IPython: beyond plain Python¶
When executing code in IPython, all valid Python syntax works as-is, but IPython provides a number of features designed to make the interactive experience more fluid and efficient.
First things first: running code, getting help¶
In the notebook, to run a cell of code, hit Shift-Enter. This executes the cell and puts the cursor in the next cell below, or makes a new one if you are at the end. Alternately, you can use:
Alt-Enterto force the creation of a new cell unconditionally (useful when inserting new content in the middle of an existing notebook).Control-Enterexecutes the cell and keeps the cursor in the same cell, useful for quick experimentation of snippets that you don't need to keep permanently.
print "Hi"
Getting help:
?
Typing object_name? will print all sorts of details about any object, including docstrings, function definition lines (for call arguments) and constructor details for classes.
import collections
collections.namedtuple?
collections.Counter??
*int*?
An IPython quick reference card:
%quickref
Tab completion¶
Tab completion, especially for attributes, is a convenient way to explore the structure of any object you’re dealing with. Simply type object_name.<TAB> to view the object’s attributes. Besides Python objects and keywords, tab completion also works on file and directory names.
collections.
The interactive workflow: input, output, history¶
2+10
_+10
You can suppress the storage and rendering of output if you append ; to the last cell (this comes in handy when plotting with matplotlib, for example):
10+20;
_
The output is stored in _N and Out[N] variables:
_16 == Out[16]
And the last three have shorthands for convenience:
print 'last output:', _
print 'next one :', __
print 'and next :', ___
In[17]
_i
_ii
print 'last input:', _i
print 'next one :', _ii
print 'and next :', _iii
%history -n 1-5
Exercise
Write the last 10 lines of history to a file named log.py.
Accessing the underlying operating system¶
!pwd
files = !ls
print "My current directory's files:"
print files
!echo $files
!echo {files[0].upper()}
Beyond Python: magic functions¶
The IPyhton 'magic' functions are a set of commands, invoked by prepending one or two % signs to their name, that live in a namespace separate from your normal Python variables and provide a more command-like interface. They take flags with -- and arguments without quotes, parentheses or commas. The motivation behind this system is two-fold:
To provide an orthogonal namespace for controlling IPython itself and exposing other system-oriented functionality.
To expose a calling mode that requires minimal verbosity and typing while working interactively. Thus the inspiration taken from the classic Unix shell style for commands.
%magic
Line vs cell magics:
%timeit range(10)
%%timeit
range(10)
range(100)
Line magics can be used even inside code blocks:
for i in range(5):
size = i*100
print 'size:',size,
%timeit range(size)
Magics can do anything they want with their input, so it doesn't have to be valid Python:
%%bash
echo "My shell is:" $SHELL
echo "My memory status is:"
free
Another interesting cell magic: create any file you want locally from the notebook:
%%file test.txt
This is a test file!
It can contain anything I want...
And more...
!cat test.txt
Let's see what other magics are currently defined in the system:
%lsmagic
Running normal Python code: execution and errors¶
Notonly can you input normal Python code, you can even paste straight from a Python or IPython shell session:
>>> # Fibonacci series:
... # the sum of two elements defines the next
... a, b = 0, 1
>>> while b < 10:
... print b
... a, b = b, a+b
In [1]: for i in range(10):
...: print i,
...:
And when your code produces errors, you can control how they are displayed with the %xmode magic:
%%file mod.py
def f(x):
return 1.0/(x-1)
def g(y):
return f(y+1)
Now let's call the function g with an argument that would produce an error:
import mod
mod.g(0)
%xmode plain
mod.g(0)
%xmode verbose
mod.g(0)
The default %xmode is "context", which shows additional context but not all local variables. Let's restore that one for the rest of our session.
%xmode context
Plotting in the notebook¶
This imports numpy as np and matplotlib's plotting routines as plt, plus setting lots of other stuff for you to work interactivel very easily:
%pylab inline
x = np.linspace(0, 2*np.pi, 300)
y = np.sin(x**2)
plt.plot(x, y)
plt.title("A little chirp")
f = gcf() # let's keep the figure object around for later...
The IPython kernel/client model¶
%connect_info
%qtconsole