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优雅的python

优雅的python

作者: 归侠与客 | 来源:发表于2019-04-25 20:48 被阅读0次

    暂时只做笔记,后续整理

    更新一些小技巧:
    自动给数字前补0
    参考:https://www.cnblogs.com/zhanglianbo/p/6202683.html
    Python中有一个zfill函数用来给字符串前面补0,非常有用,这个zfill看起来也就是zero fill的缩写吧,看一下如何使用:

    n = "123"
    s = n.zfill(5)
    assert s == '00123'
    zfill也可以给负数补0:
    
    n = '-123'
    s = n.zfill(5)
    assert s == '-0123'
    对于纯数字也可以通过格式化的方式来补0:
    
    n = 123
    s = '%05d' % n
    assert s == '00123'
    

    20181031更新

    列表和元组比较

    (3,5)<(3,6) => True
    
    [3,5] < [3,6] => True
    

    python风格

    conn = None
    if conn is not None:
        connection = conn
    else:
        connection = 'default'
    =>
    connection = conn if conn is not None else 'default'
    

    class方法

    @classmethod
    
    func(cls):
    
    @staticmethod
    
    func():
    
    func(self):
    

    any(x)判断x对象是否为空对象,如果都为空、0、false,则返回false,如果不都为空、0、false,则返回true

    all(x)如果all(x)参数x对象的所有元素不为0、''、False或者x为空对象,则返回True,否则返回False

    -----------------------------------------------------------
    
    class collections.Counter([iterable-or-mapping])
    
    from collections import Counter
    
    # Tally occurrences of words in a list
    
    cnt = Counter()
    
    for word in ['red', 'blue', 'red', 'green', 'blue', 'blue']:
    
        cnt[word] += 1
    
    cnt
    
    # Find the ten most common words in Hamlet
    
    import re
    
    words = re.findall(r'\w+', open('hamlet.txt').read().lower())
    
    Counter(words).most_common(10)
    
    c['sausage'] = 0                        # counter entry with a zero count
    
    del c['sausage']                        # del actually removes the entry
    
    from collections import namedtuple
    
    Point = nametuple('Point', ['x', 'y'])
    
    p = Point(11, y=22)
    
    p[0], p[1]
    
    p.x, py
    
    t = [11, 22]
    
    p = Point._make(t)
    
    p._asdict()
    
    p._replace(x=33)
    
    p._fields
    
    getattr(p, 'x')
    
    d = {'x': 11, 'y': 22}
    
    Point(**d)
    

    参考网址:https://yiyibooks.cn/xx/python_352/library/collections.html#collections.deque

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