如何在python中遍历具有相似名称的函数？

Question

如果我有不同的函数，名称中的数字越来越多，我该如何循环遍历它们？例如：

def Func1():
    something something

def Func2():
    something something

def Func3():
    something something

...

def Func456832():
    something something

def Func456833():
    something something

我怎样才能用a循环遍历它们：

for i in range(1,456833):

本质上是这个问题： How do I loop through functions with a for loop?

编辑：因为很多人问，这是我真正的代码：

def write(self):
    with open('distances.txt', 'a') as file:
        file.write('\n'+str(self.distance1))
        file.write('\n'+str(self.distance2))
        file.write('\n'+str(self.distance3))
        file.write('\n'+str(self.distance4))
        file.write('\n'+str(self.distance5))
        file.write('\n'+str(self.distance6))
        file.write('\n'+str(self.distance7))
        file.write('\n'+str(self.distance8))
        file.write('\n'+str(self.distance9))
        file.write('\n'+str(self.distance10))
        file.write('\n'+str(self.distance11))
        file.write('\n'+str(self.distance12))
        file.write('\n'+str(self.distance13))
        file.write('\n'+str(self.distance14))
        file.write('\n'+str(self.distance15))

我意识到这是一种非常糟糕的完成方式，特别是如果我想继续扩大列表。所以我去寻找答案，这似乎是我需要知道的才能解决它。

Edit2：我从哪里获得 self.distanceX：

class NeuralNetwork():
     def __init__(self, inputs, hidden1, hidden2, hidden3, outputs, alpha,it_1,it_2,it_3,it_4,it_5):

    ....

    self.distance1 = [alpha,hidden1,it_1,'train',0,0,0,0,0]
    self.distance2 = [alpha,hidden1,it_1,'test',0,0,0,0,0]
    self.distance3 = [alpha,hidden1,it_1,'dist',0,0,0,0,0]
    self.distance4 = [alpha,hidden1,it_2,'train',0,0,0,0,0]
    self.distance5 = [alpha,hidden1,it_2,'test',0,0,0,0,0]
    self.distance6 = [alpha,hidden1,it_2,'dist',0,0,0,0,0]
    self.distance7 = [alpha,hidden1,it_3,'train',0,0,0,0,0]
    self.distance8 = [alpha,hidden1,it_3,'test',0,0,0,0,0]
    self.distance9 = [alpha,hidden1,it_3,'dist',0,0,0,0,0]
    self.distance10 = [alpha,hidden1,it_4,'train',0,0,0,0,0]
    self.distance11 = [alpha,hidden1,it_4,'test',0,0,0,0,0]
    self.distance12 = [alpha,hidden1,it_4,'dist',0,0,0,0,0]
    self.distance13 = [alpha,hidden1,it_5,'train',0,0,0,0,0]
    self.distance14 = [alpha,hidden1,it_5,'test',0,0,0,0,0]
    self.distance15 = [alpha,hidden1,it_5,'dist',0,0,0,0,0]

编辑：已解决。谢谢大家:)

Answer 1

您需要以更好的方式存储所有这些距离。

class NeuralNetwork():
    def __init__(self, inputs, hidden1, hidden2, hidden3, outputs, alpha,it_1,it_2,it_3,it_4,it_5):
        ....
        self.distance1 = [alpha,hidden1,it_1,'train',0,0,0,0,0]
        self.distance2 = [alpha,hidden1,it_1,'test',0,0,0,0,0]
        self.distance3 = [alpha,hidden1,it_1,'dist',0,0,0,0,0]
        ...

我希望可以用一个列表压缩成：

class NeuralNetwork():
    def __init__(self, inputs, hidden1, hidden2, hidden3, outputs, alpha,it_1,it_2,it_3,it_4,it_5):
        ....
        self.distances = []
        self.distances.append([alpha,hidden1,it_1,'train',0,0,0,0,0])
        self.distances.append([alpha,hidden1,it_1,'test',0,0,0,0,0])
        self.distances.append([alpha,hidden1,it_1,'dist',0,0,0,0,0])
        ...

或者更好：

class NeuralNetwork():
    def __init__(self, inputs, hidden1, hidden2, hidden3, outputs, alpha, *iterations):
        ....
        self.distances = []
        for iteration in interations:
            for type in ['train', 'test', 'dist']:
                self.distances.append([alpha, hidden1, iteration, type, 0, 0, 0, 0, 0])

假设您有 50 万个条目，还涉及其他变量，但想法相同：将它们循环成一个列表。

然后写成：

def write(self):
    with open('distances.txt', 'a') as file:
        for distance in self.distances:
            file.write('\n'+str(distance))

Answer 2

我假设您正在从同一个文件进行迭代，如果是这样...

def a():
    pass

def b():    
    pass

g = globals()

g = g.items()

for i, symbol  in  g:
    if callable(symbol):
        print(i, symbol)

这个输出

('a', <function a at 0x107516c08>)
('b', <function b at 0x1075180c8>)

Answer 3

假设循环在同一个模块，函数在globals()

for i in range(1, 456834):
    globals()["Func{}".format(i)]()

如果函数号不连续，可以过滤命名空间，然后调用

import re

for fctn in sorted(obj for name,obj in globals().items() if re.match(r'Func\d+$' name)):
    fctn()