# 前言

> Python 是世上最好的语言？至少对新人来说：是！

当我们开始学习一门语言的时候，总是希望能够有一份全景图，在学习的一开始能够纵览全貌。

# 如何学习？

1. 登录网站：[jupyter.cda.cn]()，在线跟着操作
2. 逐行复制文末的[全部代码](#全部代码)，在你电脑端的 Python 解释器中跟着操作
3. 下载 [Notebook 文件](https://raw.githubusercontent.com/justmarkham/python-reference/master/reference.ipynb)，用本地的 Jupyter Notebook 打开，逐行操作

# 目录

点击链接即可跳转对应的 Jupyter Notebook:

1. Imports([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#1.-Imports))
2. Data Types ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#2.-Data-Types))
3. Math ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#3.-Math))
4. Comparisons and Boolean Operations ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#4.-Comparisons-and-Boolean-Operations))
5. Conditional Statements ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#5.-Conditional-Statements))
6. Lists ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#6.-Lists))
7. Tuples ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#7.-Tuples))
8. Strings ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#8.-Strings))
9. Dictionaries ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#9.-Dictionaries))
10. Sets ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#10.-Sets))
11. Defining Functions ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#11.-Defining-Functions))
12. Anonymous (Lambda) Functions ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#12.-Anonymous))
13. For Loops and While Loops ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#13.-For-Loops-and-While-Loops))
14. Comprehensions ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#14.-Comprehensions))
15. Map and Filter ([notebook](https://nbviewer.jupyter.org/github/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb#15.-Map-and-Filter))

# 进一步学习 Python

如果因为这次的了解，你对 Python 更加感兴趣，希望学习更多关于 Python 的知识，你可以尝试跟着我的这个项目来进一步学习。

[Python-Tutorial-for-Humans](https://github.com/DavidFnck/Python-Tutorial-for-Humans/tree/editing)

适合新人，免费、中文、零基础、快速入门的 Python 教程。

# 感谢

本教程以 [Data School](https://www.dataschool.io/python-quick-reference/) 为整体框架参考，但是因为是全英文不便中国学生学习，因此做了翻译，同时我也将内容进行了整理、编排，增加了更多延展。

