How to correctly repair "broken" / stopped working modules Python?

After a long "rake-in" (under both UNIX* and Windows) I decided on the following approach, which has never failed me so far.

The basic idea is to install the Anaconda package and create independent virtual environments using the package manager conda.

Anaconda checks the compatibility of module versions (including dependencies). This minimizes the chance of breaking Python by simply installing or updating a certain module(s).

The algorithm for installing Anaconda and creating a VirtualEnv (independent Python virtual environment):

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1. Installing Anaconda or Miniconda
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• Installing on Windows
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• Installing on Linux
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• Installing on macOS
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   We are updating the package manager conda (NOTE: to avoid problems - always run conda from Anaconda Prompt):

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    conda update condan

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   Never "touch" Python installed by default in the OS or installed by other software (for example, when installing Oracle Database, a separate Python is installed that will be used by Oracle). By "do not touch" Python, I mean making any changes affecting Python or its modules:

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• installing new modules
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• updating Python
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• updating modules
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   Do not install modules in the base virtual environment created by default. Install modules only in those virtual environments that you have explicitly created (see the next point - 5). The base virtual environment is a technical environment created by conda to manage other virtual environments. If you don't want to break all the virtual environments at once, don't touch base.

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   Create an independent virtual environment (VirtualEnv) for each more or less independent Python project. You can additionally create one common environment for common purposes. In this example, I will create a common environment called ml (Machine Leaing) for Python 3.7 and a basic set of modules for working on machine leaing tasks (with Nvidia GPU support):

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    conda create --name ml python=3.7 anaconda keras-gpun

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   To run Python / Jupyter / IPython / etc. you can use one of the following monitors from the created VirtualEnv:

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  launch Anaconda Prompt --> activate the desired software in it. environment (conda activate ) --launch ipython / Jupyter-Notebook

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  use the CMD/shell script to run ipython from the desired vm. environments:

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   @echo offn set conda_dir=%USERPROFILE%\Anaconda3n set env_name=%1n if1n if ""%env_name%"""%env_name%""=="""" set env_name=mln      set env_dir=%conda_dir%\envs\%env_name%n      rem cd %      rem cd %env_dir%n      call %conda_dir%\Scripts\activate.bat %env_dir%n%env_dir%\Scripts\ipython.exen Example call: `c:\bin\ipy_env.cmd ml37'n

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  use CMD/shell script to run Jupyter-Notebook from the desired wirth. environments:

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   @echo offn set env_name=%1n if>n if ""%env_name%""ame%""=="""" set env_name=mln      set env_dir=%USERPROFILE%\Anaconda3\envs\%env_name%n      rem cd %env_dir%n      callir%n      call %USERPROFILE%\Anaconda3\Scripts\activate.bat %env_dir%n start cmd.exe /k ""%USERPROFILE%\Anaconda3\envs\%env_name%\Scripts\jupyter-notebook.exe ""n Example calling: `C:\bin/span>\jupyter_env.cmd torch'n

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  for a project in PyCharm, you can specify an existing Conda Environment

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