IPYTHON_DIR -> IPYTHONDIR in comments and documentation

IPython/core/application.py

@@ -1,336 +1,336 b''
 # encoding: utf-8
 """
 An application for IPython.
 
 All top-level applications should use the classes in this module for
 handling configuration and creating componenets.
 
 The job of an :class:`Application` is to create the master configuration
 object and then create the configurable objects, passing the config to them.
 
 Authors:
 
 * Brian Granger
 * Fernando Perez
 * Min RK
 
 """
 
 #-----------------------------------------------------------------------------
 #  Copyright (C) 2008-2011  The IPython Development Team
 #
 #  Distributed under the terms of the BSD License.  The full license is in
 #  the file COPYING, distributed as part of this software.
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # Imports
 #-----------------------------------------------------------------------------
 
 import atexit
 import glob
 import logging
 import os
 import shutil
 import sys
 
 from IPython.config.application import Application, catch_config_error
 from IPython.config.configurable import Configurable
 from IPython.config.loader import Config, ConfigFileNotFound
 from IPython.core import release, crashhandler
 from IPython.core.profiledir import ProfileDir, ProfileDirError
 from IPython.utils.path import get_ipython_dir, get_ipython_package_dir
 from IPython.utils.traitlets import List, Unicode, Type, Bool, Dict
 from IPython.utils import py3compat
 
 #-----------------------------------------------------------------------------
 # Classes and functions
 #-----------------------------------------------------------------------------
 
 
 #-----------------------------------------------------------------------------
 # Base Application Class
 #-----------------------------------------------------------------------------
 
 # aliases and flags
 
 base_aliases = {
     'profile' : 'BaseIPythonApplication.profile',
     'ipython-dir' : 'BaseIPythonApplication.ipython_dir',
     'log-level' : 'Application.log_level',
 }
 
 base_flags = dict(
     debug = ({'Application' : {'log_level' : logging.DEBUG}},
             "set log level to logging.DEBUG (maximize logging output)"),
     quiet = ({'Application' : {'log_level' : logging.CRITICAL}},
             "set log level to logging.CRITICAL (minimize logging output)"),
     init = ({'BaseIPythonApplication' : {
                     'copy_config_files' : True,
                     'auto_create' : True}
             }, """Initialize profile with default config files.  This is equivalent
             to running `ipython profile create <profile>` prior to startup.
             """)
 )
 
 
 class BaseIPythonApplication(Application):
 
     name = Unicode(u'ipython')
     description = Unicode(u'IPython: an enhanced interactive Python shell.')
     version = Unicode(release.version)
 
     aliases = Dict(base_aliases)
     flags = Dict(base_flags)
     classes = List([ProfileDir])
 
     # Track whether the config_file has changed,
     # because some logic happens only if we aren't using the default.
     config_file_specified = Bool(False)
 
     config_file_name = Unicode(u'ipython_config.py')
     def _config_file_name_default(self):
         return self.name.replace('-','_') + u'_config.py'
     def _config_file_name_changed(self, name, old, new):
         if new != old:
             self.config_file_specified = True
 
     # The directory that contains IPython's builtin profiles.
     builtin_profile_dir = Unicode(
         os.path.join(get_ipython_package_dir(), u'config', u'profile', u'default')
     )
 
     config_file_paths = List(Unicode)
     def _config_file_paths_default(self):
         return [os.getcwdu()]
 
     profile = Unicode(u'default', config=True,
         help="""The IPython profile to use."""
     )
 
     def _profile_changed(self, name, old, new):
         self.builtin_profile_dir = os.path.join(
                 get_ipython_package_dir(), u'config', u'profile', new
         )
 
     ipython_dir = Unicode(get_ipython_dir(), config=True,
         help="""
         The name of the IPython directory. This directory is used for logging
         configuration (through profiles), history storage, etc. The default
         is usually $HOME/.ipython. This options can also be specified through
-        the environment variable IPYTHON_DIR.
+        the environment variable IPYTHONDIR.
         """
     )
 
     overwrite = Bool(False, config=True,
         help="""Whether to overwrite existing config files when copying""")
     auto_create = Bool(False, config=True,
         help="""Whether to create profile dir if it doesn't exist""")
 
     config_files = List(Unicode)
     def _config_files_default(self):
         return [u'ipython_config.py']
 
     copy_config_files = Bool(False, config=True,
         help="""Whether to install the default config files into the profile dir.
         If a new profile is being created, and IPython contains config files for that
         profile, then they will be staged into the new directory.  Otherwise,
         default config files will be automatically generated.
         """)
     
     verbose_crash = Bool(False, config=True,
         help="""Create a massive crash report when IPython enconters what may be an
         internal error.  The default is to append a short message to the
         usual traceback""")
 
     # The class to use as the crash handler.
     crash_handler_class = Type(crashhandler.CrashHandler)
 
     def __init__(self, **kwargs):
         super(BaseIPythonApplication, self).__init__(**kwargs)
-        # ensure even default IPYTHON_DIR exists
+        # ensure even default IPYTHONDIR exists
         if not os.path.exists(self.ipython_dir):
             self._ipython_dir_changed('ipython_dir', self.ipython_dir, self.ipython_dir)
 
     #-------------------------------------------------------------------------
     # Various stages of Application creation
     #-------------------------------------------------------------------------
 
     def init_crash_handler(self):
         """Create a crash handler, typically setting sys.excepthook to it."""
         self.crash_handler = self.crash_handler_class(self)
         sys.excepthook = self.excepthook
         def unset_crashhandler():
             sys.excepthook = sys.__excepthook__
         atexit.register(unset_crashhandler)
     
     def excepthook(self, etype, evalue, tb):
         """this is sys.excepthook after init_crashhandler
         
         set self.verbose_crash=True to use our full crashhandler, instead of
         a regular traceback with a short message (crash_handler_lite)
         """
         
         if self.verbose_crash:
             return self.crash_handler(etype, evalue, tb)
         else:
             return crashhandler.crash_handler_lite(etype, evalue, tb)
     
     def _ipython_dir_changed(self, name, old, new):
         if old in sys.path:
             sys.path.remove(old)
         sys.path.append(os.path.abspath(new))
         if not os.path.isdir(new):
             os.makedirs(new, mode=0777)
         readme = os.path.join(new, 'README')
         if not os.path.exists(readme):
             path = os.path.join(get_ipython_package_dir(), u'config', u'profile')
             shutil.copy(os.path.join(path, 'README'), readme)
         self.log.debug("IPYTHON_DIR set to: %s" % new)
 
     def load_config_file(self, suppress_errors=True):
         """Load the config file.
 
         By default, errors in loading config are handled, and a warning
         printed on screen. For testing, the suppress_errors option is set
         to False, so errors will make tests fail.
         """
         self.log.debug("Searching path %s for config files", self.config_file_paths)
         base_config = 'ipython_config.py'
         self.log.debug("Attempting to load config file: %s" %
                        base_config)
         try:
             Application.load_config_file(
                 self,
                 base_config,
                 path=self.config_file_paths
             )
         except ConfigFileNotFound:
             # ignore errors loading parent
             self.log.debug("Config file %s not found", base_config)
             pass
         if self.config_file_name == base_config:
             # don't load secondary config
             return
         self.log.debug("Attempting to load config file: %s" %
                        self.config_file_name)
         try:
             Application.load_config_file(
                 self,
                 self.config_file_name,
                 path=self.config_file_paths
             )
         except ConfigFileNotFound:
             # Only warn if the default config file was NOT being used.
             if self.config_file_specified:
                 msg = self.log.warn
             else:
                 msg = self.log.debug
             msg("Config file not found, skipping: %s", self.config_file_name)
         except:
             # For testing purposes.
             if not suppress_errors:
                 raise
             self.log.warn("Error loading config file: %s" %
                           self.config_file_name, exc_info=True)
 
     def init_profile_dir(self):
         """initialize the profile dir"""
         try:
             # location explicitly specified:
             location = self.config.ProfileDir.location
         except AttributeError:
             # location not specified, find by profile name
             try:
                 p = ProfileDir.find_profile_dir_by_name(self.ipython_dir, self.profile, self.config)
             except ProfileDirError:
                 # not found, maybe create it (always create default profile)
                 if self.auto_create or self.profile=='default':
                     try:
                         p = ProfileDir.create_profile_dir_by_name(self.ipython_dir, self.profile, self.config)
                     except ProfileDirError:
                         self.log.fatal("Could not create profile: %r"%self.profile)
                         self.exit(1)
                     else:
                         self.log.info("Created profile dir: %r"%p.location)
                 else:
                     self.log.fatal("Profile %r not found."%self.profile)
                     self.exit(1)
             else:
                 self.log.info("Using existing profile dir: %r"%p.location)
         else:
             # location is fully specified
             try:
                 p = ProfileDir.find_profile_dir(location, self.config)
             except ProfileDirError:
                 # not found, maybe create it
                 if self.auto_create:
                     try:
                         p = ProfileDir.create_profile_dir(location, self.config)
                     except ProfileDirError:
                         self.log.fatal("Could not create profile directory: %r"%location)
                         self.exit(1)
                     else:
                         self.log.info("Creating new profile dir: %r"%location)
                 else:
                     self.log.fatal("Profile directory %r not found."%location)
                     self.exit(1)
             else:
                 self.log.info("Using existing profile dir: %r"%location)
 
         self.profile_dir = p
         self.config_file_paths.append(p.location)
 
     def init_config_files(self):
         """[optionally] copy default config files into profile dir."""
         # copy config files
         path = self.builtin_profile_dir
         if self.copy_config_files:
             src = self.profile
 
             cfg = self.config_file_name
             if path and os.path.exists(os.path.join(path, cfg)):
                 self.log.warn("Staging %r from %s into %r [overwrite=%s]"%(
                         cfg, src, self.profile_dir.location, self.overwrite)
                 )
                 self.profile_dir.copy_config_file(cfg, path=path, overwrite=self.overwrite)
             else:
                 self.stage_default_config_file()
         else:
             # Still stage *bundled* config files, but not generated ones
             # This is necessary for `ipython profile=sympy` to load the profile
             # on the first go
             files = glob.glob(os.path.join(path, '*.py'))
             for fullpath in files:
                 cfg = os.path.basename(fullpath)
                 if self.profile_dir.copy_config_file(cfg, path=path, overwrite=False):
                     # file was copied
                     self.log.warn("Staging bundled %s from %s into %r"%(
                             cfg, self.profile, self.profile_dir.location)
                     )
 
 
     def stage_default_config_file(self):
         """auto generate default config file, and stage it into the profile."""
         s = self.generate_config_file()
         fname = os.path.join(self.profile_dir.location, self.config_file_name)
         if self.overwrite or not os.path.exists(fname):
             self.log.warn("Generating default config file: %r"%(fname))
             with open(fname, 'w') as f:
                 f.write(s)
 
     @catch_config_error
     def initialize(self, argv=None):
         # don't hook up crash handler before parsing command-line
         self.parse_command_line(argv)
         self.init_crash_handler()
         if self.subapp is not None:
             # stop here if subapp is taking over
             return
         cl_config = self.config
         self.init_profile_dir()
         self.init_config_files()
         self.load_config_file()
         # enforce cl-opts override configfile opts:
         self.update_config(cl_config)
 

IPython/core/profileapp.py

@@ -1,293 +1,293 b''
 # encoding: utf-8
 """
 An application for managing IPython profiles.
 
 To be invoked as the `ipython profile` subcommand.
 
 Authors:
 
 * Min RK
 
 """
 
 #-----------------------------------------------------------------------------
 #  Copyright (C) 2008-2011  The IPython Development Team
 #
 #  Distributed under the terms of the BSD License.  The full license is in
 #  the file COPYING, distributed as part of this software.
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # Imports
 #-----------------------------------------------------------------------------
 
 import logging
 import os
 
 from IPython.config.application import Application, boolean_flag
 from IPython.core.application import (
     BaseIPythonApplication, base_flags, base_aliases
 )
 from IPython.core.profiledir import ProfileDir
 from IPython.utils.path import get_ipython_dir, get_ipython_package_dir
 from IPython.utils.traitlets import Unicode, Bool, Dict
 
 #-----------------------------------------------------------------------------
 # Constants
 #-----------------------------------------------------------------------------
 
 create_help = """Create an IPython profile by name
 
 Create an ipython profile directory by its name or
 profile directory path. Profile directories contain
 configuration, log and security related files and are named
 using the convention 'profile_<name>'. By default they are
 located in your ipython directory. Once created, you will
 can edit the configuration files in the profile
 directory to configure IPython. Most users will create a
 profile directory by name,
 `ipython profile create myprofile`, which will put the directory
 in `<ipython_dir>/profile_myprofile`.
 """
 list_help = """List available IPython profiles
 
 List all available profiles, by profile location, that can
 be found in the current working directly or in the ipython
 directory. Profile directories are named using the convention
 'profile_<profile>'.
 """
 profile_help = """Manage IPython profiles
 
 Profile directories contain
 configuration, log and security related files and are named
 using the convention 'profile_<name>'. By default they are
 located in your ipython directory.  You can create profiles
 with `ipython profile create <name>`, or see the profiles you
 already have with `ipython profile list`
 
 To get started configuring IPython, simply do:
 
 $> ipython profile create
 
 and IPython will create the default profile in <ipython_dir>/profile_default,
 where you can edit ipython_config.py to start configuring IPython.
 
 """
 
 _list_examples = "ipython profile list  # list all profiles"
 
 _create_examples = """
 ipython profile create foo         # create profile foo w/ default config files
 ipython profile create foo --reset # restage default config files over current
 ipython profile create foo --parallel # also stage parallel config files
 """
 
 _main_examples = """
 ipython profile create -h  # show the help string for the create subcommand
 ipython profile list -h    # show the help string for the list subcommand
 """
 
 #-----------------------------------------------------------------------------
 # Profile Application Class (for `ipython profile` subcommand)
 #-----------------------------------------------------------------------------
 
 
 def list_profiles_in(path):
     """list profiles in a given root directory"""
     files = os.listdir(path)
     profiles = []
     for f in files:
         full_path = os.path.join(path, f)
         if os.path.isdir(full_path) and f.startswith('profile_'):
             profiles.append(f.split('_',1)[-1])
     return profiles
 
 
 def list_bundled_profiles():
     """list profiles that are bundled with IPython."""
     path = os.path.join(get_ipython_package_dir(), u'config', u'profile')
     files = os.listdir(path)
     profiles = []
     for profile in files:
         full_path = os.path.join(path, profile)
         if os.path.isdir(full_path) and profile != "__pycache__":
             profiles.append(profile)
     return profiles
 
 
 class ProfileList(Application):
     name = u'ipython-profile'
     description = list_help
     examples = _list_examples
 
     aliases = Dict({
         'ipython-dir' : 'ProfileList.ipython_dir',
         'log-level' : 'Application.log_level',
     })
     flags = Dict(dict(
         debug = ({'Application' : {'log_level' : 0}},
             "Set Application.log_level to 0, maximizing log output."
         )
     ))
 
     ipython_dir = Unicode(get_ipython_dir(), config=True,
         help="""
         The name of the IPython directory. This directory is used for logging
         configuration (through profiles), history storage, etc. The default
         is usually $HOME/.ipython. This options can also be specified through
-        the environment variable IPYTHON_DIR.
+        the environment variable IPYTHONDIR.
         """
     )
 
 
     def _print_profiles(self, profiles):
         """print list of profiles, indented."""
         for profile in profiles:
             print '    %s' % profile
 
     def list_profile_dirs(self):
         profiles = list_bundled_profiles()
         if profiles:
             print
             print "Available profiles in IPython:"
             self._print_profiles(profiles)
             print
             print "    The first request for a bundled profile will copy it"
             print "    into your IPython directory (%s)," % self.ipython_dir
             print "    where you can customize it."
         
         profiles = list_profiles_in(self.ipython_dir)
         if profiles:
             print
             print "Available profiles in %s:" % self.ipython_dir
             self._print_profiles(profiles)
         
         profiles = list_profiles_in(os.getcwdu())
         if profiles:
             print
             print "Available profiles in current directory (%s):" % os.getcwdu()
             self._print_profiles(profiles)
         
         print
         print "To use any of the above profiles, start IPython with:"
         print "    ipython --profile=<name>"
         print
 
     def start(self):
         self.list_profile_dirs()
 
 
 create_flags = {}
 create_flags.update(base_flags)
 # don't include '--init' flag, which implies running profile create in other apps
 create_flags.pop('init')
 create_flags['reset'] = ({'ProfileCreate': {'overwrite' : True}},
                         "reset config files in this profile to the defaults.")
 create_flags['parallel'] = ({'ProfileCreate': {'parallel' : True}},
                         "Include the config files for parallel "
                         "computing apps (ipengine, ipcontroller, etc.)")
 
 
 class ProfileCreate(BaseIPythonApplication):
     name = u'ipython-profile'
     description = create_help
     examples = _create_examples
     auto_create = Bool(True, config=False)
 
     def _copy_config_files_default(self):
         return True
 
     parallel = Bool(False, config=True,
         help="whether to include parallel computing config files")
     def _parallel_changed(self, name, old, new):
         parallel_files = [   'ipcontroller_config.py',
                             'ipengine_config.py',
                             'ipcluster_config.py'
                         ]
         if new:
             for cf in parallel_files:
                 self.config_files.append(cf)
         else:
             for cf in parallel_files:
                 if cf in self.config_files:
                     self.config_files.remove(cf)
 
     def parse_command_line(self, argv):
         super(ProfileCreate, self).parse_command_line(argv)
         # accept positional arg as profile name
         if self.extra_args:
             self.profile = self.extra_args[0]
 
     flags = Dict(create_flags)
 
     classes = [ProfileDir]
 
     def init_config_files(self):
         super(ProfileCreate, self).init_config_files()
         # use local imports, since these classes may import from here
         from IPython.frontend.terminal.ipapp import TerminalIPythonApp
         apps = [TerminalIPythonApp]
         try:
             from IPython.frontend.qt.console.qtconsoleapp import IPythonQtConsoleApp
         except Exception:
             # this should be ImportError, but under weird circumstances
             # this might be an AttributeError, or possibly others
             # in any case, nothing should cause the profile creation to crash.
             pass
         else:
             apps.append(IPythonQtConsoleApp)
         try:
             from IPython.frontend.html.notebook.notebookapp import NotebookApp
         except ImportError:
             pass
         except Exception:
             self.log.debug('Unexpected error when importing NotebookApp',
                            exc_info=True
             )
         else:
             apps.append(NotebookApp)
         if self.parallel:
             from IPython.parallel.apps.ipcontrollerapp import IPControllerApp
             from IPython.parallel.apps.ipengineapp import IPEngineApp
             from IPython.parallel.apps.ipclusterapp import IPClusterStart
             from IPython.parallel.apps.iploggerapp import IPLoggerApp
             apps.extend([
                 IPControllerApp,
                 IPEngineApp,
                 IPClusterStart,
                 IPLoggerApp,
             ])
         for App in apps:
             app = App()
             app.config.update(self.config)
             app.log = self.log
             app.overwrite = self.overwrite
             app.copy_config_files=True
             app.profile = self.profile
             app.init_profile_dir()
             app.init_config_files()
 
     def stage_default_config_file(self):
         pass
 
 
 class ProfileApp(Application):
     name = u'ipython-profile'
     description = profile_help
     examples = _main_examples
 
     subcommands = Dict(dict(
         create = (ProfileCreate, "Create a new profile dir with default config files"),
         list = (ProfileList, "List existing profiles")
     ))
 
     def start(self):
         if self.subapp is None:
             print "No subcommand specified. Must specify one of: %s"%(self.subcommands.keys())
             print
             self.print_description()
             self.print_subcommands()
             self.exit(1)
         else:
             return self.subapp.start()
 

IPython/core/usage.py

@@ -1,535 +1,535 b''
 # -*- coding: utf-8 -*-
 """Usage information for the main IPython applications.
 """
 #-----------------------------------------------------------------------------
 #  Copyright (C) 2008-2011  The IPython Development Team
 #  Copyright (C) 2001-2007 Fernando Perez. <[e-mail]>
 #
 #  Distributed under the terms of the BSD License.  The full license is in
 #  the file COPYING, distributed as part of this software.
 #-----------------------------------------------------------------------------
 
 import sys
 from IPython.core import release
 
 cl_usage = """\
 =========
  IPython
 =========
 
 Tools for Interactive Computing in Python
 =========================================
 
     A Python shell with automatic history (input and output), dynamic object
     introspection, easier configuration, command completion, access to the
     system shell and more.  IPython can also be embedded in running programs.
 
 
 Usage
 
     ipython [subcommand] [options] [files]
 
     If invoked with no options, it executes all the files listed in sequence
     and exits, use -i to enter interactive mode after running the files.  Files
     ending in .py will be treated as normal Python, but files ending in .ipy
     can contain special IPython syntax (magic commands, shell expansions, etc.)
 
     Almost all configuration in IPython is available via the command-line. Do
     `ipython --help-all` to see all available options.  For persistent
     configuration, look into your `ipython_config.py` configuration file for
     details.
 
-    This file is typically installed in the `IPYTHON_DIR` directory, and there
+    This file is typically installed in the `IPYTHONDIR` directory, and there
     is a separate configuration directory for each profile. The default profile
-    directory will be located in $IPYTHON_DIR/profile_default. For Linux users,
-    IPYTHON_DIR defaults to `$HOME/.config/ipython`, and for other Unix systems
+    directory will be located in $IPYTHONDIR/profile_default. For Linux users,
+    IPYTHONDIR defaults to `$HOME/.config/ipython`, and for other Unix systems
     to `$HOME/.ipython`.  For Windows users, $HOME resolves to C:\\Documents
     and Settings\\YourUserName in most instances.
 
     To initialize a profile with the default configuration file, do::
 
       $> ipython profile create
 
-    and start editing `IPYTHON_DIR/profile_default/ipython_config.py`
+    and start editing `IPYTHONDIR/profile_default/ipython_config.py`
 
     In IPython's documentation, we will refer to this directory as
-    `IPYTHON_DIR`, you can change its default location by creating an
+    `IPYTHONDIR`, you can change its default location by creating an
     environment variable with this name and setting it to the desired path.
 
     For more information, see the manual available in HTML and PDF in your
     installation, or online at http://ipython.org/documentation.html.
 """
 
 interactive_usage = """
 IPython -- An enhanced Interactive Python
 =========================================
 
 IPython offers a combination of convenient shell features, special commands
 and a history mechanism for both input (command history) and output (results
 caching, similar to Mathematica). It is intended to be a fully compatible
 replacement for the standard Python interpreter, while offering vastly
 improved functionality and flexibility.
 
 At your system command line, type 'ipython -h' to see the command line
 options available. This document only describes interactive features.
 
 MAIN FEATURES
 
 * Access to the standard Python help. As of Python 2.1, a help system is
   available with access to object docstrings and the Python manuals. Simply
   type 'help' (no quotes) to access it.
 
 * Magic commands: type %magic for information on the magic subsystem.
 
 * System command aliases, via the %alias command or the configuration file(s).
 
 * Dynamic object information:
 
   Typing ?word or word? prints detailed information about an object.  If
   certain strings in the object are too long (docstrings, code, etc.) they get
   snipped in the center for brevity.
 
   Typing ??word or word?? gives access to the full information without
   snipping long strings. Long strings are sent to the screen through the less
   pager if longer than the screen, printed otherwise.
 
   The ?/?? system gives access to the full source code for any object (if
   available), shows function prototypes and other useful information.
 
   If you just want to see an object's docstring, type '%pdoc object' (without
   quotes, and without % if you have automagic on).
 
   Both %pdoc and ?/?? give you access to documentation even on things which are
   not explicitely defined. Try for example typing {}.get? or after import os,
   type os.path.abspath??. The magic functions %pdef, %source and %file operate
   similarly.
 
 * Completion in the local namespace, by typing TAB at the prompt.
 
   At any time, hitting tab will complete any available python commands or
   variable names, and show you a list of the possible completions if there's
   no unambiguous one. It will also complete filenames in the current directory.
 
   This feature requires the readline and rlcomplete modules, so it won't work
   if your Python lacks readline support (such as under Windows).
 
 * Search previous command history in two ways (also requires readline):
 
   - Start typing, and then use Ctrl-p (previous,up) and Ctrl-n (next,down) to
   search through only the history items that match what you've typed so
   far. If you use Ctrl-p/Ctrl-n at a blank prompt, they just behave like
   normal arrow keys.
 
   - Hit Ctrl-r: opens a search prompt. Begin typing and the system searches
   your history for lines that match what you've typed so far, completing as
   much as it can.
 
   - %hist: search history by index (this does *not* require readline).
 
 * Persistent command history across sessions.
 
 * Logging of input with the ability to save and restore a working session.
 
 * System escape with !. Typing !ls will run 'ls' in the current directory.
 
 * The reload command does a 'deep' reload of a module: changes made to the
   module since you imported will actually be available without having to exit.
 
 * Verbose and colored exception traceback printouts. See the magic xmode and
   xcolor functions for details (just type %magic).
 
 * Input caching system:
 
   IPython offers numbered prompts (In/Out) with input and output caching. All
   input is saved and can be retrieved as variables (besides the usual arrow
   key recall).
 
   The following GLOBAL variables always exist (so don't overwrite them!):
   _i: stores previous input.
   _ii: next previous.
   _iii: next-next previous.
   _ih : a list of all input _ih[n] is the input from line n.
 
