Ipython Startup Config For Spyder Ide

Trying to add a few imports to my IPython profile so that when I open a kernel in the Spyder IDE they're always loaded. Spyder has a Qt interface (I think??), so I (a) checked to m

Solution 1:

Whether Spyder uses a QT interface or not shouldn't be related to which of the IPython config files you want to modify. The one you chose to modify, ipython_qtconsole_config.py is the configuration file that is loaded when you launch IPython's QT console, such as with the command line command

user@system:~$ ipython qtconsole

(I needed to update pyzmq for this to work.)

If Spyder maintains a running IPython kernel and merely manages how to display that for you, then Spyder is probably just maintaining a regular IPython session, in which case you want your configuration settings to go into the file ipython_config.py at the same directory where you found ipython_qtconsole_config.py.

I manage this slightly differently than you do. Inside of ipython_config.py the top few lines for me look like this:

# Configuration file for ipython.from os.path import join as pjoin
from IPython.utils.path import get_ipython_dir

c = get_config()
c.InteractiveShellApp.exec_files = [
    pjoin(get_ipython_dir(), "profile_default", "launch.py")
]

What this does is to obtain the IPython configuration directory for me, add on the profile_default subdirectory, and then add on the name launch.py which is a file that I created just to hold anything I want to be executed/loaded upon startup.

For example, here's the first bit from my file launch.py:

"""
IPython launch script
Author: Ely M. Spears
"""import re
import os
import abc
import sys
import mock
import time
import types
import pandas
import inspect
import cPickle
import unittest
import operator
import warnings
import datetime
import dateutil
import calendar
import copy_reg
import itertools
import contextlib
import collections
import numpy as np
import scipy as sp
import scipy.stats as st
import scipy.weave as weave
import multiprocessing as mp
from IPython.core.magic import (
    Magics,
    register_line_magic,
    register_cell_magic,
    register_line_cell_magic
)
from dateutil.relativedelta import relativedelta as drr


############################ Pickle/Unpickle methods ############################# See explanation at:# < http://bytes.com/topic/python/answers/#   552476-why-cant-you-pickle-instancemethods >def_pickle_method(method):
    func_name = method.im_func.__name__
    obj = method.im_self
    cls = method.im_classreturn _unpickle_method, (func_name, obj, cls)

def_unpickle_method(func_name, obj, cls):
    for cls in cls.mro():
        try:
            func = cls.__dict__[func_name]
        except KeyError:
            passelse:
            breakreturn func.__get__(obj, cls)

copy_reg.pickle(types.MethodType, _pickle_method, _unpickle_method)

############## Utilities ##############definterface_methods(*methods):
    """
    Class decorator that can decorate an abstract base class with method names
    that must be checked in order for isinstance or issubclass to return True.
    """defdecorator(Base):
        def__subclasshook__(Class, Subclass):
            if Class is Base:
                all_ancestor_attrs = [ancestor_class.__dict__.keys()
                                      for ancestor_classin Subclass.__mro__]
                ifall(method in all_ancestor_attrs for method in methods):
                    returnTruereturnNotImplemented
        Base.__subclasshook__ = classmethod(__subclasshook__)
        return Base

definterface(*attributes):
    """
    Class decorator checking for any kind of attributes, not just methods.

    Usage:

    @interface(('foo', 'bar', 'baz))
    class Blah
       pass

    Now, new classes will be treated as if they are subclasses of Blah, and 
    instances will be treated instances of Blah, provided they possess the
    attributes 'foo', 'bar', and 'baz'.
    """defdecorator(Base):
        defchecker(Other):
            returnall(hasattr(Other, a) for a in attributes)

        def__subclasshook__(cls, Other):
            if checker(Other):
                returnTruereturnNotImplementeddef__instancecheck__(cls, Other):
            return checker(Other)

        Base.__metaclass__.__subclasshook__ = classmethod(__subclasshook__)
        Base.__metaclass__.__instancecheck__ = classmethod(__instancecheck__)
        return Base
    return decorator

There's a lot more, probably dozens of helper functions, snippets of code I've thought are cool and just want to play with, etc. I also define some randomly generated toy data sets, like NumPy arrays and Pandas DataFrames, so that when I want to poke around with some one-off Pandas syntax or something, some toy data is always right there.

The other upside is that this factors out the custom imports, function definitions, etc. that I want loaded, so if I want the same things loaded for the notebook and/or the qt console, I can just add the same bit of code to exec the file launch.py and I can make changes in onlylaunch.py without having to manually migrate them to each of the three configuration files.

I also uncomment a few of the different settings, especially for plain IPython and for the notebook, so the config files are meaningfully different from each other, just not based on what modules I want imported on start up.