Task`` system.
+There are many options for running and managing Tasks. The best way to learn further about the ``Task`` interface is to study the examples in ``examples``. If the user do so and learn a lots about this interface, we encourage the user to expand this documentation about the ``Task`` system.
 
 Overview of the Task System
 ===========================

docs/source/interactive/reference.rst

@@ -1033,7 +1033,7 b' Second, when using the ``PyOSInputHook`` approach, a GUI application should'
 in IPython and as standalone apps need to have special code to detects how the
 application is being run. We highly recommend using IPython's support for this.
 Since the details vary slightly between toolkits, we point you to the various
-examples in our source directory :file:`docs/examples/lib` that demonstrate
+examples in our source directory :file:`examples/lib` that demonstrate
 these capabilities.
 
 Third, unlike previous versions of IPython, we no longer "hijack" (replace
@@ -1042,7 +1042,7 b' actually need to run the real event loops to do so. This is often needed to'
 process pending events at critical points.
 
 Finally, we also have a number of examples in our source directory
-:file:`docs/examples/lib` that demonstrate these capabilities.
+:file:`examples/lib` that demonstrate these capabilities.
 
 PyQt and PySide
 ---------------

docs/source/parallel/asyncresult.rst

@@ -147,4 +147,4 b' To break that down:'
     handling individual results as they arrive, but with metadata), you can always
     just split the original result's ``msg_ids`` attribute, and handle them as you like.
     
-    For an example of this, see :file:`docs/examples/parallel/customresult.py`
+    For an example of this, see :file:`examples/parallel/customresult.py`

docs/source/parallel/dag_dependencies.rst

@@ -10,7 +10,7 b' for working with Graphs is NetworkX_. Here, we will walk through a demo mapping'
 a nx DAG to task dependencies.
 
 The full script that runs this demo can be found in
-:file:`docs/examples/parallel/dagdeps.py`.
+:file:`examples/parallel/dagdeps.py`.
 
 Why are DAGs good for task dependencies?
 ----------------------------------------

docs/source/parallel/parallel_demos.rst

@@ -30,7 +30,7 b' million digits.'
 
 In both the serial and parallel calculation we will be using functions defined
 in the :file:`pidigits.py` file, which is available in the
-:file:`docs/examples/parallel` directory of the IPython source distribution.
+:file:`examples/parallel` directory of the IPython source distribution.
 These functions provide basic facilities for working with the digits of pi and
 can be loaded into IPython by putting :file:`pidigits.py` in your current
 working directory and then doing:
@@ -108,7 +108,7 b' calculation, we will need two top-level functions from :file:`pidigits.py`:'
 
 We will also use the :func:`plot_two_digit_freqs` function to plot the
 results. The code to run this calculation in parallel is contained in
-:file:`docs/examples/parallel/parallelpi.py`. This code can be run in parallel
+:file:`examples/parallel/parallelpi.py`. This code can be run in parallel
 using IPython by following these steps:
 
 1. Use :command:`ipcluster` to start 15 engines. We used 16 cores of an SGE linux

docs/source/parallel/parallel_intro.rst

@@ -9,11 +9,11 b' Examples'
 ========
 
 We have various example scripts and notebooks for using IPython.parallel in our
-:file:`docs/examples/parallel` directory, or they can be found `on GitHub`__.
+:file:`examples/parallel` directory, or they can be found `on GitHub`__.
 Some of these are covered in more detail in the :ref:`examples
 <parallel_examples>` section.
 
-.. __: https://github.com/ipython/ipython/tree/master/docs/examples/parallel
+.. __: https://github.com/ipython/ipython/tree/master/examples/parallel
 
 Introduction
 ============

docs/source/whatsnew/version0.11.rst

@@ -497,7 +497,7 b' Additional new features'
 
 * For developers :mod:`IPython.lib.inputhook` provides a simple interface
   for managing the event loops in their interactive GUI applications.
-  Examples can be found in our :file:`docs/examples/lib` directory.
+  Examples can be found in our :file:`examples/lib` directory.
 
 Backwards incompatible changes
 ------------------------------

docs/source/whatsnew/version0.13.rst

@@ -127,7 +127,7 b' to the user, with callbacks in Javascript executing calls to the Kernel. This'
 will enable many interactive elements to be added by users in notebooks.
 
 An example of this capability has been provided as a proof of concept in
-:file:`docs/examples/widgets` that lets you directly communicate with one or more
+:file:`examples/widgets` that lets you directly communicate with one or more
 parallel engines, acting as a mini-console for parallel debugging and
 introspection.