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Merge pull request #9863 from Carreau/no-parallel...
Carol Willing -
r22790:a45a4e10 merge
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@@ -43,10 +43,12 b' For example::'
43 Custom exception tracebacks
43 Custom exception tracebacks
44 ===========================
44 ===========================
45
45
46 Rarely, you might want to display a different traceback with an exception -
46 Rarely, you might want to display a custom traceback when reporting an
47 IPython's own parallel computing framework does this to display errors from the
47 exception. To do this, define the custom traceback using
48 engines. To do this, define a ``_render_traceback_(self)`` method which returns
48 `_render_traceback_(self)` method which returns a list of strings, one string
49 a list of strings, each containing one line of the traceback.
49 for each line of the traceback. For example, the `ipyparallel
50 <http://ipyparallel.readthedocs.io/>`__ a parallel computing framework for
51 IPython, does this to display errors from multiple engines.
50
52
51 Please be conservative in using this feature; by replacing the default traceback
53 Please be conservative in using this feature; by replacing the default traceback
52 you may hide important information from the user.
54 you may hide important information from the user.
@@ -41,20 +41,17 b' The next thing you need to know is what to call your configuration file. The'
41 basic idea is that each application has its own default configuration filename.
41 basic idea is that each application has its own default configuration filename.
42 The default named used by the :command:`ipython` command line program is
42 The default named used by the :command:`ipython` command line program is
43 :file:`ipython_config.py`, and *all* IPython applications will use this file.
43 :file:`ipython_config.py`, and *all* IPython applications will use this file.
44 Other applications, such as the parallel :command:`ipcluster` scripts or the
44 The IPython kernel will load its own config file *after*
45 QtConsole will load their own config files *after* :file:`ipython_config.py`. To
45 :file:`ipython_config.py`. To load a particular configuration file instead of
46 load a particular configuration file instead of the default, the name can be
46 the default, the name can be overridden by the ``config_file`` command line
47 overridden by the ``config_file`` command line flag.
47 flag.
48
48
49 To generate the default configuration files, do::
49 To generate the default configuration files, do::
50
50
51 $ ipython profile create
51 $ ipython profile create
52
52
53 and you will have a default :file:`ipython_config.py` in your IPython directory
53 and you will have a default :file:`ipython_config.py` in your IPython directory
54 under :file:`profile_default`. If you want the default config files for the
54 under :file:`profile_default`.
55 :mod:`IPython.parallel` applications, add ``--parallel`` to the end of the
56 command-line args.
57
58 .. note::
55 .. note::
59
56
60 IPython configuration options are case sensitive, and IPython cannot
57 IPython configuration options are case sensitive, and IPython cannot
@@ -232,50 +232,9 b' and clients.'
232 Interactive parallel computing
232 Interactive parallel computing
233 ==============================
233 ==============================
234
234
235 .. note::
236
235
237 This functionality is optional and now part of the `ipyparallel
236 This functionality is optional and now part of the `ipyparallel
238 <http://ipyparallel.readthedocs.io/>`_ project.
237 <http://ipyparallel.readthedocs.io/>`_ project.
239
240 Increasingly, parallel computer hardware, such as multicore CPUs, clusters and
241 supercomputers, is becoming ubiquitous. Over the last several years, we have
242 developed an architecture within IPython that allows such hardware to be used
243 quickly and easily from Python. Moreover, this architecture is designed to
244 support interactive and collaborative parallel computing.
245
246 The main features of this system are:
247
248 * Quickly parallelize Python code from an interactive Python/IPython session.
249
250 * A flexible and dynamic process model that be deployed on anything from
251 multicore workstations to supercomputers.
252
253 * An architecture that supports many different styles of parallelism, from
254 message passing to task farming. And all of these styles can be handled
255 interactively.
256
257 * Both blocking and fully asynchronous interfaces.
258
259 * High level APIs that enable many things to be parallelized in a few lines
260 of code.
261
262 * Write parallel code that will run unchanged on everything from multicore
263 workstations to supercomputers.
264
265 * Full integration with Message Passing libraries (MPI).
266
267 * Capabilities based security model with full encryption of network connections.
268
269 * Share live parallel jobs with other users securely. We call this
270 collaborative parallel computing.
271
272 * Dynamically load balanced task farming system.
273
274 * Robust error handling. Python exceptions raised in parallel execution are
275 gathered and presented to the top-level code.
276
277 For more information, see our :ref:`overview <parallel_index>` of using IPython
278 for parallel computing.
279
238
280 Portability and Python requirements
239 Portability and Python requirements
281 -----------------------------------
240 -----------------------------------
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