python cookbook 阅读笔记
第一章：数据结构和算法
1.1 队列 deque:
from collections import deque
# 保留最后 10 个元素
previous_lines = deque(maxlen=10)
# 队列
q = deque([1, 2, 3])
q.appendleft(4)
q.popleft()
q.append(10)
q.pop(2)
1.2 查找最大或最小的 N 个元素
import heapq
nums = [1, 8, 2, 23, 7, -4, 18, 23, 42, 37, 2]
print(heapq.nlargest(3, nums)) # Prints [42, 37, 23]
print(heapq.nsmallest(3, nums)) # Prints [-4, 1, 2]
heapq 可以实现优先级队列.
1.3 Counter 找出 序列中出现次数最多的元素
from collections import Counter
words = []
for index in range(10):
for _ in range(index + 1):
words.append("index-{}".format(index))
# 出现频率最高的 3 个单词
word_counts = Counter(words)
top_three = word_counts.most_common(3)
print(top_three)
第二章：字符串和文本
2.1 使用多个界定符分割字符串
import re
line = 'asdf fjdk; afed, fjek,asdf, foo'
print(re.split(r'[;,\s]\s*', line)) # ['asdf', 'fjdk', 'afed', 'fjek', 'asdf', 'foo']
# 保留分隔符
fields = re.split(r'(;|,|\s)\s*', line)
print(fields) # ['asdf', ' ', 'fjdk', ';', 'afed', ',', 'fjek', ',', 'asdf', ',', 'foo']
2.2 fnmath 实现 shell 通配符匹配功能
from fnmatch import fnmatch, fnmatchcase
print(fnmatch('foo.txt', '*.txt')) # True
print(fnmatch('foo.txt', '?oo.txt')) # True
print(fnmatch('Dat45.csv', 'Dat[0-9]*')) # True
# On Windows
print(fnmatch('foo.txt', '*.TXT')) # True
# 完全匹配
print(fnmatchcase('foo.txt', '*.TXT')) # False
2.3 字符串搜索和替换
import re
text = 'Today is 11/27/2012. PyCon starts 3/13/2013.'
print(re.sub(r'(\d+)/(\d+)/(\d+)', r'\3-\1-\2', text)) # 'Today is 2012-11-27. PyCon starts 2013-3-13.'
忽略字符串大小写的搜索替换
import re
text = 'UPPER PYTHON, lower python, Mixed Python'
print(re.findall('python', text, flags=re.IGNORECASE)) # ['PYTHON', 'python', 'Python']
print(re.sub('python', 'snake', text, flags=re.IGNORECASE)) # 'UPPER snake, lower snake, Mixed snake'
进阶: 替换字符串自动跟被匹配字符串的大小写保持一致
import re
def matchcase(word):
def replace(m):
text = m.group()
if text.isupper():
return word.upper()
elif text.islower():
return word.lower()
elif text[0].isupper():
return word.capitalize()
else:
return word
return replace
text = 'UPPER PYTHON, lower python, Mixed Python'
print(re.sub('python', matchcase('snake'), text, flags=re.IGNORECASE))
# UPPER SNAKE, lower snake, Mixed Snake
多行匹配:
import re
text1 = '/* this is a comment */'
text2 = '''/* this is a
multiline comment */
'''
# 不能匹配换行符
re.compile(r'/\*(.*?)\*/').findall(text1) # [' this is a comment ']
re.compile(r'/\*(.*?)\*/').findall(text2) # []
# 匹配多行
# 方法一: 指定了一个非捕获组匹配
re.compile(r'/\*((?:.|\n)*?)\*/').findall(text2)
# [' this is a\n multiline comment ']
# 方法二: re.DOTALL
re.compile(r'/\*(.*?)\*/', re.DOTALL).findall(text2)
# [' this is a\n multiline comment ']
第四章：迭代器与生成器
4.1 手动遍历迭代器
def manual_iter():
with open('/etc/passwd') as f:
try:
while True:
line = next(f)
print(line, end='')
except StopIteration:
pass
4.2 迭代器其他
- 关键魔法方法:
__iter__(self, )和__next__(self, ) - 反向迭代:
__reversed__(self, ), 使用reversed(iter) - 同时迭代多个序列:
for x, y in zip(x_iter, y_iter) - 依次迭代多个序列:
for x in itertools.chain(x1_iter, x2_iter, x3_iter) - 创建数据处理管道: 使用迭代器能简化逻辑