   Additionally, global variables named _i<n> are dynamically created (<n>
   being the prompt counter), such that _i<n> == _ih[<n>]
 
   For example, what you typed at prompt 14 is available as _i14 and _ih[14].
 
   You can create macros which contain multiple input lines from this history,
   for later re-execution, with the %macro function.
 
   The history function %hist allows you to see any part of your input history
   by printing a range of the _i variables. Note that inputs which contain
   magic functions (%) appear in the history with a prepended comment. This is
   because they aren't really valid Python code, so you can't exec them.
 
 * Output caching system:
 
   For output that is returned from actions, a system similar to the input
   cache exists but using _ instead of _i. Only actions that produce a result
   (NOT assignments, for example) are cached. If you are familiar with
   Mathematica, IPython's _ variables behave exactly like Mathematica's %
   variables.
 
   The following GLOBAL variables always exist (so don't overwrite them!):
   _ (one underscore): previous output.
   __ (two underscores): next previous.
   ___ (three underscores): next-next previous.
 
   Global variables named _<n> are dynamically created (<n> being the prompt
   counter), such that the result of output <n> is always available as _<n>.
 
   Finally, a global dictionary named _oh exists with entries for all lines
   which generated output.
 
 * Directory history:
 
   Your history of visited directories is kept in the global list _dh, and the
   magic %cd command can be used to go to any entry in that list.
 
 * Auto-parentheses and auto-quotes (adapted from Nathan Gray's LazyPython)
 
     1. Auto-parentheses
         Callable objects (i.e. functions, methods, etc) can be invoked like
         this (notice the commas between the arguments):
             In [1]: callable_ob arg1, arg2, arg3
         and the input will be translated to this:
             ------> callable_ob(arg1, arg2, arg3)
         This feature is off by default (in rare cases it can produce
         undesirable side-effects), but you can activate it at the command-line
         by starting IPython with `--autocall 1`, set it permanently in your
         configuration file, or turn on at runtime with `%autocall 1`.
 
         You can force auto-parentheses by using '/' as the first character
         of a line.  For example:
             In [1]: /globals             # becomes 'globals()'
         Note that the '/' MUST be the first character on the line!  This
         won't work:
             In [2]: print /globals    # syntax error
 
         In most cases the automatic algorithm should work, so you should
         rarely need to explicitly invoke /. One notable exception is if you
         are trying to call a function with a list of tuples as arguments (the
         parenthesis will confuse IPython):
             In [1]: zip (1,2,3),(4,5,6)  # won't work
         but this will work:
             In [2]: /zip (1,2,3),(4,5,6)
             ------> zip ((1,2,3),(4,5,6))
             Out[2]= [(1, 4), (2, 5), (3, 6)]
 
         IPython tells you that it has altered your command line by
         displaying the new command line preceded by -->.  e.g.:
             In [18]: callable list
             -------> callable (list)
 
     2. Auto-Quoting
         You can force auto-quoting of a function's arguments by using ',' as
         the first character of a line.  For example:
             In [1]: ,my_function /home/me   # becomes my_function("/home/me")
 
         If you use ';' instead, the whole argument is quoted as a single
         string (while ',' splits on whitespace):
             In [2]: ,my_function a b c   # becomes my_function("a","b","c")
             In [3]: ;my_function a b c   # becomes my_function("a b c")
 
         Note that the ',' MUST be the first character on the line!  This
         won't work:
             In [4]: x = ,my_function /home/me    # syntax error
 """
 
 interactive_usage_min =  """\
 An enhanced console for Python.
 Some of its features are:
 - Readline support if the readline library is present.
 - Tab completion in the local namespace.
 - Logging of input, see command-line options.
 - System shell escape via ! , eg !ls.
 - Magic commands, starting with a % (like %ls, %pwd, %cd, etc.)
 - Keeps track of locally defined variables via %who, %whos.
 - Show object information with a ? eg ?x or x? (use ?? for more info).
 """
 
 quick_reference = r"""
 IPython -- An enhanced Interactive Python - Quick Reference Card
 ================================================================
 
 obj?, obj??      : Get help, or more help for object (also works as
                    ?obj, ??obj).
 ?foo.*abc*       : List names in 'foo' containing 'abc' in them.
 %magic           : Information about IPython's 'magic' % functions.
 
 Magic functions are prefixed by %, and typically take their arguments without
 parentheses, quotes or even commas for convenience.
 
 Example magic function calls:
 
 %alias d ls -F   : 'd' is now an alias for 'ls -F'
 alias d ls -F    : Works if 'alias' not a python name
 alist = %alias   : Get list of aliases to 'alist'
 cd /usr/share    : Obvious. cd -<tab> to choose from visited dirs.
 %cd??            : See help AND source for magic %cd
 
 System commands:
 
 !cp a.txt b/     : System command escape, calls os.system()
 cp a.txt b/      : after %rehashx, most system commands work without !
 cp ${f}.txt $bar : Variable expansion in magics and system commands
 files = !ls /usr : Capture sytem command output
 files.s, files.l, files.n: "a b c", ['a','b','c'], 'a\nb\nc'
 
 History:
 
 _i, _ii, _iii    : Previous, next previous, next next previous input
 _i4, _ih[2:5]    : Input history line 4, lines 2-4
 exec _i81        : Execute input history line #81 again
 %rep 81          : Edit input history line #81
 _, __, ___       : previous, next previous, next next previous output
 _dh              : Directory history
 _oh              : Output history
 %hist            : Command history. '%hist -g foo' search history for 'foo'
 
 Autocall:
 
 f 1,2            : f(1,2)  # Off by default, enable with %autocall magic.
 /f 1,2           : f(1,2) (forced autoparen)
 ,f 1 2           : f("1","2")
 ;f 1 2           : f("1 2")
 
 Remember: TAB completion works in many contexts, not just file names
 or python names.
 
 The following magic functions are currently available:
 
 """
 
 gui_reference = """\
 ===============================
  The graphical IPython console
 ===============================
 
 This console is designed to emulate the look, feel and workflow of a terminal
 environment, while adding a number of enhancements that are simply not possible
 in a real terminal, such as inline syntax highlighting, true multiline editing,
 inline graphics and much more.
 
 This quick reference document contains the basic information you'll need to
 know to make the most efficient use of it.  For the various command line
 options available at startup, type ``ipython qtconsole --help`` at the command line.
 
 
 Multiline editing
 =================
 
 The graphical console is capable of true multiline editing, but it also tries
 to behave intuitively like a terminal when possible.  If you are used to
 IPython's old terminal behavior, you should find the transition painless, and
 once you learn a few basic keybindings it will be a much more efficient
 environment.
 
 For single expressions or indented blocks, the console behaves almost like the
 terminal IPython: single expressions are immediately evaluated, and indented
 blocks are evaluated once a single blank line is entered::
 
     In [1]: print "Hello IPython!"  # Enter was pressed at the end of the line
     Hello IPython!
 
     In [2]: for i in range(10):
        ...: 	print i,
        ...:
     0 1 2 3 4 5 6 7 8 9
 
 If you want to enter more than one expression in a single input block
 (something not possible in the terminal), you can use ``Control-Enter`` at the
 end of your first line instead of ``Enter``.  At that point the console goes
 into 'cell mode' and even if your inputs are not indented, it will continue
 accepting arbitrarily many lines until either you enter an extra blank line or
 you hit ``Shift-Enter`` (the key binding that forces execution).  When a
 multiline cell is entered, IPython analyzes it and executes its code producing
 an ``Out[n]`` prompt only for the last expression in it, while the rest of the
 cell is executed as if it was a script.  An example should clarify this::
 
     In [3]: x=1  # Hit C-Enter here
        ...: y=2  # from now on, regular Enter is sufficient
        ...: z=3
        ...: x**2  # This does *not* produce an Out[] value
        ...: x+y+z  # Only the last expression does
        ...:
     Out[3]: 6
 
 The behavior where an extra blank line forces execution is only active if you
 are actually typing at the keyboard each line, and is meant to make it mimic
 the IPython terminal behavior.  If you paste a long chunk of input (for example
 a long script copied form an editor or web browser), it can contain arbitrarily
 many intermediate blank lines and they won't cause any problems.  As always,
 you can then make it execute by appending a blank line *at the end* or hitting
 ``Shift-Enter`` anywhere within the cell.
 
 With the up arrow key, you can retrieve previous blocks of input that contain
 multiple lines.  You can move inside of a multiline cell like you would in any
 text editor.  When you want it executed, the simplest thing to do is to hit the
 force execution key, ``Shift-Enter`` (though you can also navigate to the end
 and append a blank line by using ``Enter`` twice).
 
 If you've edited a multiline cell and accidentally navigate out of it with the
 up or down arrow keys, IPython will clear the cell and replace it with the
 contents of the one above or below that you navigated to.  If this was an
 accident and you want to retrieve the cell you were editing, use the Undo
 keybinding, ``Control-z``.
 
 
 Key bindings
 ============
 
 The IPython console supports most of the basic Emacs line-oriented keybindings,
 in addition to some of its own.
 
 The keybinding prefixes mean:
 
 - ``C``: Control
 - ``S``: Shift
 - ``M``: Meta (typically the Alt key)
 
 The keybindings themselves are:
 
 - ``Enter``: insert new line (may cause execution, see above).
 - ``C-Enter``: *force* new line, *never* causes execution.
 - ``S-Enter``: *force* execution regardless of where cursor is, no newline added.
 - ``Up``: step backwards through the history.
 - ``Down``: step forwards through the history.
 - ``S-Up``: search backwards through the history (like ``C-r`` in bash).
 - ``S-Down``: search forwards through the history.
 - ``C-c``: copy highlighted text to clipboard (prompts are automatically stripped).
 - ``C-S-c``: copy highlighted text to clipboard (prompts are not stripped).
 - ``C-v``: paste text from clipboard.
 - ``C-z``: undo (retrieves lost text if you move out of a cell with the arrows).
 - ``C-S-z``: redo.
 - ``C-o``: move to 'other' area, between pager and terminal.
 - ``C-l``: clear terminal.
 - ``C-a``: go to beginning of line.
 - ``C-e``: go to end of line.
 - ``C-u``: kill from cursor to the begining of the line.
 - ``C-k``: kill from cursor to the end of the line.
 - ``C-y``: yank (paste)
 - ``C-p``: previous line (like up arrow)
 - ``C-n``: next line (like down arrow)
 - ``C-f``: forward (like right arrow)
 - ``C-b``: back (like left arrow)
 - ``C-d``: delete next character, or exits if input is empty
 - ``M-<``: move to the beginning of the input region.
 - ``M->``: move to the end of the input region.
 - ``M-d``: delete next word.
 - ``M-Backspace``: delete previous word.
 - ``C-.``: force a kernel restart (a confirmation dialog appears).
 - ``C-+``: increase font size.
 - ``C--``: decrease font size.
 - ``C-M-Space``: toggle full screen. (Command-Control-Space on Mac OS X)
 
 The IPython pager
 =================
 
 IPython will show long blocks of text from many sources using a builtin pager.
 You can control where this pager appears with the ``--paging`` command-line
 flag:
 
 - ``inside`` [default]: the pager is overlaid on top of the main terminal. You
   must quit the pager to get back to the terminal (similar to how a pager such
   as ``less`` or ``more`` works).
 
 - ``vsplit``: the console is made double-tall, and the pager appears on the
   bottom area when needed.  You can view its contents while using the terminal.
 
 - ``hsplit``: the console is made double-wide, and the pager appears on the
   right area when needed.  You can view its contents while using the terminal.
 
 - ``none``: the console never pages output.
 
 If you use the vertical or horizontal paging modes, you can navigate between
 terminal and pager as follows:
 
 - Tab key: goes from pager to terminal (but not the other way around).
 - Control-o: goes from one to another always.
 - Mouse: click on either.
 
 In all cases, the ``q`` or ``Escape`` keys quit the pager (when used with the
 focus on the pager area).
 
 Running subprocesses
 ====================
 
 The graphical IPython console uses the ``pexpect`` module to run subprocesses
 when you type ``!command``.  This has a number of advantages (true asynchronous
 output from subprocesses as well as very robust termination of rogue
 subprocesses with ``Control-C``), as well as some limitations.  The main
 limitation is that you can *not* interact back with the subprocess, so anything
 that invokes a pager or expects you to type input into it will block and hang
 (you can kill it with ``Control-C``).
 
 We have provided as magics ``%less`` to page files (aliased to ``%more``),
 ``%clear`` to clear the terminal, and ``%man`` on Linux/OSX.  These cover the
 most common commands you'd want to call in your subshell and that would cause
 problems if invoked via ``!cmd``, but you need to be aware of this limitation.
 
 Display
 =======
 
 The IPython console can now display objects in a variety of formats, including
 HTML, PNG and SVG. This is accomplished using the display functions in
 ``IPython.core.display``::
 
     In [4]: from IPython.core.display import display, display_html
 
     In [5]: from IPython.core.display import display_png, display_svg
 
 Python objects can simply be passed to these functions and the appropriate
 representations will be displayed in the console as long as the objects know
 how to compute those representations. The easiest way of teaching objects how
 to format themselves in various representations is to define special methods
 such as: ``_repr_html_``, ``_repr_svg_`` and ``_repr_png_``. IPython's display formatters
 can also be given custom formatter functions for various types::
 
     In [6]: ip = get_ipython()
 
     In [7]: html_formatter = ip.display_formatter.formatters['text/html']
 
     In [8]: html_formatter.for_type(Foo, foo_to_html)
 
 For further details, see ``IPython.core.formatters``.
 
 Inline matplotlib graphics
 ==========================
 
 The IPython console is capable of displaying matplotlib figures inline, in SVG
 or PNG format.  If started with the ``pylab=inline``, then all figures are
 rendered inline automatically (PNG by default).  If started with ``--pylab``
 or ``pylab=<your backend>``, then a GUI backend will be used, but IPython's
 ``display()`` and ``getfigs()`` functions can be used to view plots inline::
 
     In [9]: display(*getfigs())    # display all figures inline
 
     In[10]: display(*getfigs(1,2)) # display figures 1 and 2 inline
 """
 
 
 quick_guide = """\
 ?         -> Introduction and overview of IPython's features.
 %quickref -> Quick reference.
 help      -> Python's own help system.
 object?   -> Details about 'object', use 'object??' for extra details.
 """
 
 gui_note = """\
 %guiref   -> A brief reference about the graphical user interface.
 """
 
 default_banner_parts = [
     'Python %s\n' % (sys.version.split('\n')[0],),
     'Type "copyright", "credits" or "license" for more information.\n\n',
     'IPython %s -- An enhanced Interactive Python.\n' % (release.version,),
     quick_guide
 ]
 
 default_gui_banner_parts = default_banner_parts + [gui_note]
 
 default_banner = ''.join(default_banner_parts)
 
 default_gui_banner = ''.join(default_gui_banner_parts)

IPython/utils/path.py

@@ -1,464 +1,464 b''
 # encoding: utf-8
 """
 Utilities for path handling.
 """
 
 #-----------------------------------------------------------------------------
 #  Copyright (C) 2008-2011  The IPython Development Team
 #
 #  Distributed under the terms of the BSD License.  The full license is in
 #  the file COPYING, distributed as part of this software.
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # Imports
 #-----------------------------------------------------------------------------
 
 import os
 import sys
 import tempfile
 import warnings
 from hashlib import md5
 
 import IPython
 from IPython.utils.process import system
 from IPython.utils.importstring import import_item
 from IPython.utils import py3compat
 
 #-----------------------------------------------------------------------------
 # Code
 #-----------------------------------------------------------------------------
 
 fs_encoding = sys.getfilesystemencoding()
 
 def _get_long_path_name(path):
     """Dummy no-op."""
     return path
 
 def _writable_dir(path):
     """Whether `path` is a directory, to which the user has write access."""
     return os.path.isdir(path) and os.access(path, os.W_OK)
 
 if sys.platform == 'win32':
     def _get_long_path_name(path):
         """Get a long path name (expand ~) on Windows using ctypes.
 
         Examples
         --------
 
         >>> get_long_path_name('c:\\docume~1')
         u'c:\\\\Documents and Settings'
 
         """
         try:
             import ctypes
         except ImportError:
             raise ImportError('you need to have ctypes installed for this to work')
         _GetLongPathName = ctypes.windll.kernel32.GetLongPathNameW
         _GetLongPathName.argtypes = [ctypes.c_wchar_p, ctypes.c_wchar_p,
             ctypes.c_uint ]
 
         buf = ctypes.create_unicode_buffer(260)
         rv = _GetLongPathName(path, buf, 260)
         if rv == 0 or rv > 260:
             return path
         else:
             return buf.value
 
 
 def get_long_path_name(path):
     """Expand a path into its long form.
 
     On Windows this expands any ~ in the paths. On other platforms, it is
     a null operation.
     """
     return _get_long_path_name(path)
 
 
 def unquote_filename(name, win32=(sys.platform=='win32')):
     """ On Windows, remove leading and trailing quotes from filenames.
     """
     if win32:
         if name.startswith(("'", '"')) and name.endswith(("'", '"')):
             name = name[1:-1]
     return name
 
 
 def get_py_filename(name, force_win32=None):
     """Return a valid python filename in the current directory.
 
     If the given name is not a file, it adds '.py' and searches again.
     Raises IOError with an informative message if the file isn't found.
 
     On Windows, apply Windows semantics to the filename. In particular, remove
     any quoting that has been applied to it. This option can be forced for
     testing purposes.
     """
 
     name = os.path.expanduser(name)
     if force_win32 is None:
         win32 = (sys.platform == 'win32')
     else:
         win32 = force_win32
     name = unquote_filename(name, win32=win32)
     if not os.path.isfile(name) and not name.endswith('.py'):
         name += '.py'
     if os.path.isfile(name):
         return name
     else:
         raise IOError,'File `%r` not found.' % name
 
 
 def filefind(filename, path_dirs=None):
     """Find a file by looking through a sequence of paths.
 
     This iterates through a sequence of paths looking for a file and returns
     the full, absolute path of the first occurence of the file.  If no set of
     path dirs is given, the filename is tested as is, after running through
     :func:`expandvars` and :func:`expanduser`.  Thus a simple call::
 
         filefind('myfile.txt')
 
     will find the file in the current working dir, but::
 
         filefind('~/myfile.txt')
 
     Will find the file in the users home directory.  This function does not
     automatically try any paths, such as the cwd or the user's home directory.
 
     Parameters
     ----------
     filename : str
         The filename to look for.
     path_dirs : str, None or sequence of str
         The sequence of paths to look for the file in.  If None, the filename
         need to be absolute or be in the cwd.  If a string, the string is
         put into a sequence and the searched.  If a sequence, walk through
         each element and join with ``filename``, calling :func:`expandvars`
         and :func:`expanduser` before testing for existence.
 
     Returns
     -------
     Raises :exc:`IOError` or returns absolute path to file.
     """
 
     # If paths are quoted, abspath gets confused, strip them...
     filename = filename.strip('"').strip("'")
     # If the input is an absolute path, just check it exists
     if os.path.isabs(filename) and os.path.isfile(filename):
         return filename
 
     if path_dirs is None:
         path_dirs = ("",)
     elif isinstance(path_dirs, basestring):
         path_dirs = (path_dirs,)
 
     for path in path_dirs:
         if path == '.': path = os.getcwdu()
         testname = expand_path(os.path.join(path, filename))
         if os.path.isfile(testname):
             return os.path.abspath(testname)
 
     raise IOError("File %r does not exist in any of the search paths: %r" %
                   (filename, path_dirs) )
 
 
 class HomeDirError(Exception):
     pass
 
 
 def get_home_dir(require_writable=False):
     """Return the 'home' directory, as a unicode string.
 
     * First, check for frozen env in case of py2exe
     * Otherwise, defer to os.path.expanduser('~')
     
     See stdlib docs for how this is determined.
     $HOME is first priority on *ALL* platforms.
     
     Parameters
     ----------
     
     require_writable : bool [default: False]
         if True:
             guarantees the return value is a writable directory, otherwise
             raises HomeDirError
         if False:
             The path is resolved, but it is not guaranteed to exist or be writable.
     """
 
     # first, check py2exe distribution root directory for _ipython.
     # This overrides all. Normally does not exist.
 
     if hasattr(sys, "frozen"): #Is frozen by py2exe
         if '\\library.zip\\' in IPython.__file__.lower():#libraries compressed to zip-file
             root, rest = IPython.__file__.lower().split('library.zip')
         else:
             root=os.path.join(os.path.split(IPython.__file__)[0],"../../")
         root=os.path.abspath(root).rstrip('\\')
         if _writable_dir(os.path.join(root, '_ipython')):
             os.environ["IPYKITROOT"] = root
         return py3compat.cast_unicode(root, fs_encoding)
     
     homedir = os.path.expanduser('~')
     # Next line will make things work even when /home/ is a symlink to
     # /usr/home as it is on FreeBSD, for example
     homedir = os.path.realpath(homedir)
     
     if not _writable_dir(homedir) and os.name == 'nt':
         # expanduser failed, use the registry to get the 'My Documents' folder.
         try:
             import _winreg as wreg
             key = wreg.OpenKey(
                 wreg.HKEY_CURRENT_USER,
                 "Software\Microsoft\Windows\CurrentVersion\Explorer\Shell Folders"
             )
             homedir = wreg.QueryValueEx(key,'Personal')[0]
             key.Close()
         except:
             pass
     
     if (not require_writable) or _writable_dir(homedir):
         return py3compat.cast_unicode(homedir, fs_encoding)
     else:
         raise HomeDirError('%s is not a writable dir, '
                 'set $HOME environment variable to override' % homedir)
 
 def get_xdg_dir():
     """Return the XDG_CONFIG_HOME, if it is defined and exists, else None.
 
     This is only for posix (Linux,Unix,OS X, etc) systems.
     """
 
     env = os.environ
 
     if os.name == 'posix':
         # Linux, Unix, AIX, OS X
         # use ~/.config if empty OR not set
         xdg = env.get("XDG_CONFIG_HOME", None) or os.path.join(get_home_dir(), '.config')
         if xdg and _writable_dir(xdg):
             return py3compat.cast_unicode(xdg, fs_encoding)
 
     return None
 
 
 def get_ipython_dir():
     """Get the IPython directory for this platform and user.
 
     This uses the logic in `get_home_dir` to find the home directory
     and then adds .ipython to the end of the path.
     """
 
     env = os.environ
     pjoin = os.path.join
 
 
     ipdir_def = '.ipython'
     xdg_def = 'ipython'
 
     home_dir = get_home_dir()
     xdg_dir = get_xdg_dir()
     
     # import pdb; pdb.set_trace()  # dbg
     ipdir = env.get('IPYTHON_DIR', env.get('IPYTHONDIR', None))
     if ipdir is None:
         # not set explicitly, use XDG_CONFIG_HOME or HOME
         home_ipdir = pjoin(home_dir, ipdir_def)
         if xdg_dir:
             # use XDG, as long as the user isn't already
             # using $HOME/.ipython and *not* XDG/ipython
 
             xdg_ipdir = pjoin(xdg_dir, xdg_def)
 
             if _writable_dir(xdg_ipdir) or not _writable_dir(home_ipdir):
                 ipdir = xdg_ipdir
 
         if ipdir is None:
             # not using XDG
             ipdir = home_ipdir
 
     ipdir = os.path.normpath(os.path.expanduser(ipdir))
 
     if os.path.exists(ipdir) and not _writable_dir(ipdir):
         # ipdir exists, but is not writable
         warnings.warn("IPython dir '%s' is not a writable location,"
                         " using a temp directory."%ipdir)
         ipdir = tempfile.mkdtemp()
     elif not os.path.exists(ipdir):
         parent = ipdir.rsplit(os.path.sep, 1)[0]
         if not _writable_dir(parent):
             # ipdir does not exist and parent isn't writable
             warnings.warn("IPython parent '%s' is not a writable location,"
                         " using a temp directory."%parent)
             ipdir = tempfile.mkdtemp()
 
     return py3compat.cast_unicode(ipdir, fs_encoding)
 
 
 def get_ipython_package_dir():
     """Get the base directory where IPython itself is installed."""
     ipdir = os.path.dirname(IPython.__file__)
     return py3compat.cast_unicode(ipdir, fs_encoding)
 
 
 def get_ipython_module_path(module_str):
     """Find the path to an IPython module in this version of IPython.
 
     This will always find the version of the module that is in this importable
     IPython package. This will always return the path to the ``.py``
     version of the module.
     """
     if module_str == 'IPython':
         return os.path.join(get_ipython_package_dir(), '__init__.py')
     mod = import_item(module_str)
     the_path = mod.__file__.replace('.pyc', '.py')
     the_path = the_path.replace('.pyo', '.py')
     return py3compat.cast_unicode(the_path, fs_encoding)
 
 def locate_profile(profile='default'):
     """Find the path to the folder associated with a given profile.
     
-    I.e. find $IPYTHON_DIR/profile_whatever.
+    I.e. find $IPYTHONDIR/profile_whatever.
     """
     from IPython.core.profiledir import ProfileDir, ProfileDirError
     try:
         pd = ProfileDir.find_profile_dir_by_name(get_ipython_dir(), profile)
     except ProfileDirError:
         # IOError makes more sense when people are expecting a path
         raise IOError("Couldn't find profile %r" % profile)
     return pd.location
 
 def expand_path(s):
     """Expand $VARS and ~names in a string, like a shell
 
     :Examples:
 
        In [2]: os.environ['FOO']='test'
 
        In [3]: expand_path('variable FOO is $FOO')
        Out[3]: 'variable FOO is test'
     """
     # This is a pretty subtle hack. When expand user is given a UNC path
     # on Windows (\\server\share$\%username%), os.path.expandvars, removes
     # the $ to get (\\server\share\%username%). I think it considered $
     # alone an empty var. But, we need the $ to remains there (it indicates
     # a hidden share).
     if os.name=='nt':
         s = s.replace('$\\', 'IPYTHON_TEMP')
     s = os.path.expandvars(os.path.expanduser(s))
     if os.name=='nt':
         s = s.replace('IPYTHON_TEMP', '$\\')
     return s
 
 
 def target_outdated(target,deps):
     """Determine whether a target is out of date.
 
     target_outdated(target,deps) -> 1/0
 
     deps: list of filenames which MUST exist.
     target: single filename which may or may not exist.
 
     If target doesn't exist or is older than any file listed in deps, return
     true, otherwise return false.
     """
     try:
         target_time = os.path.getmtime(target)
     except os.error:
         return 1
     for dep in deps:
         dep_time = os.path.getmtime(dep)
         if dep_time > target_time:
             #print "For target",target,"Dep failed:",dep # dbg
             #print "times (dep,tar):",dep_time,target_time # dbg
             return 1
     return 0
 
 
 def target_update(target,deps,cmd):
     """Update a target with a given command given a list of dependencies.
 
     target_update(target,deps,cmd) -> runs cmd if target is outdated.
 
     This is just a wrapper around target_outdated() which calls the given
     command if target is outdated."""
 
     if target_outdated(target,deps):
         system(cmd)
 
 def filehash(path):
     """Make an MD5 hash of a file, ignoring any differences in line
     ending characters."""
     with open(path, "rU") as f:
         return md5(py3compat.str_to_bytes(f.read())).hexdigest()
 
 # If the config is unmodified from the default, we'll just delete it.
 # These are consistent for 0.10.x, thankfully. We're not going to worry about
 # older versions.
 old_config_md5 = {'ipy_user_conf.py': 'fc108bedff4b9a00f91fa0a5999140d3',
                   'ipythonrc': '12a68954f3403eea2eec09dc8fe5a9b5'}
 
 def check_for_old_config(ipython_dir=None):
     """Check for old config files, and present a warning if they exist.
 
     A link to the docs of the new config is included in the message.
 
     This should mitigate confusion with the transition to the new
     config system in 0.11.
     """
     if ipython_dir is None:
         ipython_dir = get_ipython_dir()
 
     old_configs = ['ipy_user_conf.py', 'ipythonrc', 'ipython_config.py']
     warned = False
     for cfg in old_configs:
         f = os.path.join(ipython_dir, cfg)
         if os.path.exists(f):
             if filehash(f) == old_config_md5.get(cfg, ''):
                 os.unlink(f)
             else:
                 warnings.warn("Found old IPython config file %r (modified by user)"%f)
                 warned = True
 
     if warned:
         warnings.warn("""
   The IPython configuration system has changed as of 0.11, and these files will
   be ignored. See http://ipython.github.com/ipython-doc/dev/config for details
   of the new config system.
   To start configuring IPython, do `ipython profile create`, and edit
   `ipython_config.py` in <ipython_dir>/profile_default.
   If you need to leave the old config files in place for an older version of
   IPython and want to suppress this warning message, set
   `c.InteractiveShellApp.ignore_old_config=True` in the new config.""")
 
 def get_security_file(filename, profile='default'):
     """Return the absolute path of a security file given by filename and profile
     
     This allows users and developers to find security files without
     knowledge of the IPython directory structure. The search path
     will be ['.', profile.security_dir]
     
     Parameters
     ----------
     
     filename : str
         The file to be found. If it is passed as an absolute path, it will
         simply be returned.
     profile : str [default: 'default']
         The name of the profile to search.  Leaving this unspecified
         The file to be found. If it is passed as an absolute path, fname will
         simply be returned.
     
     Returns
     -------
     Raises :exc:`IOError` if file not found or returns absolute path to file.
     """
     # import here, because profiledir also imports from utils.path
     from IPython.core.profiledir import ProfileDir
     try:
         pd = ProfileDir.find_profile_dir_by_name(get_ipython_dir(), profile)
     except Exception:
         # will raise ProfileDirError if no such profile
         raise IOError("Profile %r not found")
     return filefind(filename, ['.', pd.security_dir])
 

docs/man/ipcluster.1

@@ -1,48 +1,48 b''
 .TH IPCLUSTER 1 "July 15, 2011" "" ""
 .SH NAME
 \fBipcluster \- IPython parallel computing cluster control tool
 .SH SYNOPSIS
 .nf
 .fam C
 \fBipcluster\fP {\fmpiexec,local,mpirun,pbs,ssh\fP} [\fIoptions\fP]
 .fam T
 .fi
 .SH DESCRIPTION
 ipcluster is a control tool for IPython's parallel computing functions.
 
 IPython cluster startup. This starts a controller and engines using various
-approaches. Use the IPYTHON_DIR environment variable to change your IPython
+approaches. Use the IPYTHONDIR environment variable to change your IPython
 directory from the default of ~/.ipython or ~/.config/ipython. The log and security
 subdirectories of your IPython directory will be used by this script for log
 files and security files.
 .SH POSITIONAL ARGUMENTS
 
 The first positional argument should be one of: {start, stop, engines},
 which are the available subcommands.
 
 For detailed help on each, type "ipcluster CMD \-\-help". Briefly:
 
   start         start an IPython cluster
   stop          stop a running IPython cluster
   engines       add a number of engines to a running cluster
 .SH OPTIONS
 .TP
 .B
 \-h, \-\-help
 show help message and exit
 .SH EXAMPLE
 ipcluster start \-\-n=4
 
 This command will start 4 IPython engines on the local computer.
 .SH SEE ALSO
 .BR ipython(1),
 .BR ipcontroller(1),
 .BR ipengine(1)
 .br
 .SH AUTHOR
 \fBipcluster\fP is a tool that ships with IPython, created by
 the IPython Development Team.
 .PP
 This manual page was written by Stephan Peijnik <[e-mail]>,
 for the Debian project (but may be used by others).  Modified by Fernando Perez
 <[e-mail]> for inclusion in IPython.

docs/man/ipcontroller.1

@@ -1,164 +1,164 b''
 .TH IPCONTROLLER 1 "October 29, 2008" "" ""
 .SH NAME
 \fBipcontroller \- IPython parallel computing controller control tool
 .SH SYNOPSIS
 .nf
 .fam C
 \fBipengine\fP [\fIoptions\fP]
 .fam T
 .fi
 .SH DESCRIPTION
 ipcontroller is a control tool for IPython's parallel computing functions.
 .SH OPTIONS
 .TP
 .B
 \-h, \-\-help
 show this help message and exit
 .TP
 .B
 .TP
 .B \-\-no\-secure
 Don't authenticate messages.
 .TP
 .B \-\-usethreads
 Use threads instead of processes for the schedulers
 .TP
 .B \-\-init
 Initialize profile with default config files
 .TP
 .B \-\-log\-to\-file
 send log output to a file
 .TP
 .B \-\-reuse
 reuse existing json connection files
 .TP
 .B \-\-mongodb
 use the MongoDB backend
 .TP
 .B \-\-quiet
 set log level to logging.CRITICAL (minimize logging output)
 .TP
 .B \-\-debug
 set log level to logging.DEBUG (maximize logging output)
 .TP
 .B \-\-sqlitedb
 use the SQLiteDB backend
 .TP
 .B \-\-dictdb
 use the in-memory DictDB backend
 .TP
 .B \-\-secure
 Use HMAC digests for authentication of messages.
 .TP
 .B \-\-profile=<Unicode> (BaseIPythonApplication.profile)
 Default: u'default'
 The IPython profile to use.
 .TP
 .B \-\-hwm=<Int> (TaskScheduler.hwm)
 Default: 0
 .br
 specify the High Water Mark (HWM) for the downstream socket in the Task
 scheduler. This is the maximum number of allowed outstanding tasks on each
 engine.
 .TP
 .B \-\-secure=<Bool> (IPControllerApp.secure)
 Default: True
 Whether to use HMAC digests for extra message authentication.
 .TP
 .B \-\-ip=<Unicode> (HubFactory.ip)
 Default: '127.0.0.1'
 The IP address for registration.  This is generally either '127.0.0.1' for
 loopback only or '*' for all interfaces. [default: '127.0.0.1']
 .TP
 .B \-\-log\-url=<Unicode> (BaseParallelApplication.log_url)
 Default: ''
 The ZMQ URL of the iplogger to aggregate logging.
 .TP
 .B \-\-work\-dir=<Unicode> (BaseParallelApplication.work_dir)
 Default: u'/Users/minrk/dev/ip/mine/docs/man'
 Set the working dir for the process.
 .TP
 .B \-\-port=<Int> (HubFactory.regport)
 Default: 0
 The port on which the Hub listens for registration.
 .TP
 .B \-\-profile\-dir=<Unicode> (ProfileDir.location)
 Default: u''
 Set the profile location directly. This overrides the logic used by the
 `profile` option.
 .TP
 .B \-\-ident=<CBytes> (Session.session)
 Default: ''
 The UUID identifying this session.
 .TP
 .B \-\-log\-to\-file=<Bool> (BaseParallelApplication.log_to_file)
 Default: False
 whether to log to a file
 .TP
 .B \-\-ipython\-dir=<Unicode> (BaseIPythonApplication.ipython_dir)
 Default: u'/Users/minrk/.ipython'
 The name of the IPython directory. This directory is used for logging
 configuration (through profiles), history storage, etc. The default is
 usually $HOME/.ipython. This options can also be specified through the
-environment variable IPYTHON_DIR.
+environment variable IPYTHONDIR.
 .TP
 .B \-\-url=<Unicode> (HubFactory.url)
 Default: ''
 The 0MQ url used for registration. This sets transport, ip, and port in one
 variable. For example: url='tcp://127.0.0.1:12345' or url='epgm://*:90210'
 .TP
 .B \-\-user=<Unicode> (Session.username)
 Default: 'minrk'
 Username for the Session. Default is your system username.
 .TP
 .B \-\-ping=<CFloat> (HeartMonitor.period)
 Default: 1000
 The frequency at which the Hub pings the engines for heartbeats  (in ms)
 .TP
 .B \-\-log\-level=<Enum> (Application.log_level)
 Default: 30
 Choices: (0, 10, 20, 30, 40, 50, 'DEBUG', 'INFO', 'WARN', 'ERROR', 'CRITICAL')
 Set the log level by value or name.
 .TP
 .B \-\-location=<Unicode> (IPControllerApp.location)
 Default: u''
 The external IP or domain name of the Controller, used for disambiguating
 engine and client connections.
 .TP
 .B \-\-clean\-logs=<Bool> (BaseParallelApplication.clean_logs)
 Default: False
 whether to cleanup old logfiles before starting
 .TP
 .B \-\-scheme=<Enum> (TaskScheduler.scheme_name)
 Default: 'leastload'
 Choices: ('leastload', 'pure', 'lru', 'plainrandom', 'weighted', 'twobin')
 select the task scheduler scheme  [default: Python LRU] Options are: 'pure',
 \&'lru', 'plainrandom', 'weighted', 'twobin','leastload'
 .TP
 .B \-\-keyfile=<Unicode> (Session.keyfile)
 Default: ''
 path to file containing execution key.
 .TP
 .B \-\-transport=<Unicode> (HubFactory.transport)
 Default: 'tcp'
 The 0MQ transport for communications.  This will likely be the default of
 \&'tcp', but other values include 'ipc', 'epgm', 'inproc'.
 .TP
 .B \-\-ssh=<Unicode> (IPControllerApp.ssh_server)
 Default: u''
 ssh url for clients to use when connecting to the Controller processes. It
 should be of the form: [user@]server[:port]. The Controller's listening
 addresses must be accessible from the ssh server
 .SH SEE ALSO
 .BR ipython(1),
 .BR ipcluster(1),
 .BR ipengine(1)
 .br
 .SH AUTHOR
 \fBipcontroller\fP is a tool that ships with IPython, created by
 the IPython Development Team.
 .PP
 This manual page was written by Stephan Peijnik <[e-mail]>,
 for the Debian project (but may be used by others).  Modified by Fernando Perez
 <[e-mail]> for inclusion in IPython, and updated by
 Min Ragan-Kelley <[e-mail]> for 0.11.

docs/man/iplogger.1

@@ -1,98 +1,98 b''
 .TH IPLOGGER 1 "July 21, 2011" "" ""
 .\" Man page generated from reStructeredText.
 .SH NAME
 \fBiplogger \- IPython logger for parallel computing.
 .SH DESCRIPTION
 Start an IPython logger for parallel computing.
 .sp
 IPython controllers and engines (and your own processes) can broadcast log
 messages by registering a \fIzmq.log.handlers.PUBHandler\fP with the \fIlogging\fP
 module. The logger can be configured using command line options or using a
 cluster directory. Cluster directories contain config, log and security files
 and are usually located in your ipython directory and named as "profile_name".
 See the \fIprofile\fP and \fIprofile\-dir\fP options for details.
 .SH OPTIONS
 .sp
 IPython command\-line arguments are passed as \(aq\-\-<flag>\(aq, or \(aq\-\-<name>=<value>\(aq.
 .sp
 Arguments that take values are actually convenience aliases to full
 Configurables, whose aliases are listed on the help line. For more information
 on full configurables, see \(aq\-\-help\-all\(aq.
 .TP
 .B \-\-debug
 .
 set log level to logging.DEBUG (maximize logging output)
 .TP
 .B \-\-init
 .
 Initialize profile with default config files. This is equivalent
 to running \fIipython profile create <profile>\fP prior to startup.
 .TP
 .B \-\-log\-to\-file
 .
 send log output to a file
 .TP
 .B \-\-quiet
 .
 set log level to logging.CRITICAL (minimize logging output)
 .TP
 .B \-\-profile=<Unicode> (BaseIPythonApplication.profile)
 .
 Default: u\(aqdefault\(aq
 The IPython profile to use.
 .TP
 .B \-\-log\-to\-file=<Bool> (BaseParallelApplication.log_to_file)
 .
 Default: False
 whether to log to a file
 .TP
 .B \-\-ipython\-dir=<Unicode> (BaseIPythonApplication.ipython_dir)
 .
 The name of the IPython directory. This directory is used for logging
 configuration (through profiles), history storage, etc. The default is
 usually $XDG_CONFIG_HOME/ipython. This options can also be specified
-through the environment variable IPYTHON_DIR.
+through the environment variable IPYTHONDIR.
 .TP
 .B \-\-url=<Unicode> (LogWatcher.url)
 .
 Default: \(aq\fI\%tcp://127.0.0.1:20202\fP\(aq
 ZMQ url on which to listen for log messages
 .TP
 .B \-\-topics=<List> (LogWatcher.topics)
 .
 Default: [\(aq\(aq]
 The ZMQ topics to subscribe to. Default is to subscribe to all messages
 .TP
 .B \-\-log\-level=<Enum> (Application.log_level)
 .
 Default: 30
 Choices: (0, 10, 20, 30, 40, 50, \(aqDEBUG\(aq, \(aqINFO\(aq, \(aqWARN\(aq, \(aqERROR\(aq, \(aqCRITICAL\(aq)
 Set the log level by value or name.
 .TP
 .B \-\-log\-url=<Unicode> (BaseParallelApplication.log_url)
 .
 Default: \(aq\(aq
 The ZMQ URL of the iplogger to aggregate logging.
 .TP
 .B \-\-clean\-logs=<Bool> (BaseParallelApplication.clean_logs)
 .
 Default: False
 whether to cleanup old logfiles before starting
 .TP
 .B \-\-profile\-dir=<Unicode> (ProfileDir.location)
 .
 Default: u\(aq\(aq
 Set the profile location directly. This overrides the logic used by the
 \fIprofile\fP option.
 .TP
 .B \-\-work\-dir=<Unicode> (BaseParallelApplication.work_dir)
 .
 Set the working dir for the process.
 .SH SEE ALSO
 .BR ipython(1),
 .BR ipcontroller(1),
 .BR ipengine(1)
 .br
 .SH AUTHOR
 \fBiplogger\fP is a tool that ships with IPython, created by
 the IPython Development Team.

docs/man/ipython.1

@@ -1,241 +1,241 b''
 .\"                                      Hey, EMACS: -*- nroff -*-
 .\" First parameter, NAME, should be all caps
 .\" Second parameter, SECTION, should be 1-8, maybe w/ subsection
 .\" other parameters are allowed: see man(7), man(1)
 .TH IPYTHON 1 "July 15, 2011"
 .\" Please adjust this date whenever revising the manpage.
 .\"
 .\" Some roff macros, for reference:
 .\" .nh        disable hyphenation
 .\" .hy        enable hyphenation
 .\" .ad l      left justify
 .\" .ad b      justify to both left and right margins
 .\" .nf        disable filling
 .\" .fi        enable filling
 .\" .br        insert line break
 .\" .sp <n>    insert n+1 empty lines
 .\" for manpage-specific macros, see man(7) and groff_man(7)
 .\" .SH        section heading
 .\" .SS        secondary section heading
 .\"
 .\"
 .\" To preview this page as plain text: nroff -man ipython.1
 .\"
 .SH NAME
 ipython \- Tools for Interactive Computing in Python.
 .SH SYNOPSIS
 .B ipython
 .RI [ options ] " files" ...
 .SH DESCRIPTION
 An interactive Python shell with automatic history (input and output), dynamic
 object introspection, easier configuration, command completion, access to the
 system shell, integration with numerical and scientific computing tools, and
 more.
 .
 .SH REGULAR OPTIONS
 All options that take values, must be of the form '\-\-name=value', but
 flags that take no arguments are allowed a single '\-' to allow common
 patterns like: 'ipython \-i myscript.py'.  To pass arguments to scripts,
 rather than to IPython, specify them after '\-\-'.
 .br
 .sp 1
 All options can also be set from your ipython_config.py configuration file.
 See the provided examples for assistance.  Options given on the
 commandline override the values set in ipython_config.py.  To generate
 the default config file, do `ipython profile create`.
 .br
 .sp 1
 All options with a [no] prepended can be specified in negated form
 (\-\-no\-option instead of \-\-option) to turn the feature off.
 .TP
 .B \-h, \-\-help
 Show summary of options.
 .B \-\-no\-autoindent
 Turn off autoindenting.
 .TP
 .B \-\-autoedit\-syntax
 Turn on auto editing of files with syntax errors.
 .TP
 .B \-\-pylab
 Pre-load matplotlib and numpy for interactive use with
 the default matplotlib backend.
 .TP
 .B \-\-confirm\-exit
 Set to confirm when you try to exit IPython with an EOF (Control-D
 in Unix, Control-Z/Enter in Windows). By typing 'exit' or 'quit',
 you can force a direct exit without any confirmation.
 .TP
 .B \-\-deep\-reload
 Enable deep (recursive) reloading by default. IPython can use the
 deep_reload module which reloads changes in modules recursively (it
 replaces the reload() function, so you don't need to change anything to
 use it). deep_reload() forces a full reload of modules whose code may
 have changed, which the default reload() function does not.  When
 deep_reload is off, IPython will use the normal reload(), but
 deep_reload will still be available as dreload(). This feature is off
 by default [which means that you have both normal reload() and
 dreload()].
 .TP
 .B \-\-no\-autoedit\-syntax
 Turn off auto editing of files with syntax errors.
 .TP
 .B \-\-term\-title
 Enable auto setting the terminal title.
 .TP
 .B \-\-no\-confirm\-exit
 Don't prompt the user when exiting.
 .TP
 .B \-\-autoindent
 Turn on autoindenting.
 .TP
 .B \-\-classic
 Gives IPython a similar feel to the classic Python prompt.
 .TP
 .B \-\-no\-automagic
 Turn off the auto calling of magic commands.
 .TP
 .B \-\-banner
 Display a banner upon starting IPython.
 .TP
 .B \-\-automagic
 Turn on the auto calling of magic commands. Type %%magic at the
 IPython  prompt  for  more information.
 .TP
 .B \-\-no\-deep\-reload
 Disable deep (recursive) reloading by default.
 .TP
 .B \-\-no\-term\-title
 Disable auto setting the terminal title.
 .TP
 .B \-\-nosep
 Eliminate all spacing between prompts.
 .TP
 .B \-\-i
 also works as '\-i'
 If running code from the command line, become interactive afterwards.
 .TP
 .B \-\-debug
 set log level to logging.DEBUG (maximize logging output)
 .TP
 .B \-\-pprint
 Enable auto pretty printing of results.
 .TP
 .B \-\-quiet
 set log level to logging.CRITICAL (minimize logging output)
 .TP
 .B \-\-pdb
 Enable auto calling the pdb debugger after every exception.
 .TP
 .B \-\-color\-info
 IPython can display information about objects via a set of func-
 tions, and optionally can use colors for this, syntax highlighting
 source code and various other elements.  However, because this
 information is passed through a pager (like 'less') and many pagers get
 confused with color codes, this option is off by default.  You can test
 it and turn it on permanently in your ipython_config.py file if it
 works for you.  Test it and turn it on permanently if it works with
 your system.  The magic function %%color_info allows you to toggle this
 interactively for testing.
 .TP
 .B \-\-init
 Initialize profile with default config files
 .TP
 .B \-\-no\-pdb
 Disable auto calling the pdb debugger after every exception.
 .TP
 .B \-\-quick
 Enable quick startup with no config files.
 .TP
 .B \-\-no\-color\-info
 Disable using colors for info related things.
 .TP
 .B \-\-no\-pprint
 Disable auto auto pretty printing of results.
 .TP
 .B \-\-no\-banner
 Don't display a banner upon starting IPython.
 .TP
 .B \-\-profile=<Unicode> (BaseIPythonApplication.profile)
 Default: u'default'
 The IPython profile to use.
 .TP
 .B \-\-c=<Unicode> (InteractiveShellApp.code_to_run)
 Default: ''
 Execute the given command string.
 .TP
 .B \-\-logappend=<Unicode> (InteractiveShell.logappend)
 Default: ''
 Start logging to the given file in append mode.
 .TP
 .B \-\-autocall=<Enum> (InteractiveShell.autocall)
 Default: 1
 Choices: (0, 1, 2)
 Make IPython automatically call any callable object even if you didn't type
 explicit parentheses. For example, 'str 43' becomes 'str(43)' automatically.
 The value can be '0' to disable the feature, '1' for 'smart' autocall, where
 it is not applied if there are no more arguments on the line, and '2' for
 \&'full' autocall, where all callable objects are automatically called (even
 if no arguments are present). The default is '1'.
 .TP
 .B \-\-ipython\-dir=<Unicode> (BaseIPythonApplication.ipython_dir)
 Default: u'/Users/minrk/.ipython'
 The name of the IPython directory. This directory is used for logging
 configuration (through profiles), history storage, etc. The default is
 usually $HOME/.ipython. This options can also be specified through the
-environment variable IPYTHON_DIR.
+environment variable IPYTHONDIR.
 .TP
 .B \-\-gui=<CaselessStrEnum> (TerminalIPythonApp.gui)
 Default: None
 Choices: ('qt', 'wx', 'gtk')
 Enable GUI event loop integration ('qt', 'wx', 'gtk').
 .TP
 .B \-\-pylab=<CaselessStrEnum> (TerminalIPythonApp.pylab)
 Default: None
 Choices: ['tk', 'qt', 'wx', 'gtk', 'osx', 'auto']
 Pre-load matplotlib and numpy for interactive use, selecting a particular
 matplotlib backend and loop integration.
 .TP
 .B \-\-ext=<Unicode> (InteractiveShellApp.extra_extension)
 Default: ''
 dotted module name of an IPython extension to load.
 .TP
 .B \-\-log\-level=<Enum> (Application.log_level)
 Default: 30
 Choices: (0, 10, 20, 30, 40, 50, 'DEBUG', 'INFO', 'WARN', 'ERROR', 'CRITICAL')
 Set the log level by value or name.
 .TP
 .B \-\-colors=<CaselessStrEnum> (InteractiveShell.colors)
 Default: 'LightBG'
 Choices: ('NoColor', 'LightBG', 'Linux')
 Set the color scheme (NoColor, Linux, or LightBG).
 .TP
 .B \-\-cache\-size=<Int> (InteractiveShell.cache_size)
 Default: 1000
 Set the size of the output cache.  The default is 1000, you can change it
 permanently in your config file.  Setting it to 0 completely disables the
 caching system, and the minimum value accepted is 20 (if you provide a value
 less than 20, it is reset to 0 and a warning is issued).  This limit is
 defined because otherwise you'll spend more time re-flushing a too small
 cache than working
 .TP
 .B \-\-logfile=<Unicode> (InteractiveShell.logfile)
 Default: ''
 The name of the logfile to use.
 .
 .SH EMBEDDING
 It is possible to start an IPython instance inside your own Python
 programs.  In the documentation example files there are some
 illustrations on how to do this.
 .br
 .sp 1
 This feature allows you to evalutate dynamically the state of your
 code, operate with your variables, analyze them, etc.  Note however
 that any changes you make to values while in the shell do NOT
 propagate back to the running code, so it is safe to modify your
 values because you won't break your code in bizarre ways by doing so.
 .SH AUTHOR
 IPython was written by Fernando Perez <[e-mail]>, based on earlier
 code by Janko Hauser <[e-mail]> and Nathaniel Gray
 <[e-mail]>.  This manual page was written by Jack Moffitt
 <[e-mail]>, for the Debian project (but may be used by others), and updated by
 Min Ragan-Kelley <[e-mail]> for 0.11.

docs/source/config/old.txt

@@ -1,231 +1,231 b''
 .. _initial config:
 
 =============================================================
 Outdated configuration information that might still be useful
 =============================================================
 
 .. warning::
 
     All of the information in this file is outdated. Until the new
     configuration system is better documented, this material is being kept.
 
 This section will help you set various things in your environment for
 your IPython sessions to be as efficient as possible. All of IPython's
 configuration information, along with several example files, is stored
 in a directory named by default $HOME/.config/ipython if $HOME/.config 
 exists (Linux), or $HOME/.ipython as a secondary default. You can change this by
 defining the environment variable IPYTHONDIR, or at runtime with the
 command line option -ipythondir.
 
 If all goes well, the first time you run IPython it should automatically create
 a user copy of the config directory for you, based on its builtin defaults. You
 can look at the files it creates to learn more about configuring the
 system. The main file you will modify to configure IPython's behavior is called
 ipythonrc (with a .ini extension under Windows), included for reference
 :ref:`here <ipythonrc>`. This file is very commented and has many variables you
 can change to suit your taste, you can find more details :ref:`here
 <customization>`. Here we discuss the basic things you will want to make sure
 things are working properly from the beginning.
 
 Color
 =====
 
 The default IPython configuration has most bells and whistles turned on
 (they're pretty safe). But there's one that may cause problems on some
 systems: the use of color on screen for displaying information. This is
 very useful, since IPython can show prompts and exception tracebacks
 with various colors, display syntax-highlighted source code, and in
 general make it easier to visually parse information.
 
 The following terminals seem to handle the color sequences fine:
 
     * Linux main text console, KDE Konsole, Gnome Terminal, E-term,
       rxvt, xterm.
     * CDE terminal (tested under Solaris). This one boldfaces light colors.
     * (X)Emacs buffers. See the emacs_ section for more details on
       using IPython with (X)Emacs.
     * A Windows (XP/2k) command prompt with pyreadline_.
     * A Windows (XP/2k) CygWin shell. Although some users have reported
       problems; it is not clear whether there is an issue for everyone
       or only under specific configurations. If you have full color
       support under cygwin, please post to the IPython mailing list so
       this issue can be resolved for all users.
 
 .. _pyreadline: https://code.launchpad.net/pyreadline
       
 These have shown problems:
 
     * Windows command prompt in WinXP/2k logged into a Linux machine via
       telnet or ssh.
     * Windows native command prompt in WinXP/2k, without Gary Bishop's
       extensions. Once Gary's readline library is installed, the normal
       WinXP/2k command prompt works perfectly.
 
 Currently the following color schemes are available:
 
     * NoColor: uses no color escapes at all (all escapes are empty '' ''
       strings). This 'scheme' is thus fully safe to use in any terminal.
     * Linux: works well in Linux console type environments: dark
       background with light fonts. It uses bright colors for
       information, so it is difficult to read if you have a light
       colored background.
     * LightBG: the basic colors are similar to those in the Linux scheme
       but darker. It is easy to read in terminals with light backgrounds.
 
 IPython uses colors for two main groups of things: prompts and
 tracebacks which are directly printed to the terminal, and the object
 introspection system which passes large sets of data through a pager.
 
 Input/Output prompts and exception tracebacks
 =============================================
 
 You can test whether the colored prompts and tracebacks work on your
 system interactively by typing '%colors Linux' at the prompt (use
 '%colors LightBG' if your terminal has a light background). If the input
 prompt shows garbage like::
 
     [0;32mIn [[1;32m1[0;32m]: [0;00m
 
 instead of (in color) something like::
 
     In [1]:
 
 this means that your terminal doesn't properly handle color escape
 sequences. You can go to a 'no color' mode by typing '%colors NoColor'.
 
 You can try using a different terminal emulator program (Emacs users,
 see below). To permanently set your color preferences, edit the file
-$IPYTHON_DIR/ipythonrc and set the colors option to the desired value.
+$IPYTHONDIR/ipythonrc and set the colors option to the desired value.
 
 
 Object details (types, docstrings, source code, etc.)
 =====================================================
 
 IPython has a set of special functions for studying the objects you are working
 with, discussed in detail :ref:`here <dynamic_object_info>`. But this system
 relies on passing information which is longer than your screen through a data
 pager, such as the common Unix less and more programs. In order to be able to
 see this information in color, your pager needs to be properly configured. I
 strongly recommend using less instead of more, as it seems that more simply can
 not understand colored text correctly.
 
 In order to configure less as your default pager, do the following:
 
    1. Set the environment PAGER variable to less.
    2. Set the environment LESS variable to -r (plus any other options
       you always want to pass to less by default). This tells less to
       properly interpret control sequences, which is how color
       information is given to your terminal.
 
 For the bash shell, add to your ~/.bashrc file the lines::
 
     export PAGER=less
     export LESS=-r
 
 For the csh or tcsh shells, add to your ~/.cshrc file the lines::
 
     setenv PAGER less
     setenv LESS -r
     
 There is similar syntax for other Unix shells, look at your system
 documentation for details.
 
 If you are on a system which lacks proper data pagers (such as Windows),
 IPython will use a very limited builtin pager.
 
 .. _Prompts:
 
 Fine-tuning your prompt
 =======================
 
 IPython's prompts can be customized using a syntax similar to that of
 the bash shell. Many of bash's escapes are supported, as well as a few
 additional ones. We list them below::
 
     \#
         the prompt/history count number. This escape is automatically
         wrapped in the coloring codes for the currently active color scheme. 
     \N
         the 'naked' prompt/history count number: this is just the number
         itself, without any coloring applied to it. This lets you produce
         numbered prompts with your own colors. 
     \D
         the prompt/history count, with the actual digits replaced by dots.
         Used mainly in continuation prompts (prompt_in2) 
     \w
         the current working directory 
     \W
         the basename of current working directory 
     \Xn
         where $n=0\ldots5.$ The current working directory, with $HOME
         replaced by ~, and filtered out to contain only $n$ path elements 
     \Yn
         Similar to \Xn, but with the $n+1$ element included if it is ~ (this
         is similar to the behavior of the %cn escapes in tcsh) 
     \u
         the username of the current user 
     \$
         if the effective UID is 0, a #, otherwise a $ 
     \h
         the hostname up to the first '.' 
     \H
         the hostname 
     \n
         a newline 
     \r
         a carriage return 
     \v
         IPython version string 
 
 In addition to these, ANSI color escapes can be insterted into the
 prompts, as \C_ColorName. The list of valid color names is: Black, Blue,
 Brown, Cyan, DarkGray, Green, LightBlue, LightCyan, LightGray,
 LightGreen, LightPurple, LightRed, NoColor, Normal, Purple, Red, White,
 Yellow.
 
 Finally, IPython supports the evaluation of arbitrary expressions in
 your prompt string. The prompt strings are evaluated through the syntax
 of PEP 215, but basically you can use $x.y to expand the value of x.y,
 and for more complicated expressions you can use braces: ${foo()+x} will
 call function foo and add to it the value of x, before putting the
 result into your prompt. For example, using
 prompt_in1 '${commands.getoutput("uptime")}\nIn [\#]: ' 
 will print the result of the uptime command on each prompt (assuming the
 commands module has been imported in your ipythonrc file).
 
 
       Prompt examples
 
 The following options in an ipythonrc file will give you IPython's
 default prompts::
 
     prompt_in1 'In [\#]:' 
     prompt_in2 '   .\D.:' 
     prompt_out 'Out[\#]:'
 
 which look like this::
 
     In [1]: 1+2 
     Out[1]: 3
 
     In [2]: for i in (1,2,3): 
        ...:    print i, 
        ...: 
     1 2 3
 
 These will give you a very colorful prompt with path information::
 
     #prompt_in1 '\C_Red\u\C_Blue[\C_Cyan\Y1\C_Blue]\C_LightGreen\#>' 
     prompt_in2 ' ..\D>' 
     prompt_out '<\#>'
 
 which look like this::
 
     fperez[~/ipython]1> 1+2 
                     <1> 3 
     fperez[~/ipython]2> for i in (1,2,3): 
                    ...>     print i, 
                    ...> 
     1 2 3
 
 

docs/source/config/overview.txt

@@ -1,531 +1,531 b''
 .. _config_overview:
 
 ============================================
 Overview of the IPython configuration system
 ============================================
 
 This section describes the IPython configuration system. Starting with version
 0.11, IPython has a completely new configuration system that is quite
 different from the older :file:`ipythonrc` or :file:`ipy_user_conf.py`
 approaches. The new configuration system was designed from scratch to address
 the particular configuration needs of IPython. While there are many
 other excellent configuration systems out there, we found that none of them
 met our requirements.
 
 .. warning::
 
     If you are upgrading to version 0.11 of IPython, you will need to migrate
     your old :file:`ipythonrc` or :file:`ipy_user_conf.py` configuration files
     to the new system. You may want to read the section on 
     :ref:`configuring IPython <configuring_ipython>`. There are also some ideas
     `on the IPython wiki <http://wiki.ipython.org/Cookbook/Moving_config_to_IPython_0.11>`_
     about this.
 
 The discussion that follows is focused on teaching users how to configure
 IPython to their liking.  Developers who want to know more about how they
 can enable their objects to take advantage of the configuration system
 should consult our :ref:`developer guide <developer_guide>`
 
 The main concepts
 =================
 
 There are a number of abstractions that the IPython configuration system uses.
 Each of these abstractions is represented by a Python class.
 
 Configuration object: :class:`~IPython.config.loader.Config`
     A configuration object is a simple dictionary-like class that holds
     configuration attributes and sub-configuration objects. These classes
     support dotted attribute style access (``Foo.bar``) in addition to the
     regular dictionary style access (``Foo['bar']``). Configuration objects
     are smart. They know how to merge themselves with other configuration
     objects and they automatically create sub-configuration objects.
 
 Application: :class:`~IPython.config.application.Application`
     An application is a process that does a specific job. The most obvious
     application is the :command:`ipython` command line program. Each
     application reads *one or more* configuration files and a single set of
     command line options
     and then produces a master configuration object for the application. This
     configuration object is then passed to the configurable objects that the
     application creates. These configurable objects implement the actual logic
     of the application and know how to configure themselves given the
     configuration object.
     
     Applications always have a `log` attribute that is a configured Logger.
     This allows centralized logging configuration per-application.
 
 Configurable: :class:`~IPython.config.configurable.Configurable`
     A configurable is a regular Python class that serves as a base class for
     all main classes in an application. The
     :class:`~IPython.config.configurable.Configurable` base class is
     lightweight and only does one things.
 
     This :class:`~IPython.config.configurable.Configurable` is a subclass
     of :class:`~IPython.utils.traitlets.HasTraits` that knows how to configure
     itself. Class level traits with the metadata ``config=True`` become
     values that can be configured from the command line and configuration
     files.
     
     Developers create :class:`~IPython.config.configurable.Configurable`
     subclasses that implement all of the logic in the application. Each of
     these subclasses has its own configuration information that controls how
     instances are created.
 
 Singletons: :class:`~IPython.config.configurable.SingletonConfigurable`
     Any object for which there is a single canonical instance. These are
     just like Configurables, except they have a class method 
     :meth:`~IPython.config.configurable.SingletonConfigurable.instance`,
     that returns the current active instance (or creates one if it
     does not exist).  Examples of singletons include
     :class:`~IPython.config.application.Application`s and
     :class:`~IPython.core.interactiveshell.InteractiveShell`.  This lets
     objects easily connect to the current running Application without passing
     objects around everywhere.  For instance, to get the current running 
     Application instance, simply do: ``app = Application.instance()``.
 
 
 .. note::
 
     Singletons are not strictly enforced - you can have many instances
     of a given singleton class, but the :meth:`instance` method will always
     return the same one.
 
 Having described these main concepts, we can now state the main idea in our
 configuration system: *"configuration" allows the default values of class
 attributes to be controlled on a class by class basis*. Thus all instances of
 a given class are configured in the same way. Furthermore, if two instances
 need to be configured differently, they need to be instances of two different
 classes. While this model may seem a bit restrictive, we have found that it
 expresses most things that need to be configured extremely well. However, it
 is possible to create two instances of the same class that have different
 trait values. This is done by overriding the configuration.
 
 Now, we show what our configuration objects and files look like.
 
 Configuration objects and files
 ===============================
 
 A configuration file is simply a pure Python file that sets the attributes
 of a global, pre-created configuration object.  This configuration object is a 
 :class:`~IPython.config.loader.Config` instance.  While in a configuration
 file, to get a reference to this object, simply call the :func:`get_config`
 function.  We inject this function into the global namespace that the 
 configuration file is executed in.
 
 Here is an example of a super simple configuration file that does nothing::
 
     c = get_config()
 
 Once you get a reference to the configuration object, you simply set
 attributes on it.  All you have to know is:
 
 * The name of each attribute.
 * The type of each attribute.
 
 The answers to these two questions are provided by the various
 :class:`~IPython.config.configurable.Configurable` subclasses that an
 application uses. Let's look at how this would work for a simple configurable
 subclass::
 
     # Sample configurable:
     from IPython.config.configurable import Configurable
     from IPython.utils.traitlets import Int, Float, Unicode, Bool
     
     class MyClass(Configurable):
         name = Unicode(u'defaultname', config=True)
         ranking = Int(0, config=True)
         value = Float(99.0)
         # The rest of the class implementation would go here..
 
 In this example, we see that :class:`MyClass` has three attributes, two
 of whom (``name``, ``ranking``) can be configured.  All of the attributes
 are given types and default values.  If a :class:`MyClass` is instantiated,
 but not configured, these default values will be used.  But let's see how
 to configure this class in a configuration file::
 
     # Sample config file
     c = get_config()
     
     c.MyClass.name = 'coolname'
     c.MyClass.ranking = 10
 
 After this configuration file is loaded, the values set in it will override
 the class defaults anytime a :class:`MyClass` is created.  Furthermore,
 these attributes will be type checked and validated anytime they are set.
 This type checking is handled by the :mod:`IPython.utils.traitlets` module,
 which provides the :class:`Unicode`, :class:`Int` and :class:`Float` types.
 In addition to these traitlets, the :mod:`IPython.utils.traitlets` provides
 traitlets for a number of other types.
 
 .. note::
 
     Underneath the hood, the :class:`Configurable` base class is a subclass of
     :class:`IPython.utils.traitlets.HasTraits`. The
     :mod:`IPython.utils.traitlets` module is a lightweight version of
     :mod:`enthought.traits`. Our implementation is a pure Python subset
     (mostly API compatible) of :mod:`enthought.traits` that does not have any
     of the automatic GUI generation capabilities. Our plan is to achieve 100%
     API compatibility to enable the actual :mod:`enthought.traits` to
     eventually be used instead. Currently, we cannot use
     :mod:`enthought.traits` as we are committed to the core of IPython being
     pure Python.
 
 It should be very clear at this point what the naming convention is for 
 configuration attributes::
 
     c.ClassName.attribute_name = attribute_value
 
 Here, ``ClassName`` is the name of the class whose configuration attribute you
 want to set, ``attribute_name`` is the name of the attribute you want to set
 and ``attribute_value`` the the value you want it to have. The ``ClassName``
 attribute of ``c`` is not the actual class, but instead is another
 :class:`~IPython.config.loader.Config` instance.
 
 .. note::
 
     The careful reader may wonder how the ``ClassName`` (``MyClass`` in
     the above example) attribute of the configuration object ``c`` gets
     created. These attributes are created on the fly by the
     :class:`~IPython.config.loader.Config` instance, using a simple naming
     convention. Any attribute of a :class:`~IPython.config.loader.Config`
     instance whose name begins with an uppercase character is assumed to be a
     sub-configuration and a new empty :class:`~IPython.config.loader.Config`
     instance is dynamically created for that attribute. This allows deeply
     hierarchical information created easily (``c.Foo.Bar.value``) on the fly.
 
 Configuration files inheritance
 ===============================
 
 Let's say you want to have different configuration files for various purposes.
 Our configuration system makes it easy for one configuration file to inherit
 the information in another configuration file. The :func:`load_subconfig`
 command can be used in a configuration file for this purpose. Here is a simple
 example that loads all of the values from the file :file:`base_config.py`::
 
     # base_config.py
     c = get_config()
     c.MyClass.name = 'coolname'
     c.MyClass.ranking = 100
 
 into the configuration file :file:`main_config.py`::
 
     # main_config.py
     c = get_config()
     
     # Load everything from base_config.py
     load_subconfig('base_config.py')
     
     # Now override one of the values
     c.MyClass.name = 'bettername'
 
 In a situation like this the :func:`load_subconfig` makes sure that the
 search path for sub-configuration files is inherited from that of the parent.
 Thus, you can typically put the two in the same directory and everything will
 just work.
 
 You can also load configuration files by profile, for instance:
 
 .. sourcecode:: python
 
     load_subconfig('ipython_config.py', profile='default')
 
 to inherit your default configuration as a starting point.
 
 
 Class based configuration inheritance
 =====================================
 
 There is another aspect of configuration where inheritance comes into play.
 Sometimes, your classes will have an inheritance hierarchy that you want
 to be reflected in the configuration system.  Here is a simple example::
 
     from IPython.config.configurable import Configurable
     from IPython.utils.traitlets import Int, Float, Unicode, Bool
     
     class Foo(Configurable):
         name = Unicode(u'fooname', config=True)
         value = Float(100.0, config=True)
     
     class Bar(Foo):
         name = Unicode(u'barname', config=True)
         othervalue = Int(0, config=True)
 
 Now, we can create a configuration file to configure instances of :class:`Foo`
 and :class:`Bar`::
 
     # config file
     c = get_config()
     
     c.Foo.name = u'bestname'
     c.Bar.othervalue = 10
 
 This class hierarchy and configuration file accomplishes the following:
 
 * The default value for :attr:`Foo.name` and :attr:`Bar.name` will be
   'bestname'.  Because :class:`Bar` is a :class:`Foo` subclass it also
   picks up the configuration information for :class:`Foo`.
 * The default value for :attr:`Foo.value` and :attr:`Bar.value` will be
   ``100.0``, which is the value specified as the class default.
 * The default value for :attr:`Bar.othervalue` will be 10 as set in the
   configuration file.  Because :class:`Foo` is the parent of :class:`Bar`
   it doesn't know anything about the :attr:`othervalue` attribute.
 
 
 .. _ipython_dir:
 
 Configuration file location
 ===========================
 
 So where should you put your configuration files? IPython uses "profiles" for
 configuration, and by default, all profiles will be stored in the so called
 "IPython directory". The location of this directory is determined by the
 following algorithm:
 
 * If the ``ipython_dir`` command line flag is given, its value is used.
 
 * If not, the value returned by :func:`IPython.utils.path.get_ipython_dir`
-  is used. This function will first look at the :envvar:`IPYTHON_DIR`
+  is used. This function will first look at the :envvar:`IPYTHONDIR`
   environment variable and then default to a platform-specific default.
 
 On posix systems (Linux, Unix, etc.), IPython respects the ``$XDG_CONFIG_HOME``
 part of the `XDG Base Directory`_ specification. If ``$XDG_CONFIG_HOME`` is
 defined and exists ( ``XDG_CONFIG_HOME`` has a default interpretation of
 :file:`$HOME/.config`), then IPython's config directory will be located in
 :file:`$XDG_CONFIG_HOME/ipython`.  If users still have an IPython directory
 in :file:`$HOME/.ipython`, then that will be used. in preference to the 
 system default.
 
 For most users, the default value will simply be something like 
 :file:`$HOME/.config/ipython` on Linux, or :file:`$HOME/.ipython`
 elsewhere.
 
 Once the location of the IPython directory has been determined, you need to know
 which profile you are using. For users with a single configuration, this will
 simply be 'default', and will be located in 
-:file:`<IPYTHON_DIR>/profile_default`.
+:file:`<IPYTHONDIR>/profile_default`.
 
 The next thing you need to know is what to call your configuration file. The
 basic idea is that each application has its own default configuration filename.
 The default named used by the :command:`ipython` command line program is
 :file:`ipython_config.py`, and *all* IPython applications will use this file.
 Other applications, such as the parallel :command:`ipcluster` scripts or the
 QtConsole will load their own config files *after* :file:`ipython_config.py`. To
 load a particular configuration file instead of the default, the name can be
 overridden by the ``config_file`` command line flag.
 
 To generate the default configuration files, do::
 
     $> ipython profile create
 
 and you will have a default :file:`ipython_config.py` in your IPython directory
 under :file:`profile_default`. If you want the default config files for the
 :mod:`IPython.parallel` applications, add ``--parallel`` to the end of the
 command-line args.
 
 .. _Profiles:
 
 Profiles
 ========
 
 A profile is a directory containing configuration and runtime files, such as
 logs, connection info for the parallel apps, and your IPython command history.
 
 The idea is that users often want to maintain a set of configuration files for
 different purposes: one for doing numerical computing with NumPy and SciPy and
 another for doing symbolic computing with SymPy. Profiles make it easy to keep a
 separate configuration files, logs, and histories for each of these purposes.
 
 Let's start by showing how a profile is used:
 
 .. code-block:: bash
 
     $ ipython --profile=sympy
 
 This tells the :command:`ipython` command line program to get its configuration
 from the "sympy" profile. The file names for various profiles do not change. The
 only difference is that profiles are named in a special way. In the case above,
-the "sympy" profile means looking for :file:`ipython_config.py` in :file:`<IPYTHON_DIR>/profile_sympy`.
+the "sympy" profile means looking for :file:`ipython_config.py` in :file:`<IPYTHONDIR>/profile_sympy`.
 
 The general pattern is this: simply create a new profile with:
 
 .. code-block:: bash
 
     ipython profile create <name>
 
 which adds a directory called ``profile_<name>`` to your IPython directory. Then
 you can load this profile by adding ``--profile=<name>`` to your command line
 options. Profiles are supported by all IPython applications.
 
 IPython ships with some sample profiles in :file:`IPython/config/profile`. If
 you create profiles with the name of one of our shipped profiles, these config
 files will be copied over instead of starting with the automatically generated
 config files.
 
 Security Files
 --------------
 
 If you are using the notebook, qtconsole, or parallel code, IPython stores
 connection information in small JSON files in the active profile's security
 directory. This directory is made private, so only you can see the files inside. If
 you need to move connection files around to other computers, this is where they will
 be. If you want your code to be able to open security files by name, we have a
 convenience function :func:`IPython.utils.path.get_security_file`, which will return
 the absolute path to a security file from its filename and [optionally] profile
 name.
 
 Startup Files
 -------------
 
 If you want some code to be run at the beginning of every IPython session with a
 particular profile, the easiest way is to add Python (.py) or IPython (.ipy) scripts
 to your :file:`<profile>/startup` directory. Files in this directory will always be
 executed as soon as the IPython shell is constructed, and before any other code or
 scripts you have specified. If you have multiple files in the startup directory,
 they will be run in lexicographical order, so you can control the ordering by adding
 a '00-' prefix.
 
 .. note::
 
     Automatic startup files are new in IPython 0.12. Use the
     InteractiveShellApp.exec_files configurable for similar behavior in 0.11.
 
 
 .. _commandline:
 
 Command-line arguments
 ======================
 
 IPython exposes *all* configurable options on the command-line. The command-line
 arguments are generated from the Configurable traits of the classes associated
 with a given Application.  Configuring IPython from the command-line may look
 very similar to an IPython config file
 
 IPython applications use a parser called
 :class:`~IPython.config.loader.KeyValueLoader` to load values into a Config
 object.  Values are assigned in much the same way as in a config file:
 
 .. code-block:: bash
 
     $> ipython --InteractiveShell.use_readline=False --BaseIPythonApplication.profile='myprofile'
 
 Is the same as adding:
 
 .. sourcecode:: python
 
     c.InteractiveShell.use_readline=False
     c.BaseIPythonApplication.profile='myprofile'
 
 to your config file. Key/Value arguments *always* take a value, separated by '='
 and no spaces.
 
 Common Arguments
 ****************
 
 Since the strictness and verbosity of the KVLoader above are not ideal for everyday
 use, common arguments can be specified as flags_ or aliases_.
 
 Flags and Aliases are handled by :mod:`argparse` instead, allowing for more flexible
 parsing. In general, flags and aliases are prefixed by ``--``, except for those
 that are single characters, in which case they can be specified with a single ``-``, e.g.:
 
 .. code-block:: bash
 
     $> ipython -i -c "import numpy; x=numpy.linspace(0,1)" --profile testing --colors=lightbg
 
 Aliases
 -------
 
 For convenience, applications have a mapping of commonly used traits, so you don't have
 to specify the whole class name:
 
 .. code-block:: bash
 
     $> ipython --profile myprofile
     # and
     $> ipython --profile='myprofile'
     # are equivalent to
     $> ipython --BaseIPythonApplication.profile='myprofile'
 
 Flags
 -----
 
 Applications can also be passed **flags**. Flags are options that take no
 arguments. They are simply wrappers for
 setting one or more configurables with predefined values, often True/False.
 
 For instance:
 
 .. code-block:: bash
 
     $> ipcontroller --debug
     # is equivalent to
     $> ipcontroller --Application.log_level=DEBUG
     # and
     $> ipython --pylab
     # is equivalent to
     $> ipython --pylab=auto
     # or
     $> ipython --no-banner
     # is equivalent to
     $> ipython --TerminalIPythonApp.display_banner=False
 
 Subcommands
 ***********
 
 
 Some IPython applications have **subcommands**. Subcommands are modeled after
 :command:`git`, and are called with the form :command:`command subcommand
 [...args]`.  Currently, the QtConsole is a subcommand of terminal IPython:
 
 .. code-block:: bash
 
     $> ipython qtconsole --profile=myprofile
 
 and :command:`ipcluster` is simply a wrapper for its various subcommands (start,
 stop, engines).
 
