##// END OF EJS Templates
add genutils.wrap_deprecated
add genutils.wrap_deprecated

File last commit:

Show More
330 lines | 9.8 KiB | text/x-python | PythonLexer
''' IPython customization API
Your one-stop module for configuring & extending ipython
The API will probably break when ipython 1.0 is released, but so
will the other configuration method (rc files).
All names prefixed by underscores are for internal use, not part
of the public api.
Below is an example that you can just put to a module and import from ipython.
A good practice is to install the config script below as e.g.
And do
import_mod my_private_conf
in ~/.ipython/ipythonrc
That way the module is imported at startup and you can have all your
personal configuration (as opposed to boilerplate ipythonrc-PROFILENAME
stuff) in there.
import IPython.ipapi
ip = IPython.ipapi.get()
def ankka_f(self, arg):
print "Ankka",self,"says uppercase:",arg.upper()
ip.magic('alias sayhi echo "Testing, hi ok"')
ip.magic('alias helloworld echo "Hello world"')
ip.ex('import re')
def funcci(a,b):
print a+b
print funcci(3,4)
def jed_editor(self,filename, linenum=None):
print "Calling my own editor, jed ... via hook!"
import os
if linenum is None: linenum = 0
os.system('jed +%d %s' % (linenum, filename))
print "exiting jed"
o = ip.options
o.autocall = 2 # FULL autocall mode
print "done!"
# stdlib imports
import __builtin__
import sys
# our own
from IPython.genutils import warn,error
class TryNext(Exception):
"""Try next hook exception.
Raise this in your hook function to indicate that the next hook handler
should be used to handle the operation. If you pass arguments to the
constructor those arguments will be used by the next hook instead of the
original ones.
def __init__(self, *args, **kwargs):
self.args = args
self.kwargs = kwargs
# contains the most recently instantiated IPApi
class IPythonNotRunning:
"""Dummy do-nothing class.
Instances of this class return a dummy attribute on all accesses, which
can be called and warns. This makes it easier to write scripts which use
the ipapi.get() object for informational purposes to operate both with and
without ipython. Obviously code which uses the ipython object for
computations will not work, but this allows a wider range of code to
transparently work whether ipython is being used or not."""
def __str__(self):
return "<IPythonNotRunning>"
__repr__ = __str__
def __getattr__(self,name):
return self.dummy
def dummy(self,*args,**kw):
"""Dummy function, which doesn't do anything but warn."""
warn("IPython is not running, this is a dummy no-op function")
_recent = None
def get(allow_dummy=False):
"""Get an IPApi object.
If allow_dummy is true, returns an instance of IPythonNotRunning
instead of None if not running under IPython.
Running this should be the first thing you do when writing extensions that
can be imported as normal modules. You can then direct all the
configuration operations against the returned object.
global _recent
if allow_dummy and not _recent:
_recent = IPythonNotRunning()
return _recent
class IPApi:
""" The actual API class for configuring IPython
You should do all of the IPython configuration by getting an IPApi object
with IPython.ipapi.get() and using the attributes and methods of the
returned object."""
def __init__(self,ip):
# All attributes exposed here are considered to be the public API of
# IPython. As needs dictate, some of these may be wrapped as
# properties.
self.magic = ip.ipmagic
self.system = ip.ipsystem
self.set_hook = ip.set_hook
self.set_custom_exc = ip.set_custom_exc
self.user_ns = ip.user_ns
self.set_crash_handler = ip.set_crash_handler
# Session-specific data store, which can be used to store
# data that should persist through the ipython session.
self.meta = ip.meta
# The ipython instance provided
self.IP = ip
global _recent
_recent = self
# Use a property for some things which are added to the instance very
# late. I don't have time right now to disentangle the initialization
# order issues, so a property lets us delay item extraction while
# providing a normal attribute API.
def get_db(self):
"""A handle to persistent dict-like database (a PickleShareDB object)"""
return self.IP.db
db = property(get_db,None,None,get_db.__doc__)
def get_options(self):
"""All configurable variables."""
return self.IP.rc
options = property(get_options,None,None,get_options.__doc__)
def expose_magic(self,magicname, func):
''' Expose own function as magic function for ipython
def foo_impl(self,parameter_s=''):
"""My very own magic!. (Use docstrings, IPython reads them)."""
print 'Magic function. Passed parameter is between < >: <'+parameter_s+'>'
print 'The self object is:',self
import new
im = new.instancemethod(func,self.IP, self.IP.__class__)
setattr(self.IP, "magic_" + magicname, im)
def ex(self,cmd):
""" Execute a normal python statement in user namespace """
exec cmd in self.user_ns
def ev(self,expr):
""" Evaluate python expression expr in user namespace
Returns the result of evaluation"""
return eval(expr,self.user_ns)
def runlines(self,lines):
""" Run the specified lines in interpreter, honoring ipython directives.
This allows %magic and !shell escape notations.
Takes either all lines in one string or list of lines.
if isinstance(lines,basestring):
def to_user_ns(self,vars):
"""Inject a group of variables into the IPython user namespace.
- vars: string with variable names separated by whitespace
This utility routine is meant to ease interactive debugging work,
where you want to easily propagate some internal variable in your code
up to the interactive namespace for further exploration.
When you run code via %run, globals in your script become visible at
the interactive prompt, but this doesn't happen for locals inside your
own functions and methods. Yet when debugging, it is common to want
to explore some internal variables further at the interactive propmt.
To use this, you first must obtain a handle on the ipython object as
indicated above, via:
import IPython.ipapi
ip = IPython.ipapi.get()
Once this is done, inside a routine foo() where you want to expose
variables x and y, you do the following:
def foo():
x = your_computation()
y = something_else()
# This pushes x and y to the interactive prompt immediately, even
# if this routine crashes on the next line after:
ip.to_user_ns('x y')
# return
If you need to rename variables, just use ip.user_ns with dict
and update:
# exposes variables 'foo' as 'x' and 'bar' as 'y' in IPython
# user namespace
# print 'vars given:',vars # dbg
# Get the caller's frame to evaluate the given names in
cf = sys._getframe(1)
user_ns = self.user_ns
for name in vars.split():
user_ns[name] = eval(name,cf.f_globals,cf.f_locals)
error('could not get var. %s from %s' %
def launch_new_instance(user_ns = None):
""" Make and start a new ipython instance.
This can be called even without having an already initialized
ipython session running.
This is also used as the egg entry point for the 'ipython' script.
ses = make_session(user_ns)
def make_user_ns(user_ns = None):
"""Return a valid user interactive namespace.
This builds a dict with the minimal information needed to operate as a
valid IPython user namespace, which you can pass to the various embedding
classes in ipython.
if user_ns is None:
# Set __name__ to __main__ to better match the behavior of the
# normal interpreter.
user_ns = {'__name__' :'__main__',
'__builtins__' : __builtin__,
return user_ns
def make_user_global_ns(ns = None):
"""Return a valid user global namespace.
Similar to make_user_ns(), but global namespaces are really only needed in
embedded applications, where there is a distinction between the user's
interactive namespace and the global one where ipython is running."""
if ns is None: ns = {}
return ns
def make_session(user_ns = None):
"""Makes, but does not launch an IPython session.
Later on you can call obj.mainloop() on the returned object.
- user_ns(None): a dict to be used as the user's namespace with initial
WARNING: This should *not* be run when a session exists already."""
import IPython
return IPython.Shell.start(user_ns)