ImportError：无法在 python 中导入名称

Question

我正在尝试为业务分析创建 python 模块。 我创建了这些 python 文件：

1. 主文件
2. export_to_csv（用于将数据保存到文件中）
3. 平稳性（用于平稳性测试和差分）

这些文件位于同一文件夹中。

export_to_file 中的代码：

import json
import csv


def save_to_json(data: dict, title: str):
    with open(f"{title}.json", mode="w", encoding="UTF-8") as file:
        json.dump(data, file, indent=4, ensure_ascii=False)



def save_to_csv(data: dict, title: str, first_row: list):
    with open(title, "w", encoding="UTF-8", newline="") as file:
        writer = csv.writer(file, delimiter=";")
        writer.writerow(first_row)
    
    for var, val in data.item():
        with open(title, "a", encoding="UTF-8", newline="") as file:
            writer = csv.writer(file, delimiter=";")
            writer.writerow([var, *val])

将模块导入到我的主文件中使用函数时，python 显示导入错误：

ImportError: cannot import name 'save_to_json' from 'export_to_file' (c:\Users\user\Desktop\123\python\export_to_file.py)

主文件代码：

import openpyxl
import pandas as pd
from export_to_file import save_to_csv
from stationarity import stationarity_test


book = openpyxl.open(r"C:\Users\user\Desktop\123\data.xlsx")
sheet = book.active


# get data from table
data = {}
i = 0
for col in sheet.iter_cols(min_row=2, max_row=24, min_col=2, max_col=315):
    values = []
    for cell in col:
        if cell.value is None:
            values.append(0)
        else:
            values.append(cell.value) 
    values = pd.Series(values)
    var = values[0]
    data[var] = values[1:]
    i += 1


# stationarity test and differencing
pvalues, stationary_data = stationarity_test(data)

first_row_pvalue = ["variable", "p-value", "d1_p_value", "d2_p-value", "d3_p-value", "d4_p-value"]
first_row_data = ["years", 2000,    2001,   2002,   2003,   2004,   2005,   2006,   2007,   2008,   2009,   2010,   2011,   2012,   2013,   2014,   2015,   2016,   2017,   2018,   2019,   2020,   2021]
save_to_csv(pvalues, "stationarity.csv", first_row_pvalue)
save_to_csv(stationary_data, "stationary_data.csv", first_row_data)

第三个文件代码：

import pandas as pd
from statsmodels.tsa.stattools import adfuller


# differencing
def difference(dataset, interval=1):
    diff = list()
    for i in range(interval, len(dataset)):
        value = dataset[i] - dataset[i - interval]
        value = pd.Series(value)
        diff.append(value)
    return diff


# function removing 0 from the beginning and end in dataset
def clear_zeros(dataset):
    for i in dataset:
        if i == 0:
            dataset = dataset[1:]
        else:
            break
    for i in dataset[::-1]:
        if i == 0:
            dataset = dataset[:-1:]
        else:
            break
    return dataset


# check stationarity
# if non-stationary => differencing
def stationarity_test(data):
    data_pvalues = {}
    data_stationary = {}

    for var, val in data.items():
        v = clear_zeros(val)
        res = adfuller(v, maxlag=0)
        stationary_data = [var, *val]
        
        res2 = [0, None]
        res3 = [0, None]
        res4 = [0, None]
        res5 = [0, None]

        if res[1] > 0.05:
            d1val = difference(v)
            res2 = adfuller(d1val, maxlag=0)
            var = var + "1"
            stationary_data = [var, 0, *d1val]
            if res2[1] > 0.05:
                d2val = difference(d1val)
                res3 = adfuller(d2val, maxlag=0) 
                var = var[:-1:] + "2"
                stationary_data = [var, 0, 0, *d2val]
                if res3[1] > 0.05:
                    d3val = difference(d2val)
                    res4 = adfuller(d3val, maxlag=0)
                    var = var[:-1:] + "3"
                    stationary_data = [var, 0, 0, 0, *d3val]
                    if res4[1] > 0.05:
                        d4val = difference(d3val)
                        res5 = adfuller(d4val, maxlag=0)
                        var = var[:-1:] + "4"
                        stationary_data = [var, 0, 0, 0, 0, *d4val]
                    
        pvalues = [var, res[1], res2[1], res3[1], res4[1], res5[1]]

        data_pvalues[pvalues[0]] = pvalues[1:]
        data_stationary[stationary_data[0]] = stationary_data[1:]
    
    return data_pvalues, data_stationary  

我尝试执行以下操作：

1. 修改了导入文件的位置，第二个文件也有同样的问题
2. 从所有文件中删除 pandas，但没有帮助
3. 用谷歌搜索，它说可能是拼写错误或循环依赖。 拼写正确，我找不到循环依赖。

Answer 1

你所做的是正确的，只是文件名在 main.py 中是错误的，更正它并且代码可以正常工作

从同一目录的单独文件导入和调用 function 的一般语法：

主要文件：

from function_file import function_name

function_name(arguments)

function_file.py 将是其中定义了 function_name 方法的文件。

注意：当您使用文件夹来保存代码时，您需要使用文件夹名称，例如 stats 是我的文件夹，然后存储 function_file.py

from stats.function_file import function_name