they see me stylin'

This commit is contained in:
2016-02-21 19:10:42 -05:00
parent f829b315b9
commit ad28c338ee
+20 -14
View File
@@ -350,7 +350,7 @@ Instead, use a list comprehension:
.. code-block:: python
four_lists = [[] for __ in xrange(4)]
Note: Use range() instead of xrange() in Python 3
Create a string from a list
@@ -389,29 +389,29 @@ Take the following code for example:
Even though both functions look identical, because *lookup_set* is utilizing
the fact that sets in Python are hashtables, the lookup performance
between the two is very different. To determine whether an item is in a list,
Python will have to go through each item until it finds a matching item.
Python will have to go through each item until it finds a matching item.
This is time consuming, especially for long lists. In a set, on the other
hand, the hash of the item will tell Python where in the set to look for
a matching item. As a result, the search can be done quickly, even if the
set is large. Searching in dictionaries works the same way. For
set is large. Searching in dictionaries works the same way. For
more information see this
`StackOverflow <http://stackoverflow.com/questions/513882/python-list-vs-dict-for-look-up-table>`_
page. For detailed information on the amount of time various common operations
take on each of these data structures, see
take on each of these data structures, see
`this page <https://wiki.python.org/moin/TimeComplexity?>`_.
Because of these differences in performance, it is often a good idea to use
sets or dictionaries instead of lists in cases where:
Because of these differences in performance, it is often a good idea to use
sets or dictionaries instead of lists in cases where:
* The collection will contain a large number of items
* You will be repeatedly searching for items in the collection
* You do not have duplicate items.
* You do not have duplicate items.
For small collections, or collections which you will not frequently be
searching through, the additional time and memory required to set up the
hashtable will often be greater than the time saved by the improved search
For small collections, or collections which you will not frequently be
searching through, the additional time and memory required to set up the
hashtable will often be greater than the time saved by the improved search
speed.
@@ -451,11 +451,17 @@ group <http://artifex.org/~hblanks/talks/2011/pep20_by_example.pdf>`_.
PEP 8
-----
:pep:`8` is the de-facto code style guide for Python.
:pep:`8` is the de-facto code style guide for Python. A high quality,
easy-to-read version of PEP 8 is also available at `pep8.org <http://pep8.org/>`_.
Conforming your Python code to PEP 8 is generally a good idea and helps make
code more consistent when working on projects with other developers. There
is a command-line program, `pep8 <https://github.com/jcrocholl/pep8>`_,
This is highly recommended reading. The entire Python community does their
best to adhere to the guidelines laidout within this document. Some project
may sway from it from time to time, while others may
`ammend its recommendations <http://docs.python-requests.org/en/master/dev/contributing/#kenneth-reitz-s-code-style>`_.
That being said, conforming your Python code to PEP 8 is generally a good
idea and helps make code more consistent when working on projects with other
developers. There is a command-line program, `pep8 <https://github.com/jcrocholl/pep8>`_,
that can check your code for conformance. Install it by running the following
command in your terminal: