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''' IPython customization API
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Your one-stop module for configuring & extending ipython
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The API will probably break when ipython 1.0 is released, but so
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will the other configuration method (rc files).
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All names prefixed by underscores are for internal use, not part
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of the public api.
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Below is an example that you can just put to a module and import from ipython.
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A good practice is to install the config script below as e.g.
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~/.ipython/my_private_conf.py
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And do
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import_mod my_private_conf
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in ~/.ipython/ipythonrc
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That way the module is imported at startup and you can have all your
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personal configuration (as opposed to boilerplate ipythonrc-PROFILENAME
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stuff) in there.
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-----------------------------------------------
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import IPython.ipapi
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ip = IPython.ipapi.get()
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def ankka_f(self, arg):
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print "Ankka",self,"says uppercase:",arg.upper()
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ip.expose_magic("ankka",ankka_f)
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ip.magic('alias sayhi echo "Testing, hi ok"')
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ip.magic('alias helloworld echo "Hello world"')
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ip.system('pwd')
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ip.ex('import re')
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ip.ex("""
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def funcci(a,b):
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print a+b
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print funcci(3,4)
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""")
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ip.ex("funcci(348,9)")
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def jed_editor(self,filename, linenum=None):
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print "Calling my own editor, jed ... via hook!"
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import os
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if linenum is None: linenum = 0
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os.system('jed +%d %s' % (linenum, filename))
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print "exiting jed"
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ip.set_hook('editor',jed_editor)
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o = ip.options
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o.autocall = 2 # FULL autocall mode
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print "done!"
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'''
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# stdlib imports
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import __builtin__
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import sys
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# our own
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from IPython.genutils import warn,error
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class TryNext(Exception):
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"""Try next hook exception.
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Raise this in your hook function to indicate that the next hook handler
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should be used to handle the operation. If you pass arguments to the
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constructor those arguments will be used by the next hook instead of the
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original ones.
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"""
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def __init__(self, *args, **kwargs):
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self.args = args
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self.kwargs = kwargs
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# contains the most recently instantiated IPApi
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class IPythonNotRunning:
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"""Dummy do-nothing class.
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Instances of this class return a dummy attribute on all accesses, which
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can be called and warns. This makes it easier to write scripts which use
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the ipapi.get() object for informational purposes to operate both with and
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without ipython. Obviously code which uses the ipython object for
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computations will not work, but this allows a wider range of code to
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transparently work whether ipython is being used or not."""
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def __str__(self):
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return "<IPythonNotRunning>"
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__repr__ = __str__
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def __getattr__(self,name):
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return self.dummy
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def dummy(self,*args,**kw):
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"""Dummy function, which doesn't do anything but warn."""
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warn("IPython is not running, this is a dummy no-op function")
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_recent = None
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def get(allow_dummy=False):
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"""Get an IPApi object.
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If allow_dummy is true, returns an instance of IPythonNotRunning
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instead of None if not running under IPython.
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Running this should be the first thing you do when writing extensions that
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can be imported as normal modules. You can then direct all the
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configuration operations against the returned object.
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"""
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global _recent
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if allow_dummy and not _recent:
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_recent = IPythonNotRunning()
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return _recent
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class IPApi:
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""" The actual API class for configuring IPython
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You should do all of the IPython configuration by getting an IPApi object
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with IPython.ipapi.get() and using the attributes and methods of the
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returned object."""
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def __init__(self,ip):
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# All attributes exposed here are considered to be the public API of
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# IPython. As needs dictate, some of these may be wrapped as
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# properties.
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self.magic = ip.ipmagic
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self.system = ip.ipsystem
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self.set_hook = ip.set_hook
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self.set_custom_exc = ip.set_custom_exc
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self.user_ns = ip.user_ns
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# Session-specific data store, which can be used to store
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# data that should persist through the ipython session.
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self.meta = ip.meta
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# The ipython instance provided
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self.IP = ip
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global _recent
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_recent = self
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# Use a property for some things which are added to the instance very
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# late. I don't have time right now to disentangle the initialization
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# order issues, so a property lets us delay item extraction while
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# providing a normal attribute API.
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def get_db(self):
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"""A handle to persistent dict-like database (a PickleShareDB object)"""
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return self.IP.db
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db = property(get_db,None,None,get_db.__doc__)
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def get_options(self):
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"""All configurable variables."""
