Python 是一门高阶、动态类型的多范式编程语言；定义 Python 文件的时候我们往往会先声明文件编码方式:
# 指定脚本调用方式#!/usr/bin/env python# 配置 utf-8 编码# -*- Coding: utf-8 -*-# 配置其他编码# -*- Coding:-*-# Vim 中还可以使用如下方式# vim:fileenCoding=
人生苦短，请用 Python，大量功能强大的语法糖的同时让很多时候 Python 代码看上去有点像伪代码。譬如我们用 Python 实现的简易的快排相较于 Java 会显得很短小精悍:
def quicksort(arr): if len(arr) <= 1: return arr pivot = arr[len(arr) / 2] left = [x for x in arr if x < pivot] middle = [x for x in arr if x == pivot] right = [x for x in arr if x > pivot] return quicksort(left) + mIDdle + quicksort(right)print quicksort([3,6,8,10,1,2,1])# Prints "[1,3,10]"进群：548377875控制台交互
可以根据 __name__ 关键字来判断是否是直接使用 python 命令执行某个脚本，还是外部引用；Google 开源的 fire 也是不错的快速将某个类封装为命令行工具的框架：
import fireclass Calculator(object): """A simple calculator class.""" def double(self,number): return 2 * numberif __name__ == '__main__': fire.Fire(Calculator)# python calculator.py double 10 # 20# python calculator.py double --number=15 # 30Python 2 中 print 是表达式，而 Python 3 中 print 是函数；如果希望在 Python 2 中将 print 以函数方式使用，则需要自定义引入:
from __future__ import print_function我们也可以使用 pprint 来美化控制台输出内容：
import pprintstuff = ['spam','eggs','lumberjack','knights','ni']pprint.pprint(stuff)# 自定义参数pp = pprint.PrettyPrinter(depth=6)tup = ('spam',('eggs',('lumberjack',('knights',('ni',('dead',('parrot',('fresh fruit',))))))))pp.pprint(tup)模块
Python 中的模块（Module）即是 Python 源码文件，其可以导出类、函数与全局变量；当我们从某个模块导入变量时，函数名往往就是命名空间（namespace）。而 Python 中的包（Package）则是模块的文件夹，往往由 __init__.py 指明某个文件夹为包:
# 文件目录someDir/ main.py siblingModule.py# siblingModule.pydef siblingModuleFun(): print('Hello from siblingModuleFun')def siblingModuleFunTwo(): print('Hello from siblingModuleFunTwo')import siblingModuleimport siblingModule as sibModsibMod.siblingModuleFun()from siblingModule import siblingModuleFunsiblingModuleFun()try: # import 'someModuleA' that is only available in windows import someModuleAexcept importError: try: # import 'someModuleB' that is only available in linux import someModuleB except importError:Package 可以为某个目录下所有的文件设置统一入口:
someDir/ main.py subModules/ __init__.py subA.py subSubModules/ __init__.py subSubA.py# subA.pydef subAFun(): print('Hello from subAFun')def subAFunTwo(): print('Hello from subAFunTwo')# subSubA.pydef subSubAFun(): print('Hello from subSubAFun')def subSubAFunTwo(): print('Hello from subSubAFunTwo')# __init__.py from subDir# Adds 'subAFun()' and 'subAFunTwo()' to the 'subDir' namespace from .subA import *# The following two import statement do the same thing,they add 'subSubAFun()' and 'subSubAFunTwo()' to the 'subDir' namespace. The first one assumes '__init__.py' is empty in 'subSubDir',and the second one,assumes '__init__.py' in 'subSubDir' contains 'from .subSubA import *'.# Assumes '__init__.py' is empty in 'subSubDir'# Adds 'subSubAFun()' and 'subSubAFunTwo()' to the 'subDir' namespacefrom .subSubDir.subSubA import *# Assumes '__init__.py' in 'subSubDir' has 'from .subSubA import *'# Adds 'subSubAFun()' and 'subSubAFunTwo()' to the 'subDir' namespacefrom .subSubDir import *# __init__.py from subSubDir# Adds 'subSubAFun()' and 'subSubAFunTwo()' to the 'subSubDir' namespacefrom .subSubA import *# main.pyimport subDirsubDir.subAFun() # Hello from subAFunsubDir.subAFunTwo() # Hello from subAFunTwosubDir.subSubAFun() # Hello from subSubAFunsubDir.subSubAFunTwo() # Hello from subSubAFunTwo表达式与控制流条件选择
Python 中使用 if、elif、else 来进行基础的条件选择 *** 作：
if x < 0: x = 0 print('Negative changed to zero') elif x == 0: print('Zero') else: print('More')Python 同样支持 ternary conditional operator:
a if condition else b也可以使用 Tuple 来实现类似的效果：
# test 需要返回 True 或者 False(falseValue,trueValue)[test]# 更安全的做法是进行强制判断(falseValue,trueValue)[test == True]# 或者使用 bool 类型转换函数(falseValue,trueValue)[bool()] 进行强制判断(falseValue,trueValue)[test == True]# 或者使用 bool 类型转换函数(falseValue,trueValue)[bool(
)] 循环遍历
for-in 可以用来遍历数组与字典：
words = ['cat','window','defenestrate']for w in words: print(w,len(w))# 使用数组访问 *** 作符，能够迅速地生成数组的副本for w in words[:]: if len(w) > 6: words.insert(0,w)# words -> ['defenestrate','cat','defenestrate']如果我们希望使用数字序列进行遍历，可以使用 Python 内置的 range 函数：
a = ['Mary','had','a','little','lamb']for i in range(len(a)): print(i,a[i])基本数据类型可以使用内建函数进行强制类型转换（Casting）:
int(str)float(str)str(int)str(float)Number: 数值类型
x = 3print type(x) # Prints ""print x # Prints "3"print x + 1 # Addition; prints "4"print x - 1 # Subtraction; prints "2"print x * 2 # Multiplication; prints "6"print x ** 2 # Exponentiation; prints "9"x += 1print x # Prints "4"x *= 2print x # Prints "8"y = 2.5print type(y) # Prints " "print y,y + 1,y * 2,y ** 2 # Prints "2.5 3.5 5.0 6.25" 布尔类型
Python 提供了常见的逻辑 *** 作符，不过需要注意的是 Python 中并没有使用 &&、|| 等，而是直接使用了英文单词。
t = Truef = Falseprint type(t) # Prints ""print t and f # Logical AND; prints "False"print t or f # Logical OR; prints "True"print not t # Logical NOT; prints "False"print t != f # Logical XOR; prints "True" String: 字符串
Python 2 中支持 Ascii 码的 str() 类型，独立的 unicode() 类型，没有 byte 类型；而 Python 3 中默认的字符串为 utf-8 类型，并且包含了 byte 与 bytearray 两个字节类型：
type("GuIDo") # string type is str in python2## 使用 __future__ 中提供的模块来降级使用 Unicodefrom __future__ import unicode_literalstype("GuIDo") # string type become unicode# Python 字符串支持分片、模板字符串等常见 *** 作:
var1 = 'Hello World!'var2 = "Python Programming"print "var1[0]: ",var1[0]print "var2[1:5]: ",var2[1:5]# var1[0]: H# var2[1:5]: ythoprint "My name is %s and weight is %d kg!" % ('Zara',21)# My name is Zara and weight is 21 kg!str[0:4]len(str)string.replace("-"," ")",".join(List)"hi {0}".format('j')str.find(",")str.index(",") # same,but raises IndexErrorstr.count(",")str.split(",")str.lower()str.upper()str.Title()str.lstrip()str.rstrip()str.strip()str.islower()# 移除所有的特殊字符re.sub('[^A-Za-z0-9]+','',mystring)如果需要判断是否包含某个子字符串，或者搜索某个字符串的下标:
# in *** 作符可以判断字符串if "blah" not in somestring: continue# find 可以搜索下标s = "This be a string"if s.find("is") == -1: print "No 'is' here!"else: print "Found 'is' in the string."Regex: 正则表达式
import re# 判断是否匹配re.match(r'^[aeIoU]',str)# 以第二个参数指定的字符替换原字符串中内容re.sub(r'^[aeIoU]','?',str)re.sub(r'(xyz)',r'',str)# 编译生成独立的正则表达式对象expr = re.compile(r'^...$')expr.match(...)expr.sub(...)下面列举了常见的表达式使用场景:
# 检测是否为 HTML 标签re.search('<[^/>][^>]*>',' 集合类型List: 列表
Operation: 创建增删
list 是基础的序列类型：
l = []l = list()# 使用字符串的 split 方法，可以将字符串转化为列表str.split(".")# 如果需要将数组拼装为字符串，则可以使用 join list1 = ['1','2','3']str1 = ''.join(list1)# 如果是数值数组，则需要先进行转换list1 = [1,3]str1 = ''.join(str(e) for e in list1)可以使用 append 与 extend 向数组中插入元素或者进行数组连接
x = [1,3]x.append([4,5]) # [1,[4,5]]x.extend([4,4,5]，注意 extend 返回值为 None可以使用 pop、slices、del、remove 等移除列表中元素：
myList = [10,20,30,40,50]# d出第二个元素myList.pop(1) # 20# myList: myList.pop(1)# 如果不加任何参数，则默认d出最后一个元素myList.pop()# 使用 slices 来删除某个元素a = [ 1,5,6 ]index = 3 # Only Positive indexa = a[:index] + a[index+1 :]# 根据下标删除元素myList = [10,50]rmovIndxNo = 3del myList[rmovIndxNo] # myList: [10,50]# 使用 remove 方法，直接根据元素删除letters = ["a","b","c","d","e"]numbers.remove(numbers[1])print(*letters) # used a * to make it unpack you don't have toIteration: 索引遍历
你可以使用基本的 for 循环来遍历数组中的元素，就像下面介个样纸:
animals = ['cat','dog','monkey']for animal in animals: print animal# Prints "cat","dog","monkey",each on its own line.如果你在循环的同时也希望能够获取到当前元素下标，可以使用 enumerate 函数:
animals = ['cat','monkey']for idx,animal in enumerate(animals): print '#%d: %s' % (idx + 1,animal)# Prints "#1: cat","#2: dog","#3: monkey",each on its own linePython 也支持切片（Slices）
:
nums = range(5) # range is a built-in function that creates a list of integersprint nums # Prints "[0,4]"print nums[2:4] # Get a slice from index 2 to 4 (exclusive); prints "[2,3]"print nums[2:] # Get a slice from index 2 to the end; prints "[2,4]"print nums[:2] # Get a slice from the start to index 2 (exclusive); prints "[0,1]"print nums[:] # Get a slice of the whole list; prints ["0,4]"print nums[:-1] # Slice indices can be negative; prints ["0,3]"nums[2:4] = [8,9] # Assign a new sublist to a sliceprint nums # Prints "[0,9,4]"Comprehensions: 变换
Python 中同样可以使用 map、reduce、filter，map 用于变换数组:
# 使用 map 对数组中的每个元素计算平方items = [1,5]squared = list(map(lambda x: x**2,items))# map 支持函数以数组方式连接使用def multiply(x): return (x*x)def add(x): return (x+x)funcs = [multiply,add]for i in range(5): value = list(map(lambda x: x(i),funcs)) print(value)reduce 用于进行归纳计算:
# reduce 将数组中的值进行归纳from functools import reduceproduct = reduce((lambda x,y: x * y),[1,4])# Output: 24filter 则可以对数组进行过滤:
number_list = range(-5,5)less_than_zero = list(filter(lambda x: x < 0,number_list))print(less_than_zero)# Output: [-5,-4,-3,-2,-1]字典类型
创建增删
d = {'cat': 'cute','dog': 'furry'} # 创建新的字典print d['cat'] # 字典不支持点（Dot）运算符取值如果需要合并两个或者多个字典类型：
# python 3.5z = {**x,**y}# python 2.7def merge_dicts(*dict_args): """ Given any number of dicts,shallow copy and merge into a new dict,precedence goes to key value pairs in latter dicts. """ result = {} for dictionary in dict_args: result.update(dictionary) return result索引遍历
可以根据键来直接进行元素访问:
# Python 中对于访问不存在的键会抛出 KeyError 异常，需要先行判断或者使用 getprint 'cat' in d # Check if a dictionary has a given key; prints "True"# 如果直接使用 [] 来取值，需要先确定键的存在，否则会抛出异常print d['monkey'] # KeyError: 'monkey' not a key of d# 使用 get 函数则可以设置默认值print d.get('monkey','N/A') # Get an element with a default; prints "N/A"print d.get('fish','N/A') # Get an element with a default; prints "wet"d.keys() # 使用 keys 方法可以获取所有的键可以使用 for-in 来遍历数组:
# 遍历键for key in d:# 比前一种方式慢for k in dict.keys(): ...# 直接遍历值for value in dict.itervalues(): ...# Python 2.x 中遍历键值for key,value in d.iteritems():# Python 3.x 中遍历键值for key,value in d.items():其他序列类型
集合
# Same as {"a","c"}normal_set = set(["a","c"])# Adding an element to normal set is finenormal_set.add("d")print("Normal Set")print(normal_set)# A frozen setfrozen_set = frozenset(["e","f","g"])print("Frozen Set")print(frozen_set)# Uncommenting below line would cause error as# we are trying to add element to a frozen set# frozen_set.add("h")函数函数定义
Python 中的函数使用 def 关键字进行定义，譬如:
def sign(x): if x > 0: return 'positive' elif x < 0: return 'negative' else: return 'zero'for x in [-1,1]: print sign(x)# Prints "negative","zero","positive"Python 支持运行时创建动态函数，也即是所谓的 lambda 函数：
def f(x): return x**2# 等价于g = lambda x: x**2参数
Option Arguments: 不定参数
def example(a,b=None,*args,**kwargs): print a,b print args print kwargsexample(1,"var",word="hello")# 1 var# (2,3)# {'word': 'hello'}a_tuple = (1,5)a_dict = {"1":1,"2":2,"3":3}example(1,*a_tuple,**a_dict)# 1 var# (1,5)# {'1': 1,'2': 2,'3': 3}生成器
def simple_generator_function(): yield 1 yield 2 yield 3for value in simple_generator_function(): print(value)# 输出结果# 1# 2# 3our_generator = simple_generator_function()next(our_generator)# 1next(our_generator)# 2next(our_generator)#3# 生成器典型的使用场景譬如无限数组的迭代def get_primes(number): while True: if is_prime(number): yield number number += 1装饰器
装饰器是非常有用的设计模式:
# 简单装饰器from functools import wrapsdef decorator(func): @wraps(func) def wrapper(*args,**kwargs): print('wrap function') return func(*args,**kwargs) return wrapper@decoratordef example(*a,**kw): passexample.__name__ # attr of function preserve# 'example'# Decorator # 带输入值的装饰器from functools import wrapsdef decorator_with_argument(val): def decorator(func): @wraps(func) def wrapper(*args,**kwargs): print "Val is {0}".format(val) return func(*args,**kwargs) return wrapper return decorator@decorator_with_argument(10)def example(): print "This is example function."example()# Val is 10# This is example function.# 等价于def example(): print "This is example function."example = decorator_with_argument(10)(example)example()# Val is 10# This is example function.类与对象类定义
Python 中对于类的定义也很直接:
class Greeter(object): # Constructor def __init__(self,name): self.name = name # Create an instance variable # Instance method def greet(self,loud=False): if loud: print 'HELLO,%s!' % self.name.upper() else: print 'Hello,%s' % self.nameg = Greeter('Fred') # Construct an instance of the Greeter classg.greet() # Call an instance method; prints "Hello,Fred"g.greet(loud=True) # Call an instance method; prints "HELLO,FRED!"# isinstance 方法用于判断某个对象是否源自某个类ex = 10isinstance(ex,int)Managed Attributes: 受控属性
# property、setter、deleter 可以用于复写点方法class Example(object): def __init__(self,value): self._val = value @property def val(self): return self._val @val.setter def val(self,value): if not isintance(value,int): raise TypeError("Expected int") self._val = value @val.deleter def val(self): del self._val @property def square3(self): return 2**3ex = Example(123)ex.val = "str"# Traceback (most recent call last):# File "",line 1,in# File "test.py",line 12,in val# raise TypeError("Expected int")# TypeError: Expected int类方法与静态方法
class example(object): @classmethod def clsmethod(cls): print "I am classmethod" @staticmethod def stmethod(): print "I am staticmethod" def instmethod(self): print "I am instancemethod"ex = example()ex.clsmethod()# I am classmethodex.stmethod()# I am staticmethodex.instmethod()# I am instancemethodexample.clsmethod()# I am classmethodexample.stmethod()# I am staticmethodexample.instmethod()# Traceback (most recent call last):# File "",in# TypeError: unbound method instmethod() ...对象
实例化
属性 *** 作
Python 中对象的属性不同于字典键，可以使用点运算符取值，直接使用 in 判断会存在问题:
class A(object): @property def prop(self): return 3a = A()print "'prop' in a.__dict__ =",'prop' in a.__dict__print "hasattr(a,'prop') =",hasattr(a,'prop')print "a.prop =",a.prop# 'prop' in a.__dict__ = False# hasattr(a,'prop') = True# a.prop = 3建议使用 hasattr、getattr、setattr 这种方式对于对象属性进行 *** 作:
class Example(object): def __init__(self): self.name = "ex" def printex(self): print "This is an example"# Check object has attributes# hasattr(obj,'attr')ex = Example()hasattr(ex,"name")# Truehasattr(ex,"printex")# Truehasattr(ex,"print")# False# Get object attribute# getattr(obj,'attr')getattr(ex,'name')# 'ex'# Set object attribute# setattr(obj,'attr',value)setattr(ex,'name','example')ex.name# 'example''
异常与测试异常处理
Context Manager - with
with 常用于打开或者关闭某些资源:
host = 'localhost'port = 5566with Socket(host,port) as s: while True: conn,addr = s.accept() msg = conn.recv(1024) print msg conn.send(msg) conn.close()单元测试
from __future__ import print_functionimport unittestdef fib(n): return 1 if n<=2 else fib(n-1)+fib(n-2)def setUpModule(): print("setup module")def tearDownModule(): print("teardown module")class TestFib(unittest.TestCase): def setUp(self): print("setUp") self.n = 10 def tearDown(self): print("tearDown") del self.n @classmethod def setUpClass(cls): print("setUpClass") @classmethod def tearDownClass(cls): print("tearDownClass") def test_fib_assert_equal(self): self.assertEqual(fib(self.n),55) def test_fib_assert_true(self): self.assertTrue(fib(self.n) == 55)if __name__ == "__main__": unittest.main()存储文件读写
路径处理
Python 内置的 __file__ 关键字会指向当前文件的相对路径，可以根据它来构造绝对路径，或者索引其他文件:
# 获取当前文件的相对目录dir = os.path.dirname(__file__) # srcapp## once you're at the directory level you want,with the desired directory as the final path node:dirname1 = os.path.basename(dir) dirname2 = os.path.split(dir)[1] ## if you look at the documentation,this is exactly what os.path.basename does.# 获取当前代码文件的绝对路径，abspath 会自动根据相对路径与当前工作空间进行路径补全os.path.abspath(os.path.dirname(__file__)) # D:WorkSpaceOWS ool\ui-tool-svnpythonsrcapp# 获取当前文件的真实路径os.path.dirname(os.path.realpath(__file__)) # D:WorkSpaceOWS ool\ui-tool-svnpythonsrcapp# 获取当前执行路径os.getcwd()可以使用 listdir、walk、glob 模块来进行文件枚举与检索：
# 仅列举所有的文件from os import listdirfrom os.path import isfile,joinonlyfiles = [f for f in listdir(mypath) if isfile(join(mypath,f))]# 使用 walk 递归搜索from os import walkf = []for (dirpath,dirnames,filenames) in walk(mypath): f.extend(filenames) break# 使用 glob 进行复杂模式匹配import globprint(glob.glob("/home/adam/*.txt"))# ['/home/adam/file1.txt','/home/adam/file2.txt',.... ]简单文件读写
# 可以根据文件是否存在选择写入模式mode = 'a' if os.path.exists(writepath) else 'w'# 使用 with 方法能够自动处理异常with open("file.dat",mode) as f: f.write(...) ... # *** 作完毕之后记得关闭文件 f.close()# 读取文件内容message = f.read()复杂格式文件
JSON
import json# Writing JSON datawith open('data.json','w') as f: json.dump(data,f)# Reading data backwith open('data.json','r') as f: data = json.load(f)XML
我们可以使用 lxml 来解析与处理 XML 文件，本部分即对其常用 *** 作进行介绍。lxml 支持从字符串或者文件中创建 Element 对象：
from lxml import etree# 可以从字符串开始构造xml = ''root = etree.fromstring(xml)etree.tostring(root)# b''# 也可以从某个文件开始构造tree = etree.parse("doc/test.xml")# 或者指定某个 baseURLroot = etree.fromstring(xml,base_url="http://where.it/is/from.xml")其提供了迭代器以对所有元素进行遍历：
# 遍历所有的节点for tag in tree.iter(): if not len(tag): print tag.keys() # 获取所有自定义属性 print (tag.tag,tag.text) # text 即文本子元素值# 获取 XPathfor e in root.iter(): print tree.getpath(e)lxml 支持以 XPath 查找元素，不过需要注意的是，XPath 查找的结果是数组，并且在包含命名空间的情况下，需要指定命名空间：
root.xpath('//page/text/text()',ns={prefix:url})# 可以使用 getparent 递归查找父元素el.getparent()lxml 提供了 insert、append 等方法进行元素 *** 作：
# append 方法默认追加到尾部st = etree.Element("state",name="New Mexico")co = etree.Element("county",name="Socorro")st.append(co)# insert 方法可以指定位置node.insert(0,newKID)Excel
可以使用 [xlrd]() 来读取 Excel 文件，使用 xlsxwriter 来写入与 *** 作 Excel 文件。
# 读取某个 Cell 的原始值sh.cell(rx,col).value# 创建新的文件workbook = xlsxwriter.Workbook(outputfile)worksheet = workbook.add_worksheet()# 设置从第 0 行开始写入row = 0# 遍历二维数组，并且将其写入到 Excel 中for rowData in array: for col,data in enumerate(rowData): worksheet.write(row,col,data) row = row + 1workbook.close()文件系统
对于高级的文件 *** 作，我们可以使用 Python 内置的 shutil
# 递归删除 appname 下面的所有的文件夹shutil.rmtree(appname)网络交互Requests
Requests 是优雅而易用的 Python 网络请求库:
import requestsr = requests.get('https://API.github.com/events')r = requests.get('https://API.github.com/user',auth=('user','pass'))r.status_code# 200r.headers['content-type']# 'application/Json; charset=utf8'r.enCoding# 'utf-8'r.text# u'{"type":"User"...'r.Json()# {u'private_gists': 419,u'total_private_repos': 77,...}r = requests.put('http://httpbin.org/put',data = {'key':'value'})r = requests.delete('http://httpbin.org/delete')r = requests.head('http://httpbin.org/get')r = requests.options('http://httpbin.org/get')数据存储MysqL
import pyMysqL.cursors# Connect to the databaseconnection = pyMysqL.connect(host='localhost',user='user',password='passwd',db='db',charset='utf8mb4',cursorclass=pyMysqL.cursors.DictCursor)try: with connection.cursor() as cursor: # Create a new record sql = "INSERT INTO `users` (`email`,`password`) VALUES (%s,%s)" cursor.execute(sql,('[email protected]','very-secret')) # connection is not autocommit by default. So you must commit to save # your changes. connection.commit() with connection.cursor() as cursor: # Read a single record sql = "SELECT `ID`,`password` FROM `users` WHERE `email`=%s" cursor.execute(sql,)) result = cursor.fetchone() print(result)finally: connection.close()总结以上是内存溢出为你收集整理的这是我见过最完整的Python语法和实战清单！是个人都能看懂学会！全部内容，希望文章能够帮你解决这是我见过最完整的Python语法和实战清单！是个人都能看懂学会！所遇到的程序开发问题。
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