An in-depth analysis of Lambda function usage in Python

A lambda function is a small anonymous function.

lambda syntax

lambda function:

lambda [arg1 [,arg2,...[,argn]]] : expression

• Input: any number of parameters can be accepted, such aslambda : print('hello')，lambda x, y : x * y
• Output: the value calculated by expression;
• Function body: can only be a single line with an expression;
• Functions are anonymous (no function name);

Example 1: A lambda function is similar to a normal function in that it can directly reference (in a readable way) an external variable.

gAll = 10
if __name__ == '__main__':
    count = 2
    result = map(lambda x: x * count + gAll, range(10))
    print(list(result))
# [10, 12, 14, 16, 18, 20, 22, 24, 26, 28]

Example 2: lambda function call (and the expression can be a simple if statement)

result = []
for i in range(10):
    ((lambda x: x * 2 if x % 2 == 0 else x)(i))
print(result)
# [0, 1, 4, 3, 8, 5, 12, 7, 16, 9]

Example 3: lambda delayed calculation caused by the problem (if you do not use the parameter, all prints are 9), in order to avoid this problem, you can pass i in as a parameter (similar to example 2), or directly assign i as a parameter a bit (similar to generating a local variable of the same name):

result = []
for i in range(10):
    # ((lambda: print("lambda:", i))) # all 9s
    ((lambda i=i: print("lambda:", i)))
for f in result:
    f()

(math.) higher order function

The lambda function can be used as the return value of a function to enhance its functionality; take power multiplication as an example:

def powMulti(n):
    return lambda x: x**n
if __name__ == '__main__':
    p = powMulti(2)
    for i in range(10):
        print(p(i))

Built-in higher-order functions

lambda can be easily applied to:

• map(fun, iterable, ...): Shadowing; a generator that operates sequentially on elements of a collection with fun and returns the corresponding result;
• reduce(fun, iterable[, initializer]): accumulate; operate on the set elements sequentially with fun (two arguments) (val = fun(val, ele); val initializes to initializer, or the first element in the set if ignored), returns the final result;
• sorted(iterable[, cmp[, key[, reverse]]]): Sort;
• filter(fun, iterable): Filtering;

src = [(0, 100) for _ in range(10)]
print(src)
dest = sorted(src)
print(dest)
ret = (lambda x, y: x + y, range(10), 10)
print(ret)  # 55

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