下标问题（脚本实例化并从另一个脚本调用）只运行被调用的 function，而不是整个脚本

Question

Goal: From the superscript, per each iteration of the for loop, send a list to a function in the subscript, update that list, exit the function in the subscript, and perform several actions, then onto the next iteration.

Issue: Only the function I call from the superscript is run and not the entire subscript.

CrossValidationSmall.py (superscript)

import subfileTest

data = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J','K']
n = 2

for start in range(0, len(data), n):
    stop = start + n
    test = data[start: stop]
    train = data[:start] + data[stop:]
    subfileTest.set_train_data(train)

subfileTest.py (subscript)

train_data = []

def set_train_data(train):
    global train_data
    train_data = train

print(train_data) #should output the lists each time subfileTest is called.

Expected Output

MacBook-Pro:SmallerEnviromentTest Me$ python CrossValidationSmall.py
['C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
['A', 'B', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
['A', 'B', 'C', 'D', 'G', 'H', 'I', 'J', 'K']
['A', 'B', 'C', 'D', 'E', 'F', 'I', 'J', 'K']
['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'K']
['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J']

Current Output

MacBook-Pro:SmallerEnviromentTest Me$ python CrossValidationSmall.py
[]

Answer 1

From what I understood, you need your subscript to be called in entirety on every iteration.

Here's the thing:

• A new module once found is executed and module from the initial execution is cached .
• When the same module is imported in a different file, the cached version is returned.
• This cached version lives throughout the lifetime of the process.

Since you need you subscript to be run fresh on each iteration, a Class can be used. an object of the class to:

• Store data from each iteration
• Write any number of functions that work with this data
• Retain values from each object as long as you need

Superscript :

from subscript import ModelCrossValidator

trial = 0

data = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
n = 2

for start in range(0, len(data), n):
    trial += 1

    stop = start + n
    test = data[start: stop]

    # train_subset to be used for cross validation
    train_subset = data[:start] + data[stop:]

    cross_validator = ModelCrossValidator(train_subset)
    cross_val_score = cross_validator.calc_score()

print("CrossValSet: {}, Data: {}, Score: {:.2}".format(trial, cross_validator.data, cross_val_score))

Subscript :

import random

class ModelCrossValidator:

    def __init__(self, train_subset):
        self.data = train_subset     # your folded cross-val data
        self.model = None            # can pass in a model too here
        self.accuracy = 0            # other fields that you might need

    def calc_score(self):
        # you can have any number of functions like this.
        # all will deal with only the data from a single object.

        self.accuracy = 0.8 + (random.random()) % 0.2
        return self.accuracy

Output:

Macbook-Pro: chimichanga$ python superscript.py 
CrossValSet: 1, Data: ['C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K'], Score: 0.89
CrossValSet: 2, Data: ['A', 'B', 'E', 'F', 'G', 'H', 'I', 'J', 'K'], Score: 0.94
CrossValSet: 3, Data: ['A', 'B', 'C', 'D', 'G', 'H', 'I', 'J', 'K'], Score: 0.9
CrossValSet: 4, Data: ['A', 'B', 'C', 'D', 'E', 'F', 'I', 'J', 'K'], Score: 0.84
CrossValSet: 5, Data: ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'K'], Score: 0.88
CrossValSet: 6, Data: ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'], Score: 0.94