Python Basics Tutorial: Data Types, Variables, Control Flow, Functions, Classes, Modules and Advanced Features

Python was designed by Guido van Rossum in the early 1990s and is now one of the most widely used programming languages. Its syntax is concise and readable, often resembling executable pseudocode.

Note: This tutorial is based on Python 3. Source code can be downloaded from https://learnxinyminutes.com/docs/files/learnpython3-cn.py .

1. Primitive Data Types and Operators

#用井字符开头的是单行注释

""" 多行字符串用三个引号
    包裹，也常被用来做多
    行注释
"""
# 整数
3  # => 3

# 算术没有什么出乎意料的
1 + 1  # => 2
8 - 1  # => 7
10 * 2  # => 20

# 但是除法例外，会自动转换成浮点数
35 / 5  # => 7.0
5 / 3  # => 1.6666666666666667

# 整数除法的结果都是向下取整
5 // 3      # => 1
5.0 // 3.0  # => 1.0 # 浮点数也可以
-5 // 3  # => -2
-5.0 // 3.0  # => -2.0

# 浮点数的运算结果也是浮点数
3 * 2.0  # => 6.0

# 模除
7 % 3  # => 1

# x的y次方
2**4  # => 16

# 用括号决定优先级
(1 + 3) * 2  # => 8

# 布尔值
True
False

# 用not取非
not True  # => False
not False  # => True

# 逻辑运算符，注意and和or都是小写
True and False  # => False
False or True  # => True

# 整数也可以当作布尔值
0 and 2  # => 0
-5 or 0  # => -5
0 == False  # => True
2 == True  # => False
1 == True  # => True

# 用==判断相等
1 == 1  # => True
2 == 1  # => False

# 用!=判断不等
1 != 1  # => False
2 != 1  # => True

# 比较大小
1 < 10  # => True
1 > 10  # => False
2 <= 2  # => True
2 >= 2  # => True

# 大小比较可以连起来！
1 < 2 < 3  # => True
2 < 3 < 2  # => False

# 字符串用单引双引都可以
"这是个字符串"
'这也是个字符串'

# 用加号连接字符串
"Hello " + "world!"  # => "Hello world!"

# 字符串可以被当作字符列表
"This is a string"[0]  # => 'T'

# 用.format来格式化字符串
"{} can be {}".format("strings", "interpolated")
"{0} be nimble, {0} be quick, {0} jump over the {1}".format("Jack", "candle stick")  # => "Jack be nimble, Jack be quick, Jack jump over the candle stick"

# 如果不想数参数，可以用关键字
"{name} wants to eat {food}".format(name="Bob", food="lasagna")  # => "Bob wants to eat lasagna"

# 老式的格式化语法（兼容 Python 2.5 以下）
"%s can be %s the %s way" % ("strings", "interpolated", "old")

# None是一个对象
None  # => None
"etc" is None  # => False
None is None  # => True

# None，0，空字符串，空列表，空字典都算是False
bool(0)  # => False
bool("")  # => False
bool([])  # => False
bool({})  # => False

2. Variables and Collections

# print是内置的打印函数
print("I'm Python. Nice to meet you!")

# 在给变量赋值前不用提前声明
# 传统的变量命名是小写，用下划线分隔单词
some_var = 5
some_var  # => 5

# 访问未赋值的变量会抛出异常
some_unknown_var  # 抛出NameError

# 用列表(list)储存序列
li = []
# 创建列表时也可以同时赋给元素
other_li = [4, 5, 6]

# 用append在列表最后追加元素
li.append(1)    # li现在是[1]
li.append(2)    # li现在是[1, 2]
li.append(4)    # li现在是[1, 2, 4]
li.append(3)    # li现在是[1, 2, 4, 3]

# 用pop从列表尾部删除
li.pop()        # => 3  且li现在是[1, 2, 4]
# 把3再放回去
li.append(3)    # li变回[1, 2, 4, 3]

# 列表存取跟数组一样
li[0]  # => 1
# 取出最后一个元素
li[-1]  # => 3

# 越界存取会造成IndexError
li[4]  # 抛出IndexError

# 列表有切割语法
li[1:3]  # => [2, 4]
li[2:]   # => [4, 3]
li[:3]   # => [1, 2, 4]
li[::2]  # =>[1, 4]
li[::-1] # => [3, 4, 2, 1]

# 用del删除任何一个元素
del li[2]   # li is now [1, 2, 3]

# 列表可以相加（不改变原列表）
li + other_li   # => [1, 2, 3, 4, 5, 6]

# 用extend拼接列表
li.extend(other_li)   # li现在是[1, 2, 3, 4, 5, 6]

# 用in测试列表是否包含值
1 in li   # => True

# 用len取列表长度
len(li)   # => 6

# 元组是不可改变的序列
tup = (1, 2, 3)
tup[0]   # => 1
# tup[0] = 3  # 抛出TypeError

# 元组大多数操作与列表相同
len(tup)   # => 3
tup + (4, 5, 6)   # => (1, 2, 3, 4, 5, 6)
tup[:2]   # => (1, 2)
2 in tup   # => True

# 把元组合列表解包，赋值给变量
a, b, c = (1, 2, 3)      # 现在a是1，b是2，c是3
d, e, f = 4, 5, 6
# 交换两个变量的值
e, d = d, e      # 现在d是5，e是4

# 用字典表达映射关系
empty_dict = {}
filled_dict = {"one": 1, "two": 2, "three": 3}
filled_dict["one"]   # => 1
list(filled_dict.keys())   # => ["three", "two", "one"] (order not guaranteed)
list(filled_dict.values()) # => [3, 2, 1]
"one" in filled_dict   # => True
1 in filled_dict   # => False
# 访问不存在的键会导致KeyError
filled_dict["four"]   # KeyError
# 用get来避免KeyError
filled_dict.get("one")   # => 1
filled_dict.get("four")   # => None
filled_dict.get("one", 4)   # => 1
filled_dict.get("four", 4)   # => 4
# setdefault方法只有当键不存在的时候插入新值
filled_dict.setdefault("five", 5)  # filled_dict["five"]设为5
filled_dict.setdefault("five", 6)  # filled_dict["five"]还是5
# 字典赋值
filled_dict.update({"four":4})  # => {"one": 1, "two": 2, "three": 3, "four": 4}
filled_dict["four"] = 4  # 另一种赋值方法
# 用del删除键
del filled_dict["one"]  # 从filled_dict中把one删除

# 用set表达集合
empty_set = set()
some_set = {1, 1, 2, 2, 3, 4}   # some_set现在是{1, 2, 3, 4}
filled_set = some_set
filled_set.add(5)   # filled_set现在是{1, 2, 3, 4, 5}
other_set = {3, 4, 5, 6}
filled_set & other_set   # => {3, 4, 5}
filled_set | other_set   # => {1, 2, 3, 4, 5, 6}
{1, 2, 3, 4} - {2, 3, 5}   # => {1, 4}
2 in filled_set   # => True
10 in filled_set   # => False

3. Control Flow and Iterators

# 先随便定义一个变量
some_var = 5

# 这是个if语句。注意缩进在Python里是有意义的
# 印出"some_var比10小"
if some_var > 10:
    print("some_var比10大")
elif some_var < 10:    # elif句是可选的
    print("some_var比10小")
else:                  # else也是可选的
    print("some_var就是10")

"""
用for循环语句遍历列表
打印:
    dog is a mammal
    cat is a mammal
    mouse is a mammal
"""
for animal in ["dog", "cat", "mouse"]:
    print("{} is a mammal".format(animal))

"""
"range(number)"返回数字列表从0到给的数字
打印:
    0
    1
    2
    3
"""
for i in range(4):
    print(i)

"""
while循环直到条件不满足
打印:
    0
    1
    2
    3
"""
x = 0
while x < 4:
    print(x)
    x += 1  # x = x + 1 的简写

# 用try/except块处理异常状况
try:
    # 用raise抛出异常
    raise IndexError("This is an index error")
except IndexError as e:
    pass    # pass是无操作，但是应该在这里处理错误
except (TypeError, NameError):
    pass    # 可以同时处理不同类的错误
else:
    # else语句是可选的，必须在所有的except之后
    print("All good!")   # 只有当try运行完没有错误的时候这句才会运行

# Python提供一个叫做可迭代(iterable)的基本抽象。一个可迭代对象是可以被当作序列的对象。比如说上面range返回的对象就是可迭代的。
filled_dict = {"one": 1, "two": 2, "three": 3}
our_iterable = filled_dict.keys()
print(our_iterable)  # => dict_keys(['one', 'two', 'three'])，是一个实现可迭代接口的对象

# 可迭代对象可以遍历
for i in our_iterable:
    print(i)    # 打印 one, two, three

# 但是不可以随机访问
our_iterable[1]  # 抛出TypeError

# 可迭代对象知道怎么生成迭代器
our_iterator = iter(our_iterable)

# 迭代器是一个可以记住遍历的位置的对象
# 用__next__可以取得下一个元素
our_iterator.__next__()  # => "one"
# 再一次调取__next__时会记得位置
our_iterator.__next__()  # => "two"
our_iterator.__next__()  # => "three"
# 当迭代器所有元素都取出后，会抛出StopIteration
our_iterator.__next__() # 抛出StopIteration

# 可以用list一次取出迭代器所有的元素
list(filled_dict.keys())  # => Returns ["one", "two", "three"]

4. Functions

# 用def定义新函数
def add(x, y):
    print("x is {} and y is {}".format(x, y))
    return x + y    # 用return语句返回

# 调用函数
add(5, 6)   # => 印出"x is 5 and y is 6"并且返回11

# 也可以用关键字参数来调用函数
add(y=6, x=5)   # 关键字参数可以用任何顺序

# 我们可以定义一个可变参数函数
def varargs(*args):
    return args

varargs(1, 2, 3)   # => (1, 2, 3)

# 我们也可以定义一个关键字可变参数函数
def keyword_args(**kwargs):
    return kwargs

keyword_args(big="foot", loch="ness")   # => {"big": "foot", "loch": "ness"}

# 这两种可变参数可以混着用
def all_the_args(*args, **kwargs):
    print(args)
    print(kwargs)
"""
all_the_args(1, 2, a=3, b=4) prints:
    (1, 2)
    {"a": 3, "b": 4}
"""
args = (1, 2, 3, 4)
kwargs = {"a": 3, "b": 4}
all_the_args(*args)   # 相当于 foo(1, 2, 3, 4)
all_the_args(**kwargs)   # 相当于 foo(a=3, b=4)
all_the_args(*args, **kwargs)   # 相当于 foo(1, 2, 3, 4, a=3, b=4)

# 函数作用域
x = 5

def setX(num):
    # 局部作用域的x和全局域的x是不同的
    x = num  # => 43
    print(x)  # => 43

def setGlobalX(num):
    global x
    print(x)  # => 5
    x = num  # 现在全局域的x被赋值
    print(x)  # => 6

setX(43)
setGlobalX(6)

# 函数在Python是一等公民
def create_adder(x):
    def adder(y):
        return x + y
    return adder

add_10 = create_adder(10)
add_10(3)   # => 13

# 匿名函数
(lambda x: x > 2)(3)   # => True

# 内置的高阶函数
map(add_10, [1, 2, 3])   # => [11, 12, 13]
filter(lambda x: x > 5, [3, 4, 5, 6, 7])   # => [6, 7]

# 列表推导式可以简化映射和过滤。列表推导式的返回值是另一个列表。
[add_10(i) for i in [1, 2, 3]]  # => [11, 12, 13]
[x for x in [3, 4, 5, 6, 7] if x > 5]   # => [6, 7]

5. Classes

# 定义一个继承object的类
class Human(object):
    # 类属性，被所有此类的实例共用。
    species = "H. sapiens"

    # 构造方法，当实例被初始化时被调用。
    def __init__(self, name):
        # Assign the argument to the instance's name attribute
        self.name = name

    # 实例方法，第一个参数总是self，就是这个实例对象
    def say(self, msg):
        return "{name}: {message}".format(name=self.name, message=msg)

    # 类方法，被所有此类的实例共用。第一个参数是这个类对象。
    @classmethod
    def get_species(cls):
        return cls.species

    # 静态方法。调用时没有实例或类的绑定。
    @staticmethod
    def grunt():
        return "*grunt*"

# 构造一个实例
i = Human(name="Ian")
print(i.say("hi"))      # 印出 "Ian: hi"

j = Human("Joel")
print(j.say("hello"))  # 印出 "Joel: hello"

# 调用一个类方法
i.get_species()   # => "H. sapiens"

# 改一个共用的类属性
Human.species = "H. neanderthalensis"
i.get_species()   # => "H. neanderthalensis"
j.get_species()   # => "H. neanderthalensis"

# 调用静态方法
Human.grunt()   # => "*grunt*"

6. Modules

# 用import导入模块
import math
print(math.sqrt(16))  # => 4.0

# 也可以从模块中导入个别值
from math import ceil, floor
print(ceil(3.7))  # => 4.0
print(floor(3.7))   # => 3.0

# 可以导入一个模块中所有值（不建议）
from math import *

# 如此缩写模块名字
import math as m
math.sqrt(16) == m.sqrt(16)   # => True

# Python模块其实就是普通的Python文件。你可以自己写，然后导入，模块的名字就是文件的名字。
import math
dir(math)

7. Advanced Usage

# 用生成器(generators)方便地写惰性运算
def double_numbers(iterable):
    for i in iterable:
        yield i + i

# range的返回值也是一个生成器，不然一个1到900000000的列表会花很多时间和内存。
range_ = range(1, 900000000)
# 当找到一个 >=30 的结果就会停，这意味着 double_numbers 不会生成大于30的数。
for i in double_numbers(range_):
    print(i)
    if i >= 30:
        break

# 装饰器(decorators)
# 这个例子中，beg装饰say
# beg会先调用say。如果返回的say_please为真，beg会改变返回的字符串。
from functools import wraps

def beg(target_function):
    @wraps(target_function)
    def wrapper(*args, **kwargs):
        msg, say_please = target_function(*args, **kwargs)
        if say_please:
            return "{} {}".format(msg, "Please! I am poor :(")
        return msg
    return wrapper

@beg
def say(say_please=False):
    msg = "Can you buy me a beer?"
    return msg, say_please

print(say())  # Can you buy me a beer?
print(say(say_please=True))  # Can you buy me a beer? Please! I am poor :(