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return self.IP.rc
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options = property(get_options,None,None,get_options.__doc__)
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def expose_magic(self,magicname, func):
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''' Expose own function as magic function for ipython
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def foo_impl(self,parameter_s=''):
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"""My very own magic!. (Use docstrings, IPython reads them)."""
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print 'Magic function. Passed parameter is between < >: <'+parameter_s+'>'
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print 'The self object is:',self
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ipapi.expose_magic("foo",foo_impl)
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'''
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import new
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im = new.instancemethod(func,self.IP, self.IP.__class__)
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setattr(self.IP, "magic_" + magicname, im)
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def ex(self,cmd):
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""" Execute a normal python statement in user namespace """
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exec cmd in self.user_ns
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def ev(self,expr):
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""" Evaluate python expression expr in user namespace
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Returns the result of evaluation"""
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return eval(expr,self.user_ns)
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def runlines(self,lines):
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""" Run the specified lines in interpreter, honoring ipython directives.
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This allows %magic and !shell escape notations.
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Takes either all lines in one string or list of lines.
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"""
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if isinstance(lines,basestring):
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self.IP.runlines(lines)
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else:
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self.IP.runlines('\n'.join(lines))
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def to_user_ns(self,vars):
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"""Inject a group of variables into the IPython user namespace.
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Inputs:
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- vars: string with variable names separated by whitespace
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This utility routine is meant to ease interactive debugging work,
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where you want to easily propagate some internal variable in your code
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up to the interactive namespace for further exploration.
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When you run code via %run, globals in your script become visible at
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the interactive prompt, but this doesn't happen for locals inside your
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own functions and methods. Yet when debugging, it is common to want
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to explore some internal variables further at the interactive propmt.
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Examples:
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To use this, you first must obtain a handle on the ipython object as
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indicated above, via:
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import IPython.ipapi
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ip = IPython.ipapi.get()
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Once this is done, inside a routine foo() where you want to expose
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variables x and y, you do the following:
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def foo():
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...
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x = your_computation()
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y = something_else()
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# This pushes x and y to the interactive prompt immediately, even
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# if this routine crashes on the next line after:
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ip.to_user_ns('x y')
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...
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# return
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If you need to rename variables, just use ip.user_ns with dict
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and update:
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# exposes variables 'foo' as 'x' and 'bar' as 'y' in IPython
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# user namespace
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ip.user_ns.update(dict(x=foo,y=bar))
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"""
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# print 'vars given:',vars # dbg
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# Get the caller's frame to evaluate the given names in
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cf = sys._getframe(1)
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user_ns = self.user_ns
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for name in vars.split():
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try:
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user_ns[name] = eval(name,cf.f_globals,cf.f_locals)
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except:
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error('could not get var. %s from %s' %
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(name,cf.f_code.co_name))
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def launch_new_instance(user_ns = None):
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""" Make and start a new ipython instance.
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This can be called even without having an already initialized
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ipython session running.
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This is also used as the egg entry point for the 'ipython' script.
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"""
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ses = make_session(user_ns)
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ses.mainloop()
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def make_user_ns(user_ns = None):
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"""Return a valid user interactive namespace.
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This builds a dict with the minimal information needed to operate as a
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valid IPython user namespace, which you can pass to the various embedding
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classes in ipython.
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"""
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if user_ns is None:
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# Set __name__ to __main__ to better match the behavior of the
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# normal interpreter.
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user_ns = {'__name__' :'__main__',
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'__builtins__' : __builtin__,
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}
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else:
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user_ns.setdefault('__name__','__main__')
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user_ns.setdefault('__builtins__',__builtin__)
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return user_ns
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def make_user_global_ns(ns = None):
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"""Return a valid user global namespace.
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Similar to make_user_ns(), but global namespaces are really only needed in
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embedded applications, where there is a distinction between the user's
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interactive namespace and the global one where ipython is running."""
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if ns is None: ns = {}
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return ns
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def make_session(user_ns = None):
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"""Makes, but does not launch an IPython session.
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Later on you can call obj.mainloop() on the returned object.
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Inputs:
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- user_ns(None): a dict to be used as the user's namespace with initial
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data.
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WARNING: This should *not* be run when a session exists already."""
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import IPython
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return IPython.Shell.start(user_ns)
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