Check if variable equals a constant
You don’t need to explicitly compare a value to True, or None, or 0 - you can just add it to the if statement. See Truth Value Testing for a list of what is considered false.
Bad:
if attr == True:
print 'True!'
if attr == None:
print 'attr is None!'
Good:
# Just check the value
if attr:
print 'attr is truthy!'
# or check for the opposite
if not attr:
print 'attr is falsey!'
# or, since None is considered false, explicitly check for it
if attr is None:
print 'attr is None!'
Access a Dictionary Element
Don’t use the dict.has_key() method. Instead, use x in d syntax, or pass a default argument to dict.get().
Bad:
d = {'hello': 'world'}
if d.has_key('hello'):
print d['hello'] # prints 'world'
else:
print 'default_value'
Good:
d = {'hello': 'world'}
print d.get('hello', 'default_value') # prints 'world'
print d.get('thingy', 'default_value') # prints 'default_value'
# Or:
if 'hello' in d:
print d['hello']
Short Ways to Manipulate Lists
List comprehensions provide a powerful, concise way to work with lists. Also, the map() and filter() functions can perform operations on lists using a different, more concise syntax.
Bad:
# Filter elements greater than 4
a = [3, 4, 5]
b = []
for i in a:
if i > 4:
b.append(i)
Good:
a = [3, 4, 5]
b = [i for i in a if i > 4]
# Or:
b = filter(lambda x: x > 4, a)
Bad:
# Add three to all list members.
a = [3, 4, 5]
for i in range(len(a)):
a[i] += 3
Good:
a = [3, 4, 5]
a = [i + 3 for i in a]
# Or:
a = map(lambda i: i + 3, a)
Use enumerate() keep a count of your place in the list.
a = [3, 4, 5]
for i, item in enumerate(a):
print i, item
# prints
# 0 3
# 1 4
# 2 5
The enumerate() function has better readability than handling a counter manually. Moreover, it is better optimized for iterators.
Read From a File
Use the with open syntax to read from files. This will automatically close files for you.
Bad:
f = open('file.txt')
a = f.read()
print a
f.close()
Good:
with open('file.txt') as f:
for line in f:
print line
The with statement is better because it will ensure you always close the file, even if an exception is raised inside the with block.
Line Continuations
When a logical line of code is longer than the accepted limit, you need to split it over multiple physical lines. The Python interpreter will join consecutive lines if the last character of the line is a backslash. This is helpful in some cases, but should usually be avoided because of its fragility: a white space added to the end of the line, after the backslash, will break the code and may have unexpected results.
A better solution is to use parentheses around your elements. Left with an unclosed parenthesis on an end-of-line the Python interpreter will join the next line until the parentheses are closed. The same behavior holds for curly and square braces.
Bad:
my_very_big_string = """For a long time I used to go to bed early. Sometimes, \
when I had put out my candle, my eyes would close so quickly that I had not even \
time to say “I’m going to sleep.”"""
from some.deep.module.inside.a.module import a_nice_function, another_nice_function, \
yet_another_nice_function
Good:
my_very_big_string = (
"For a long time I used to go to bed early. Sometimes, "
"when I had put out my candle, my eyes would close so quickly "
"that I had not even time to say “I’m going to sleep.”"
)
from some.deep.module.inside.a.module import (
a_nice_function, another_nice_function, yet_another_nice_function)
However, more often than not, having to split a long logical line is a sign that you are trying to do too many things at the same time, which may hinder readability.
Importing of module
Very bad
[...]
from modu import *
[...]
x = sqrt(4) # Is sqrt part of modu? A builtin? Defined above?
Better
from modu import sqrt
[...]
x = sqrt(4) # sqrt may be part of modu, if not redefined in between
Best
import modu
[...]
x = modu.sqrt(4) # sqrt is visibly part of modu's namespace
Readability is one of the main features of Python. Readability means to avoid useless boilerplate text and clutter, therefore some efforts are spent trying to achieve a certain level of brevity. But terseness and obscurity are the limits where brevity should stop. Being able to tell immediately where a class or function comes from, as in the modu.func idiom, greatly improves code readability and understandability in all but the simplest single file projects.
Dynamic typing
Avoid using the same variable name for different things.
Bad
a = 1
a = 'a string'
def a():
pass # Do something
Good
count = 1
msg = 'a string'
def func():
pass # Do something
Using short functions or methods helps reduce the risk of using the same name for two unrelated things.
It is better to use different names even for things that are related, when they have a different type:
Bad
items = 'a b c d' # This is a string...
items = items.split(' ') # ...becoming a list
items = set(items) # ...and then a set
One peculiarity of Python that can surprise beginners is that strings are immutable. This means that when constructing a string from its parts, it is much more efficient to accumulate the parts in a list, which is mutable, and then glue (‘join’) the parts together when the full string is needed. One thing to notice, however, is that list comprehensions are better and faster than constructing a list in a loop with calls to append().
Bad
# create a concatenated string from 0 to 19 (e.g. "012..1819")
nums = ""
for n in range(20):
nums += str(n) # slow and inefficient
print nums
Good
# create a concatenated string from 0 to 19 (e.g. "012..1819")
nums = []
for n in range(20):
nums.append(str(n))
print "".join(nums) # much more efficient
Best
# create a concatenated string from 0 to 19 (e.g. "012..1819")
nums = [str(n) for n in range(20)]
print "".join(nums)
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