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188 lines (157 loc) · 3.66 KB
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#########
# 函数式编程
#########
#########
# 高阶函数：函数作为参数传递给函数
#########
def add(x, y, f):
print(f(x) + f(y))
add(-6, 5, abs)
#########
# 高阶函数：
# Iterator map(函数名，Iterable)
# 1.map 函数的好处在于可以清晰的看出两个数据集合之间的映射关系
# 2.reduce(f, [x1, x2, x3, x4]) = f(f(f(x1, x2), x3), x4)
# 可见 reduce 返回值和定义的映射关系类型一致的
#########
# TODO:exe1:大小写转换
# def normalize(name):
# for i in range(len(name)):
# if i == 0:
# str(name[i]).upper()
# else:
# str(name[i]).lower()
# return name
#
#
# L1 = ['adam', 'LISA', 'barT']
# L2 = list(map(normalize, L1))
# print(L2)
# exe2:求和
# from functools import reduce
# def prod(L):
# if L == None or L == []:
# return 0
#
# if len(L) < 2:
# return L[0]
# return reduce(lambda x, y: x * y, L)
#
# print('3 * 5 * 7 * 9 =', prod([3, 5, 7, 9]))
# if prod([3, 5, 7, 9]) == 945:
# print('测试成功!')
# else:
# print('测试失败!')
# # TODO:exe3:浮点数转字符串
# from functools import reduce
#
# DIGITS = {'0': 0, '1': 1, '2': 2, '3': 3, '4': 4, '5': 5, '6': 6, '7': 7, '8': 8, '9': 9}
#
#
# def _aboveZero(x, y):
# return 10 * x + y
#
#
# def _belowZero(x, y):
# return x + y * 0.1
#
#
# # @param s: a list of char
# # @param offset: an integer
# # @return: nothing
# def rotateString(s, offset):
# # write you code here
# if not offset: return
# if not s: return
#
# n = len(s)
# offset = offset % n
#
# for i in range(offset):
# t = s.pop()
# s.insert(0, t)
#
#
# def char2Num(k):
# return DIGITS[k]
#
#
# def str2float(s):
# strArray = s.split('.')
# print(strArray)
# if len(strArray) > 1:
# rotateString(strArray[1], 2)
# print(strArray[1])
# return reduce(_aboveZero, map(char2Num, strArray[0])) + 0.1 * reduce(_belowZero, map(char2Num, strArray[1]))
# else:
# return reduce(_aboveZero, map(char2Num, strArray[0]))
#
#
# print('str2float(\'123.456\') =', str2float('123.456'))
# if abs(str2float('123.456') - 123.456) < 0.00001:
# print('测试成功!')
# else:
# print('测试失败!')
##########
# 装饰器( decorator )：aop 编程：利用 Python 语言函数可传递的特性，在原先函数的执行上包裹并增加新的内容
##########
# def log(text):
# def log(func):
# def wrapper(*args, **kw):
# print('%s call %s():' % (text, func.__name__))
# return func(*args, **kw)
#
# return wrapper;
#
# return log
##########
# functools
##########
import functools
# def log(text):
# def log(func):
# @functools.wraps(func)
# def wrapper(*args, **kw):
# print('%s call %s():' % (text, func.__name__))
# return func(*args, **kw)
#
# return wrapper;
#
# return log
#
# @log('haha')
# def now():
# print('2019-01-15')
#
# now()
##########
# exe 1:打印函数执行时间
##########
from datetime import datetime
import time, functools
def metric(fn):
@functools.wraps(fn)
def wrapper(*args, **kw):
start = datetime.now()
result = fn(*args, **kw)
end = datetime.now()
print('%s executed in %s ms' % (fn.__name__, end - start))
return result
return wrapper
# 测试
@metric
def fast(x, y):
time.sleep(0.0012)
return x + y;
@metric
def slow(x, y, z):
time.sleep(0.1234)
return x * y * z;
f = fast(11, 22)
s = slow(11, 22, 33)
if f != 33:
print('测试失败!')
elif s != 7986:
print('测试失败!')