感谢 [Kevin Markham 老师](https://twitter.com/justmarkham)，欢迎关注他的 Twitter。

同时，我的水平有限，如果教程中有问题的地方，请立言告诉我，欢迎大家批评指正，谢谢。

# 全部代码

```python
'''
[Python 快速入门](https://github.com/DavidFnck/Python-Tutorial-for-Humans/blob/editing/001-Python%20%E6%95%99%E7%A8%8B%E7%AE%80%E4%BB%8B/002-Python-Quick-Reference.ipynb)

作者: CDA.cn 联合创始人曹鑫(caoxin@cda.cn)
官网: http://cda.cn
'''
### IMPORTS ###

# 'generic import' of math module
import math
math.sqrt(25)

# import a function
from math import sqrt
sqrt(25)    # no longer have to reference the module

# import multiple functions at once
from math import cos, floor

# import all functions in a module (generally discouraged)
from csv import *

# define an alias
import datetime as dt

# show all functions in math module
dir(math)



### DATA TYPES ###

# determine the type of an object
type(2)         # returns 'int'
type(2.0)       # returns 'float'
type('two')     # returns 'str'
type(True)      # returns 'bool'
type(None)      # returns 'NoneType'

# check if an object is of a given type
isinstance(2.0, int)            # returns False
isinstance(2.0, (int, float))   # returns True

# convert an object to a given type
float(2)
int(2.9)
str(2.9)

# zero, None, and empty containers are converted to False
bool(0)
bool(None)
bool('')    # empty string
bool([])    # empty list
bool({})    # empty dictionary

# non-empty containers and non-zeros are converted to True
bool(2)
bool('two')
bool([2])



### MATH ###

# basic operations
10 + 4          # add (returns 14)
10 - 4          # subtract (returns 6)
10 * 4          # multiply (returns 40)
10 ** 4         # exponent (returns 10000)
5 % 4           # modulo (returns 1) - computes the remainder
10 / 4          # divide (returns 2 in Python 2, returns 2.5 in Python 3)
10 / float(4)   # divide (returns 2.5)

# force '/' in Python 2 to perform 'true division' (unnecessary in Python 3)
from __future__ import division
10 / 4          # true division (returns 2.5)
10 // 4         # floor division (returns 2)



### COMPARISONS AND BOOLEAN OPERATIONS ###

# assignment statement
x = 5

# comparisons (these return True)
x > 3
x >= 3
x != 3
x == 5

# boolean operations (these return True)
5 > 3 and 6 > 3
5 > 3 or 5 < 3
not False
False or not False and True     # evaluation order: not, and, or



### CONDITIONAL STATEMENTS ###

# if statement
if x > 0:
    print('positive')

# if/else statement
if x > 0:
    print('positive')
else:
    print('zero or negative')

# if/elif/else statement
if x > 0:
    print('positive')
elif x == 0:
    print('zero')
else:
    print('negative')

# single-line if statement (sometimes discouraged)
if x > 0: print('positive')

# single-line if/else statement (sometimes discouraged)
# known as a 'ternary operator'
'positive' if x > 0 else 'zero or negative'



### LISTS ###
## properties: ordered, iterable, mutable, can contain multiple data types

# create an empty list (two ways)
empty_list = []
empty_list = list()

# create a list
simpsons = ['homer', 'marge', 'bart']

# examine a list
simpsons[0]     # print element 0 ('homer')
len(simpsons)   # returns the length (3)

# modify a list (does not return the list)
simpsons.append('lisa')                 # append element to end
simpsons.extend(['itchy', 'scratchy'])  # append multiple elements to end
simpsons.insert(0, 'maggie')            # insert element at index 0 (shifts everything right)
simpsons.remove('bart')                 # search for first instance and remove it
simpsons.pop(0)                         # remove element 0 and return it
del simpsons[0]                         # remove element 0 (does not return it)
simpsons[0] = 'krusty'                  # replace element 0

# concatenate lists (slower than 'extend' method)
neighbors = simpsons + ['ned', 'rod', 'todd']

# find elements in a list
simpsons.count('lisa')      # counts the number of instances
simpsons.index('itchy')     # returns index of first instance

# list slicing [start:end:step]
weekdays = ['mon', 'tues', 'wed', 'thurs', 'fri']
weekdays[0]         # element 0
weekdays[0:3]       # elements 0, 1, 2
weekdays[:3]        # elements 0, 1, 2
weekdays[3:]        # elements 3, 4
weekdays[-1]        # last element (element 4)
weekdays[::2]       # every 2nd element (0, 2, 4)
weekdays[::-1]      # backwards (4, 3, 2, 1, 0)

# alternative method for returning the list backwards
list(reversed(weekdays))

# sort a list in place (modifies but does not return the list)
simpsons.sort()
simpsons.sort(reverse=True)     # sort in reverse
simpsons.sort(key=len)          # sort by a key

