This repository contains ancillary function which code in python3. Use it freely.
Crawl web function may contain error(s) as the web elements changed.
If you had any idea to improve my code or you find any mistake in my file, please contact me. (Email me at [email protected])
需求：
- 过滤 list 中大于 0 的数：[14, 0, -6, 0, -10, -8, -1, 19, -10, -16]
- 筛选出字典中值大于 0 的项目：{0: 9, 1: -3, 2: -8, 3: 6, 4: -4, 5: -4, 6: -7, 7: -8, 8: 7, 9: -3}
- 筛选出集合中能被 2 整除的数：{3, 4, 9, 12, 15, 17, 19, 20}
- 找到字典中值最小的健值对：prices = {'ACME': 45.23,'AAPL': 612.78,'IBM': 205.55,'HPQ': 37.20,'FB': 10.75}
- 对字典排序，首先按照值排序，值相同再按照健排序 6. 对字典的健按照值排序
list_bigger = [x for x in list_numbers if x > 0]
dict_bigger = {k: v for k, v in dict_numbers.items() if v > 0}
set_two = {x for x in set_numbers if not x % 2}
min_pairs = min(zip(prices.values(),prices.keys()))
sorted_pairs = sorted(zip(prices.values(),prices.keys()))
sorted_keys = sorted(prices,prices.get)
# zip 创建的对象只能访问一次需求：在表格中，每一行的信息固定，为了访问某个位置的值，不使用索引
from collections import namedtuple
student = namedtuple("Student", ["name", "age", "sex"])
s1 = student(name="12", age=12, sex="female")
s2 = student(name="12", age=12, sex="male")需求： 统计 [5, 2, 2, 3, 1, 5, 1, 3, 2, 4] 出现次数最高的 3 的元素，并找到它们的出现次数 统计一个段落中出现次数最高的前 3 个元素，并确定次数
import re
from collections import Counter
nums = [5, 2, 2, 3, 1, 5, 1, 3, 2, 4]
times = Counter(nums)
com = times.most_common(3)
text = """If operators with different priorities are used, consider adding
whitespace around the operators with the lowest priority(ies). Use
your own judgment; however, never use more than one space, and
always have the same amount of whitespace on both sides of a binary
operator."""
times = Counter(re.split(r"\W+",text))
com = times.most_common(3)需求：根据字典中值的大小，对字典排序
numbers = {0: 9, 1: -3, 2: -8, 3: 6, 4: -4, 5: -4, 6: -7, 7: -8, 8: 7, 9: -3}
res = sorted(numbers.items(), key=lambda x: x[1])需求：找到多个字典中的公共键
from functools import reduce
a = {'b': 7, 'f': 3, 'e': 9}
b = {'d': 8, 'b': 2, 'f': 8, 'e': 10, 'g': 6}
c = {'h': 2, 'e': 7, 'b': 11}
res = reduce(lambda x, y: x & y, map(dict.keys, [a, b, c]))需求：让字典保持有序
from collections import OrderedDict
order = OrderedDict()
for x in sample("abcdefgh", randint(3, 6)):
order[x] = randint(4,10)需求：根据多个分隔符，拆分字符串
import re
text = """If\roperators\r\n with\different<<priorities are\vused, consider adding
whitespace around the operators with the lowest priority(ies). Use
your own judgment;;\however, never use more than one space, and
always have}the\\same amount of whitespace on both sides of a binary
operator."""
