If for whatever reason you need to use different versions of the same package on different projects, virtual environments will allow you to have both packages on the same system without hassle. Using different versions of the same package This can be easily resolved by installing the conflicting packages in different virtual environments, provided they are not needed for the same project.
The conflict may arise because some packages depend on different versions of the same package. Once in a while, you will come across the awkward situation where some Python packages cannot be installed side-by-side because they conflict. Working with packages that conflict with each other (Activating virtual environments and installing packages from the requirements file will be covered under the How to use virtual environments section. Note that this command should be run after the virtual environment has been activated, otherwise pip will freeze the packages in your main installation of Python. The requirements file can then be used to install the project-specific packages in other virtual environments, thereby simplifying the process of collaborating on the same project. This command will save all the packages in your virtual environment to the file named requirements.txt in the directory where the command was run. For example, the packages in a virtual environment can be stored in a file using the following command: $ pip freeze > requirements.txt The ability to have a clean installation where project-specific packages can be found makes it easy to keep track of those packages, and makes it easy for several developers to work on the same project. Having a single installation of Python means that the packages for each of your projects will be installed in the same location.
Keeping track of the packages required for a particular project The ability to have several installations of virtual environments presents the user with certain advantages, such as: The ability to have virtual installations of Python with their own packages makes virtual environments similar to containers however, unlike containers, virtual environments do not make it possible to assign specific resources to different environments. Programs running in one virtual environment do not interfere with the main installation of Python and other installations of Python. A Python virtual environment is a package that makes it possible to have several virtual installations of Python with their own packages.
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