 .. code-block:: bash
 
     $> ipcluster start --profile=myprofile --n=4
 
 
 To see a list of the available aliases, flags, and subcommands for an IPython application, simply pass ``-h`` or ``--help``.  And to see the full list of configurable options (*very* long), pass ``--help-all``.
 
 
 Design requirements
 ===================
 
 Here are the main requirements we wanted our configuration system to have:
 
 * Support for hierarchical configuration information.
 
 * Full integration with command line option parsers.  Often, you want to read
   a configuration file, but then override some of the values with command line
   options.  Our configuration system automates this process and allows each
   command line option to be linked to a particular attribute in the 
   configuration hierarchy that it will override.
 
 * Configuration files that are themselves valid Python code. This accomplishes
   many things. First, it becomes possible to put logic in your configuration
   files that sets attributes based on your operating system, network setup,
   Python version, etc. Second, Python has a super simple syntax for accessing
   hierarchical data structures, namely regular attribute access
   (``Foo.Bar.Bam.name``). Third, using Python makes it easy for users to
   import configuration attributes from one configuration file to another.
   Fourth, even though Python is dynamically typed, it does have types that can
   be checked at runtime. Thus, a ``1`` in a config file is the integer '1',
   while a ``'1'`` is a string.
 
 * A fully automated method for getting the configuration information to the
   classes that need it at runtime. Writing code that walks a configuration
   hierarchy to extract a particular attribute is painful. When you have
   complex configuration information with hundreds of attributes, this makes
   you want to cry.
 
 * Type checking and validation that doesn't require the entire configuration
   hierarchy to be specified statically before runtime. Python is a very
   dynamic language and you don't always know everything that needs to be
   configured when a program starts.
 
 
 .. _`XDG Base Directory`: http://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html

docs/source/interactive/qtconsole.txt

@@ -1,609 +1,609 b''
 .. _qtconsole:
 
 =========================
 A Qt Console for IPython
 =========================
 
 We now have a version of IPython, using the new two-process :ref:`ZeroMQ Kernel
 <ipythonzmq>`, running in a PyQt_ GUI.  This is a very lightweight widget that
 largely feels like a terminal, but provides a number of enhancements only
 possible in a GUI, such as inline figures, proper multiline editing with syntax
 highlighting, graphical calltips, and much more.
 
 .. figure:: ../_static/qtconsole.png
     :width: 400px
     :alt: IPython Qt console with embedded plots
     :align: center
     :target: ../_static/qtconsole.png
 
     The Qt console for IPython, using inline matplotlib plots.
 
 To get acquainted with the Qt console, type `%guiref` to see a quick
 introduction of its main features.
 
 The Qt frontend has hand-coded emacs-style bindings for text navigation. This
 is not yet configurable.
 
 .. tip::
 
    Since the Qt console tries hard to behave like a terminal, by default it
    immediately executes single lines of input that are complete.  If you want
    to force multiline input, hit :kbd:`Ctrl-Enter` at the end of the first line
    instead of :kbd:`Enter`, and it will open a new line for input.  At any
    point in a multiline block, you can force its execution (without having to
    go to the bottom) with :kbd:`Shift-Enter`.
 
 ``%loadpy``
 ===========
 
 The new ``%loadpy`` magic takes any python script (must end in '.py'), and
 pastes its contents as your next input, so you can edit it before
 executing. The script may be on your machine, but you can also specify a url,
 and it will download the script from the web. This is particularly useful for
 playing with examples from documentation, such as matplotlib.
 
 .. sourcecode:: ipython
 
     In [6]: %loadpy http://matplotlib.sourceforge.net/plot_directive/mpl_examples/mplot3d/contour3d_demo.py
 
     In [7]: from mpl_toolkits.mplot3d import axes3d
        ...: import matplotlib.pyplot as plt
        ...: 
        ...: fig = plt.figure()
        ...: ax = fig.add_subplot(111, projection='3d')
        ...: X, Y, Z = axes3d.get_test_data(0.05)
        ...: cset = ax.contour(X, Y, Z)
        ...: ax.clabel(cset, fontsize=9, inline=1)
        ...: 
        ...: plt.show()
 
 Pylab
 =====
 
 One of the most exciting features of the new console is embedded matplotlib
 figures. You can use any standard matplotlib GUI backend
 to draw the figures, and since there is now a two-process model, there is no
 longer a conflict between user input and the drawing eventloop.
 
 .. image:: figs/besselj.png
     :width: 519px
 
 .. display:
 
 :func:`display`
 ***************
 
 An additional function, :func:`display`, will be added to the global namespace
 if you specify the ``--pylab`` option at the command line. The IPython display
 system provides a mechanism for specifying PNG or SVG (and more)
 representations of objects for GUI frontends. By default, IPython registers
 convenient PNG and SVG renderers for matplotlib figures, so you can embed them
 in your document by calling :func:`display` on one or more of them. This is
 especially useful for saving_ your work.
 
 .. sourcecode:: ipython
 
     In [5]: plot(range(5)) # plots in the matplotlib window
     
     In [6]: display(gcf()) # embeds the current figure in the qtconsole
     
     In [7]: display(*getfigs()) # embeds all active figures in the qtconsole
 
 If you have a reference to a matplotlib figure object, you can always display
 that specific figure:
 
 .. sourcecode:: ipython
 
    In [1]: f = figure()
 
    In [2]: plot(rand(100))
    Out[2]: [<matplotlib.lines.Line2D at 0x7fc6ac03dd90>]
 
    In [3]: display(f)
 
    # Plot is shown here
 
    In [4]: title('A title')
    Out[4]: <matplotlib.text.Text at 0x7fc6ac023450>
 
    In [5]: display(f)
 
    # Updated plot with title is shown here.
 
 .. _inline:
 
 ``--pylab=inline``
 ******************
 
 If you want to have all of your figures embedded in your session, instead of
 calling :func:`display`, you can specify ``--pylab=inline`` when you start the
 console, and each time you make a plot, it will show up in your document, as if
 you had called :func:`display(fig)`.
 
 The inline backend can use either SVG or PNG figures (PNG being the default).
 To switch between them, set the ``InlineBackend.figure_format`` configurable
 in a config file, or via the ``%config`` magic:
 
 .. sourcecode:: ipython
 
     In [10]: %config InlineBackend.figure_format = 'svg'
 
 .. note::
 
     Changing the inline figure format also affects calls to :func:`display` above,
     even if you are not using the inline backend for all figures.
 
 By default, IPython closes all figures at the completion of each execution. This means you
 don't have to manually close figures, which is less convenient when figures aren't attached
 to windows with an obvious close button.  It also means that the first matplotlib call in
 each cell will always create a new figure:
 
 .. sourcecode:: ipython
 
     In [11]: plot(range(100))
     <single-line plot>
     
     In [12]: plot([1,3,2])
     <another single-line plot>
 
 
 However, it does prevent the list of active figures surviving from one input cell to the
 next, so if you want to continue working with a figure, you must hold on to a reference to
 it:
 
 .. sourcecode:: ipython
 
     In [11]: fig = gcf()
        ....: fig.plot(rand(100))
     <plot>
     In [12]: fig.title('Random Title')
     <redraw plot with title>
 
 This behavior is controlled by the :attr:`InlineBackend.close_figures` configurable, and
 if you set it to False, via %config or config file, then IPython will *not* close figures,
 and tools like :func:`gcf`, :func:`gca`, :func:`getfigs` will behave the same as they
 do with other backends.  You will, however, have to manually close figures:
 
 .. sourcecode:: ipython
 
     # close all active figures:
     In [13]: [ fig.close() for fig in getfigs() ]
 
 
 
 .. _saving:
 
 Saving and Printing
 ===================
 
 IPythonQt has the ability to save your current session, as either HTML or
 XHTML. If you have been using :func:`display` or inline_ pylab, your figures
 will be PNG in HTML, or inlined as SVG in XHTML. PNG images have the option to
 be either in an external folder, as in many browsers' "Webpage, Complete"
 option, or inlined as well, for a larger, but more portable file.
 
 .. note::
 
     Export to SVG+XHTML requires that you are using SVG figures, which is *not*
     the default.  To switch the inline figure format to use SVG during an active
     session, do:
     
     .. sourcecode:: ipython
     
         In [10]: %config InlineBackend.figure_format = 'svg'
     
     Or, you can add the same line (c.Inline... instead of %config Inline...) to
     your config files.
     
     This will only affect figures plotted after making this call
 
 
 The widget also exposes the ability to print directly, via the default print
 shortcut or context menu.
 
 
 .. Note:: 
 
     Saving is only available to richtext Qt widgets, which are used by default,
     but if you pass the ``--plain`` flag, saving will not be available to you.
 
 
 See these examples of :download:`png/html<figs/jn.html>` and
 :download:`svg/xhtml <figs/jn.xhtml>` output. Note that syntax highlighting
 does not survive export. This is a known issue, and is being investigated.
 
 
 Colors and Highlighting
 =======================
 
 Terminal IPython has always had some coloring, but never syntax
 highlighting. There are a few simple color choices, specified by the ``colors``
 flag or ``%colors`` magic:
 
 * LightBG for light backgrounds
 * Linux for dark backgrounds
 * NoColor for a simple colorless terminal
 
 The Qt widget has full support for the ``colors`` flag used in the terminal shell.
 
 The Qt widget, however, has full syntax highlighting as you type, handled by
 the `pygments`_ library. The ``style`` argument exposes access to any style by
 name that can be found by pygments, and there are several already
 installed. The ``colors`` argument, if unspecified, will be guessed based on
 the chosen style. Similarly, there are default styles associated with each
 ``colors`` option.
 
 
 Screenshot of ``ipython qtconsole --colors=linux``, which uses the 'monokai'
 theme by default:
 
 .. image:: figs/colors_dark.png
     :width: 627px
     
 .. Note::
 
     Calling ``ipython qtconsole -h`` will show all the style names that
     pygments can find on your system.
 
 You can also pass the filename of a custom CSS stylesheet, if you want to do
 your own coloring, via the ``stylesheet`` argument.  The default LightBG
 stylesheet:
 
 .. sourcecode:: css
 
     QPlainTextEdit, QTextEdit { background-color: white;
             color: black ;
             selection-background-color: #ccc}
     .error { color: red; }
     .in-prompt { color: navy; }
     .in-prompt-number { font-weight: bold; }
     .out-prompt { color: darkred; }
     .out-prompt-number { font-weight: bold; }
 
 Fonts
 =====
 
 The QtConsole has configurable via the ConsoleWidget. To change these, set the
 ``font_family`` or ``font_size`` traits of the ConsoleWidget. For instance, to
 use 9pt Anonymous Pro::
 
     $> ipython qtconsole --ConsoleWidget.font_family="Anonymous Pro" --ConsoleWidget.font_size=9
 
 Process Management
 ==================
 
 With the two-process ZMQ model, the frontend does not block input during
 execution. This means that actions can be taken by the frontend while the
 Kernel is executing, or even after it crashes. The most basic such command is
 via 'Ctrl-.', which restarts the kernel.  This can be done in the middle of a
 blocking execution. The frontend can also know, via a heartbeat mechanism, that
 the kernel has died. This means that the frontend can safely restart the
 kernel.
 
 .. _multiple_consoles:
 
 Multiple Consoles
 *****************
 
 Since the Kernel listens on the network, multiple frontends can connect to it.
 These do not have to all be qt frontends - any IPython frontend can connect and
 run code.  When you start ipython qtconsole, there will be an output line,
 like::
 
     [IPKernelApp] To connect another client to this kernel, use:
     [IPKernelApp] --existing kernel-12345.json
 
 Other frontends can connect to your kernel, and share in the execution. This is
 great for collaboration.  The ``--existing`` flag means connect to a kernel
 that already exists.  Starting other consoles
 with that flag will not try to start their own kernel, but rather connect to
 yours.  :file:`kernel-12345.json` is a small JSON file with the ip, port, and
 authentication information necessary to connect to your kernel. By default, this file
 will be in your default profile's security directory.  If it is somewhere else,
 the output line will print the full path of the connection file, rather than
 just its filename.
 
 If you need to find the connection info to send, and don't know where your connection file
 lives, there are a couple of ways to get it. If you are already running an IPython console
 connected to the kernel, you can use the ``%connect_info`` magic to display the information
 necessary to connect another frontend to the kernel.
 
 .. sourcecode:: ipython
 
     In [2]: %connect_info
     {
       "stdin_port":50255,
       "ip":"127.0.0.1",
       "hb_port":50256,
       "key":"70be6f0f-1564-4218-8cda-31be40a4d6aa",
       "shell_port":50253,
       "iopub_port":50254
     }
 
     Paste the above JSON into a file, and connect with:
         $> ipython <app> --existing <file>
     or, if you are local, you can connect with just:
         $> ipython <app> --existing kernel-12345.json
     or even just:
         $> ipython <app> --existing
     if this is the most recent IPython session you have started.
 
 Otherwise, you can find a connection file by name (and optionally profile) with
 :func:`IPython.lib.kernel.find_connection_file`:
 
 .. sourcecode:: bash
 
     $> python -c "from IPython.lib.kernel import find_connection_file;\
     print find_connection_file('kernel-12345.json')"
     /home/you/.ipython/profile_default/security/kernel-12345.json
 
 And if you are using a particular IPython profile:
 
 .. sourcecode:: bash
 
     $> python -c "from IPython.lib.kernel import find_connection_file;\
     print find_connection_file('kernel-12345.json', profile='foo')"
     /home/you/.ipython/profile_foo/security/kernel-12345.json
 
 You can even launch a standalone kernel, and connect and disconnect Qt Consoles
 from various machines.  This lets you keep the same running IPython session
 on your work machine (with matplotlib plots and everything), logging in from home,
 cafés, etc.::
 
     $> ipython kernel
     [IPKernelApp] To connect another client to this kernel, use:
     [IPKernelApp] --existing kernel-12345.json
 
 This is actually exactly the same as the subprocess launched by the qtconsole, so
 all the information about connecting to a standalone kernel is identical to that
 of connecting to the kernel attached to a running console.
 
 .. _kernel_security:
 
 Security
 --------
 
 .. warning::
 
     Since the ZMQ code currently has no encryption, listening on an
     external-facing IP is dangerous.  You are giving any computer that can see
     you on the network the ability to connect to your kernel, and view your traffic.
     Read the rest of this section before listening on external ports
     or running an IPython kernel on a shared machine.
 
 By default (for security reasons), the kernel only listens on localhost, so you
 can only connect multiple frontends to the kernel from your local machine. You
 can specify to listen on an external interface by specifying the ``ip``
 argument::
 
     $> ipython qtconsole --ip=192.168.1.123
 
 If you specify the ip as 0.0.0.0 or '*', that means all interfaces, so any
 computer that can see yours on the network can connect to the kernel.
 
 Messages are not encrypted, so users with access to the ports your kernel is using will be
 able to see any output of the kernel. They will **NOT** be able to issue shell commands as
 you due to message signatures, which are enabled by default as of IPython 0.12.
 
 .. warning::
 
     If you disable message signatures, then any user with access to the ports your
     kernel is listening on can issue arbitrary code as you. **DO NOT** disable message
     signatures unless you have a lot of trust in your environment.
 
 The one security feature IPython does provide is protection from unauthorized execution.
 IPython's messaging system will sign messages with HMAC digests using a shared-key. The key
 is never sent over the network, it is only used to generate a unique hash for each message,
 based on its content. When IPython receives a message, it will check that the digest
 matches, and discard the message. You can use any file that only you have access to to
 generate this key, but the default is just to generate a new UUID. You can generate a random
 private key with::
 
     # generate 1024b of random data, and store in a file only you can read:
-    # (assumes IPYTHON_DIR is defined, otherwise use your IPython directory)
-    $> python -c "import os; print os.urandom(128).encode('base64')" > $IPYTHON_DIR/sessionkey
-    $> chmod 600 $IPYTHON_DIR/sessionkey
+    # (assumes IPYTHONDIR is defined, otherwise use your IPython directory)
+    $> python -c "import os; print os.urandom(128).encode('base64')" > $IPYTHONDIR/sessionkey
+    $> chmod 600 $IPYTHONDIR/sessionkey
 
 The *contents* of this file will be stored in the JSON connection file, so that file
 contains everything you need to connect to and use a kernel.
 
 To use this generated key, simply specify the ``Session.keyfile`` configurable
 in :file:`ipython_config.py` or at the command-line, as in::
 
     # instruct IPython to sign messages with that key, instead of a new UUID
-    $> ipython qtconsole --Session.keyfile=$IPYTHON_DIR/sessionkey
+    $> ipython qtconsole --Session.keyfile=$IPYTHONDIR/sessionkey
 
 .. _ssh_tunnels:
 
 SSH Tunnels
 -----------
 
 Sometimes you want to connect to machines across the internet, or just across
 a LAN that either doesn't permit open ports or you don't trust the other
 machines on the network.  To do this, you can use SSH tunnels.  SSH tunnels
 are a way to securely forward ports on your local machine to ports on another
 machine, to which you have SSH access.
 
 In simple cases, IPython's tools can forward ports over ssh by simply adding the
 ``--ssh=remote`` argument to the usual ``--existing...`` set of flags for connecting
 to a running kernel, after copying the JSON connection file (or its contents) to
 the second computer.
 
 .. warning::
 
     Using SSH tunnels does *not* increase localhost security.  In fact, when
     tunneling from one machine to another *both* machines have open
     ports on localhost available for connections to the kernel.
 
 There are two primary models for using SSH tunnels with IPython.  The first
 is to have the Kernel listen only on localhost, and connect to it from
 another machine on the same LAN.
 
 First, let's start a kernel on machine **worker**, listening only
 on loopback::
 
     user@worker $> ipython kernel
     [IPKernelApp] To connect another client to this kernel, use:
     [IPKernelApp] --existing kernel-12345.json
 
 In this case, the IP that you would connect
 to would still be 127.0.0.1, but you want to specify the additional ``--ssh`` argument
 with the hostname of the kernel (in this example, it's 'worker')::
 
     user@client $> ipython qtconsole  --ssh=worker --existing /path/to/kernel-12345.json
 
 Which will write a new connection file with the forwarded ports, so you can reuse them::
 
     [IPythonQtConsoleApp] To connect another client via this tunnel, use:
     [IPythonQtConsoleApp] --existing kernel-12345-ssh.json
 
 Note again that this opens ports on the *client* machine that point to your kernel.
 
 .. note::
 
     the ssh argument is simply passed to openssh, so it can be fully specified ``user@host:port``
     but it will also respect your aliases, etc. in :file:`.ssh/config` if you have any.
 
 The second pattern is for connecting to a machine behind a firewall across the internet
 (or otherwise wide network). This time, we have a machine **login** that you have ssh access
 to, which can see **kernel**, but **client** is on another network. The important difference
 now is that **client** can see **login**, but *not* **worker**. So we need to forward ports from
 client to worker *via* login. This means that the kernel must be started listening
 on external interfaces, so that its ports are visible to `login`::
 
     user@worker $> ipython kernel --ip=0.0.0.0
     [IPKernelApp] To connect another client to this kernel, use:
     [IPKernelApp] --existing kernel-12345.json
 
 Which we can connect to from the client with::
 
     user@client $> ipython qtconsole --ssh=login --ip=192.168.1.123 --existing /path/to/kernel-12345.json
 
 .. note::
 
     The IP here is the address of worker as seen from *login*, and need only be specified if
     the kernel used the ambiguous 0.0.0.0 (all interfaces) address. If it had used
     192.168.1.123 to start with, it would not be needed.
 
 
 Manual SSH tunnels
 ------------------
 
 It's possible that IPython's ssh helper functions won't work for you, for various
 reasons.  You can still connect to remote machines, as long as you set up the tunnels
 yourself.  The basic format of forwarding a local port to a remote one is::
 
     [client] $> ssh <server> <localport>:<remoteip>:<remoteport> -f -N
 
 This will forward local connections to **localport** on client to **remoteip:remoteport**
 *via* **server**. Note that remoteip is interpreted relative to *server*, not the client.
 So if you have direct ssh access to the machine to which you want to forward connections,
 then the server *is* the remote machine, and remoteip should be server's IP as seen from the
 server itself, i.e. 127.0.0.1.  Thus, to forward local port 12345 to remote port 54321 on
 a machine you can see, do::
 
     [client] $> ssh machine 12345:127.0.0.1:54321 -f -N
 
 But if your target is actually on a LAN at 192.168.1.123, behind another machine called **login**,
 then you would do::
 
     [client] $> ssh login 12345:192.168.1.16:54321 -f -N
 
 The ``-f -N`` on the end are flags that tell ssh to run in the background,
 and don't actually run any commands beyond creating the tunnel.
 
 .. seealso::
 
     A short discussion of ssh tunnels: http://www.revsys.com/writings/quicktips/ssh-tunnel.html
 
 
 
 Stopping Kernels and Consoles
 *****************************
 
 Since there can be many consoles per kernel, the shutdown mechanism and dialog
 are probably more complicated than you are used to. Since you don't always want
 to shutdown a kernel when you close a window, you are given the option to just
 close the console window or also close the Kernel and *all other windows*. Note
 that this only refers to all other *local* windows, as remote Consoles are not
 allowed to shutdown the kernel, and shutdowns do not close Remote consoles (to
 allow for saving, etc.).
 
 Rules:
 
     * Restarting the kernel automatically clears all *local* Consoles, and prompts remote
       Consoles about the reset.
     * Shutdown closes all *local* Consoles, and notifies remotes that
       the Kernel has been shutdown.
     * Remote Consoles may not restart or shutdown the kernel.
 
 Qt and the QtConsole
 ====================
 
 An important part of working with the QtConsole when you are writing your own
 Qt code is to remember that user code (in the kernel) is *not* in the same
 process as the frontend.  This means that there is not necessarily any Qt code
 running in the kernel, and under most normal circumstances there isn't. If,
 however, you specify ``--pylab=qt`` at the command-line, then there *will* be a
 :class:`QCoreApplication` instance running in the kernel process along with
 user-code. To get a reference to this application, do:
 
 .. sourcecode:: python
 
     from PyQt4 import QtCore
     app = QtCore.QCoreApplication.instance()
     # app will be None if there is no such instance
 
 A common problem listed in the PyQt4 Gotchas_ is the fact that Python's garbage
 collection will destroy Qt objects (Windows, etc.) once there is no longer a
 Python reference to them, so you have to hold on to them.  For instance, in:
 
 .. sourcecode:: python
 
     def make_window():
         win = QtGui.QMainWindow()
     
     def make_and_return_window():
         win = QtGui.QMainWindow()
         return win
 
 :func:`make_window` will never draw a window, because garbage collection will
 destroy it before it is drawn, whereas :func:`make_and_return_window` lets the
 caller decide when the window object should be destroyed.  If, as a developer,
 you know that you always want your objects to last as long as the process, you
 can attach them to the QApplication instance itself:
 
 .. sourcecode:: python
     
     # do this just once:
     app = QtCore.QCoreApplication.instance()
     app.references = set()
     # then when you create Windows, add them to the set
     def make_window():
         win = QtGui.QMainWindow()
         app.references.add(win)
 
 Now the QApplication itself holds a reference to ``win``, so it will never be
 garbage collected until the application itself is destroyed.
 
 .. _Gotchas: http://www.riverbankcomputing.co.uk/static/Docs/PyQt4/html/gotchas.html#garbage-collection
 
 Regressions
 ===========
 
 There are some features, where the qt console lags behind the Terminal
 frontend:
 
 * !cmd input: Due to our use of pexpect, we cannot pass input to subprocesses
   launched using the '!' escape, so you should never call a command that
   requires interactive input.  For such cases, use the terminal IPython.  This
   will not be fixed, as abandoning pexpect would significantly degrade the
   console experience.
 
 * Use of ``\b`` and ``\r`` characters in the console: these are control
   characters that allow the cursor to move backwards on a line, and are used to
   display things like in-place progress bars in a terminal.  We currently do
   not support this, but it is being tracked as issue :ghissue:`629`.
 
 .. _PyQt: http://www.riverbankcomputing.co.uk/software/pyqt/download
 .. _pygments: http://pygments.org/

docs/source/interactive/reference.txt

@@ -1,1005 +1,1005 b''
 =================
 IPython reference
 =================
 
 .. _command_line_options:
 
 Command-line usage
 ==================
 
 You start IPython with the command::
 
     $ ipython [options] files
 
 .. note::
 
   For IPython on Python 3, use ``ipython3`` in place of ``ipython``.
 
 If invoked with no options, it executes all the files listed in sequence
 and drops you into the interpreter while still acknowledging any options
 you may have set in your ipython_config.py. This behavior is different from
 standard Python, which when called as python -i will only execute one
 file and ignore your configuration setup.
 
 Please note that some of the configuration options are not available at
 the command line, simply because they are not practical here. Look into
 your configuration files for details on those. There are separate configuration 
 files for each profile, and the files look like "ipython_config.py" or 
 "ipython_config_<frontendname>.py".  Profile directories look like 
-"profile_profilename" and are typically installed in the IPYTHON_DIR directory. 
+"profile_profilename" and are typically installed in the IPYTHONDIR directory.
 For Linux users, this will be $HOME/.config/ipython, and for other users it 
 will be $HOME/.ipython.  For Windows users, $HOME resolves to C:\\Documents and
 Settings\\YourUserName in most instances.
 
