Ошибка library in ab incompatible

Incompatible Python workflow library

Note: Most workflows which contained a very old affected version of the alfred-workflow library should have been updated by now. If not, the following fix should still work.

Due to an incompatibility between macOS 10.12.4+ and a 3rd party library, Alfred-Workflow, Alfred 3.4.1+ doesn’t load workflows containing older, affected versions of this library.

Disabling these workflows prevents the incompatibility from causing high CPU usage.

How to fix

Install and run the following workflow to automatically update Alfred-Workflow in any affected installed workflows.

[Solved] ImportError: numpy.core.multiarray Failed to Import

In this article, we will take a look at how to solve “ImportError: numpy.core.multiarray failed to import “. We will understand why these kinds of errors occur and what are the possible solutions for them. Let’s get started,

What is Numpy?

NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms introductory linear algebra, basic statistical operations, random simulation and much more.

It is vastly used in data pre-processing and later implemented on ML and DL algorithms. Hence, we can say that it is a much-needed library in the field of data science and also provides bases to several other libraries like pandas, matplotlib e.t.c.

Understanding the error

Understanding the error is one of the significant aspects of programming, as there may be one or more reasons for the error. So, it is essential to know the exact reason for the error and then fix them.

We will discuss significant reasons why this error occurs:

Incompatible Numpy Version

The main reason for occurrence is that we try to import an incompatible version of numpy to build our program. However, there will be several cases in that also, and we will discuss them one by one.

ImportError: numpy.core.multiarray failed to import in cv2 / matplotlib / pyinstaller / pytorch

Let’s try to understand this. Most machine learning and deep learning python libraries like cv2, matplotlib, pyinstaller, PyTorch, etc. Uses numpy for several operations they perform. More often, we need more than one of them to build our program. To meet that requirement, sometimes, we install one module after the other. Subsequently, each module alters the numpy version according to its compatibility.

Now, when we use two or more modules, it might be the case that both the modules use different numpy versions . The system fails to meet the dependable requirement and then raises the “ImportError: numpy.core.multiarray failed to import” error.

Solving issue for cv2 / matplotlib / pyinstaller / pytorch

In this case, we can fix the error by updating the existing numpy and other modules version to the latest version. To do that open the command-line interface in your system and run the following command:

If your python version is python 3.x, then run the following command to uninstall numpy and OpenCV :

Then run the following command to install it again:

If your python version is python 2.x, then run the following command to uninstall numpy and OpenCV :

Then run the following command to install it again:

Now, You can check the numpy, OpenCV, and other versions from python shell.

ImportError: numpy.core.multiarray failed to import in Raspberry Pi

Several times, it happens that we will able to successfully build our model on our local computer or google collab. But when we try to download that model on our Raspberry Pi model, it cannot compile them. This might happen due to the different version of numpy we are using on our local computer or google collab than one installed on the raspberry pi model.

Solving issue for Raspberry pi

To solve this issue, we need to reinstall numpy with the compatible version of the raspberry pi model. To do that, we have to use the following command in CLI of the raspberry pi model:

ImportError: numpy.core.multiarray failed to import in Docker / Shap

In this scenario again, the reason for getting the error is the same, i.e., the numpy version is not compatible with the docker container version or the shap version. This incompatibility is the main reason for the occurrence of error.

There are some data points, according to which:

1.) Python 3.6 works with numpy 1.19 and shap 0.39.

2.) Python 3.9 fails with numpy 1.19 and shap 0.39

3.) Python 3.9 works with numpy 1.20 and shap 0.39

4.)Python 3.9 works with numpy 1.19 and shap 0.38

Solving issue for Docker / Shap

To solve the issue, numpy and the shap version must be compatible with the python version. To do that, first, check the python version using:

After that, we need to install the numpy version and the shap version according to need. To do that, run the following command in CLI:

After completing, run the following command in python shell to check shap and numpy version:

Conclusion

So, before building any program, we should be aware of the libraries and our versions. We should also check the required dependency for the project. I always prefer to work on virtual environments and manage different virtual environments according to the need of the project.

If we are deploying our model to raspberry pi or some other devices, we should ensure the dependencies are successfully installed there and take care of the versions installed.

Решение ошибки «ModuleNotFoundError: No module named ‘…’»

В Python может быть несколько причин возникновения ошибки ModuleNotFoundError: No module named . :

• Модуль Python не установлен.
• Есть конфликт в названиях пакета и модуля.
• Есть конфликт зависимости модулей Python.

Рассмотрим варианты их решения.

Модуль не установлен

В первую очередь нужно проверить, установлен ли модуль. Для использования модуля в программе его нужно установить. Например, если попробовать использовать numpy без установки с помощью pip install будет следующая ошибка:

Для установки нужного модуля используйте следующую команду:

Или вот эту если используете Anaconda:

Учтите, что может быть несколько экземпляров Python (или виртуальных сред) в системе. Модуль нужно устанавливать в определенный экземпляр.

Конфликт имен библиотеки и модуля

Еще одна причина ошибки No module named — конфликт в названиях пакета и модуля. Предположим, есть следующая структура проекта Python: