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01 Swap Variables
>>>a=3
>>>b=6
If you want to swap variables in C++, you definitely need an empty variable. But Python doesn’t require this, just one line, everyone pay attention
>>>a,b=b,a
>>>print(a)>>>6
>>>print(b)>>>3
02 Dictionary Comprehensions and Set Comprehensions
Most Python programmers know and have used list comprehensions. If you are not very familiar with the concept of list comprehensions—a list comprehension is a shorter and more concise way to create a list.
>>> some_list = [1, 2, 3, 4, 5]
>>> another_list = [ x + 1 for x in some_list ]
>>> another_list
[2, 3, 4, 5, 6]
Since Python 3.1, we can use the same syntax to create sets and dictionaries:
>>> # Set Comprehensions
>>> some_list = [1, 2, 3, 4, 5, 2, 5, 1, 4, 8]
>>> even_set = { x for x in some_list if x % 2 == 0 }
>>> even_set
set([8, 2, 4])
>>> # Dict Comprehensions
>>> d = { x: x % 2 == 0 for x in range(1, 11) }
>>> d
{1: False, 2: True, 3: False, 4: True, 5: False, 6: True, 7: False, 8: True, 9: False, 10: True}
In the first example, we created a set with unique elements based on some_list, and the set only contains even numbers. In the dictionary example, we created a key that is unique integers between 1 and 10, and the value is a boolean indicating whether the key is even.
Another thing worth noting is the literal representation of sets. We can simply create a set using this method:
>>> my_set = {1, 2, 1, 2, 3, 4}
>>> my_set
set([1, 2, 3, 4])
Without needing to use the built-in set() function.
03 Using Counter for Counting
This seems obvious, but is often forgotten. Counting something is a common task for most programmers, and in most cases, it is not very challenging—here are a few ways to accomplish this task more simply.
Python’s collections library has a built-in subclass of the dict class that is specifically designed for this:
>>> from collections import Counter
>>> c = Counter('hello world')
>>> c
Counter({'l': 3, 'o': 2, ' ': 1, 'e': 1, 'd': 1, 'h': 1, 'r': 1, 'w': 1})
>>> c.most_common(2)
[('l', 3), ('o', 2)]
04 Pretty Print JSON
JSON is a very good form of data serialization, widely used by various APIs and web services today. Using Python’s built-in JSON processing can make JSON strings somewhat readable, but when dealing with large data, it can appear as a long, continuous line, making it difficult for the human eye to read.
To make JSON data more user-friendly, we can use the indent parameter to output pretty JSON. This is especially useful when programming interactively in the console or logging:
>>> import json
>>> print(json.dumps(data)) # No indentation
{"status": "OK", "count": 2, "results": [{"age": 27, "name": "Oz", "lactose_intolerant": true}, {"age": 29, "name": "Joe", "lactose_intolerant": false}]}
>>> print(json.dumps(data, indent=2)) # With indentation
{
"status": "OK",
"count": 2,
"results": [
{
"age": 27,
"name": "Oz",
"lactose_intolerant": true
},
{
"age": 29,
"name": "Joe",
"lactose_intolerant": false
}
]
}
Similarly, using the built-in pprint module can also make anything else printed out look nicer.
05 Solving FizzBuzz
Recently, Jeff Atwood promoted a simple programming exercise called FizzBuzz, the problem is stated as follows:
Write a program that prints the numbers from 1 to 100. For multiples of 3, print “Fizz” instead of the number, for multiples of 5, print “Buzz”, and for numbers that are multiples of both 3 and 5, print “FizzBuzz”.