res = re.split(r"[\r\n\t\v\\}; .<]+",text)需求：调整文本中的字符串格式，将 07/20/2019 替换成为 2019-07-20
## 使用了正则的捕获组
import re
text = "07/20/2019"
res = re.sub(r"(\d{2})\/(\d{2})\/(\d{4})", r"\3-\1-\2", text)需求：同时遍历可迭代对象
from itertools import chain
nums1 = [1, 5, 4, 5]
nums2 = [2, 3, 3]
nums3 = [4, 3, 3, 5, 7, 8, 3]
## 并行遍历
for x, y, z in zip(nums1, nums2, nums3):
print(x, y, z)
## 串行遍历
for x in chain(nums1, nums2, nums3):
print(x)需求：为了确保用户输入正确格式的数，强制用户使用函数进行访问；为了简介，通过 property 自动调用函数，实现「设置属性自动调用函数的效果」
property 为类创建可管理的属性
class Control(object):
def __init__(self, value):
self.value = value
def get_value(self):
return self.value
def set_value(self, num: int):
if not isinstance(num, (int, float)):
raise ValueError("please enter num")
self.value = num
r = property(get_value, set_value)需求：实现类的比较
from functools import total_ordering
from abc import ABCMeta, abstractmethod
@total_ordering
class Shape(object):
@abstractmethod
def area(self):
pass
def __lt__(self, obj):
if not isinstance(obj, Shape):
raise TypeError("obj is not a shape")
return self.area() < obj.area()
def __eq__(self, obj):
if not isinstance(obj, Shape):
raise TypeError("obj is not a shape")
return self.area() == obj.area()
class Cirlcle(Shape):
def __init__(self, radius):
self.radius = radius
def area(self):
return 3.14*self.radius**2
class Rect(Shape):
def __init__(self, weight, height):
self.weight = weight
self.height = height
def area(self):
return self.weight*self.height
cricle = Cirlcle(3)
rect = Rect(3, 4)
print(cricle >= rect)需求：对实例的类做类型检查
class Attr(object):
def __init__(self, name, type_):
self.name = name
self.type_ = type_
def __get__(self, instance, cls):
return instance.__dict__[self.name]
def __set__(self, instance, value):
if not isinstance(value, self.type_):
raise TypeError("expect a {}".format(self.type_))
instance.__dict__[self.name] = value
def __delete__(self, instance):
del instance.__dict__[self.name]
class Monkey(object):
name = Attr("name", str)
age = Attr("age", int)
gender = Attr("gender", str)需求：根据字符串执行实例的函数
from operator import methodcaller
class MethonCall(object):
def get_value(self, value: int, value2: int):
return 12*value*value2
mc = MethonCall()
fun = methodcaller("get_value", 2, -1)
print(fun(mc))- 需求：为某一个函数增加功能，不影响原来的函数
from functools import wraps, update_wrapper
def add_cache(fun):
cache = dict()
@wraps(fun)
def handler(*arg):
if arg not in cache:
cache[arg] = fun(*arg)
return cache[arg]
## update_wrapper(handler, fun, ("__name__", "__doc__"), ("__dict__",))
return handler
@add_cache
def fibonacci(n):
if n <= 1:
return 1
return fibonacci(n-1)+fibonacci(n-2)
print(fibonacci(89))- 带参数的装饰器
import time
import logging
from random import randint
def warn(timeout):
timeout = [timeout]
def decorator(fun):
def wrapper(*args, **kwargs):
start = time.time()
res = fun(*args, **kwargs)
end = time.time()
used = end-start
if used > timeout[0]:
logging.warn("{}:{} > {}".format(fun.__name__, used, timeout[0]))
return res
def set_timeout(k):
timeout[0] = k
wrapper.set_timeout = set_timeout
return wrapper
return decorator
@warn(1)
def test():
print("正在测试")
while randint(0, 1):
time.sleep(0.5)
for i in range(20):
test()
test.set_timeout(1.2)
for i in range(20):
test()需求：实现一个有优先级的队列
import heapq
class PriorityQueue(object):
def __init__(self):
self._queue = []
self._index = 0
def push(self, item, priority):
heapq.heappush(self._queue, (-priority, self._index, item))
self._index += 1
def pop(self):
return heapq.heappop(self._queue)[-1] if self._queue else Nonefrom collections.abc import Iterable
def flatten(items, ignore_types=(str, bytes)):
for x in items:
if isinstance(x, Iterable) and not isinstance(x, ignore_types):
yield from flatten(x)
else:
yield x
items = [1, 2, [3, 4, (5, 6), 7], 8, "temp", "core", {-1, -2, -4, -6}]
for x in flatten(items):
print(x)- 打印输出到文件中
with open('d:/work/test.txt', 'wt') as f:
print('Hello World!', file=f)
# 文件必须以文本格式打开- 文件不存在时才能写入
with open('somefile', 'xt') as f:
f.write('Hello\n')def recv(maxsize, *, block):
'Receives a message'
pass
recv(1024, True) # TypeError
recv(1024, block=True) # Ok- 键个数相等，键名一一对应，键值一一对应相等
import json
from datetime import datetime
from bson.json_util import default
def compare_2_dict(dict_1, dict_2):
return (json.dumps(dict_1, default=default, sort_keys=dict.keys) ==
json.dumps(dict_2, default=default, sort_keys=dict.keys))
dicta = {"a": datetime.now(), "b": 2}
dictb = {"a": datetime.now(), "b": 2}
print(compare_2_dict(dicta, dictb))- 在 for loop 中使用 lambda，如果有赋值，请小心
t = [lambda : i for i in range(4)]
m = [lambda i=i: i for i in range(4)]
res_t = [func() for func in t]
res_m = [func() for func in m]- res_t: [3, 3, 3, 3]
- rest_m: [0, 1, 2, 3]
- iterator 不走回头路，可以利用此特性来判断 list 是否存在于另一个 list 中
# a = [1,2,3]
# b = [1,3,2,4,5,6]
# check if all num in a is in b, ordered
# [1,2,3] is in [1,2,3,4] but [1,2,3] is not in [1,3,2,4]
def check(a, b):
b = iter(b)
return all(i in b for i in a)