Module object is not callable python ошибка

В процессе работы с Python иногда возникает ошибка «TypeError: ‘module’ object is not callable». Эта ошибка обычно происходит, когда разработчик пытается вызвать

В процессе работы с Python иногда возникает ошибка «TypeError: ‘module’ object is not callable». Эта ошибка обычно происходит, когда разработчик пытается вызвать модуль, как функцию.

Пример ошибки:

import math

result = math(5)

В этом коде разработчик пытается вызвать модуль math как функцию, что невозможно и вызывает ошибку TypeError: 'module' object is not callable.

Причина ошибки:

Модули в Python — это файлы, содержащие Python код, которые можно импортировать в другие Python файлы. Они не являются функциями и не могут быть вызваны как функции. Вместо этого, модули предоставляют функции, переменные и классы, которые можно использовать в другом коде после импорта модуля.

Решение ошибки:

Для решения этой ошибки необходимо вызвать функцию, класс или переменную из модуля, а не сам модуль. В приведенном выше примере, если был импортирован модуль math, следует вызвать функцию из этого модуля, а не сам модуль.

Исправленный пример:

import math

result = math.sqrt(5)

В этом коде вызывается функция sqrt() из модуля math, а не сам модуль math. Этот код не вызовет ошибку TypeError: 'module' object is not callable, так как вызывается функция, а не модуль.

В заключение, ошибка «TypeError: ‘module’ object is not callable» в Python обычно указывает на то, что разработчик пытается вызвать модуль, как функцию. Для решения этой ошибки необходимо вызвать функцию, класс или переменную из модуля, а не сам модуль.

I had this error when I was trying to use optuna (a library for hyperparameter tuning) with LightGBM. After an hour struggle I realized that I was importing class directly and that was creating an issue.

import lightgbm as lgb

def LGB_Objective(trial):
        parameters = {
            'objective_type': 'regression',
            'max_depth': trial.suggest_int('max_depth', 10, 60),
            'boosting': trial.suggest_categorical('boosting', ['gbdt', 'rf', 'dart']),
            'data_sample_strategy': 'bagging',
            'num_iterations': trial.suggest_int('num_iterations', 50, 250),
            'learning_rate': trial.suggest_float('learning_rate', 0.01, 1.0),
            'reg_alpha': trial.suggest_float('reg_alpha', 0.01, 1.0), 
            'reg_lambda': trial.suggest_float('reg_lambda', 0.01, 1.0)
            }
        
        '''.....LightGBM model....''' 
        model_lgb = lgb(**parameters)
        model_lgb.fit(x_train, y_train)
        y_pred = model_lgb.predict(x_test)
        return mse(y_test, y_pred, squared=True)

study_lgb = optuna.create_study(direction='minimize', study_name='lgb_regression') 
study_lgb.optimize(LGB_Objective, n_trials=200)

Here, the line model_lgb = lgb(**parameters) was trying to call the cLass itself.
When I digged into the __init__.py file in site_packages folder of LGB installation as below, I identified the module which was fit to me (I was working on regression problem). I therefore imported LGBMRegressor and replaced lgb in my code with LGBMRegressor and it started working.

You can check in your code if you are importing the entire class/directory (by mistake) or the target module within the class.

from lightgbm import LGBMRegressor

def LGB_Objective(trial):
        parameters = {
            'objective_type': 'regression',
            'max_depth': trial.suggest_int('max_depth', 10, 60),
            'boosting': trial.suggest_categorical('boosting', ['gbdt', 'rf', 'dart']),
            'data_sample_strategy': 'bagging',
            'num_iterations': trial.suggest_int('num_iterations', 50, 250),
            'learning_rate': trial.suggest_float('learning_rate', 0.01, 1.0),
            'reg_alpha': trial.suggest_float('reg_alpha', 0.01, 1.0), 
            'reg_lambda': trial.suggest_float('reg_lambda', 0.01, 1.0)
            }
        
        '''.....LightGBM model....''' 
        model_lgb = LGBMRegressor(**parameters) #here I've changed lgb to LGBMRegressor
        model_lgb.fit(x_train, y_train)
        y_pred = model_lgb.predict(x_test)
        return mse(y_test, y_pred, squared=True)

study_lgb = optuna.create_study(direction='minimize', study_name='lgb_regression') 
study_lgb.optimize(LGB_Objective, n_trials=200)

Python is well known for the different modules it provides to make our tasks easier. Not just that, we can even make our own modules as well., and in case you don’t know, any Python file with a .py extension can act like a module in Python. 

In this article, we will discuss the error called “typeerror ‘module’ object is not callable” which usually occurs while working with modules in Python. Let us discuss why this error exactly occurs and how to resolve it. 

Fixing the typeerror module object is not callable error in Python 

Since Python supports modular programming, we can divide code into different files to make the programs organized and less complex. These files are nothing but modules that contain variables and functions which can either be pre-defined or written by us. Now, in order to use these modules successfully in programs, we must import them carefully. Otherwise, you will run into the “typeerror ‘module’ object is not callable” error. Also, note that this usually happens when you import any kind of module as a function.  Let us understand this with the help of a few examples.

Example 1: Using an in-built module

Look at the example below wherein we are importing the Python time module which further contains the time() function. But when we run the program, we get the typeerror. This happens because we are directly calling the time module and using the time() function without referring to the module which contains it.

Output

TypeError                                 Traceback (most recent call last)
Input In [1], in <module>
      1 import time
----> 2 inst = time()
      3 print(inst)

TypeError: 'module' object is not callable

From this, we can infer that modules might contain one or multiple functions, and thus, it is important to mention the exact function that we want to use. If we don’t mention the exact function, Python gets confused and ends up giving this error. 

Here is how you should be calling the module to get the correct answer:

Output

1668661030.3790345

You can also use the dot operator to do the same as shown below-

Output

1668661346.5753343

Example 2: Using a custom module

Previously, we used an in-built module. Now let us make a custom module and try importing it. Let us define a module named Product to multiply two numbers. To do that, write the following code and save the file as Product.py. 

Now let us create a program where we have to call the Product module to multiply two numbers. 

Output

Enter first number: 5
Enter second number: 10
Traceback (most recent call last):
  File "demo.py", line 6, in <module>
    print(Product(a, b))
TypeError: 'module' object is not callable

Why this error occurs this time? 

Well again, Python gets confused because the module as well as the function, both have the same name. When we import the module Product, Python does not know if it has to bring the module or the function. Here is the code to solve this issue:

Output

Enter the cost: 5
Enter the price: 10
50 

We can also use the dot operator to solve this issue. 

Output

Enter the cost: 5
Enter the price: 10
50 

Last Updated :
18 Apr, 2023

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