基礎語法

 

Python 是一門高階、動態型別的多正規化程式語言；定義 Python 檔案的時候我們往往會先宣告檔案編碼方式:

 

 

# 指定指令碼呼叫方式
#!/usr/bin/env python
# 配置 utf-8 編碼
# -*- coding: utf-8 -*-
# 配置其他編碼
# -*- coding: <encoding-name> -*-
# Vim 中還可以使用如下方式
# vim:fileencoding=<encoding-name>

 

人生苦短，請用 Python，大量功能強大的語法糖的同時讓很多時候 Python 程式碼看上去有點像虛擬碼。譬如我們用 Python 實現的簡易的快排相較於 Java 會顯得很短小精悍:

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]"

 

 

控制檯互動

可以根據 __name__ 關鍵字來判斷是否是直接使用 python 命令執行某個指令碼，還是外部引用；Google 開源的 fire 也是不錯的快速將某個類封裝為命令列工具的框架：

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 是表示式，而 Python 3 中 print 是函式；如果希望在 Python 2 中將 print 以函式方式使用，則需要自定義引入:

from __future__ import print_function

 

我們也可以使用 pprint 來美化控制檯輸出內容：

import pprint
stuff = ['spam', 'eggs', 'lumberjack', 'knights', 'ni']
pprint.pprint(stuff)
# 自定義引數
pp = pprint.PrettyPrinter(depth=6)
tup = ('spam', ('eggs', ('lumberjack', ('knights', ('ni', ('dead',('parrot', ('fresh fruit',))))))))
pp.pprint(tup)

 

 

模組

Python 中的模組（Module）即是 Python 原始碼檔案，其可以匯出類、函式與全域性變數；當我們從某個模組匯入變數時，函式名往往就是名稱空間（Namespace）。而 Python 中的包（Package）則是模組的資料夾，往往由 __init__.py 指明某個資料夾為包:

# 檔案目錄
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 可以為某個目錄下所有的檔案設定統一入口:

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

 

 

表示式與控制流

 

 

條件選擇

Python 中使用 if、elif、else 來進行基礎的條件選擇操作：

if x < 0:
 x = 0
 print('Negative changed to zero')
 elif x == 0:
 print('Zero')
 else:
 print('More')

 

Python 同樣支援 ternary conditional operator:

a if condition else b

 

也可以使用 Tuple 來實現類似的效果：

# test 需要返回 True 或者 False
(falseValue, trueValue)[test]
# 更安全的做法是進行強制判斷
(falseValue, trueValue)[test == True]
# 或者使用 bool 型別轉換函式
(falseValue, trueValue)[bool(<expression>)]

 

進行強制判斷(falseValue, trueValue)[test == True]# 或者使用 bool 型別轉換函式(falseValue, trueValue)[bool(<expression>)]

 

迴圈遍歷

for-in 可以用來遍歷陣列與字典：

words = ['cat', 'window', 'defenestrate']
for w in words:
 print(w, len(w))
# 使用陣列訪問操作符，能夠迅速地生成陣列的副本
for w in words[:]:
 if len(w) > 6:
 words.insert(0, w)
# words -> ['defenestrate', 'cat', 'window', 'defenestrate']

 

如果我們希望使用數字序列進行遍歷，可以使用 Python 內建的 range 函式：

a = ['Mary', 'had', 'a', 'little', 'lamb']
for i in range(len(a)):
 print(i, a[i])

 

 

基本資料型別

 

可以使用內建函式進行強制型別轉換（Casting）:

int(str)
float(str)
str(int)
str(float)

 

 

Number: 數值型別

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"

 

 

布林型別

Python 提供了常見的邏輯操作符，不過需要注意的是 Python 中並沒有使用 &&、|| 等，而是直接使用了英文單詞。

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: 字串

Python 2 中支援 Ascii 碼的 str() 型別，獨立的 unicode() 型別，沒有 byte 型別；而 Python 3 中預設的字串為 utf-8 型別，並且包含了 byte 與 bytearray 兩個位元組型別：

type("Guido") # string type is str in python2
# <type 'str'>
# 使用 __future__ 中提供的模組來降級使用 Unicode
from __future__ import unicode_literals
type("Guido") # string type become unicode
# <type 'unicode'>

 

Python 字串支援分片、模板字串等常見操作:

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()

 

# 移除所有的特殊字元
re.sub('[^A-Za-z0-9]+', '', mystring) 

 

如果需要判斷是否包含某個子字串，或者搜尋某個字串的下標:

# in 操作符可以判斷字串
if "blah" not in somestring: 
 continue
# find 可以搜尋下標
s = "This be a string"
if s.find("is") == -1:
 print "No 'is' here!"
else:
 print "Found 'is' in the string."

 

 

Regex: 正則表示式

import re
# 判斷是否匹配
re.match(r'^[aeiou]', str)
# 以第二個引數指定的字元替換原字串中內容
re.sub(r'^[aeiou]', '?', str)
re.sub(r'(xyz)', r'', str)
# 編譯生成獨立的正則表示式物件
expr = re.compile(r'^...$')
expr.match(...)
expr.sub(...)

 

下面列舉了常見的表示式使用場景:

# 檢測是否為 HTML 標籤
re.search('<[^/>][^>]*>', '<a href="#label">')
# 常見的使用者名稱密碼
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})$', '[email protected]')
# Url
exp = re.compile(r'''^(https?://)? # match http or https
 ([da-z.-]+) # match domain
 .([a-z.]{2,6}) # match domain
 ([/w .-]*)/?$ # 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')

 

 

集合型別

 

 

List: 列表

 

Operation: 建立增刪

list 是基礎的序列型別：

l = []
l = list()
# 使用字串的 split 方法，可以將字串轉化為列表
str.split(".")
# 如果需要將陣列拼裝為字串，則可以使用 join 
list1 = ['1', '2', '3']
str1 = ''.join(list1)
# 如果是數值陣列，則需要先進行轉換
list1 = [1, 2, 3]
str1 = ''.join(str(e) for e in list1)

 

可以使用 append 與 extend 向陣列中插入元素或者進行陣列連線

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 返回值為 None

 

可以使用 pop、slices、del、remove 等移除列表中元素：

myList = [10,20,30,40,50]
# 彈出第二個元素
myList.pop(1) # 20
# myList: myList.pop(1)
# 如果不加任何引數，則預設彈出最後一個元素
myList.pop()
# 使用 slices 來刪除某個元素
a = [ 1, 2, 3, 4, 5, 6 ]
index = 3 # Only Positive index
a = a[:index] + a[index+1 :]
# 根據下標刪除元素
myList = [10,20,30,40,50]
rmovIndxNo = 3
del myList[rmovIndxNo] # myList: [10, 20, 30, 50]
# 使用 remove 方法，直接根據元素刪除
letters = ["a", "b", "c", "d", "e"]
numbers.remove(numbers[1])
print(*letters) # used a * to make it unpack you don't have to

 

 

Iteration: 索引遍歷

你可以使用基本的 for 迴圈來遍歷陣列中的元素，就像下面介個樣紙:

animals = ['cat', 'dog', 'monkey']
for animal in animals:
 print animal
# Prints "cat", "dog", "monkey", each on its own line.

 

如果你在迴圈的同時也希望能夠獲取到當前元素下標，可以使用 enumerate 函式:

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 也支援切片（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: 變換

Python 中同樣可以使用 map、reduce、filter，map 用於變換陣列:

# 使用 map 對陣列中的每個元素計算平方
items = [1, 2, 3, 4, 5]
squared = list(map(lambda x: x**2, items))
# map 支援函式以陣列方式連線使用
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 用於進行歸納計算:

# reduce 將陣列中的值進行歸納
from functools import reduce
product = reduce((lambda x, y: x * y), [1, 2, 3, 4])
# Output: 24

 

filter 則可以對陣列進行過濾:

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]

 

 

字典型別

 

建立增刪

d = {'cat': 'cute', 'dog': 'furry'} # 建立新的字典
print d['cat'] # 字典不支援點（Dot）運算子取值

 

如果需要合併兩個或者多個字典型別：

# 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

 

 

索引遍歷

可以根據鍵來直接進行元素訪問:

# Python 中對於訪問不存在的鍵會丟擲 KeyError 異常，需要先行判斷或者使用 get
print 'cat' in d # Check if a dictionary has a given key; prints "True"
# 如果直接使用 [] 來取值，需要先確定鍵的存在，否則會丟擲異常
print d['monkey'] # KeyError: 'monkey' not a key of d
# 使用 get 函式則可以設定預設值
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 方法可以獲取所有的鍵

 

可以使用 for-in 來遍歷陣列:

# 遍歷鍵
for key in d:
# 比前一種方式慢
for k in dict.keys(): ...
# 直接遍歷值
for value in dict.itervalues(): ...
# Python 2.x 中遍歷鍵值
for key, value in d.iteritems():
# Python 3.x 中遍歷鍵值
for key, value in d.items():

 

 

其他序列型別

 

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")

 

 

 

函式

 

 

函式定義

Python 中的函式使用 def 關鍵字進行定義，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 支援執行時建立動態函式，也即是所謂的 lambda 函式：

def f(x): return x**2
# 等價於
g = lambda x: x**2

 

 

引數

 

Option Arguments: 不定引數

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)
# 輸出結果
# 1
# 2
# 3
our_generator = simple_generator_function()
next(our_generator)
# 1
next(our_generator)
# 2
next(our_generator)
#3
# 生成器典型的使用場景譬如無限陣列的迭代
def get_primes(number):
 while True:
 if is_prime(number):
 yield number
 number += 1

 

 

裝飾器

裝飾器是非常有用的設計模式:

# 簡單裝飾器
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 
# 帶輸入值的裝飾器
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.
# 等價於
def example():
 print "This is example function."
example = decorator_with_argument(10)(example)
example()
# Val is 10
# This is example function.

 

 

類與物件

 

 

類定義

Python 中對於類的定義也很直接:

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 方法用於判斷某個物件是否源自某個類
ex = 10
isinstance(ex,int)

 

 

Managed Attributes: 受控屬性

# property、setter、deleter 可以用於複寫點方法
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

 

 

類方法與靜態方法

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() ...

 

 

物件

 

例項化

 

屬性操作

Python 中物件的屬性不同於字典鍵，可以使用點運算子取值，直接使用 in 判斷會存在問題:

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

 

建議使用 hasattr、getattr、setattr 這種方式對於物件屬性進行操作:

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'

'

 

 

異常與測試

 

 

異常處理

 

Context Manager - with

with 常用於開啟或者關閉某些資源:

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()

 

 

單元測試

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()

 

 

 

儲存

 

 

檔案讀寫

 

路徑處理

Python 內建的 __file__ 關鍵字會指向當前檔案的相對路徑，可以根據它來構造絕對路徑，或者索引其他檔案:

# 獲取當前檔案的相對目錄
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.
# 獲取當前程式碼檔案的絕對路徑，abspath 會自動根據相對路徑與當前工作空間進行路徑補全
os.path.abspath(os.path.dirname(__file__)) # D:WorkSpaceOWS	ool\ui-tool-svnpythonsrcapp
# 獲取當前檔案的真實路徑
os.path.dirname(os.path.realpath(__file__)) # D:WorkSpaceOWS	ool\ui-tool-svnpythonsrcapp
# 獲取當前執行路徑
os.getcwd()

 

可以使用 listdir、walk、glob 模組來進行檔案列舉與檢索：

# 僅列舉所有的檔案
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 遞迴搜尋
from os import walk
f = []
for (dirpath, dirnames, filenames) in walk(mypath):
 f.extend(filenames)
 break
# 使用 glob 進行復雜模式匹配
import glob
print(glob.glob("/home/adam/*.txt"))
# ['/home/adam/file1.txt', '/home/adam/file2.txt', .... ]

 

 

簡單檔案讀寫

# 可以根據檔案是否存在選擇寫入模式
mode = 'a' if os.path.exists(writepath) else 'w'
# 使用 with 方法能夠自動處理異常
with open("file.dat",mode) as f:
 f.write(...)
 ...
 # 操作完畢之後記得關閉檔案
 f.close()
# 讀取檔案內容
message = f.read()

 

 

複雜格式檔案

 

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

我們可以使用 lxml 來解析與處理 XML 檔案，本部分即對其常用操作進行介紹。lxml 支援從字串或者檔案中建立 Element 物件：

from lxml import etree
# 可以從字串開始構造
xml = '<a xmlns="test"><b xmlns="test"/></a>'
root = etree.fromstring(xml)
etree.tostring(root)
# b'<a xmlns="test"><b xmlns="test"/></a>'
# 也可以從某個檔案開始構造
tree = etree.parse("doc/test.xml")
# 或者指定某個 baseURL
root = etree.fromstring(xml, base_url="http://where.it/is/from.xml")

 

其提供了迭代器以對所有元素進行遍歷：

# 遍歷所有的節點
for tag in tree.iter():
 if not len(tag):
 print tag.keys() # 獲取所有自定義屬性
 print (tag.tag, tag.text) # text 即文字子元素值
# 獲取 XPath
for e in root.iter():
 print tree.getpath(e)

 

lxml 支援以 XPath 查詢元素，不過需要注意的是，XPath 查詢的結果是陣列，並且在包含名稱空間的情況下，需要指定名稱空間：

root.xpath('//page/text/text()',ns={prefix:url})
# 可以使用 getparent 遞迴查詢父元素
el.getparent()

 

lxml 提供了 insert、append 等方法進行元素操作：

# append 方法預設追加到尾部
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]() 來讀取 Excel 檔案，使用 xlsxwriter 來寫入與操作 Excel 檔案。

# 讀取某個 Cell 的原始值
sh.cell(rx, col).value
# 建立新的檔案
workbook = xlsxwriter.Workbook(outputFile)
worksheet = workbook.add_worksheet()
# 設定從第 0 行開始寫入
row = 0
# 遍歷二維陣列，並且將其寫入到 Excel 中
for rowData in array:
 for col, data in enumerate(rowData):
 worksheet.write(row, col, data)
 row = row + 1
workbook.close()

 

 

檔案系統

對於高階的檔案操作，我們可以使用 Python 內建的 shutil

# 遞迴刪除 appName 下面的所有的資料夾
shutil.rmtree(appName)

 

 

網路互動

 

 

Requests

Requests 是優雅而易用的 Python 網路請求庫:

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')

 

 

資料儲存

 

 

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, ('[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, ('[email protected]',))
 result = cursor.fetchone()
 print(result)
finally:
 connection.close()