 
 Eventloop integration
 ---------------------
 
 Previously IPython had command line options for controlling GUI event loop
 integration (-gthread, -qthread, -q4thread, -wthread, -pylab). As of IPython
 version 0.11, these have been removed. Please see the new ``%gui``
 magic command or :ref:`this section <gui_support>` for details on the new
 interface, or specify the gui at the commandline::
 
     $ ipython --gui=qt
 
 
 Command-line Options
 --------------------
 
 To see the options IPython accepts, use ``ipython --help`` (and you probably
 should run the output through a pager such as ``ipython --help | less`` for
 more convenient reading).  This shows all the options that have a single-word
 alias to control them, but IPython lets you configure all of its objects from
 the command-line by passing the full class name and a corresponding value; type
 ``ipython --help-all`` to see this full list.  For example::
 
   ipython --pylab qt
 
 is equivalent to::
 
   ipython --TerminalIPythonApp.pylab='qt'
 
 Note that in the second form, you *must* use the equal sign, as the expression
 is evaluated as an actual Python assignment.  While in the above example the
 short form is more convenient, only the most common options have a short form,
 while any configurable variable in IPython can be set at the command-line by
 using the long form.  This long form is the same syntax used in the
 configuration files, if you want to set these options permanently.
 
 
 Interactive use
 ===============
 
 IPython is meant to work as a drop-in replacement for the standard interactive
 interpreter. As such, any code which is valid python should execute normally
 under IPython (cases where this is not true should be reported as bugs). It
 does, however, offer many features which are not available at a standard python
 prompt. What follows is a list of these.
 
 
 Caution for Windows users
 -------------------------
 
 Windows, unfortunately, uses the '\\' character as a path separator. This is a
 terrible choice, because '\\' also represents the escape character in most
 modern programming languages, including Python. For this reason, using '/'
 character is recommended if you have problems with ``\``.  However, in Windows
 commands '/' flags options, so you can not use it for the root directory. This
 means that paths beginning at the root must be typed in a contrived manner
 like: ``%copy \opt/foo/bar.txt \tmp``
 
 .. _magic:
 
 Magic command system
 --------------------
 
 IPython will treat any line whose first character is a % as a special
 call to a 'magic' function. These allow you to control the behavior of
 IPython itself, plus a lot of system-type features. They are all
 prefixed with a % character, but parameters are given without
 parentheses or quotes.
 
 Example: typing ``%cd mydir`` changes your working directory to 'mydir', if it
 exists.
 
 If you have 'automagic' enabled (as it by default), you don't need
 to type in the % explicitly. IPython will scan its internal list of
 magic functions and call one if it exists. With automagic on you can
 then just type ``cd mydir`` to go to directory 'mydir'. The automagic
 system has the lowest possible precedence in name searches, so defining
 an identifier with the same name as an existing magic function will
 shadow it for automagic use. You can still access the shadowed magic
 function by explicitly using the % character at the beginning of the line.
 
 An example (with automagic on) should clarify all this:
 
 .. sourcecode:: ipython
 
     In [1]: cd ipython     # %cd is called by automagic
     /home/fperez/ipython
 
     In [2]: cd=1 	   # now cd is just a variable
 
     In [3]: cd .. 	   # and doesn't work as a function anymore
     File "<ipython-input-3-9fedb3aff56c>", line 1
       cd ..
           ^
     SyntaxError: invalid syntax
 
 
     In [4]: %cd .. 	   # but %cd always works
     /home/fperez
 
     In [5]: del cd     # if you remove the cd variable, automagic works again
 
     In [6]: cd ipython
 
     /home/fperez/ipython
 
 You can define your own magic functions to extend the system. The
 following example defines a new magic command, %impall:
 
 .. sourcecode:: python
 
     ip = get_ipython()
 
     def doimp(self, arg):
         ip = self.api
         ip.ex("import %s; reload(%s); from %s import *" % (arg,arg,arg) )
 
     ip.define_magic('impall', doimp)
 
 Type ``%magic`` for more information, including a list of all available magic
 functions at any time and their docstrings. You can also type
 ``%magic_function_name?`` (see :ref:`below <dynamic_object_info>` for information on
 the '?' system) to get information about any particular magic function you are
 interested in.
 
 The API documentation for the :mod:`IPython.core.magic` module contains the full
 docstrings of all currently available magic commands.
 
 
 Access to the standard Python help
 ----------------------------------
 
 Simply type ``help()`` to access Python's standard help system. You can
 also type ``help(object)`` for information about a given object, or
 ``help('keyword')`` for information on a keyword. You may need to configure your
 PYTHONDOCS environment variable for this feature to work correctly.
 
 .. _dynamic_object_info:
 
 Dynamic object information
 --------------------------
 
 Typing ``?word`` or ``word?`` prints detailed information about an object. If
 certain strings in the object are too long (e.g. function signatures) they get
 snipped in the center for brevity. This system gives access variable types and
 values, docstrings, function prototypes and other useful information.
 
 If the information will not fit in the terminal, it is displayed in a pager
 (``less`` if available, otherwise a basic internal pager).
 
 Typing ``??word`` or ``word??`` gives access to the full information, including
 the source code where possible. Long strings are not snipped.
 
 The following magic functions are particularly useful for gathering
 information about your working environment. You can get more details by
 typing ``%magic`` or querying them individually (``%function_name?``);
 this is just a summary:
 
     * **%pdoc <object>**: Print (or run through a pager if too long) the
       docstring for an object. If the given object is a class, it will
       print both the class and the constructor docstrings.
     * **%pdef <object>**: Print the definition header for any callable
       object. If the object is a class, print the constructor information.
     * **%psource <object>**: Print (or run through a pager if too long)
       the source code for an object.
     * **%pfile <object>**: Show the entire source file where an object was
       defined via a pager, opening it at the line where the object
       definition begins.
     * **%who/%whos**: These functions give information about identifiers
       you have defined interactively (not things you loaded or defined
       in your configuration files). %who just prints a list of
       identifiers and %whos prints a table with some basic details about
       each identifier.
 
 Note that the dynamic object information functions (?/??, ``%pdoc``,
 ``%pfile``, ``%pdef``, ``%psource``) work on object attributes, as well as
 directly on variables. For example, after doing ``import os``, you can use
 ``os.path.abspath??``.
 
 .. _readline:
 
 Readline-based features
 -----------------------
 
 These features require the GNU readline library, so they won't work if your
 Python installation lacks readline support. We will first describe the default
 behavior IPython uses, and then how to change it to suit your preferences.
 
 
 Command line completion
 +++++++++++++++++++++++
 
 At any time, hitting TAB will complete any available python commands or
 variable names, and show you a list of the possible completions if
 there's no unambiguous one. It will also complete filenames in the
 current directory if no python names match what you've typed so far.
 
 
 Search command history
 ++++++++++++++++++++++
 
 IPython provides two ways for searching through previous input and thus
 reduce the need for repetitive typing:
 
    1. Start typing, and then use Ctrl-p (previous,up) and Ctrl-n
       (next,down) to search through only the history items that match
       what you've typed so far. If you use Ctrl-p/Ctrl-n at a blank
       prompt, they just behave like normal arrow keys.
    2. Hit Ctrl-r: opens a search prompt. Begin typing and the system
       searches your history for lines that contain what you've typed so
       far, completing as much as it can.
 
 
 Persistent command history across sessions
 ++++++++++++++++++++++++++++++++++++++++++
 
 IPython will save your input history when it leaves and reload it next
 time you restart it. By default, the history file is named
-$IPYTHON_DIR/profile_<name>/history.sqlite. This allows you to keep
+$IPYTHONDIR/profile_<name>/history.sqlite. This allows you to keep
 separate histories related to various tasks: commands related to
 numerical work will not be clobbered by a system shell history, for
 example.
 
 
 Autoindent
 ++++++++++
 
 IPython can recognize lines ending in ':' and indent the next line,
 while also un-indenting automatically after 'raise' or 'return'.
 
 This feature uses the readline library, so it will honor your
 :file:`~/.inputrc` configuration (or whatever file your INPUTRC variable points
 to). Adding the following lines to your :file:`.inputrc` file can make
 indenting/unindenting more convenient (M-i indents, M-u unindents)::
 
     $if Python 
     "\M-i": "    "  
     "\M-u": "\d\d\d\d"  
     $endif
 
 Note that there are 4 spaces between the quote marks after "M-i" above.
 
 .. warning::
 
     Setting the above indents will cause problems with unicode text entry in
     the terminal.
 
 .. warning::
 
     Autoindent is ON by default, but it can cause problems with the pasting of
     multi-line indented code (the pasted code gets re-indented on each line). A
     magic function %autoindent allows you to toggle it on/off at runtime. You
     can also disable it permanently on in your :file:`ipython_config.py` file
     (set TerminalInteractiveShell.autoindent=False).
     
     If you want to paste multiple lines in the terminal, it is recommended that
     you use ``%paste``.
 
 
 Customizing readline behavior
 +++++++++++++++++++++++++++++
 
 All these features are based on the GNU readline library, which has an
 extremely customizable interface. Normally, readline is configured via a
 file which defines the behavior of the library; the details of the
 syntax for this can be found in the readline documentation available
 with your system or on the Internet. IPython doesn't read this file (if
 it exists) directly, but it does support passing to readline valid
 options via a simple interface. In brief, you can customize readline by
 setting the following options in your configuration file (note
 that these options can not be specified at the command line):
 
     * **readline_parse_and_bind**: this holds a list of strings to be executed
       via a readline.parse_and_bind() command. The syntax for valid commands
       of this kind can be found by reading the documentation for the GNU
       readline library, as these commands are of the kind which readline
       accepts in its configuration file.
     * **readline_remove_delims**: a string of characters to be removed
       from the default word-delimiters list used by readline, so that
       completions may be performed on strings which contain them. Do not
       change the default value unless you know what you're doing.
 
 You will find the default values in your configuration file.
 
 
 Session logging and restoring
 -----------------------------
 
 You can log all input from a session either by starting IPython with the
 command line switch ``--logfile=foo.py`` (see :ref:`here <command_line_options>`)
 or by activating the logging at any moment with the magic function %logstart.
 
 Log files can later be reloaded by running them as scripts and IPython
 will attempt to 'replay' the log by executing all the lines in it, thus
 restoring the state of a previous session. This feature is not quite
 perfect, but can still be useful in many cases.
 
 The log files can also be used as a way to have a permanent record of
 any code you wrote while experimenting. Log files are regular text files
 which you can later open in your favorite text editor to extract code or
 to 'clean them up' before using them to replay a session.
 
 The `%logstart` function for activating logging in mid-session is used as
 follows::
 
     %logstart [log_name [log_mode]]
 
 If no name is given, it defaults to a file named 'ipython_log.py' in your
 current working directory, in 'rotate' mode (see below).
 
 '%logstart name' saves to file 'name' in 'backup' mode. It saves your
 history up to that point and then continues logging.
 
 %logstart takes a second optional parameter: logging mode. This can be
 one of (note that the modes are given unquoted):
 
     * [over:] overwrite existing log_name.
     * [backup:] rename (if exists) to log_name~ and start log_name.
     * [append:] well, that says it.
     * [rotate:] create rotating logs log_name.1~, log_name.2~, etc.
 
 The %logoff and %logon functions allow you to temporarily stop and
 resume logging to a file which had previously been started with
 %logstart. They will fail (with an explanation) if you try to use them
 before logging has been started.
 
 .. _system_shell_access:
 
 System shell access
 -------------------
 
 Any input line beginning with a ! character is passed verbatim (minus
 the !, of course) to the underlying operating system. For example,
 typing ``!ls`` will run 'ls' in the current directory.
 
 Manual capture of command output
 --------------------------------
 
 You can assign the result of a system command to a Python variable with the
 syntax ``myfiles = !ls``. This gets machine readable output from stdout 
 (e.g. without colours), and splits on newlines. To explicitly get this sort of
 output without assigning to a variable, use two exclamation marks (``!!ls``) or
 the ``%sx`` magic command.
 
 The captured list has some convenience features. ``myfiles.n`` or ``myfiles.s``
 returns a string delimited by newlines or spaces, respectively. ``myfiles.p``
 produces `path objects <http://pypi.python.org/pypi/path.py>`_ from the list items.
 See :ref:`string_lists` for details.
 
 IPython also allows you to expand the value of python variables when
 making system calls. Wrap variables or expressions in {braces}::
 
     In [1]: pyvar = 'Hello world' 
     In [2]: !echo "A python variable: {pyvar}"  
     A python variable: Hello world
     In [3]: import math
     In [4]: x = 8
     In [5]: !echo {math.factorial(x)}
     40320
 
 For simple cases, you can alternatively prepend $ to a variable name::
 
     In [6]: !echo $sys.argv  
     [/home/fperez/usr/bin/ipython]
     In [7]: !echo "A system variable: $$HOME"  # Use $$ for literal $
     A system variable: /home/fperez
 
 System command aliases
 ----------------------
 
 The %alias magic function allows you to define magic functions which are in fact
 system shell commands. These aliases can have parameters.
 
 ``%alias alias_name cmd`` defines 'alias_name' as an alias for 'cmd'
 
 Then, typing ``alias_name params`` will execute the system command 'cmd
 params' (from your underlying operating system).
 
 You can also define aliases with parameters using %s specifiers (one per
 parameter). The following example defines the parts function as an
 alias to the command 'echo first %s second %s' where each %s will be
 replaced by a positional parameter to the call to %parts::
 
     In [1]: %alias parts echo first %s second %s
     In [2]: parts A B
     first A second B
     In [3]: parts A  
     ERROR: Alias <parts> requires 2 arguments, 1 given.
 
 If called with no parameters, %alias prints the table of currently
 defined aliases.
 
 The %rehashx magic allows you to load your entire $PATH as
 ipython aliases. See its docstring for further details.
 
 
 .. _dreload:
 
 Recursive reload
 ----------------
 
 The :mod:`IPython.lib.deepreload` module allows you to recursively reload a
 module: changes made to any of its dependencies will be reloaded without
 having to exit. To start using it, do::
 
     from IPython.lib.deepreload import reload as dreload
 
 
 Verbose and colored exception traceback printouts
 -------------------------------------------------
 
 IPython provides the option to see very detailed exception tracebacks,
 which can be especially useful when debugging large programs. You can
 run any Python file with the %run function to benefit from these
 detailed tracebacks. Furthermore, both normal and verbose tracebacks can
 be colored (if your terminal supports it) which makes them much easier
 to parse visually.
 
 See the magic xmode and colors functions for details (just type %magic).
 
 These features are basically a terminal version of Ka-Ping Yee's cgitb
 module, now part of the standard Python library.
 
 
 .. _input_caching:
 
 Input caching system
 --------------------
 
 IPython offers numbered prompts (In/Out) with input and output caching
 (also referred to as 'input history'). All input is saved and can be 
 retrieved as variables (besides the usual arrow key recall), in 
 addition to the %rep magic command that brings a history entry
 up for editing on the next  command line.
 
 The following GLOBAL variables always exist (so don't overwrite them!):
 
 * _i, _ii, _iii: store previous, next previous and next-next previous inputs.
 * In, _ih : a list of all inputs; _ih[n] is the input from line n. If you
   overwrite In with a variable of your own, you can remake the assignment to the
   internal list with a simple ``In=_ih``.
 
 Additionally, global variables named _i<n> are dynamically created (<n>
 being the prompt counter), so ``_i<n> == _ih[<n>] == In[<n>]``.
 
 For example, what you typed at prompt 14 is available as _i14, _ih[14]
 and In[14].
 
 This allows you to easily cut and paste multi line interactive prompts
 by printing them out: they print like a clean string, without prompt
 characters. You can also manipulate them like regular variables (they
 are strings), modify or exec them (typing ``exec _i9`` will re-execute the
 contents of input prompt 9.
 
 You can also re-execute multiple lines of input easily by using the
 magic %rerun or %macro functions. The macro system also allows you to re-execute
 previous lines which include magic function calls (which require special
 processing). Type %macro? for more details on the macro system.
 
 A history function %hist allows you to see any part of your input
 history by printing a range of the _i variables.
 
 You can also search ('grep') through your history by typing 
 ``%hist -g somestring``. This is handy for searching for URLs, IP addresses,
 etc. You can bring history entries listed by '%hist -g' up for editing
 with the %recall command, or run them immediately with %rerun.
 
 .. _output_caching:
 
 Output caching system
 ---------------------
 
 For output that is returned from actions, a system similar to the input
 cache exists but using _ instead of _i. Only actions that produce a
 result (NOT assignments, for example) are cached. If you are familiar
 with Mathematica, IPython's _ variables behave exactly like
 Mathematica's % variables.
 
 The following GLOBAL variables always exist (so don't overwrite them!):
 
     * [_] (a single underscore) : stores previous output, like Python's
       default interpreter.
     * [__] (two underscores): next previous.
     * [___] (three underscores): next-next previous.
 
 Additionally, global variables named _<n> are dynamically created (<n>
 being the prompt counter), such that the result of output <n> is always
 available as _<n> (don't use the angle brackets, just the number, e.g.
 _21).
 
 These variables are also stored in a global dictionary (not a
 list, since it only has entries for lines which returned a result)
 available under the names _oh and Out (similar to _ih and In). So the
 output from line 12 can be obtained as _12, Out[12] or _oh[12]. If you
 accidentally overwrite the Out variable you can recover it by typing
 'Out=_oh' at the prompt.
 
 This system obviously can potentially put heavy memory demands on your
 system, since it prevents Python's garbage collector from removing any
 previously computed results. You can control how many results are kept
 in memory with the option (at the command line or in your configuration
 file) cache_size. If you set it to 0, the whole system is completely
 disabled and the prompts revert to the classic '>>>' of normal Python.
 
 
 Directory history
 -----------------
 
 Your history of visited directories is kept in the global list _dh, and
 the magic %cd command can be used to go to any entry in that list. The
 %dhist command allows you to view this history. Do ``cd -<TAB>`` to
 conveniently view the directory history.
 
 
 Automatic parentheses and quotes
 --------------------------------
 
 These features were adapted from Nathan Gray's LazyPython. They are
 meant to allow less typing for common situations.
 
 
 Automatic parentheses
 +++++++++++++++++++++
 
 Callable objects (i.e. functions, methods, etc) can be invoked like this
 (notice the commas between the arguments)::
 
     In [1]: callable_ob arg1, arg2, arg3
     ------> callable_ob(arg1, arg2, arg3)
 
 You can force automatic parentheses by using '/' as the first character
 of a line. For example::
 
     In [2]: /globals # becomes 'globals()'
 
 Note that the '/' MUST be the first character on the line! This won't work::
 
     In [3]: print /globals # syntax error
 
 In most cases the automatic algorithm should work, so you should rarely
 need to explicitly invoke /. One notable exception is if you are trying
 to call a function with a list of tuples as arguments (the parenthesis
 will confuse IPython)::
 
     In [4]: zip (1,2,3),(4,5,6) # won't work
 
 but this will work::
 
     In [5]: /zip (1,2,3),(4,5,6) 
     ------> zip ((1,2,3),(4,5,6))  
     Out[5]: [(1, 4), (2, 5), (3, 6)]
 
 IPython tells you that it has altered your command line by displaying
 the new command line preceded by ->. e.g.::
 
     In [6]: callable list 
     ------> callable(list)
 
 
 Automatic quoting
 +++++++++++++++++
 
 You can force automatic quoting of a function's arguments by using ','
 or ';' as the first character of a line. For example::
 
     In [1]: ,my_function /home/me  # becomes my_function("/home/me")
 
 If you use ';' the whole argument is quoted as a single string, while ',' splits
 on whitespace::
 
     In [2]: ,my_function a b c    # becomes my_function("a","b","c")
 
     In [3]: ;my_function a b c    # becomes my_function("a b c")
 
 Note that the ',' or ';' MUST be the first character on the line! This
 won't work::
 
     In [4]: x = ,my_function /home/me # syntax error
 
 IPython as your default Python environment
 ==========================================
 
 Python honors the environment variable PYTHONSTARTUP and will execute at
 startup the file referenced by this variable. If you put the following code at
 the end of that file, then IPython will be your working environment anytime you
 start Python::
 
     from IPython.frontend.terminal.ipapp import launch_new_instance
     launch_new_instance()
     raise SystemExit
 
 The ``raise SystemExit`` is needed to exit Python when
 it finishes, otherwise you'll be back at the normal Python '>>>'
 prompt.
 
 This is probably useful to developers who manage multiple Python
 versions and don't want to have correspondingly multiple IPython
 versions. Note that in this mode, there is no way to pass IPython any
 command-line options, as those are trapped first by Python itself.
 
 .. _Embedding:
 
 Embedding IPython
 =================
 
 It is possible to start an IPython instance inside your own Python
 programs. This allows you to evaluate dynamically the state of your
 code, operate with your variables, analyze them, etc. Note however that
 any changes you make to values while in the shell do not propagate back
 to the running code, so it is safe to modify your values because you
 won't break your code in bizarre ways by doing so.
 
 .. note::
 
   At present, trying to embed IPython from inside IPython causes problems. Run
   the code samples below outside IPython.
 
 This feature allows you to easily have a fully functional python
 environment for doing object introspection anywhere in your code with a
 simple function call. In some cases a simple print statement is enough,
 but if you need to do more detailed analysis of a code fragment this
 feature can be very valuable.
 
 It can also be useful in scientific computing situations where it is
 common to need to do some automatic, computationally intensive part and
 then stop to look at data, plots, etc.
 Opening an IPython instance will give you full access to your data and
 functions, and you can resume program execution once you are done with
 the interactive part (perhaps to stop again later, as many times as
 needed).
 
 The following code snippet is the bare minimum you need to include in
 your Python programs for this to work (detailed examples follow later)::
 
     from IPython import embed
 
     embed() # this call anywhere in your program will start IPython
 
 .. note::
 
     As of 0.13, you can embed an IPython *kernel*, for use with qtconsole,
     etc. via ``IPython.embed_kernel()`` instead of ``IPython.embed()``.
     It should function just the same as regular embed, but you connect
     an external frontend rather than IPython starting up in the local
     terminal.
 
 You can run embedded instances even in code which is itself being run at
 the IPython interactive prompt with '%run <filename>'. Since it's easy
 to get lost as to where you are (in your top-level IPython or in your
 embedded one), it's a good idea in such cases to set the in/out prompts
 to something different for the embedded instances. The code examples
 below illustrate this.
 
 You can also have multiple IPython instances in your program and open
 them separately, for example with different options for data
 presentation. If you close and open the same instance multiple times,
 its prompt counters simply continue from each execution to the next.
 
 Please look at the docstrings in the :mod:`~IPython.frontend.terminal.embed` 
 module for more details on the use of this system.
 
 The following sample file illustrating how to use the embedding
 functionality is provided in the examples directory as example-embed.py.
 It should be fairly self-explanatory:
 
 .. literalinclude:: ../../examples/core/example-embed.py
     :language: python
 
 Once you understand how the system functions, you can use the following
 code fragments in your programs which are ready for cut and paste:
 
 .. literalinclude:: ../../examples/core/example-embed-short.py
     :language: python
 
 Using the Python debugger (pdb)
 ===============================
 
 Running entire programs via pdb
 -------------------------------
 
 pdb, the Python debugger, is a powerful interactive debugger which
 allows you to step through code, set breakpoints, watch variables,
 etc.  IPython makes it very easy to start any script under the control
 of pdb, regardless of whether you have wrapped it into a 'main()'
 function or not. For this, simply type '%run -d myscript' at an
 IPython prompt. See the %run command's documentation (via '%run?' or
 in Sec. magic_ for more details, including how to control where pdb
 will stop execution first.
 
 For more information on the use of the pdb debugger, read the included
 pdb.doc file (part of the standard Python distribution). On a stock
 Linux system it is located at /usr/lib/python2.3/pdb.doc, but the
 easiest way to read it is by using the help() function of the pdb module
 as follows (in an IPython prompt)::
 
     In [1]: import pdb
     In [2]: pdb.help()
 
 This will load the pdb.doc document in a file viewer for you automatically.
 
 
 Automatic invocation of pdb on exceptions
 -----------------------------------------
 
 IPython, if started with the ``--pdb`` option (or if the option is set in
 your config file) can call the Python pdb debugger every time your code
 triggers an uncaught exception. This feature
 can also be toggled at any time with the %pdb magic command. This can be
 extremely useful in order to find the origin of subtle bugs, because pdb
 opens up at the point in your code which triggered the exception, and
 while your program is at this point 'dead', all the data is still
 available and you can walk up and down the stack frame and understand
 the origin of the problem.
 
 Furthermore, you can use these debugging facilities both with the
 embedded IPython mode and without IPython at all. For an embedded shell
 (see sec. Embedding_), simply call the constructor with
 ``--pdb`` in the argument string and pdb will automatically be called if an
 uncaught exception is triggered by your code.
 
 For stand-alone use of the feature in your programs which do not use
 IPython at all, put the following lines toward the top of your 'main'
 routine::
 
     import sys
     from IPython.core import ultratb
     sys.excepthook = ultratb.FormattedTB(mode='Verbose',
     color_scheme='Linux', call_pdb=1)
 
 The mode keyword can be either 'Verbose' or 'Plain', giving either very
 detailed or normal tracebacks respectively. The color_scheme keyword can
 be one of 'NoColor', 'Linux' (default) or 'LightBG'. These are the same
 options which can be set in IPython with ``--colors`` and ``--xmode``.
 
