函数Function ¶

def pressure(v, t, n):
  """计算理想气体的压力，单位为帕斯卡

  使用理想气体定律：http://en.wikipedia.org/wiki/Ideal_gas_law

  v -- 气体体积，单位为立方米
  t -- 绝对温度，单位为开尔文
  n -- 气体粒子
  """
  k = 1.38e-23  # 玻尔兹曼常数
  return n * k * t / v

def sqrt(a):
    def sqrt_update(x):
        return average(x, a/x)
    def sqrt_close(x):
        return approx_eq(x * x, a)
    return improve(sqrt_update, sqrt_close)

def with_if_statement():
    if cond():
        return true_func()
    else:
        return false_func()

def with_if_function():
    return if_function(cond(), true_func(), false_func())

x = 2
def f():
	print(x)
	x = 3
#UnboundLocalError: local varibale x referenced before assignment

# None is not displayed by the interpreter as the value of an expreesion

>>> print(print(1),print(2))
1
2
None None
# 注意Print的返回值是None

>>> None + 7 
TypeError

def f(a,b):
    return a//b, a%b
x,y=f(10,3)
print(x,y)##单个

x=f(10,3)
print(x)##元组

def improve(update, close , guess=1):
  while not close(guess):
    guess = update(guess)
  return guess

def print_sums(n):
  print(n)
  def f(k):
    return print_sums(n+k)
  return f

g = print_sums(1)
h = g(3)
w = h(5)

print(list(map(lambda x: x ** 2, [1, 2, 3, 4, 5]))) 
# 使⽤ lambda 匿名函数
print(list(map(lambda x, y: x + y, [1, 3, 5, 7, 9], [2, 4, 6, 8, 10])))
# 提供了两个列表，对相同位置的列表数据进⾏相加

def is_even(x):
    return x % 2 == 0

filter(is_even, range(5))

map(square, filter(is_even, range(5)))

def reduce(function, sequence, initial=_initial_missing):
    """
    reduce(function, iterable[, initial], /) -> value

    Apply a function of two arguments cumulatively to the items of an iterable, from left to right.

    This effectively reduces the iterable to a single value.  If initial is present,
    it is placed before the items of the iterable in the calculation, and serves as
    a default when the iterable is empty.

    For example, reduce(lambda x, y: x+y, [1, 2, 3, 4, 5])
    calculates ((((1 + 2) + 3) + 4) + 5).
    """

    it = iter(sequence)

    if initial is _initial_missing:
        try:
            value = next(it)
        except StopIteration:
            raise TypeError(
                "reduce() of empty iterable with no initial value") from None
    else:
        value = initial

    for element in it:
        value = function(value, element)

    return value

from functools import reduce
def my_add(x, y):
    return x + y
reduce(my_add, [1,2,3,4,5])

##
from functools import reduce
s1 = reduce(lambda x, y: x+y, map(lambda x: x**2, range(1,10)))
print(s1)

from functools import reduce

def make_repeater(f, n):
    """Returns the function that computes the nth application of f."""
    >>> add_three = make_repeater(increment, 3)
    >>> add_three(5)
    8
    >>> make_repeater(triple, 5)(1) # 3 * (3 * (3 * (3 * (3 * 1))))
    243
    >>> make_repeater(square, 2)(5) # square(square(5))
    625
    >>> make_repeater(square, 3)(5) # square(square(square(5)))
    390625
    """
    return lambda x: reduce(lambda acc, _: f(acc), range(n), x)

sorted(iterable ,key=None, reverse=False)

def lambda_curry2(func):
"""
    Returns a Curried version of a two-argument function FUNC.
"""
    return lambda x:lambda y: func(x,y)

def curry2(f):
    """Return a curried version of given weo-argument function"""
    def g(x):
        def h(y):
            return f(x,y)
        return h #注意这里不可以加括号
    return g

function sendEmail(from, content, to){
    console.log(`${from} send email to ${to}, content is ${content}`)
}

sendEmail('xx公司', '双11优惠折上5折', 'zhangsan@xx.com')
sendEmail('xx公司', '双11优惠折上5折', 'lisi@xx.com')
sendEmail('xx公司', '双11优惠折上6折', 'wangwu@xx.com')
sendEmail('xx公司', '双11优惠折上6折', 'maliu@xx.com')

