Here's a generator that yields the chunks you want:
def chunks(lst, n):
"""Yield successive n-sized chunks from lst."""
for i in range(0, len(lst), n):
yield lst[i:i + n]
import pprint
pprint.pprint(list(chunks(range(10, 75), 10)))
[[10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
[20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
[30, 31, 32, 33, 34, 35, 36, 37, 38, 39],
[40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
[50, 51, 52, 53, 54, 55, 56, 57, 58, 59],
[60, 61, 62, 63, 64, 65, 66, 67, 68, 69],
[70, 71, 72, 73, 74]]
If you're using Python 2, you should use xrange()
instead of range()
:
def chunks(lst, n):
"""Yield successive n-sized chunks from lst."""
for i in xrange(0, len(lst), n):
yield lst[i:i + n]
Also you can simply use list comprehension instead of writing a function, though it's a good idea to encapsulate operations like this in named functions so that your code is easier to understand. Python 3:
[lst[i:i + n] for i in range(0, len(lst), n)]
Python 2 version:
[lst[i:i + n] for i in xrange(0, len(lst), n)]
Actually, this is not a design flaw, and it is not because of internals or performance.
It comes simply from the fact that functions in Python are first-class objects, and not only a piece of code.
As soon as you think of it this way, then it completely makes sense: a function is an object being evaluated on its definition; default parameters are kind of "member data" and therefore their state may change from one call to the other - exactly as in any other object.
In any case, Effbot has a very nice explanation of the reasons for this behavior in Default Parameter Values in Python.
I found it very clear, and I really suggest reading it for a better knowledge of how function objects work.
Best Answer
pip's documentation lists the supported mechanisms to install it: https://pip.pypa.io/en/stable/installation/#supported-methods
It is generally recommended to avoid installing pip on the OS-provided
python
commands, and to install Python via the https://python.org installers or using something like Homebrew or pyenv.Python 3.4+ will have
ensurepip
, so if you're unable to runpython3 -m pip
-- runpython3 -m ensurepip
and it'll install pip for you.If you're using an end-of-life version of Python, you can use
get-pip.py
instead.Old answer (outdated, and results in a broken installation)
If you need admin privileges to run this, try: