符合語言習慣的Python優雅程式設計技巧
阿新 • • 發佈:2018-11-02
Python最大的優點之一就是語法簡潔,好的程式碼就像虛擬碼一樣,乾淨、整潔、一目瞭然。要寫出 Pythonic(優雅的、地道的、整潔的)程式碼,需要多看多學大牛們寫的程式碼,github 上有很多非常優秀的原始碼值得閱讀,比如:requests、flask、tornado,下面列舉一些常見的Pythonic寫法。
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程式必須先讓人讀懂,然後才能讓計算機執行。
“Programs must be written for people to read, and only incidentally for machines to execute.”
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交換賦值
temp = a a = b b = a ##推薦 a, b = b, a # 先生成一個元組(tuple)物件,然後unpack `
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Unpacking
l = ['David', 'Pythonista', '+1-514-555-1234'] first_name = l[0] last_name = l[1] phone_number = l[2] ##推薦 l = ['David', 'Pythonista', '+1-514-555-1234'] first_name, last_name, phone_number = l # Python 3 Only first, *middle, last = another_list`
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使用操作符in
if fruit == "apple" or fruit == "orange" or fruit == "berry": # 多次判斷 ##推薦 if fruit in ["apple", "orange", "berry"]: # 使用 in 更加簡潔`
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字串操作
colors = ['red', 'blue', 'green', 'yellow'] result = '' for s in colors: result += s # 每次賦值都丟棄以前的字串物件, 生成一個新物件 ##推薦 colors = ['red', 'blue', 'green', 'yellow'] result = ''.join(colors) # 沒有額外的記憶體分配```
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字典鍵值列表
for key in my_dict.keys(): # my_dict[key] ... ##推薦 for key in my_dict: # my_dict[key] ... # 只有當迴圈中需要更改key值的情況下,我們需要使用 my_dict.keys() # 生成靜態的鍵值列表。```
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字典鍵值判斷
if my_dict.has_key(key): # ...do something with d[key] ##推薦 if key in my_dict: # ...do something with d[key]```
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字典 get 和 setdefault 方法
navs = {} for (portfolio, equity, position) in data: if portfolio not in navs: navs[portfolio] = 0 navs[portfolio] += position * prices[equity] ##推薦 navs = {} for (portfolio, equity, position) in data: # 使用 get 方法 navs[portfolio] = navs.get(portfolio, 0) + position * prices[equity] # 或者使用 setdefault 方法 navs.setdefault(portfolio, 0) navs[portfolio] += position * prices[equity]```
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判斷真偽
if x == True: # .... if len(items) != 0: # ... if items != []: # ... ##推薦 if x: # .... if items: # ...```
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遍歷列表以及索引
items = 'zero one two three'.split() # method 1 i = 0 for item in items: print i, item i += 1 # method 2 for i in range(len(items)): print i, items[i] ##推薦 items = 'zero one two three'.split() for i, item in enumerate(items): print i, item```
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列表推導
new_list = [] for item in a_list: if condition(item): new_list.append(fn(item)) ##推薦 new_list = [fn(item) for item in a_list if condition(item)]```
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列表推導-巢狀
for sub_list in nested_list: if list_condition(sub_list): for item in sub_list: if item_condition(item): # do something... ##推薦 gen = (item for sl in nested_list if list_condition(sl) \ for item in sl if item_condition(item)) for item in gen: # do something...```
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迴圈巢狀
for x in x_list: for y in y_list: for z in z_list: # do something for x & y ##推薦 from itertools import product for x, y, z in product(x_list, y_list, z_list): # do something for x, y, z```
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儘量使用生成器代替列表
def my_range(n): i = 0 result = [] while i < n: result.append(fn(i)) i += 1 return result # 返回列表 ##推薦 def my_range(n): i = 0 result = [] while i < n: yield fn(i) # 使用生成器代替列表 i += 1 *儘量用生成器代替列表,除非必須用到列表特有的函式。```
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中間結果儘量使用imap/ifilter代替map/filter
reduce(rf, filter(ff, map(mf, a_list))) ##推薦 from itertools import ifilter, imap reduce(rf, ifilter(ff, imap(mf, a_list))) *lazy evaluation 會帶來更高的記憶體使用效率,特別是當處理大資料操作的時候。```
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使用any/all函式
found = False for item in a_list: if condition(item): found = True break if found: # do something if found... ##推薦 if any(condition(item) for item in a_list): # do something if found...```
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屬性(property)
=
##不推薦
class Clock(object):
def __init__(self):
self.__hour = 1
def setHour(self, hour):
if 25 > hour > 0: self.__hour = hour
else: raise BadHourException
def getHour(self):
return self.__hour
##推薦
class Clock(object):
def __init__(self):
self.__hour = 1
def __setHour(self, hour):
if 25 > hour > 0: self.__hour = hour
else: raise BadHourException
def __getHour(self):
return self.__hour
hour = property(__getHour, __setHour)
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使用 with 處理檔案開啟
f = open("some_file.txt") try: data = f.read() # 其他檔案操作.. finally: f.close() ##推薦 with open("some_file.txt") as f: data = f.read() # 其他檔案操作...```
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使用 with 忽視異常(僅限Python 3)
try: os.remove("somefile.txt") except OSError: pass ##推薦 from contextlib import ignored # Python 3 only with ignored(OSError): os.remove("somefile.txt")```
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使用 with 處理加鎖
import threading
lock = threading.Lock()
lock.acquire()
try:
# 互斥操作...
finally:
lock.release()
##推薦
import threading
lock = threading.Lock()
with lock:
# 互斥操作...
- 參考
2) PEP 8: Style Guide for Python Code: http://www.python.org/dev/peps/pep-0008/