python.md

Syntax

Function

Decorator

• See: https://www.liaoxuefeng.com/wiki/1016959663602400/1017451662295584

@dec2
@dec1
def func(arg1, arg2, ...):
    pass

is equivalent to:

def func(arg1, arg2, ...):
    pass
func = dec2(dec1(func))

Another example, used to record function's running time:

import time
import functools

def metric(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        t = time.time()
        r = func(*args, **kwargs)
        t = time.time() - t
        print("Function: %s is completed in %ss" % (func.__name__, t))
        return r
    return wrapper
    
@metric
def test(x, y):
    time.sleep(0.1234)
    print("Hello")
    return x + y
    
print(test.__name__)
# test
f = test(11 + 22)
print(f)
# Function: test is completed in 0.1234s
# 33

The decorator @functools.wraps is used to maintain functions' __name__, with this decorator, test.__name__ will become wrapper.

Positional-Only / Keyword-Only Syntax

• / is positional-only symbol, means that all parameters before the / can only be passed by position
• * is keyword-only symbol, means that all parameters after the * can only be passed by keyword

For a function like def test(a, b, /, c, d=1, *, e, f=2)

• a, b can only be passed as postional arguments
• c, d can be passed as positional or keyword arguments
• e, f can only be passed as keywork arguments

Also see:

def f(pos1, pos2, /, pos_or_kwd, *, kwd1, kwd2):
      -----------    ----------     ----------
        |             |                  |
        |        Positional or keyword   |
        |                                - Keyword only
         -- Positional only

Class

@property

• Function decorated by @property is used when get attributes, the value returned will be attributes' value
• Function decorated by @.setter is called when set attributes, usually used for checking legality of values

A example:

class test:
    def __init__(self,):
        self._a = 123
        
    @property
    def a(self,):
        return self._a
    
    @a.setter
    def a(self, value):
        if value >= 100:
            raise ValueError("Cannot larger than 100!")
        self._a = value

t = test()
print(t.a)
# 123
t.a = 13
print(t.a)
# 13
t.a = 111
# Traceback ...
# ...
# ValueError: Cannot larger than 100!