# return a sorted list (does not modify the original list)
sorted(simpsons)
sorted(simpsons, reverse=True)
sorted(simpsons, key=len)

# insert into an already sorted list, and keep it sorted
num = [10, 20, 40, 50]
from bisect import insort
insort(num, 30)

# create a second reference to the same list
same_num = num
same_num[0] = 0         # modifies both 'num' and 'same_num'

# copy a list (two ways)
new_num = num[:]
new_num = list(num)

# examine objects
num is same_num         # returns True (checks whether they are the same object)
num is new_num          # returns False
num == same_num         # returns True (checks whether they have the same contents)
num == new_num          # returns True



### TUPLES ###
## properties: ordered, iterable, immutable, can contain multiple data types
## like lists, but they don't change size

# create a tuple
digits = (0, 1, 'two')          # create a tuple directly
digits = tuple([0, 1, 'two'])   # create a tuple from a list
zero = (0,)                     # trailing comma is required to indicate it's a tuple

# examine a tuple
digits[2]           # returns 'two'
len(digits)         # returns 3
digits.count(0)     # counts the number of instances of that value (1)
digits.index(1)     # returns the index of the first instance of that value (1)

# elements of a tuple cannot be modified
digits[2] = 2       # throws an error

# concatenate tuples
digits = digits + (3, 4)

# create a single tuple with elements repeated (also works with lists)
(3, 4) * 2          # returns (3, 4, 3, 4)

# sort a list of tuples
tens = [(20, 60), (10, 40), (20, 30)]
sorted(tens)        # sorts by first element in tuple, then second element
                    #   returns [(10, 40), (20, 30), (20, 60)]

# tuple unpacking
bart = ('male', 10, 'simpson')  # create a tuple
(sex, age, surname) = bart      # assign three values at once



### STRINGS ###
## properties: iterable, immutable

# create a string
s = str(42)         # convert another data type into a string
s = 'I like you'

# examine a string
s[0]                # returns 'I'
len(s)              # returns 10

# string slicing is like list slicing
s[:6]               # returns 'I like'
s[7:]               # returns 'you'
s[-1]               # returns 'u'

# basic string methods (does not modify the original string)
s.lower()           # returns 'i like you'
s.upper()           # returns 'I LIKE YOU'
s.startswith('I')   # returns True
s.endswith('you')   # returns True
s.isdigit()         # returns False (returns True if every character in the string is a digit)
s.find('like')      # returns index of first occurrence (2), but doesn't support regex
s.find('hate')      # returns -1 since not found
s.replace('like', 'love')    # replaces all instances of 'like' with 'love'

# split a string into a list of substrings separated by a delimiter
s.split(' ')        # returns ['I', 'like', 'you']
s.split()           # equivalent (since space is the default delimiter)
s2 = 'a, an, the'
s2.split(',')       # returns ['a', ' an', ' the']

# join a list of strings into one string using a delimiter
stooges = ['larry', 'curly', 'moe']
' '.join(stooges)   # returns 'larry curly moe'

# concatenate strings
s3 = 'The meaning of life is'
s4 = '42'
s3 + ' ' + s4       # returns 'The meaning of life is 42'

# remove whitespace from start and end of a string
s5 = '  ham and cheese  '
s5.strip()          # returns 'ham and cheese'

# string substitutions: all of these return 'raining cats and dogs'
'raining %s and %s' % ('cats', 'dogs')                       # old way
'raining {} and {}'.format('cats', 'dogs')                   # new way
'raining {arg1} and {arg2}'.format(arg1='cats', arg2='dogs') # named arguments

# string formatting
# more examples: https://mkaz.blog/code/python-string-format-cookbook/
'pi is {:.2f}'.format(3.14159)      # returns 'pi is 3.14'

# normal strings versus raw strings
print('first line\nsecond line')    # normal strings allow for escaped characters
print(r'first line\nfirst line')    # raw strings treat backslashes as literal characters



### DICTIONARIES ###
## properties: unordered, iterable, mutable, can contain multiple data types
## made of key-value pairs
## keys must be unique, and can be strings, numbers, or tuples
## values can be any type

# create an empty dictionary (two ways)
empty_dict = {}
empty_dict = dict()

# create a dictionary (two ways)
family = {'dad':'homer', 'mom':'marge', 'size':6}
family = dict(dad='homer', mom='marge', size=6)

# convert a list of tuples into a dictionary
list_of_tuples = [('dad', 'homer'), ('mom', 'marge'), ('size', 6)]
family = dict(list_of_tuples)

# examine a dictionary
family['dad']       # returns 'homer'
len(family)         # returns 3
'mom' in family     # returns True
'marge' in family   # returns False (only checks keys)

# returns a list (Python 2) or an iterable view (Python 3)
family.keys()       # keys: ['dad', 'mom', 'size']
family.values()     # values: ['homer', 'marge', 6]
family.items()      # key-value pairs: [('dad', 'homer'), ('mom', 'marge'), ('size', 6)]

# modify a dictionary (does not return the dictionary)
family['cat'] = 'snowball'              # add a new entry
family['cat'] = 'snowball ii'           # edit an existing entry
del family['cat']                       # delete an entry
family['kids'] = ['bart', 'lisa']       # dictionary value can be a list
family.pop('dad')                       # remove an entry and return the value ('homer')
family.update({'baby':'maggie', 'grandpa':'abe'})   # add multiple entries

# access values more safely with 'get'
family['mom']                       # returns 'marge'
family.get('mom')                   # equivalent
family['grandma']                   # throws an error since the key does not exist
family.get('grandma')               # returns None instead
family.get('grandma', 'not found')  # returns 'not found' (the default)

# access a list element within a dictionary
family['kids'][0]                   # returns 'bart'
family['kids'].remove('lisa')       # removes 'lisa'

# string substitution using a dictionary
'youngest child is %(baby)s' % family   # returns 'youngest child is maggie'



### SETS ###
## properties: unordered, iterable, mutable, can contain multiple data types
## made of unique elements (strings, numbers, or tuples)
## like dictionaries, but with keys only (no values)

# create an empty set
empty_set = set()

# create a set
languages = {'python', 'r', 'java'}         # create a set directly
snakes = set(['cobra', 'viper', 'python'])  # create a set from a list

# examine a set
len(languages)              # returns 3
'python' in languages       # returns True

# set operations
languages & snakes          # returns intersection: {'python'}
languages | snakes          # returns union: {'cobra', 'r', 'java', 'viper', 'python'}
languages - snakes          # returns set difference: {'r', 'java'}
snakes - languages          # returns set difference: {'cobra', 'viper'}

# modify a set (does not return the set)
languages.add('sql')        # add a new element
languages.add('r')          # try to add an existing element (ignored, no error)
languages.remove('java')    # remove an element
languages.remove('c')       # try to remove a non-existing element (throws an error)
languages.discard('c')      # remove an element if present, but ignored otherwise
languages.pop()             # remove and return an arbitrary element
languages.clear()           # remove all elements
languages.update(['go', 'spark'])  # add multiple elements (can also pass a set)

# get a sorted list of unique elements from a list
sorted(set([9, 0, 2, 1, 0]))    # returns [0, 1, 2, 9]



### DEFINING FUNCTIONS ###

# define a function with no arguments and no return values
def print_text():
    print('this is text')

# call the function
print_text()

# define a function with one argument and no return values
def print_this(x):
    print(x)

# call the function
print_this(3)       # prints 3
n = print_this(3)   # prints 3, but doesn't assign 3 to n
                    #   because the function has no return statement

# define a function with one argument and one return value
def square_this(x):
    return x**2

# include an optional docstring to describe the effect of a function
def square_this(x):
    """Return the square of a number."""
    return x**2

# call the function
square_this(3)          # prints 9
var = square_this(3)    # assigns 9 to var, but does not print 9

# define a function with two 'positional arguments' (no default values) and
# one 'keyword argument' (has a default value)
def calc(a, b, op='add'):
    if op == 'add':
        return a + b
    elif op == 'sub':
        return a - b
    else:
        print('valid operations are add and sub')

# call the function
calc(10, 4, op='add')   # returns 14
calc(10, 4, 'add')      # also returns 14: unnamed arguments are inferred by position
calc(10, 4)             # also returns 14: default for 'op' is 'add'
calc(10, 4, 'sub')      # returns 6
calc(10, 4, 'div')      # prints 'valid operations are add and sub'

# use 'pass' as a placeholder if you haven't written the function body
def stub():
    pass

# return two values from a single function
def min_max(nums):
    return min(nums), max(nums)

# return values can be assigned to a single variable as a tuple
nums = [1, 2, 3]
min_max_num = min_max(nums)         # min_max_num = (1, 3)

# return values can be assigned into multiple variables using tuple unpacking
min_num, max_num = min_max(nums)    # min_num = 1, max_num = 3



### ANONYMOUS (LAMBDA) FUNCTIONS ###
## primarily used to temporarily define a function for use by another function

# define a function the "usual" way
def squared(x):
    return x**2

# define an identical function using lambda
squared = lambda x: x**2

# sort a list of strings by the last letter (without using lambda)
simpsons = ['homer', 'marge', 'bart']
def last_letter(word):
    return word[-1]
sorted(simpsons, key=last_letter)

# sort a list of strings by the last letter (using lambda)
sorted(simpsons, key=lambda word: word[-1])



### FOR LOOPS AND WHILE LOOPS ###

# range returns a list of integers (Python 2) or a sequence (Python 3)
range(0, 3)     # returns [0, 1, 2]: includes start value but excludes stop value
range(3)        # equivalent: default start value is 0
range(0, 5, 2)  # returns [0, 2, 4]: third argument is the step value

# Python 2 only: use xrange to create a sequence rather than a list (saves memory)
xrange(100, 100000, 5)

# for loop (not the recommended style)
fruits = ['apple', 'banana', 'cherry']
for i in range(len(fruits)):
    print(fruits[i].upper())

# for loop (recommended style)
for fruit in fruits:
    print(fruit.upper())

# iterate through two things at once (using tuple unpacking)
family = {'dad':'homer', 'mom':'marge', 'size':6}
for key, value in family.items():
    print(key, value)

# use enumerate if you need to access the index value within the loop
for index, fruit in enumerate(fruits):
    print(index, fruit)

# for/else loop
for fruit in fruits:
    if fruit == 'banana':
        print('Found the banana!')
        break    # exit the loop and skip the 'else' block
else:
    # this block executes ONLY if the for loop completes without hitting 'break'
    print("Can't find the banana")

# while loop
count = 0
while count < 5:
    print('This will print 5 times')
    count += 1    # equivalent to 'count = count + 1'



### COMPREHENSIONS ###

# for loop to create a list of cubes
nums = [1, 2, 3, 4, 5]
cubes = []
for num in nums:
    cubes.append(num**3)

# equivalent list comprehension
cubes = [num**3 for num in nums]    # [1, 8, 27, 64, 125]

# for loop to create a list of cubes of even numbers
cubes_of_even = []
for num in nums:
    if num % 2 == 0:
        cubes_of_even.append(num**3)

# equivalent list comprehension
# syntax: [expression for variable in iterable if condition]
cubes_of_even = [num**3 for num in nums if num % 2 == 0]    # [8, 64]

# for loop to cube even numbers and square odd numbers
cubes_and_squares = []
for num in nums:
    if num % 2 == 0:
        cubes_and_squares.append(num**3)
    else:
        cubes_and_squares.append(num**2)

# equivalent list comprehension (using a ternary expression)
# syntax: [true_condition if condition else false_condition for variable in iterable]
cubes_and_squares = [num**3 if num % 2 == 0 else num**2 for num in nums]    # [1, 8, 9, 64, 25]

# for loop to flatten a 2d-matrix
matrix = [[1, 2], [3, 4]]
items = []
for row in matrix:
    for item in row:
        items.append(item)

# equivalent list comprehension
items = [item for row in matrix
              for item in row]      # [1, 2, 3, 4]

# set comprehension
fruits = ['apple', 'banana', 'cherry']
unique_lengths = {len(fruit) for fruit in fruits}   # {5, 6}

# dictionary comprehension
fruit_lengths = {fruit:len(fruit) for fruit in fruits}              # {'apple': 5, 'banana': 6, 'cherry': 6}
fruit_indices = {fruit:index for index, fruit in enumerate(fruits)} # {'apple': 0, 'banana': 1, 'cherry': 2}



### MAP AND FILTER ###

# 'map' applies a function to every element of a sequence
# ...and returns a list (Python 2) or iterator (Python 3)
simpsons = ['homer', 'marge', 'bart']
map(len, simpsons)                      # returns [5, 5, 4]
map(lambda word: word[-1], simpsons)    # returns ['r', 'e', 't']

# equivalent list comprehensions
[len(word) for word in simpsons]
[word[-1] for word in simpsons]

# 'filter' returns a list (Python 2) or iterator (Python 3) containing
# ...the elements from a sequence for which a condition is True
nums = range(5)
filter(lambda x: x % 2 == 0, nums)      # returns [0, 2, 4]

# equivalent list comprehension
[num for num in nums if num % 2 == 0]


```