![]() ![]() It might seem like a hassle to create a virtual environment for every Python project, but it offers enough advantages to do so. A virtual environment is a lightweight Python installation with its own package directories and a Python binary copied (or linked) from the binary used to create the environment. To make sure your packages donât collide, it is recommended that you use a virtual environment. You can simply download and extract code to your project directory, use the package manager from your operating system, or use a tool such as pip to install a package. The Python ecosystem offers many methods of installing and managing packages. Managing dependencies using requirements.txt, poetry, and pipenv.Package installation through pip, poetry, pipenv, and conda.Creating environments using venv, pipenv, poetry, pyenv, and anaconda.To summarize, the following topics will be covered: ![]() Lastly, we will look at several methods of keeping track of project dependencies. In this chapter, youâll learn about the different ways of setting up Python environments for your projects and how to use multiple Python versions on a single system outside of what your package manager offers.Īfter the environment is set up, we will continue with the installation of packages using both the Python Package Index ( PyPI) and conda-forge, the package index that is coupled with Anaconda. 1 Getting Started â One Environment per Project ![]()
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