- 展开嵌套的序列:
yield from
顺序迭代合并后的排序迭代对象: 性能更好
import heapq
a = [1, 4, 7, 10]
b = [2, 5, 6, 11]
for c in heapq.merge(a, b):
print(c)
# 1 2 4 5 6 7 10 11
第八章：类与对象
8.1 创建新的类或实例属性
# Descriptor attribute for an integer type-checked attribute
class Integer:
def __init__(self, name):
self.name = name
def __get__(self, instance, cls):
if instance is None:
return self
else:
return instance.__dict__[self.name]
def __set__(self, instance, value):
if not isinstance(value, int):
raise TypeError('Expected an int')
instance.__dict__[self.name] = value
def __delete__(self, instance):
del instance.__dict__[self.name]
class Point:
x = Integer('x')
y = Integer('y')
def __init__(self, x, y):
self.x = x
self.y = y
p = Point(2, 3)
print(p.x) # Calls Point.x.__get__(p,Point)
p.y = 5 # Calls Point.y.__set__(p, 5)
p.x = 2.3 # Calls Point.x.__set__(p, 2.3)
# raise TypeError
8.2 使用延迟计算属性
import math
class lazyproperty:
def __init__(self, func):
self.func = func
def __get__(self, instance, cls):
if instance is None:
return self
else:
value = self.func(instance)
setattr(instance, self.func.__name__, value)
return value
class Circle:
def __init__(self, radius):
self.radius = radius
@lazyproperty
def area(self):
print('Computing area')
return math.pi * self.radius ** 2
@lazyproperty
def perimeter(self):
print('Computing perimeter')
return 2 * math.pi * self.radius
# 使用
c = Circle(4.0)
print(vars(c)) # {'radius': 4.0}
c.area
print(vars(c)) # {'area': 50.26548245743669, 'radius': 4.0}
del c.area
print(vars(c)) # {'radius': 4.0}
8.3 实现自定义容器
你想实现一个自定义的类来模拟内置的容器类功能，比如列表和字典。但是你不确定到底要实现哪些方法。
collections 定义了很多抽象基类，当你想自定义容器类的时候它们会非常有用。
比如你想让你的类支持迭代，那就让你的类继承 collections.Iterable 即可：
import collections
class A(collections.Iterable):
pass
8.4 利用 Mixins 扩展类功能
class LoggedMappingMixin:
"""
Add logging to get/set/delete operations for debugging.
"""
__slots__ = () # 混入类都没有实例变量，因为直接实例化混入类没有任何意义
def __getitem__(self, key):
print('Getting ' + str(key))
return super().__getitem__(key)
def __setitem__(self, key, value):
print('Setting {} = {!r}'.format(key, value))
return super().__setitem__(key, value)
def __delitem__(self, key):
print('Deleting ' + str(key))
return super().__delitem__(key)
8.5 创建缓存实例
import weakref
class CachedSpamManager:
def __init__(self):
self._cache = weakref.WeakValueDictionary()
def get_spam(self, name):
if name not in self._cache:
s = Spam._new(name)
self._cache[name] = s
else:
s = self._cache[name]
return s
def clear(self):
self._cache.clear()
class Spam:
def __init__(self, *args, **kwargs):
raise RuntimeError("Can't instantiate directly")
# Alternate constructor
@classmethod
def _new(cls, name):
self = cls.__new__(cls)
self.name = name
return self
if __name__ == '__main__':
cache = CachedSpamManager()
a = cache.get_spam("a")
b = cache.get_spam("b")
c = cache.get_spam("a")
print(a)
print(b)
print(c)
assert a is not b
assert a is c
TODO
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