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Managing environments# With conda, you can create, export, list, remove, and update environments that have different versions of Python and/or packages installed in them. Switching or moving between environments is called activating the environment. You can also share an environment file. There are many options available for the commands described on this page. For a detailed reference on all avai
Note There are many options available for the commands described on this page. For details, see commands. Searching for packages# Use the terminal for the following steps. To see if a specific package, such as SciPy, is available for installation:
Environments# An environment is a directory that contains a specific collection of packages that you have installed. For example, you may have one environment with NumPy 1.7 and its dependencies, and another environment with NumPy 1.6 for legacy testing. If you change one environment, your other environments are not affected. You can easily activate or deactivate environments, which is how you swi
Conda Documentation# Welcome to conda's documentation! Conda provides package, dependency, and environment management for any language. Here, you will find everything you need to get started using conda in your own projects. Install # We recommend the following conda distribtions to install conda:
Conda Documentation# Conda provides package, dependency, and environment management for any language. The following documentation site provides all you need to get started with leveraging the power of conda.
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