That lets you keep the dependencies for each project separate from each other and from your system installation. Each virtual environment can have its own Python version, separate packages and modules, and other variables. Python lets you create a small virtual environment for each project that you're working on. You should use Python's built-in virtual environments instead. If there is a compatibility problem, it can cause instability or bugs when you try to use Python. Modules and packages sometimes conflict with each other and with the version of Python you have installed on your system. Do not install the modules or packages directly to your "system install" of Python. If you're learning Python, you might be told to install a variety of packages as part of a tutorial. If you're not actively using it, you can ignore this section. This section is only relevant if you're planning on actually coding with Python. Usually someone has encountered it (or something similar) and you'll be able to figure out a solution from there. Your best bet is to try searching the Internet for your specific error. In our Stable Diffusion example, the only way you'd know that Python 3.12 was the problem would be if you knew what Stable Diffusion required and that it wasn't available for Python 3.12 yet. There isn't always an easy way to know what errors occur because of a problem with your Python version and what errors occur because of some other reason. Consequently, if you try to run Stable Diffusion on Python 3.12 you'll get an error about PyTorch being missing. PyTorch (at the time of writing) is not available on Python 3.12. As an example, the AUTOMATIC1111 fork of Stable Diffusion requires PyTorch, a Python library, to run. Other times, you'll get less helpful errors. In those instances, make sure that the correct version of Python is installed and set on your PATH. Sometimes you'll get an error that directly states what version you should be using. In that case, the solution is simple-switch your Python version.
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