本文是对于 现代 Python 开发：语法基础与工程实践的总结，更多 Python 相关资料参考 Python 学习与实践资料索引；本文参考了 Python Crash Course – Cheat Sheets，pysheeet 等。本文仅包含笔者在日常工作中经常使用的，并且认为较为关键的知识点与语法，如果想要进一步学习 Python 相关内容或者对于机器学习与数据挖掘方向感兴趣，可以参考程序猿的数据科学与机器学习实战手册。
基础语法
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: <encoding-name> -*- # Vim 中还可以使用如下方式 # vim:fileencoding=<encoding-name>
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, 1, 2, 3, 6, 8, 10]"
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 fire
class Calculator(object):
"""A simple calculator class."""
def double(self, number):
return 2 * number
if __name__ == '__main__':
fire.Fire(Calculator)
# python calculator.py double 10 # 20
# python calculator.py double --number=15 # 30
Python 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 pprint
stuff = ['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.py
def siblingModuleFun():
print('Hello from siblingModuleFun')
def siblingModuleFunTwo():
print('Hello from siblingModuleFunTwo')
import siblingModule
import siblingModule as sibMod
sibMod.siblingModuleFun()
from siblingModule import siblingModuleFun
siblingModuleFun()
try:
# Import 'someModuleA' that is only available in Windows
import someModuleA
except 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.py
def subAFun():
print('Hello from subAFun')
def subAFunTwo():
print('Hello from subAFunTwo')
# subSubA.py
def 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' namespace
from .subSubDir.subSubA import *
# Assumes '__init__.py' in 'subSubDir' has 'from .subSubA import *'
# Adds 'subSubAFun()' and 'subSubAFunTwo()' to the 'subDir' namespace
from .subSubDir import *
# __init__.py from subSubDir
# Adds 'subSubAFun()' and 'subSubAFunTwo()' to the 'subSubDir' namespace
from .subSubA import *
# main.py
import subDir
subDir.subAFun() # Hello from subAFun
subDir.subAFunTwo() # Hello from subAFunTwo
subDir.subSubAFun() # Hello from subSubAFun
subDir.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操作：
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(<expression>)]
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))
# 使用数组访问操作符，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', 'window', '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 = 3 print type(x) # Prints "<type 'int'>" 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 += 1 print x # Prints "4" x *= 2 print x # Prints "8" y = 2.5 print type(y) # Prints "<type 'float'>" print y, y + 1, y * 2, y ** 2 # Prints "2.5 3.5 5.0 6.25"
布尔类型
Python 提供了常见的逻辑操作符，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 = True f = False print type(t) # Prints "<type 'bool'>" 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 Unicode
from __future__ import unicode_literals
type("Guido") # string type become unicode
# <type 'unicode'>
Python 字符串支持分片、模板字符串等常见操作:
var1 = 'Hello World!'
var2 = "Python Programming"
print "var1[0]: ", var1[0]
print "var2[1:5]: ", var2[1:5]
# var1[0]: H
# var2[1:5]: ytho
print "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 IndexError
str.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 操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'\1', str) # 编译生成独立的正则表达式对象 expr = re.compile(r'^...$') expr.match(...) expr.sub(...)
下面列举了常见的表达式使用场景:
# 检测是否为 HTML 标签
re.search('<[^/>][^>]*>', '<a href="#label">')
# 常见的用户名密码
re.match('^[a-zA-Z0-9-_]{3,16}$', 'Foo') is not None
re.match('^\w|[-_]{3,16}$', 'Foo') is not None
# Email
re.match('^([a-z0-9_\.-]+)@([\da-z\.-]+)\.([a-z\.]{2,6})$', 'hello.world@example.com')
# Url
exp = re.compile(r'''^(https?:\/\/)? # match http or https
([\da-z\.-]+) # match domain
\.([a-z\.]{2,6}) # match domain
([\/\w \.-]*)\/?$ # match api or file
''', re.X)
exp.match('www.google.com')
# IP 地址
exp = re.compile(r'''^(?:(?:25[0-5]
|2[0-4][0-9]
|[1]?[0-9][0-9]?)\.){3}
(?:25[0-5]
|2[0-4][0-9]
|[1]?[0-9][0-9]?)$''', re.X)
exp.match('192.168.1.1')
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, 2, 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, 2, 3] x.append([4, 5]) # [1, 2, 3, [4, 5]]
x.extend([4, 5]) # [1, 2, 3, 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] # 弹出第二个元素 myList.pop(1) # 20 # myList: myList.pop(1) # 如果不加任何参数，则默认弹出最后一个元素 myList.pop() # 使用 slices 来删除某个元素 a = [ 1, 2, 3, 4, 5, 6 ] index = 3 # Only Positive index a = a[:index] + a[index+1 :] # 根据下标删除元素 myList = [10,20,30,40,50] rmovIndxNo = 3 del myList[rmovIndxNo] # myList: [10, 20, 30, 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 to
Iteration: 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', 'dog', 'monkey']
for idx, animal in enumerate(animals):
print '#%d: %s' % (idx + 1, animal)
# Prints "#1: cat", "#2: dog", "#3: monkey", each on its own line
Python 也支持切片（Slices）:
nums = range(5) # range is a built-in function that creates a list of integers print nums # Prints "[0, 1, 2, 3, 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, 3, 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, 1, 2, 3, 4]" print nums[:-1] # Slice indices can be negative; prints ["0, 1, 2, 3]" nums[2:4] = [8, 9] # Assign a new sublist to a slice print nums # Prints "[0, 1, 8, 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, 2, 3, 4, 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 reduce
product = reduce((lambda x, y: x * y), [1, 2, 3, 4])
# Output: 24
filter 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 3.5
z = {**x, **y}
# python 2.7
def 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 get
print '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", "b","c"}
normal_set = set(["a", "b","c"])
# Adding an element to normal set is fine
normal_set.add("d")
print("Normal Set")
print(normal_set)
# A frozen set
frozen_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, 0, 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 kwargs
example(1, "var", 2, 3, word="hello")
# 1 var
# (2, 3)
# {'word': 'hello'}
a_tuple = (1, 2, 3, 4, 5)
a_dict = {"1":1, "2":2, "3":3}
example(1, "var", *a_tuple, **a_dict)
# 1 var
# (1, 2, 3, 4, 5)
# {'1': 1, '2': 2, '3': 3}
生成器
def simple_generator_function():
yield 1
yield 2
yield 3
for value in simple_generator_function():
print(value)
# 输出结果
# 1
# 2
# 3
our_generator = simple_generator_function()
next(our_generator)
# 1
next(our_generator)
# 2
next(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 wraps
def decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
print('wrap function')
return func(*args, **kwargs)
return wrapper
@decorator
def example(*a, **kw):
pass
example.__name__ # attr of function preserve
# 'example'
# Decorator
# 带输入值的装饰器
from functools import wraps
def 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.name
g = Greeter('Fred') # Construct an instance of the Greeter class
g.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 = 10
isinstance(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**3
ex = 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 classmethod
ex.stmethod()
# I am staticmethod
ex.instmethod()
# I am instancemethod
example.clsmethod()
# I am classmethod
example.stmethod()
# I am staticmethod
example.instmethod()
# Traceback (most recent call last):
# File "", line 1, in
# TypeError: unbound method instmethod() ...
对象
实例化
属性操作
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 3
a = 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操作:
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")
# True
hasattr(ex,"printex")
# True
hasattr(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 = 5566
with 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_function
import unittest
def 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__) # src\app ## 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:\WorkSpace\OWS\tool\ui-tool-svn\python\src\app # 获取当前文件的真实路径 os.path.dirname(os.path.realpath(__file__)) # D:\WorkSpace\OWS\tool\ui-tool-svn\python\src\app # 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 listdir
from os.path import isfile, join
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
# 使用 walk 递归搜索
from os import walk
f = []
for (dirpath, dirnames, filenames) in walk(mypath):
f.extend(filenames)
break
# 使用 glob 进行复杂模式匹配
import glob
print(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(...)
...
# 操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 data
with open('data.json', 'w') as f:
json.dump(data, f)
# Reading data back
with 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，本部分即对其常用操作进行介绍。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 baseURL root = 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 XPath
for 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 等方法进行元素操作：
# 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 来写入与操作 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 + 1
workbook.close()
文件系统
对于高级的文件操作，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 requests
r = requests.get('https://api.github.com/events')
r = requests.get('https://api.github.com/user', auth=('user', 'pass'))
r.status_code
# 200
r.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 database
connection = 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, ('webmaster@python.org', '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, ('webmaster@python.org',))
result = cursor.fetchone()
print(result)
finally:
connection.close()
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p class="source">原文链接:https://segmentfault.com/a/1190000012129654
