- PyTorch 1.x Reinforcement Learning Cookbook
- Yuxi (Hayden) Liu
- 191字
- 2021-06-24 12:34:37
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Some of you may question the necessity of installing Anaconda and using conda to manage packages since it is easy to install packages with pip. In fact, conda is a better packaging tool than pip. We mainly use conda for the following four reasons:
- It handles library dependencies nicely: Installing a package with conda will automatically download all of its dependencies. However, doing so with pip will lead to a warning, and installation will be aborted.
- It solves conflicts of packages gracefully: If installing a package requires another package of a specific version (let's say 2.3 or after, for example), conda will update the version of the other package automatically.
- It creates a virtual environment easily: A virtual environment is a self-contained package directory tree. Different applications or projects can use different virtual environments. All virtual environments are isolated from each other. It is recommended to use virtual environments so that whatever we do for one application doesn't affect our system environment or any other environment.
- It is also compatible with pip: We can still use pip in conda with the following command:
conda install pip
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