Here is a short, interesting way to solve this problem:
for x in range(1,101):
print"fizz"[x%3*len('fizz')::]+"buzz"[x%5*len('buzz')::] or x
06 Inline if Statements
print "Hello" if True else "World"
>>> Hello
07 Concatenation
The last method here is very cool when binding two different types of objects.
nfc = ["Packers", "49ers"]
afс = ["Ravens", "Patriots"]
print nfc + afc
>>> ['Packers', '49ers', 'Ravens', 'Patriots']
print str(1) + " world"
>>> 1 world
print `1` + " world"
>>> 1 world
print 1, "world"
>>> 1 world
print nfc, 1
>>> ['Packers', '49ers'] 1
08 Numeric Comparison
This is an awesome and simple method that I have rarely seen in many languages.
x = 2
if 3 > x > 1:
print x
>>> 2
if 1 < x > 0:
print x
>>> 2
09 Iterating Two Lists Simultaneously
nfc = ["Packers", "49ers"]
afс = ["Ravens", "Patriots"]
for teama, teamb in zip(nfc, afc):
print teama + " vs. " + teamb
>>> Packers vs. Ravens
>>> 49ers vs. Patriots
10 Iterating Lists with Index
teams = ["Packers", "49ers", "Ravens", "Patriots"]
for index, team in enumerate(teams):
print index, team
>>> 0 Packers
>>> 1 49ers
>>> 2 Ravens
>>> 3 Patriots
11 List Comprehensions
Given a list, we can filter out even numbers:
numbers = [1,2,3,4,5,6]
even = []
for number in numbers:
if number%2 == 0:
even.append(number)
Transform it into:
numbers = [1,2,3,4,5,6]
even = [number for number in numbers if number%2 == 0]
12 Dictionary Comprehension
Similar to list comprehensions, dictionaries can do the same work:
teams = ["Packers", "49ers", "Ravens", "Patriots"]
print {key: value for value, key in enumerate(teams)}
>>> {'49ers': 1, 'Ravens': 2, 'Patriots': 3, 'Packers': 0}
13 Initializing List Values
items = [0]*3
print items
>>> [0,0,0]
14 Converting List to String
teams = ["Packers", "49ers", "Ravens", "Patriots"]
print ", ".join(teams)
>>> 'Packers, 49ers, Ravens, Patriots'
15 Getting Elements from a Dictionary
I admit that try/except code is not elegant, but here is a simple method to try to look up a key in a dictionary, if not found, use the second parameter as its variable value.
data = {'user': 1, 'name': 'Max', 'three': 4}
try:
is_admin = data['admin']
except KeyError:
is_admin = False
Replace it with:
data = {'user': 1, 'name': 'Max', 'three': 4}
is_admin = data.get('admin', False)
16 Getting a Subset of a List
Sometimes, you only need a subset of elements from a list, here are some ways to get subsets of a list.
x = [1,2,3,4,5,6]
# First 3
print x[:3]
>>> [1,2,3]
# Middle 4
print x[1:5]
>>> [2,3,4,5]
# Last 3
print x[3:]
>>> [4,5,6]
# Odd items
print x[::2]
>>> [1,3,5]
# Even items
print x[1::2]
>>> [2,4,6]
In addition to Python’s built-in data types, the collections module also includes some special use cases, where Counter is very useful. If you participated in this year’s Facebook Hacker Cup, you might even find its practicality.
from collections import Counter
print Counter("hello")
>>> Counter({'l': 2, 'h': 1, 'e': 1, 'o': 1})
17 Itertools
Similar to the collections library, there is also a library called itertools, which can efficiently solve certain problems. One use case is to find all combinations, which can tell you all the possible combinations of elements in a group.
from itertools import combinations
teams = ["Packers", "49ers", "Ravens", "Patriots"]
for game in combinations(teams, 2):
print game
>>> ('Packers', '49ers')
>>> ('Packers', 'Ravens')
>>> ('Packers', 'Patriots')
>>> ('49ers', 'Ravens')
>>> ('49ers', 'Patriots')
>>> ('Ravens', 'Patriots')
18 False == True
Compared to practical techniques, this is a very interesting fact: in Python, True and False are global variables, so:
False = True
if False:
print "Hello"
else:
print "World"
>>> Hello
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