If you are a Matlab user, but want to use Python, check out numpy:

In [37]: import numpy as np

In [38]: a = np.arange(100)

In [39]: s = a[[5,13,25]]

In [40]: s
Out[40]: array([ 5, 13, 25])

Here is a comparison of NumPy and Matlab, and here is a table of common Matlab commands and their equivalents in NumPy.

You can leave one end of the slice open by not specifying the value.

test[3:] = [3, 4, 5, 6, 7, 8, 9]
test[:3] = [0, 1, 2]

With numpy it is very simple - you could just perform the slice:

In [1]: import numpy as np

In [2]: A = np.array([[1,2,3,4,5],[1,2,3,4,5],[1,2,3,4,5]])

In [3]: A[:,:3]
Out[3]: 
array([[1, 2, 3],
       [1, 2, 3],
       [1, 2, 3]])

You could, of course, transform numpy.array back to the list:

In [4]: A[:,:3].tolist()
Out[4]: [[1, 2, 3], [1, 2, 3], [1, 2, 3]]

When you specify a on the left side of the = operator, you are using Python's normal assignment, which changes the name a in the current context to point to the new value. This does not change the previous value to which a was pointing.

By specifying a[0:2] on the left side of the = operator, you are telling Python you want to use slice assignment. Slice assignment is a special syntax for lists, where you can insert, delete, or replace contents from a list:

Insertion:

>>> a = [1, 2, 3]
>>> a[0:0] = [-3, -2, -1, 0]
>>> a
[-3, -2, -1, 0, 1, 2, 3]

Deletion:

>>> a
[-3, -2, -1, 0, 1, 2, 3]
>>> a[2:4] = []
>>> a
[-3, -2, 1, 2, 3]

Replacement:

>>> a
[-3, -2, 1, 2, 3]
>>> a[:] = [1, 2, 3]
>>> a
[1, 2, 3]

Note:

The length of the slice may be different from the length of the assigned sequence, thus changing the length of the target sequence, if the target sequence allows it. - source

Slice assignment provides similar function to tuple unpacking. For example, a[0:1] = [4, 5] is equivalent to:

# Tuple Unpacking
a[0], a[1] = [4, 5]

With tuple unpacking, you can modify non-sequential lists:

>>> a
[4, 5, 3]
>>> a[-1], a[0] = [7, 3]
>>> a
[3, 5, 7]

However, tuple unpacking is limited to replacement, as you cannot insert or remove elements.

Before and after all these operations, a is the same exact list. Python simply provides nice syntactic sugar to modify a list in-place.