// ...

var sendEmailContent = currying(sendEmail)('xx公司')
var sendEmailToS5 = sendEmailContent('双11优惠折上5折')
var sendEmailToS5 = sendEmailContent('双11优惠折上6折')

// 打五折的群组
sendEmailToS5('zhangsan@xx.com')
sendEmailToS5('lisi@xx.com')

// ...

// 打六折的群组
sendEmailToS6('wangwu@xx.com')
sendEmailToS6('maliu@xx.com')

# nonnested lambda
lambda n, i: count_factors(i)
count_factors(n,i)

# nested lambda 
g = lambda x: lambda y : y+1
eight = g(2)(7)

>>> b = lambda x: lambda: x
>>> c = b(88)
>>> c
<function <lambda> at 0x...>

(lambda f: lambda n: 1 if n == 1 else mul(n,f(f)(n-1)))(lambda f: lambda n: 1 if n == 1 else mul(n,f(f)(n-1)))

leaders.sort(key=lambda x: len(x))

li = [1,2,3,4,5]
# 序列中的每个元素加1 
map(lambda x: x+1, li) # [2,3,4,5,6] 
# 返回序列中的偶数
filter(lambda x: x % 2 == 0, li) # [2, 4] 
# 返回所有元素相乘的结果 
reduce(lambda x, y: x * y, li) # 1*2*3*4*5 = 120 

def announce_lead_changes(prev_leader=None):
    """输出两玩家分数差"""
    def say1(score0, score1):
        if score0 > score1:
            leader = 0
        elif score1 > score0:
            leader = 1
        else:
            leader = None
        if leader != None and leader != prev_leader:
            print('Player', leader, 'takes the lead by', abs(score0 - score1))
        return announce_lead_changes(leader)
    return say1

def decorator_function(func):
    def wrapper():
        print("Before function execution")
        func()
        print("After function execution")
    return wrapper

@decorator_function
def greet():
    print("Hello, World!")

#等价于
greet = decorator_function(greet)

import time

def timer(func):
    def wrapper(*args, **kwargs):
        start_time = time.time()
        result = func(*args, **kwargs)
        end_time = time.time()
        print(f"{func.__name__} took {end_time - start_time:.4f} seconds")
        return result
    return wrapper

@timer
def train_model(data):
    # 模拟训练过程
    time.sleep(2)
    print("Training completed")

train_model("dataset")  # 输出：Training completed 和 train_model took 2.0002 seconds

def set_eval_mode(func):
    def wrapper(model, *args, **kwargs):
        model.eval()  # 进入评估模式
        result = func(model, *args, **kwargs)
        model.train()  # 恢复训练模式
        return result
    return wrapper

@set_eval_mode
def evaluate_model(model, data):
    # 评估逻辑
    print("Evaluating model...")

model = ...  # 某个 PyTorch 模型
evaluate_model(model, test_data)  # 自动切换模式

import time
from functools import wraps

def retry(max_retries=3, delay=1):
    def decorator(func):
        @wraps(func)
        def wrapper(*args, **kwargs):
            for attempt in range(max_retries):
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    print(f"Attempt {attempt + 1} failed: {e}")
                    time.sleep(delay)
            raise RuntimeError(f"Failed after {max_retries} retries")
        return wrapper
    return decorator

@retry(max_retries=3, delay=1)
def fetch_data(url):
    # 模拟可能失败的 HTTP 请求
    if "fail" in url:
        raise ConnectionError("Failed to fetch data")
    return {"data": "..."}

fetch_data("https://example.com/data")  # 成功
fetch_data("https://example.com/fail")  # 重试 3 次后报错

names = ["Alice", "Bob", "Charlie"]
scores = [85, 92, 78]

for name, score in zip(names, scores):
    print(f"{name}: {score}")