 This will give any of your programs detailed, colored tracebacks with
 automatic invocation of pdb.
 
 
 Extensions for syntax processing
 ================================
 
 This isn't for the faint of heart, because the potential for breaking
 things is quite high. But it can be a very powerful and useful feature.
 In a nutshell, you can redefine the way IPython processes the user input
 line to accept new, special extensions to the syntax without needing to
 change any of IPython's own code.
 
 In the IPython/extensions directory you will find some examples
 supplied, which we will briefly describe now. These can be used 'as is'
 (and both provide very useful functionality), or you can use them as a
 starting point for writing your own extensions.
 
 .. _pasting_with_prompts:
 
 Pasting of code starting with Python or IPython prompts
 -------------------------------------------------------
 
 IPython is smart enough to filter  out input prompts, be they plain Python ones
 (``>>>`` and ``...``) or IPython ones (``In [N]:`` and `` ...:``).  You can
 therefore copy and paste from existing interactive sessions without worry.
 
 The following is a 'screenshot' of how things work, copying an example from the
 standard Python tutorial::
 
     In [1]: >>> # Fibonacci series:
 
     In [2]: ... # the sum of two elements defines the next
 
     In [3]: ... a, b = 0, 1
 
     In [4]: >>> while b < 10:
        ...:     ...     print b
        ...:     ...     a, b = b, a+b
        ...:     
     1
     1
     2
     3
     5
     8
 
 And pasting from IPython sessions works equally well::
 
     In [1]: In [5]: def f(x):
        ...:        ...:     "A simple function"
        ...:        ...:     return x**2
        ...:    ...: 
 
     In [2]: f(3)
     Out[2]: 9
 
 .. _gui_support:
 
 GUI event loop support
 ======================
 
 .. versionadded:: 0.11
     The ``%gui`` magic and :mod:`IPython.lib.inputhook`.
 
 IPython has excellent support for working interactively with Graphical User
 Interface (GUI) toolkits, such as wxPython, PyQt4/PySide, PyGTK and Tk. This is
 implemented using Python's builtin ``PyOSInputHook`` hook. This implementation
 is extremely robust compared to our previous thread-based version. The
 advantages of this are:
 
 * GUIs can be enabled and disabled dynamically at runtime.
 * The active GUI can be switched dynamically at runtime.
 * In some cases, multiple GUIs can run simultaneously with no problems.
 * There is a developer API in :mod:`IPython.lib.inputhook` for customizing 
   all of these things.
 
 For users, enabling GUI event loop integration is simple.  You simple use the
 ``%gui`` magic as follows::
 
     %gui [GUINAME]
 
 With no arguments, ``%gui`` removes all GUI support.  Valid ``GUINAME``
 arguments are ``wx``, ``qt``, ``gtk`` and ``tk``.
 
 Thus, to use wxPython interactively and create a running :class:`wx.App`
 object, do::
 
     %gui wx
 
 For information on IPython's Matplotlib integration (and the ``pylab`` mode)
 see :ref:`this section <matplotlib_support>`.
 
 For developers that want to use IPython's GUI event loop integration in the
 form of a library, these capabilities are exposed in library form in the
 :mod:`IPython.lib.inputhook` and :mod:`IPython.lib.guisupport` modules.
 Interested developers should see the module docstrings for more information,
 but there are a few points that should be mentioned here.
 
 First, the ``PyOSInputHook`` approach only works in command line settings 
 where readline is activated.  The integration with various eventloops
 is handled somewhat differently (and more simply) when using the standalone
 kernel, as in the qtconsole and notebook.
 
 Second, when using the ``PyOSInputHook`` approach, a GUI application should
 *not* start its event loop. Instead all of this is handled by the
 ``PyOSInputHook``. This means that applications that are meant to be used both
 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
 these capabilities.
 
 Third, unlike previous versions of IPython, we no longer "hijack" (replace
 them with no-ops) the event loops. This is done to allow applications that
 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.
 
 PyQt and PySide
 ---------------
 
 .. attempt at explanation of the complete mess that is Qt support
 
 When you use ``--gui=qt`` or ``--pylab=qt``, IPython can work with either
 PyQt4 or PySide.  There are three options for configuration here, because
 PyQt4 has two APIs for QString and QVariant - v1, which is the default on
 Python 2, and the more natural v2, which is the only API supported by PySide.
 v2 is also the default for PyQt4 on Python 3.  IPython's code for the QtConsole
 uses v2, but you can still use any interface in your code, since the
 Qt frontend is in a different process.
 
 The default will be to import PyQt4 without configuration of the APIs, thus
 matching what most applications would expect. It will fall back of PySide if
 PyQt4 is unavailable.
 
 If specified, IPython will respect the environment variable ``QT_API`` used
 by ETS.  ETS 4.0 also works with both PyQt4 and PySide, but it requires
 PyQt4 to use its v2 API.  So if ``QT_API=pyside`` PySide will be used,
 and if ``QT_API=pyqt`` then PyQt4 will be used *with the v2 API* for
 QString and QVariant, so ETS codes like MayaVi will also work with IPython.
 
 If you launch IPython in pylab mode with ``ipython --pylab=qt``, then IPython
 will ask matplotlib which Qt library to use (only if QT_API is *not set*), via
 the 'backend.qt4' rcParam.  If matplotlib is version 1.0.1 or older, then
 IPython will always use PyQt4 without setting the v2 APIs, since neither v2
 PyQt nor PySide work.
 
 .. warning::
 
     Note that this means for ETS 4 to work with PyQt4, ``QT_API`` *must* be set
     to work with IPython's qt integration, because otherwise PyQt4 will be
     loaded in an incompatible mode.
     
     It also means that you must *not* have ``QT_API`` set if you want to
     use ``--gui=qt`` with code that requires PyQt4 API v1.
 
 
 .. _matplotlib_support:
 
 Plotting with matplotlib
 ========================
 
 `Matplotlib`_ provides high quality 2D and 3D plotting for Python. Matplotlib
 can produce plots on screen using a variety of GUI toolkits, including Tk,
 PyGTK, PyQt4 and wxPython. It also provides a number of commands useful for
 scientific computing, all with a syntax compatible with that of the popular
 Matlab program.
 
 To start IPython with matplotlib support, use the ``--pylab`` switch.  If no
 arguments are given, IPython will automatically detect your choice of
 matplotlib backend.  You can also request a specific backend with ``--pylab
 backend``, where ``backend`` must be one of: 'tk', 'qt', 'wx', 'gtk', 'osx'.
 In the web notebook and Qt console, 'inline' is also a valid backend value,
 which produces static figures inlined inside the application window instead of
 matplotlib's interactive figures that live in separate windows.
 
 .. _Matplotlib: http://matplotlib.sourceforge.net
 
 .. _interactive_demos:
 
 Interactive demos with IPython
 ==============================
 
 IPython ships with a basic system for running scripts interactively in
 sections, useful when presenting code to audiences. A few tags embedded
 in comments (so that the script remains valid Python code) divide a file
 into separate blocks, and the demo can be run one block at a time, with
 IPython printing (with syntax highlighting) the block before executing
 it, and returning to the interactive prompt after each block. The
 interactive namespace is updated after each block is run with the
 contents of the demo's namespace.
 
 This allows you to show a piece of code, run it and then execute
 interactively commands based on the variables just created. Once you
 want to continue, you simply execute the next block of the demo. The
 following listing shows the markup necessary for dividing a script into
 sections for execution as a demo:
 
 .. literalinclude:: ../../examples/lib/example-demo.py
     :language: python
 
 In order to run a file as a demo, you must first make a Demo object out
 of it. If the file is named myscript.py, the following code will make a
 demo::
 
     from IPython.lib.demo import Demo
 
     mydemo = Demo('myscript.py')
 
 This creates the mydemo object, whose blocks you run one at a time by
 simply calling the object with no arguments. If you have autocall active
 in IPython (the default), all you need to do is type::
 
     mydemo 
 
 and IPython will call it, executing each block. Demo objects can be
 restarted, you can move forward or back skipping blocks, re-execute the
 last block, etc. Simply use the Tab key on a demo object to see its
 methods, and call '?' on them to see their docstrings for more usage
 details. In addition, the demo module itself contains a comprehensive
 docstring, which you can access via::
 
     from IPython.lib import demo
 
     demo?
 
 Limitations: It is important to note that these demos are limited to
 fairly simple uses. In particular, you cannot break up sections within
 indented code (loops, if statements, function definitions, etc.)
 Supporting something like this would basically require tracking the
 internal execution state of the Python interpreter, so only top-level
 divisions are allowed. If you want to be able to open an IPython
 instance at an arbitrary point in a program, you can use IPython's
 embedding facilities, see :func:`IPython.embed` for details.
 

docs/source/interactive/shell.txt

@@ -1,294 +1,294 b''
 .. _ipython_as_shell:
 
 =========================
 IPython as a system shell
 =========================
 
 .. warning::
 
     As of the 0.11 version of IPython, most of the APIs used by the shell
     profile have been changed, so the profile currently does very little
     beyond changing the IPython prompt.  To help restore the shell
     profile to past functionality described here, the old code is found in 
     :file:`IPython/deathrow`, which needs to be updated to use the
     APIs in 0.11.
 
 Overview
 ========
 
 The 'sh' profile optimizes IPython for system shell usage. Apart from
 certain job control functionality that is present in unix (ctrl+z does
 "suspend"), the sh profile should provide you with most of the
 functionality you use daily in system shell, and more. Invoke IPython
 in 'sh' profile by doing 'ipython -p sh', or (in win32) by launching
 the "pysh" shortcut in start menu.
 
 If you want to use the features of sh profile as your defaults (which
 might be a good idea if you use other profiles a lot of the time but
 still want the convenience of sh profile), add ``import ipy_profile_sh``
-to your $IPYTHON_DIR/ipy_user_conf.py.
+to your $IPYTHONDIR/ipy_user_conf.py.
 
 The 'sh' profile is different from the default profile in that:
 
  * Prompt shows the current directory
  * Spacing between prompts and input is more compact (no padding with
    empty lines). The startup banner is more compact as well.
  * System commands are directly available (in alias table) without
    requesting %rehashx - however, if you install new programs along
    your PATH, you might want to run %rehashx to update the persistent
    alias table
  * Macros are stored in raw format by default. That is, instead of
    '_ip.system("cat foo"), the macro will contain text 'cat foo')
  * Autocall is in full mode
  * Calling "up" does "cd .."
 
 The 'sh' profile is different from the now-obsolete (and unavailable)
 'pysh' profile in that the ``$$var = command`` and ``$var = command`` syntax is
 not supported anymore. Use ``var = !command`` instead (which is available in all
 IPython profiles).
 
 Aliases
 =======
 
 All of your $PATH has been loaded as IPython aliases, so you should be
 able to type any normal system command and have it executed. See
 %alias?  and %unalias? for details on the alias facilities. See also
 %rehashx? for details on the mechanism used to load $PATH.
 
 
 Directory management
 ====================
 
 Since each command passed by ipython to the underlying system is executed
 in a subshell which exits immediately, you can NOT use !cd to navigate
 the filesystem.
 
 IPython provides its own builtin '%cd' magic command to move in the
 filesystem (the % is not required with automagic on). It also maintains
 a list of visited directories (use %dhist to see it) and allows direct
 switching to any of them. Type 'cd?' for more details.
 
 %pushd, %popd and %dirs are provided for directory stack handling.
 
 
 Enabled extensions
 ==================
 
 Some extensions, listed below, are enabled as default in this profile.
 
 envpersist
 ----------
 
 %env can be used to "remember" environment variable manipulations. Examples::
 
 	%env - Show all environment variables
 	%env VISUAL=jed  - set VISUAL to jed
 	%env PATH+=;/foo - append ;foo to PATH
 	%env PATH+=;/bar - also append ;bar to PATH
 	%env PATH-=/wbin; - prepend /wbin; to PATH
 	%env -d VISUAL   - forget VISUAL persistent val
 	%env -p          - print all persistent env modifications
 
 ipy_which
 ---------
 
 %which magic command. Like 'which' in unix, but knows about ipython aliases.
 
 Example::
 
  [C:/ipython]|14> %which st
  st -> start .
  [C:/ipython]|15> %which d
  d -> dir /w /og /on
  [C:/ipython]|16> %which cp
  cp -> cp
    == c:\bin\cp.exe
  c:\bin\cp.exe
 
 ipy_app_completers
 ------------------
 
 Custom tab completers for some apps like svn, hg, bzr, apt-get. Try 'apt-get install <TAB>' in debian/ubuntu.
 
 ipy_rehashdir
 -------------
 
 Allows you to add system command aliases for commands that are not along your path. Let's say that you just installed Putty and want to be able to invoke it without adding it to path, you can create the alias for it with rehashdir::
 
  [~]|22> cd c:/opt/PuTTY/
  [c:opt/PuTTY]|23> rehashdir .
               <23> ['pageant', 'plink', 'pscp', 'psftp', 'putty', 'puttygen', 'unins000']
 
 Now, you can execute any of those commams directly::
 
  [c:opt/PuTTY]|24> cd
  [~]|25> putty
 
 (the putty window opens).
 
 If you want to store the alias so that it will always be available, do '%store putty'. If you want to %store all these aliases persistently, just do it in a for loop::
 
  [~]|27> for a in _23:
     |..>     %store $a
     |..>
     |..>
  Alias stored: pageant (0, 'c:\\opt\\PuTTY\\pageant.exe')
  Alias stored: plink (0, 'c:\\opt\\PuTTY\\plink.exe')
  Alias stored: pscp (0, 'c:\\opt\\PuTTY\\pscp.exe')
  Alias stored: psftp (0, 'c:\\opt\\PuTTY\\psftp.exe')
  ...
 
 mglob
 -----
 
 Provide the magic function %mglob, which makes it easier (than the 'find' command) to collect (possibly recursive) file lists. Examples::
 
  [c:/ipython]|9> mglob *.py
  [c:/ipython]|10> mglob *.py rec:*.txt
  [c:/ipython]|19> workfiles = %mglob !.svn/ !.hg/ !*_Data/ !*.bak rec:.
 
 Note that the first 2 calls will put the file list in result history (_, _9, _10), and the last one will assign it to 'workfiles'.
 
 
 Prompt customization
 ====================
 
 The sh profile uses the following prompt configurations::
 
     c.PromptManager.in_template = r'{color.LightGreen}\u@\h{color.LightBlue}[{color.LightCyan}\Y1{color.LightBlue}]{color.Green}|\#> '
     c.PromptManager.in2_template = r'{color.Green}|{color.LightGreen}\D{color.Green}> '
     c.PromptManager.out_template = r'<\#> '
 
 You can change the prompt configuration to your liking by editing
 ipython_config.py.
 
 .. _string_lists:
 
 String lists
 ============
 
 String lists (IPython.utils.text.SList) are handy way to process output
 from system commands. They are produced by ``var = !cmd`` syntax.
 
 First, we acquire the output of 'ls -l'::
 
     [Q:doc/examples]|2> lines = !ls -l
      ==
     ['total 23',
      '-rw-rw-rw- 1 ville None 1163 Sep 30  2006 example-demo.py',
      '-rw-rw-rw- 1 ville None 1927 Sep 30  2006 example-embed-short.py',
      '-rwxrwxrwx 1 ville None 4606 Sep  1 17:15 example-embed.py',
      '-rwxrwxrwx 1 ville None 1017 Sep 30  2006 example-gnuplot.py',
      '-rwxrwxrwx 1 ville None  339 Jun 11 18:01 extension.py',
      '-rwxrwxrwx 1 ville None  113 Dec 20  2006 seteditor.py',
      '-rwxrwxrwx 1 ville None  245 Dec 12  2006 seteditor.pyc']
 
 Now, let's take a look at the contents of 'lines' (the first number is
 the list element number)::
 
     [Q:doc/examples]|3> lines
                     <3> SList (.p, .n, .l, .s, .grep(), .fields() available). Value:
 
     0: total 23
     1: -rw-rw-rw- 1 ville None 1163 Sep 30  2006 example-demo.py
     2: -rw-rw-rw- 1 ville None 1927 Sep 30  2006 example-embed-short.py
     3: -rwxrwxrwx 1 ville None 4606 Sep  1 17:15 example-embed.py
     4: -rwxrwxrwx 1 ville None 1017 Sep 30  2006 example-gnuplot.py
     5: -rwxrwxrwx 1 ville None  339 Jun 11 18:01 extension.py
     6: -rwxrwxrwx 1 ville None  113 Dec 20  2006 seteditor.py
     7: -rwxrwxrwx 1 ville None  245 Dec 12  2006 seteditor.pyc
 
 Now, let's filter out the 'embed' lines::
 
     [Q:doc/examples]|4> l2 = lines.grep('embed',prune=1)
     [Q:doc/examples]|5> l2
                     <5> SList (.p, .n, .l, .s, .grep(), .fields() available). Value:
 
     0: total 23
     1: -rw-rw-rw- 1 ville None 1163 Sep 30  2006 example-demo.py
     2: -rwxrwxrwx 1 ville None 1017 Sep 30  2006 example-gnuplot.py
     3: -rwxrwxrwx 1 ville None  339 Jun 11 18:01 extension.py
     4: -rwxrwxrwx 1 ville None  113 Dec 20  2006 seteditor.py
     5: -rwxrwxrwx 1 ville None  245 Dec 12  2006 seteditor.pyc
 
 Now, we want strings having just file names and permissions::
 
     [Q:doc/examples]|6> l2.fields(8,0)
                     <6> SList (.p, .n, .l, .s, .grep(), .fields() available). Value:
 
     0: total
     1: example-demo.py -rw-rw-rw-
     2: example-gnuplot.py -rwxrwxrwx
     3: extension.py -rwxrwxrwx
     4: seteditor.py -rwxrwxrwx
     5: seteditor.pyc -rwxrwxrwx
 
 Note how the line with 'total' does not raise IndexError.
 
 If you want to split these (yielding lists), call fields() without
 arguments::
 
     [Q:doc/examples]|7> _.fields()
                     <7>
     [['total'],
      ['example-demo.py', '-rw-rw-rw-'],
      ['example-gnuplot.py', '-rwxrwxrwx'],
      ['extension.py', '-rwxrwxrwx'],
      ['seteditor.py', '-rwxrwxrwx'],
      ['seteditor.pyc', '-rwxrwxrwx']]
 
 If you want to pass these separated with spaces to a command (typical
 for lists if files), use the .s property::
 
 
     [Q:doc/examples]|13> files = l2.fields(8).s
     [Q:doc/examples]|14> files
                     <14> 'example-demo.py example-gnuplot.py extension.py seteditor.py seteditor.pyc'
     [Q:doc/examples]|15> ls $files
     example-demo.py  example-gnuplot.py  extension.py  seteditor.py  seteditor.pyc
 
 SLists are inherited from normal python lists, so every list method is
 available::
 
     [Q:doc/examples]|21> lines.append('hey')
 
 
 Real world example: remove all files outside version control
 ------------------------------------------------------------
 
 First, capture output of "hg status"::
 
     [Q:/ipython]|28> out = !hg status
      ==
     ['M IPython\\extensions\\ipy_kitcfg.py',
      'M IPython\\extensions\\ipy_rehashdir.py',
     ...
      '? build\\lib\\IPython\\Debugger.py',
      '? build\\lib\\IPython\\extensions\\InterpreterExec.py',
      '? build\\lib\\IPython\\extensions\\InterpreterPasteInput.py',
     ...
 
 (lines starting with ? are not under version control).
 
 ::
 
     [Q:/ipython]|35> junk = out.grep(r'^\?').fields(1)
     [Q:/ipython]|36> junk
                 <36> SList (.p, .n, .l, .s, .grep(), .fields() availab
     ...
     10: build\bdist.win32\winexe\temp\_ctypes.py
     11: build\bdist.win32\winexe\temp\_hashlib.py
     12: build\bdist.win32\winexe\temp\_socket.py
 
 Now we can just remove these files by doing 'rm $junk.s'. 
 
 The .s, .n, .p properties
 -------------------------
 
 The ``.s`` property returns one string where lines are separated by
 single space (for convenient passing to system commands). The ``.n``
 property return one string where the lines are separated by a newline
 (i.e. the original output of the function). If the items in string
 list are file names, ``.p`` can be used to get a list of "path" objects
 for convenient file manipulation.
 

docs/source/parallel/parallel_multiengine.txt

@@ -1,865 +1,865 b''
 .. _parallel_multiengine:
 
 ==========================
 IPython's Direct interface
 ==========================
 
 The direct, or multiengine, interface represents one possible way of working with a set of
 IPython engines. The basic idea behind the multiengine interface is that the
 capabilities of each engine are directly and explicitly exposed to the user.
 Thus, in the multiengine interface, each engine is given an id that is used to
 identify the engine and give it work to do. This interface is very intuitive
 and is designed with interactive usage in mind, and is the best place for
 new users of IPython to begin.
 
 Starting the IPython controller and engines
 ===========================================
 
 To follow along with this tutorial, you will need to start the IPython
 controller and four IPython engines. The simplest way of doing this is to use
 the :command:`ipcluster` command::
 
     $ ipcluster start -n 4
     
 For more detailed information about starting the controller and engines, see
 our :ref:`introduction <parallel_overview>` to using IPython for parallel computing.
 
 Creating a ``DirectView`` instance
 ==================================
 
 The first step is to import the IPython :mod:`IPython.parallel`
 module and then create a :class:`.Client` instance:
 
 .. sourcecode:: ipython
 
     In [1]: from IPython.parallel import Client
     
     In [2]: rc = Client()
 
 This form assumes that the default connection information (stored in
-:file:`ipcontroller-client.json` found in :file:`IPYTHON_DIR/profile_default/security`) is
+:file:`ipcontroller-client.json` found in :file:`IPYTHONDIR/profile_default/security`) is
 accurate. If the controller was started on a remote machine, you must copy that connection
 file to the client machine, or enter its contents as arguments to the Client constructor:
 
 .. sourcecode:: ipython
 
     # If you have copied the json connector file from the controller:
     In [2]: rc = Client('/path/to/ipcontroller-client.json')
     # or to connect with a specific profile you have set up:
     In [3]: rc = Client(profile='mpi')
     
 
 To make sure there are engines connected to the controller, users can get a list
 of engine ids:
 
 .. sourcecode:: ipython
 
     In [3]: rc.ids
     Out[3]: [0, 1, 2, 3]
 
 Here we see that there are four engines ready to do work for us.
 
 For direct execution, we will make use of a :class:`DirectView` object, which can be
 constructed via list-access to the client:
 
 .. sourcecode:: ipython
 
     In [4]: dview = rc[:] # use all engines
 
 .. seealso::
 
     For more information, see the in-depth explanation of :ref:`Views <parallel_details>`.
 
 
 Quick and easy parallelism
 ==========================
 
 In many cases, you simply want to apply a Python function to a sequence of
 objects, but *in parallel*. The client interface provides a simple way
 of accomplishing this: using the DirectView's :meth:`~DirectView.map` method.
 
 Parallel map
 ------------
 
 Python's builtin :func:`map` functions allows a function to be applied to a
 sequence element-by-element. This type of code is typically trivial to
 parallelize. In fact, since IPython's interface is all about functions anyway,
 you can just use the builtin :func:`map` with a :class:`RemoteFunction`, or a 
 DirectView's :meth:`map` method:
 
 .. sourcecode:: ipython
 
     In [62]: serial_result = map(lambda x:x**10, range(32))
     
     In [63]: parallel_result = dview.map_sync(lambda x: x**10, range(32))
 
     In [67]: serial_result==parallel_result
     Out[67]: True
 
 
 .. note::
 
     The :class:`DirectView`'s version of :meth:`map` does
     not do dynamic load balancing. For a load balanced version, use a
     :class:`LoadBalancedView`.
 
 .. seealso::
     
     :meth:`map` is implemented via :class:`ParallelFunction`.
 
 Remote function decorators
 --------------------------
 
 Remote functions are just like normal functions, but when they are called,
 they execute on one or more engines, rather than locally. IPython provides
 two decorators:
 
 .. sourcecode:: ipython
 
     In [10]: @dview.remote(block=True)
        ....: def getpid():
        ....:     import os
        ....:     return os.getpid()
        ....: 
 
     In [11]: getpid()
     Out[11]: [12345, 12346, 12347, 12348]
 
 The ``@parallel`` decorator creates parallel functions, that break up an element-wise
 operations and distribute them, reconstructing the result.
 
 .. sourcecode:: ipython
 
     In [12]: import numpy as np
     
     In [13]: A = np.random.random((64,48))
     
     In [14]: @dview.parallel(block=True)
        ....: def pmul(A,B):
        ....:     return A*B
     
     In [15]: C_local = A*A
     
     In [16]: C_remote = pmul(A,A)
     
     In [17]: (C_local == C_remote).all()
     Out[17]: True
 
 Calling a ``@parallel`` function *does not* correspond to map. It is used for splitting
 element-wise operations that operate on a sequence or array.  For ``map`` behavior,
 parallel functions do have a map method.
 
