Python内置函数复习

filter sorted heapq counter namedtuple  reduce deque pickle islice re.split endswith stat os

#filter

>>> aa = [1,2,3,45,6,7]

>>> list(filter(lambda x:x>3,aa))

>>> [45, 6, 7]

#sorted

>>> sorted(d.items(),key=lambda x:x[1],reverse=True)

#heapq

>>> import heapq

>>> heap.nlargest(3,[1,2,2,2,3,4,4,45,5,6])

#counter

>>> from collections import Counter

>>> aa = Counter([1,2,2,2,3,4,4,45,5,6])

>>> aa.most_common(3)

#namedtuple

>>> from collection import namedtuple

>>> Stu = namedtuple('Stu',['name','age','sex'])

>>> s2 = Stu('jm',16,'male')

>>> s2.name

'jm'

#reduce

>>> dl = [{'d':3,'a':2,'b':4},{'f':3,'g':2,'b':4},{'d':3,'f':2,'b':4}]

>>> reduce(lambda a,b : a & b ,map(dict.keys,dl))

#deque

>>> from collections import deque

>>> q = deque([],5)

>>> q.append(1)

>>> import pickle

>>> pickle.dump(q,open('save.pkl','wb'))

>>> pickle.load(open('save.pkl','rb'))

deque([1], maxlen=5)

#islice

>>> from functools import islice

>>> list(islice(range(10),4,6))

[4, 5]

>>> def query_by_order(d,a,b=None):

...     a -= 1

...     if b is None:

...             b= a+1

...     return list(islice(d,a,b))

#re.split

>>> re.split('[;,|]+','ab;ffff|gdhgdjh,jfjje')

['ab', 'ffff', 'gdhgdjh', 'jfjje']

#endswith stat os 可执行权限

>>> import stat

>>> import os

>>> for fn in os.listdir():

...     if fn.endswith(('.py','.sh')):

...             fs = os.stat(fn)

...             os.chmod(fn,fs.st_mode | stat.S_IXUSR)

# re.sub 替换字符串

>>> re.sub(r'(\d{4})-(\d{2})-(\d{2})',r'\2/\3/\1',log)

# iterator 和iterable的区别为迭代器只能使用一次，可迭代对象可使用多次
from collections import Iterable, Iterator
import requests

class WeatherIterator(Iterator):
    def __init__(self, caties):
        self.caties = caties
        self.index = 0

    def __next__(self):
        if self.index == len(self.caties):
            raise StopIteration
        city = self.caties[self.index]
        self.index += 1
        return self.get_weather(city)

    def get_weather(self, city):
        url = 'http://wthrcdn.etouch.cn/weather_mini?city=' + city
        r = requests.get(url)
        data = r.json()['data']['forecast'][0]
        return city, data['high'], data['low']

class WeatherIterable(Iterable):
    def __init__(self, cities):
        self.cities = cities

    def __iter__(self):
        return WeatherIterator(self.cities)

def show(w):
    for x in w:
        print(x)

w = WeatherIterable(['北京', '上海', '广州'] * 10)
show(w)

#yield生成器对象自动维护迭代状态

from collections import Iterable

class PrimeNumbers(Iterable):
    def __init__(self, a, b):
        self.a = a
        self.b = b

    def __iter__(self):
        for k in range(self.a, self.b + 1):
            if self.is_prime(k):
                yield k

    def is_prime(self, k):
        return False if k < 2 else all(map(lambda x: k % x, range(2, k)))

pn = PrimeNumbers(1, 30)
for n in pn:
    print(n)

#reversed 反向迭代实现
from decimal import Decimal

class FloatRange:
    def __init__(self, a, b, step):
        self.a = Decimal(str(a))
        self.b = Decimal(str(b))
        self.step = Decimal(str(step))

    def __iter__(self):
        t = self.a
        while t <= self.b:
            yield float(t)
            t += self.step

    def __reversed__(self):
        t = self.b
        while t >= self.a:
            yield float(t)
            t -= self.step

fr = FloatRange(3.0, 4.0, 0.2)
for x in fr:
    print(x)
print('-' * 20)
for x in reversed(fr):
    print(x)