# 输出：
# Alice: 85
# Bob: 92
# Charlie: 78

keys = ["a", "b", "c"]
values = [1, 2, 3]
d = dict(zip(keys, values))
print(d)  # {'a': 1, 'b': 2, 'c': 3}

matrix = [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
]
transposed = list(zip(*matrix))
print(transposed)  # [(1, 4, 7), (2, 5, 8), (3, 6, 9)]

long = [1, 2, 3, 4, 5]
short = ["a", "b", "c"]
result = list(zip(long, short))
print(result)  # [(1, 'a'), (2, 'b'), (3, 'c')]

names = ["Alice", "Bob", "Charlie"]
for i, (name, score) in enumerate(zip(names, scores)):
    print(f"{i}: {name} -> {score}")
# 输出：
# 0: Alice -> 85
# 1: Bob -> 92
# 2: Charlie -> 78

pairs = [("a", 1), ("b", 2), ("c", 3)]
letters, numbers = zip(*pairs)
print(letters)  # ('a', 'b', 'c')
print(numbers)  # (1, 2, 3)

vector1 = [1, 2, 3]
vector2 = [4, 5, 6]

sums = [x + y for x, y in zip(vector1, vector2)]
print(sums)  # [5, 7, 9]

from itertools import zip_longest

long = [1, 2, 3, 4]
short = ["a", "b"]

result = list(zip_longest(long, short, fillvalue="NULL"))
print(result)  # [(1, 'a'), (2, 'b'), (3, 'NULL'), (4, 'NULL')]

exec('print("hello world")')
while True:
    line = input()
    if 'bye' in line:
        break
    exec(line)

def interleaved_sum(n, odd_func, even_func):
    """Compute the sum odd_func(1) + even_func(2) + odd_func(3) + ..., up
    to n.

    >>> identity = lambda x: x
    >>> square = lambda x: x * x
    >>> triple = lambda x: x * 3
    >>> interleaved_sum(5, identity, square) # 1   + 2*2 + 3   + 4*4 + 5
    29
    >>> interleaved_sum(5, square, identity) # 1*1 + 2   + 3*3 + 4   + 5*5
    41
    >>> interleaved_sum(4, triple, square)   # 1*3 + 2*2 + 3*3 + 4*4
    32
    >>> interleaved_sum(4, square, triple)   # 1*1 + 2*3 + 3*3 + 4*3
    28
    >>> from construct_check import check
    >>> check(HW_SOURCE_FILE, 'interleaved_sum', ['While', 'For', 'Mod']) # ban loops and %
    True
    >>> check(HW_SOURCE_FILE, 'interleaved_sum', ['BitAnd', 'BitOr', 'BitXor']) # ban bitwise operators, don't worry about these if you don't know what they are
    True
    """
    def inter(k,state):
        if k > n:
            return 0
        elif state == True:
            return odd_func(k) + inter(k+1,not state)
        else:
            return even_func(k) + inter(k+1,not state)
    return inter(1,True)

from operator import sub, mul

def make_anonymous_factorial():
    """Return the value of an expression that computes factorial.

    >>> make_anonymous_factorial()(5)
    120
    >>> from construct_check import check
    >>> # ban any assignments or recursion
    >>> check(HW_SOURCE_FILE, 'make_anonymous_factorial',
    ...     ['Assign', 'AnnAssign', 'AugAssign', 'NamedExpr', 'FunctionDef', 'Recursion'])
    True
    """
    return (lambda f: lambda x: f(f,x))(lambda f,x: 1 if x == 1 else mul(x,f(f,sub(x,1))))

return (lambda f: lambda x: f(f, x))(
           lambda f, x: 1 if x == 1 else mul(x, f(f, sub(x, 1)))
       )

(lambda f: lambda x: f(f, x))

lambda f, x: 1 if x == 1 else mul(x, f(f, sub(x, 1)))