 ====================    ============================    =============================
 call                    pfunc(seq)                      pfunc.map(seq)
 ====================    ============================    =============================
 # of tasks              # of engines (1 per engine)     # of engines (1 per engine)
 # of remote calls       # of engines (1 per engine)     ``len(seq)``
 argument to remote      ``seq[i:j]`` (sub-sequence)     ``seq[i]`` (single element)
 ====================    ============================    =============================
 
 A quick example to illustrate the difference in arguments for the two modes:
 
 .. sourcecode:: ipython
 
     In [16]: @dview.parallel(block=True)
        ....: def echo(x):
        ....:     return str(x)
        ....: 
 
     In [17]: echo(range(5))
     Out[17]: ['[0, 1]', '[2]', '[3]', '[4]']
 
     In [18]: echo.map(range(5))
     Out[18]: ['0', '1', '2', '3', '4']
 
 
 .. seealso::
 
     See the :func:`~.remotefunction.parallel` and :func:`~.remotefunction.remote`
     decorators for options.
 
 Calling Python functions
 ========================
 
 The most basic type of operation that can be performed on the engines is to
 execute Python code or call Python functions. Executing Python code can be
 done in blocking or non-blocking mode (non-blocking is default) using the
 :meth:`.View.execute` method, and calling functions can be done via the
 :meth:`.View.apply` method.
 
 apply
 -----
 
 The main method for doing remote execution (in fact, all methods that
 communicate with the engines are built on top of it), is :meth:`View.apply`.
 
 We strive to provide the cleanest interface we can, so `apply` has the following
 signature:
 
 .. sourcecode:: python
 
     view.apply(f, *args, **kwargs)
 
 There are various ways to call functions with IPython, and these flags are set as
 attributes of the View.  The ``DirectView`` has just two of these flags:
 
 dv.block : bool
     whether to wait for the result, or return an :class:`AsyncResult` object
     immediately
 dv.track : bool
     whether to instruct pyzmq to track when zeromq is done sending the message.
     This is primarily useful for non-copying sends of numpy arrays that you plan to
     edit in-place.  You need to know when it becomes safe to edit the buffer
     without corrupting the message.
 dv.targets : int, list of ints
     which targets this view is associated with.
 
 
 Creating a view is simple: index-access on a client creates a :class:`.DirectView`.
 
 .. sourcecode:: ipython
 
     In [4]: view = rc[1:3]
     Out[4]: <DirectView [1, 2]>
 
     In [5]: view.apply<tab>
     view.apply  view.apply_async  view.apply_sync
 
 For convenience, you can set block temporarily for a single call with the extra sync/async methods.
 
 Blocking execution
 ------------------
 
 In blocking mode, the :class:`.DirectView` object (called ``dview`` in
 these examples) submits the command to the controller, which places the
 command in the engines' queues for execution. The :meth:`apply` call then
 blocks until the engines are done executing the command:
 
 .. sourcecode:: ipython
 
     In [2]: dview = rc[:] # A DirectView of all engines
     In [3]: dview.block=True
     In [4]: dview['a'] = 5
 
     In [5]: dview['b'] = 10
 
     In [6]: dview.apply(lambda x: a+b+x, 27)
     Out[6]: [42, 42, 42, 42]
 
 You can also select blocking execution on a call-by-call basis with the :meth:`apply_sync`
 method:
 
     In [7]: dview.block=False
 
     In [8]: dview.apply_sync(lambda x: a+b+x, 27)
     Out[8]: [42, 42, 42, 42]
 
 Python commands can be executed as strings on specific engines by using a View's ``execute``
 method:
 
 .. sourcecode:: ipython
 
     In [6]: rc[::2].execute('c=a+b')
 
     In [7]: rc[1::2].execute('c=a-b')
 
     In [8]: dview['c'] # shorthand for dview.pull('c', block=True)
     Out[8]: [15, -5, 15, -5]
 
 
 Non-blocking execution
 ----------------------
 
 In non-blocking mode, :meth:`apply` submits the command to be executed and
 then returns a :class:`AsyncResult` object immediately. The
 :class:`AsyncResult` object gives you a way of getting a result at a later
 time through its :meth:`get` method.
 
 .. seealso::
 
     Docs on the :ref:`AsyncResult <parallel_asyncresult>` object.
 
 This allows you to quickly submit long running commands without blocking your
 local Python/IPython session:
 
 .. sourcecode:: ipython
     
     # define our function
     In [6]: def wait(t):
       ....:     import time
       ....:     tic = time.time()
       ....:     time.sleep(t)
       ....:     return time.time()-tic
     
     # In non-blocking mode
     In [7]: ar = dview.apply_async(wait, 2)
 
     # Now block for the result
     In [8]: ar.get()
     Out[8]: [2.0006198883056641, 1.9997570514678955, 1.9996809959411621, 2.0003249645233154]
 
     # Again in non-blocking mode
     In [9]: ar = dview.apply_async(wait, 10)
 
     # Poll to see if the result is ready
     In [10]: ar.ready()
     Out[10]: False
     
     # ask for the result, but wait a maximum of 1 second:
     In [45]: ar.get(1)
     ---------------------------------------------------------------------------
     TimeoutError                              Traceback (most recent call last)
     /home/you/<ipython-input-45-7cd858bbb8e0> in <module>()
     ----> 1 ar.get(1)
 
     /path/to/site-packages/IPython/parallel/asyncresult.pyc in get(self, timeout)
          62                 raise self._exception
          63         else:
     ---> 64             raise error.TimeoutError("Result not ready.")
          65 
          66     def ready(self):
 
     TimeoutError: Result not ready.
 
 .. Note::
 
     Note the import inside the function. This is a common model, to ensure
     that the appropriate modules are imported where the task is run. You can
     also manually import modules into the engine(s) namespace(s) via 
     :meth:`view.execute('import numpy')`.
 
 Often, it is desirable to wait until a set of :class:`AsyncResult` objects
 are done. For this, there is a the method :meth:`wait`. This method takes a
 tuple of :class:`AsyncResult` objects (or `msg_ids` or indices to the client's History),
 and blocks until all of the associated results are ready:
 
 .. sourcecode:: ipython
 
     In [72]: dview.block=False
 
     # A trivial list of AsyncResults objects
     In [73]: pr_list = [dview.apply_async(wait, 3) for i in range(10)]
 
     # Wait until all of them are done
     In [74]: dview.wait(pr_list)
 
     # Then, their results are ready using get() or the `.r` attribute
     In [75]: pr_list[0].get()
     Out[75]: [2.9982571601867676, 2.9982588291168213, 2.9987530708312988, 2.9990990161895752]
 
 
 
 The ``block`` and ``targets`` keyword arguments and attributes
 --------------------------------------------------------------
 
 Most DirectView methods (excluding :meth:`apply`) accept ``block`` and
 ``targets`` as keyword arguments. As we have seen above, these keyword arguments control the
 blocking mode and which engines the command is applied to. The :class:`View` class also has
 :attr:`block` and :attr:`targets` attributes that control the default behavior when the keyword
 arguments are not provided. Thus the following logic is used for :attr:`block` and :attr:`targets`:
 
 * If no keyword argument is provided, the instance attributes are used.
 * Keyword argument, if provided override the instance attributes for
   the duration of a single call.
   
 The following examples demonstrate how to use the instance attributes:
 
 .. sourcecode:: ipython
 
     In [16]: dview.targets = [0,2]
     
     In [17]: dview.block = False
 
     In [18]: ar = dview.apply(lambda : 10)
 
     In [19]: ar.get()
     Out[19]: [10, 10]
 
     In [16]: dview.targets = v.client.ids # all engines (4)
     
     In [21]: dview.block = True
 
     In [22]: dview.apply(lambda : 42)
     Out[22]: [42, 42, 42, 42]
 
 The :attr:`block` and :attr:`targets` instance attributes of the
 :class:`.DirectView` also determine the behavior of the parallel magic commands.
 
 Parallel magic commands
 -----------------------
 
 We provide a few IPython magic commands (``%px``, ``%autopx`` and ``%result``)
 that make it more pleasant to execute Python commands on the engines
 interactively. These are simply shortcuts to :meth:`execute` and
 :meth:`get_result` of the :class:`DirectView`. The ``%px`` magic executes a single 
 Python command on the engines specified by the :attr:`targets` attribute of the
 :class:`DirectView` instance:
 
 .. sourcecode:: ipython
 
     # Create a DirectView for all targets
     In [22]: dv = rc[:]
     
     # Make this DirectView active for parallel magic commands
     In [23]: dv.activate()
 
     In [24]: dv.block=True
 
     # import numpy here and everywhere
     In [25]: with dv.sync_imports():
        ....:    import numpy
     importing numpy on engine(s)
 
     In [27]: %px a = numpy.random.rand(2,2)
     Parallel execution on engines: [0, 1, 2, 3]
 
     In [28]: %px ev = numpy.linalg.eigvals(a)
     Parallel execution on engines: [0, 1, 2, 3]
 
     In [28]: dv['ev']
     Out[28]: [ array([ 1.09522024, -0.09645227]), 
        ....:   array([ 1.21435496, -0.35546712]), 
        ....:   array([ 0.72180653,  0.07133042]), 
        ....:   array([  1.46384341,   1.04353244e-04])
        ....: ]
 
 The ``%result`` magic gets the most recent result, or takes an argument
 specifying the index of the result to be requested. It is simply a shortcut to the
 :meth:`get_result` method:
 
 .. sourcecode:: ipython
     
     In [29]: dv.apply_async(lambda : ev)
     
     In [30]: %result
     Out[30]: [ [ 1.28167017  0.14197338],
        ....:    [-0.14093616  1.27877273],
        ....:    [-0.37023573  1.06779409],
        ....:    [ 0.83664764 -0.25602658] ]
 
 The ``%autopx`` magic switches to a mode where everything you type is executed
 on the engines given by the :attr:`targets` attribute:
 
 .. sourcecode:: ipython
 
     In [30]: dv.block=False
 
     In [31]: %autopx
     Auto Parallel Enabled
     Type %autopx to disable
 
     In [32]: max_evals = []
     <IPython.parallel.AsyncResult object at 0x17b8a70>
 
     In [33]: for i in range(100):
        ....:     a = numpy.random.rand(10,10)
        ....:     a = a+a.transpose()
        ....:     evals = numpy.linalg.eigvals(a)
        ....:     max_evals.append(evals[0].real)
        ....:
        ....:
     <IPython.parallel.AsyncResult object at 0x17af8f0>
 
     In [34]: %autopx
     Auto Parallel Disabled
 
     In [35]: dv.block=True
 
     In [36]: px ans= "Average max eigenvalue is: %f"%(sum(max_evals)/len(max_evals))
     Parallel execution on engines: [0, 1, 2, 3]
     
     In [37]: dv['ans']
     Out[37]: [ 'Average max eigenvalue is:  10.1387247332',
        ....:   'Average max eigenvalue is:  10.2076902286',
        ....:   'Average max eigenvalue is:  10.1891484655',
        ....:   'Average max eigenvalue is:  10.1158837784',]
 
 
 Moving Python objects around
 ============================
 
 In addition to calling functions and executing code on engines, you can
 transfer Python objects to and from your IPython session and the engines. In
 IPython, these operations are called :meth:`push` (sending an object to the
 engines) and :meth:`pull` (getting an object from the engines).
 
 Basic push and pull
 -------------------
 
 Here are some examples of how you use :meth:`push` and :meth:`pull`:
 
 .. sourcecode:: ipython
 
     In [38]: dview.push(dict(a=1.03234,b=3453))
     Out[38]: [None,None,None,None]
 
     In [39]: dview.pull('a')
     Out[39]: [ 1.03234, 1.03234, 1.03234, 1.03234]
 
     In [40]: dview.pull('b', targets=0)
     Out[40]: 3453
 
     In [41]: dview.pull(('a','b'))
     Out[41]: [ [1.03234, 3453], [1.03234, 3453], [1.03234, 3453], [1.03234, 3453] ]
     
     In [43]: dview.push(dict(c='speed'))
     Out[43]: [None,None,None,None]
 
 In non-blocking mode :meth:`push` and :meth:`pull` also return
 :class:`AsyncResult` objects:
 
 .. sourcecode:: ipython
 
     In [48]: ar = dview.pull('a', block=False)
 
     In [49]: ar.get()
     Out[49]: [1.03234, 1.03234, 1.03234, 1.03234]
 
 
 Dictionary interface
 --------------------
 
 Since a Python namespace is just a :class:`dict`, :class:`DirectView` objects provide
 dictionary-style access by key and methods such as :meth:`get` and
 :meth:`update` for convenience. This make the remote namespaces of the engines
 appear as a local dictionary. Underneath, these methods call :meth:`apply`:
 
 .. sourcecode:: ipython
 
     In [51]: dview['a']=['foo','bar']
 
     In [52]: dview['a']
     Out[52]: [ ['foo', 'bar'], ['foo', 'bar'], ['foo', 'bar'], ['foo', 'bar'] ]
 
 Scatter and gather
 ------------------
 
 Sometimes it is useful to partition a sequence and push the partitions to
 different engines. In MPI language, this is know as scatter/gather and we
 follow that terminology. However, it is important to remember that in
 IPython's :class:`Client` class, :meth:`scatter` is from the
 interactive IPython session to the engines and :meth:`gather` is from the
 engines back to the interactive IPython session. For scatter/gather operations
 between engines, MPI, pyzmq, or some other direct interconnect should be used.
 
 .. sourcecode:: ipython
 
     In [58]: dview.scatter('a',range(16))
     Out[58]: [None,None,None,None]
 
     In [59]: dview['a']
     Out[59]: [ [0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11], [12, 13, 14, 15] ]
 
     In [60]: dview.gather('a')
     Out[60]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
 
 Other things to look at
 =======================
 
 How to do parallel list comprehensions
 --------------------------------------
 
 In many cases list comprehensions are nicer than using the map function. While
 we don't have fully parallel list comprehensions, it is simple to get the
 basic effect using :meth:`scatter` and :meth:`gather`:
 
 .. sourcecode:: ipython
 
     In [66]: dview.scatter('x',range(64))
 
     In [67]: %px y = [i**10 for i in x]
     Parallel execution on engines: [0, 1, 2, 3]
     Out[67]:
 
     In [68]: y = dview.gather('y')
 
     In [69]: print y
     [0, 1, 1024, 59049, 1048576, 9765625, 60466176, 282475249, 1073741824,...]
 
 Remote imports
 --------------
 
 Sometimes you will want to import packages both in your interactive session
 and on your remote engines.  This can be done with the :class:`ContextManager`
 created by a DirectView's :meth:`sync_imports` method:
 
 .. sourcecode:: ipython
 
     In [69]: with dview.sync_imports():
        ....:     import numpy
     importing numpy on engine(s)
 
 Any imports made inside the block will also be performed on the view's engines.
 sync_imports also takes a `local` boolean flag that defaults to True, which specifies
 whether the local imports should also be performed.  However, support for `local=False`
 has not been implemented, so only packages that can be imported locally will work
 this way.
 
 You can also specify imports via the ``@require`` decorator.  This is a decorator
 designed for use in Dependencies, but can be used to handle remote imports as well.
 Modules or module names passed to ``@require`` will be imported before the decorated
 function is called.  If they cannot be imported, the decorated function will never
 execution, and will fail with an UnmetDependencyError.
 
 .. sourcecode:: ipython
 
     In [69]: from IPython.parallel import require
 
     In [70]: @require('re'):
        ....: def findall(pat, x):
        ....:     # re is guaranteed to be available
        ....:     return re.findall(pat, x)
           
     # you can also pass modules themselves, that you already have locally:
     In [71]: @require(time):
        ....: def wait(t):
        ....:     time.sleep(t)
        ....:     return t
 
 .. _parallel_exceptions:
 
 Parallel exceptions
 -------------------
 
 In the multiengine interface, parallel commands can raise Python exceptions,
 just like serial commands. But, it is a little subtle, because a single
 parallel command can actually raise multiple exceptions (one for each engine
 the command was run on). To express this idea, we have a
 :exc:`CompositeError` exception class that will be raised in most cases. The
 :exc:`CompositeError` class is a special type of exception that wraps one or
 more other types of exceptions. Here is how it works:
 
 .. sourcecode:: ipython
 
     In [76]: dview.block=True
 
     In [77]: dview.execute('1/0')
     ---------------------------------------------------------------------------
     CompositeError                            Traceback (most recent call last)
     /home/user/<ipython-input-10-5d56b303a66c> in <module>()
     ----> 1 dview.execute('1/0')
 
     /path/to/site-packages/IPython/parallel/client/view.pyc in execute(self, code, targets, block)
         591                 default: self.block
         592         """
     --> 593         return self._really_apply(util._execute, args=(code,), block=block, targets=targets)
         594 
         595     def run(self, filename, targets=None, block=None):
 
     /home/user/<string> in _really_apply(self, f, args, kwargs, targets, block, track)
 
     /path/to/site-packages/IPython/parallel/client/view.pyc in sync_results(f, self, *args, **kwargs)
          55 def sync_results(f, self, *args, **kwargs):
          56     """sync relevant results from self.client to our results attribute."""
     ---> 57     ret = f(self, *args, **kwargs)
          58     delta = self.outstanding.difference(self.client.outstanding)
          59     completed = self.outstanding.intersection(delta)
 
     /home/user/<string> in _really_apply(self, f, args, kwargs, targets, block, track)
 
     /path/to/site-packages/IPython/parallel/client/view.pyc in save_ids(f, self, *args, **kwargs)
          44     n_previous = len(self.client.history)
          45     try:
     ---> 46         ret = f(self, *args, **kwargs)
          47     finally:
          48         nmsgs = len(self.client.history) - n_previous
 
     /path/to/site-packages/IPython/parallel/client/view.pyc in _really_apply(self, f, args, kwargs, targets, block, track)
         529         if block:
         530             try:
     --> 531                 return ar.get()
         532             except KeyboardInterrupt:
         533                 pass
 
     /path/to/site-packages/IPython/parallel/client/asyncresult.pyc in get(self, timeout)
         101                 return self._result
         102             else:
     --> 103                 raise self._exception
         104         else:
         105             raise error.TimeoutError("Result not ready.")
 
     CompositeError: one or more exceptions from call to method: _execute
     [0:apply]: ZeroDivisionError: integer division or modulo by zero
     [1:apply]: ZeroDivisionError: integer division or modulo by zero
     [2:apply]: ZeroDivisionError: integer division or modulo by zero
     [3:apply]: ZeroDivisionError: integer division or modulo by zero
 
 Notice how the error message printed when :exc:`CompositeError` is raised has
 information about the individual exceptions that were raised on each engine.
 If you want, you can even raise one of these original exceptions:
 
 .. sourcecode:: ipython
 
     In [80]: try:
        ....:     dview.execute('1/0')
        ....: except parallel.error.CompositeError, e:
        ....:     e.raise_exception()
        ....:     
        ....:     
     ---------------------------------------------------------------------------
     RemoteError                               Traceback (most recent call last)
     /home/user/<ipython-input-17-8597e7e39858> in <module>()
           2     dview.execute('1/0')
           3 except CompositeError as e:
     ----> 4     e.raise_exception()
 
     /path/to/site-packages/IPython/parallel/error.pyc in raise_exception(self, excid)
         266             raise IndexError("an exception with index %i does not exist"%excid)
         267         else:
     --> 268             raise RemoteError(en, ev, etb, ei)
         269 
         270 
 
     RemoteError: ZeroDivisionError(integer division or modulo by zero)
     Traceback (most recent call last):
       File "/path/to/site-packages/IPython/parallel/engine/streamkernel.py", line 330, in apply_request
         exec code in working,working
       File "<string>", line 1, in <module>
       File "/path/to/site-packages/IPython/parallel/util.py", line 354, in _execute
         exec code in globals()
       File "<string>", line 1, in <module>
     ZeroDivisionError: integer division or modulo by zero
 
 If you are working in IPython, you can simple type ``%debug`` after one of
 these :exc:`CompositeError` exceptions is raised, and inspect the exception
 instance:
 
 .. sourcecode:: ipython
 
     In [81]: dview.execute('1/0')
     ---------------------------------------------------------------------------
     CompositeError                            Traceback (most recent call last)
     /home/user/<ipython-input-10-5d56b303a66c> in <module>()
     ----> 1 dview.execute('1/0')
 
     /path/to/site-packages/IPython/parallel/client/view.pyc in execute(self, code, targets, block)
         591                 default: self.block
         592         """
     --> 593         return self._really_apply(util._execute, args=(code,), block=block, targets=targets)
         594 
         595     def run(self, filename, targets=None, block=None):
 
     /home/user/<string> in _really_apply(self, f, args, kwargs, targets, block, track)
 
     /path/to/site-packages/IPython/parallel/client/view.pyc in sync_results(f, self, *args, **kwargs)
          55 def sync_results(f, self, *args, **kwargs):
          56     """sync relevant results from self.client to our results attribute."""
     ---> 57     ret = f(self, *args, **kwargs)
          58     delta = self.outstanding.difference(self.client.outstanding)
          59     completed = self.outstanding.intersection(delta)
 
     /home/user/<string> in _really_apply(self, f, args, kwargs, targets, block, track)
 
     /path/to/site-packages/IPython/parallel/client/view.pyc in save_ids(f, self, *args, **kwargs)
          44     n_previous = len(self.client.history)
          45     try:
     ---> 46         ret = f(self, *args, **kwargs)
          47     finally:
          48         nmsgs = len(self.client.history) - n_previous
 
     /path/to/site-packages/IPython/parallel/client/view.pyc in _really_apply(self, f, args, kwargs, targets, block, track)
         529         if block:
         530             try:
     --> 531                 return ar.get()
         532             except KeyboardInterrupt:
         533                 pass
 
     /path/to/site-packages/IPython/parallel/client/asyncresult.pyc in get(self, timeout)
         101                 return self._result
         102             else:
     --> 103                 raise self._exception
         104         else:
         105             raise error.TimeoutError("Result not ready.")
 
     CompositeError: one or more exceptions from call to method: _execute
     [0:apply]: ZeroDivisionError: integer division or modulo by zero
     [1:apply]: ZeroDivisionError: integer division or modulo by zero
     [2:apply]: ZeroDivisionError: integer division or modulo by zero
     [3:apply]: ZeroDivisionError: integer division or modulo by zero
     
     In [82]: %debug
     > /path/to/site-packages/IPython/parallel/client/asyncresult.py(103)get()
         102             else:
     --> 103                 raise self._exception
         104         else:
     
     # With the debugger running, self._exception is the exceptions instance.  We can tab complete
     # on it and see the extra methods that are available.
     ipdb> self._exception.<tab>
     e.__class__         e.__getitem__       e.__new__           e.__setstate__      e.args
     e.__delattr__       e.__getslice__      e.__reduce__        e.__str__           e.elist
     e.__dict__          e.__hash__          e.__reduce_ex__     e.__weakref__       e.message
     e.__doc__           e.__init__          e.__repr__          e._get_engine_str   e.print_tracebacks
     e.__getattribute__  e.__module__        e.__setattr__       e._get_traceback    e.raise_exception
     ipdb> self._exception.print_tracebacks()
     [0:apply]: 
     Traceback (most recent call last):
       File "/path/to/site-packages/IPython/parallel/engine/streamkernel.py", line 330, in apply_request
         exec code in working,working
       File "<string>", line 1, in <module>
       File "/path/to/site-packages/IPython/parallel/util.py", line 354, in _execute
         exec code in globals()
       File "<string>", line 1, in <module>
     ZeroDivisionError: integer division or modulo by zero
 
 
     [1:apply]: 
     Traceback (most recent call last):
       File "/path/to/site-packages/IPython/parallel/engine/streamkernel.py", line 330, in apply_request
         exec code in working,working
       File "<string>", line 1, in <module>
       File "/path/to/site-packages/IPython/parallel/util.py", line 354, in _execute
         exec code in globals()
       File "<string>", line 1, in <module>
     ZeroDivisionError: integer division or modulo by zero
 
 
     [2:apply]: 
     Traceback (most recent call last):
       File "/path/to/site-packages/IPython/parallel/engine/streamkernel.py", line 330, in apply_request
         exec code in working,working
       File "<string>", line 1, in <module>
       File "/path/to/site-packages/IPython/parallel/util.py", line 354, in _execute
         exec code in globals()
       File "<string>", line 1, in <module>
     ZeroDivisionError: integer division or modulo by zero
 
 
     [3:apply]: 
     Traceback (most recent call last):
       File "/path/to/site-packages/IPython/parallel/engine/streamkernel.py", line 330, in apply_request
         exec code in working,working
       File "<string>", line 1, in <module>
       File "/path/to/site-packages/IPython/parallel/util.py", line 354, in _execute
         exec code in globals()
       File "<string>", line 1, in <module>
     ZeroDivisionError: integer division or modulo by zero
 
 
 All of this same error handling magic even works in non-blocking mode:
 
 .. sourcecode:: ipython
 
     In [83]: dview.block=False
 
     In [84]: ar = dview.execute('1/0')
 
     In [85]: ar.get()
     ---------------------------------------------------------------------------
     CompositeError                            Traceback (most recent call last)
     /home/user/<ipython-input-21-8531eb3d26fb> in <module>()
     ----> 1 ar.get()
 
     /path/to/site-packages/IPython/parallel/client/asyncresult.pyc in get(self, timeout)
         101                 return self._result
         102             else:
     --> 103                 raise self._exception
         104         else:
         105             raise error.TimeoutError("Result not ready.")
 
     CompositeError: one or more exceptions from call to method: _execute
     [0:apply]: ZeroDivisionError: integer division or modulo by zero
     [1:apply]: ZeroDivisionError: integer division or modulo by zero
     [2:apply]: ZeroDivisionError: integer division or modulo by zero
     [3:apply]: ZeroDivisionError: integer division or modulo by zero