environ- ment, and then downloading and extracting the .zip file and its dependencies—all with the single conda install [packagename] command. 1.3 Getting started with conda Conda is a powerful package - http://some.custom/channel - file:///some/local/directory - defaults To select channels for a single environment, put a .condarc file in the root directory of that environment (or use the --env option of its values: conda config --remove-key channels To configure channels and their priority for a single environment, make a .condarc file in the root directory of that environment. 1.5.2 Sample .condarc

environ- ment, and then downloading and extracting the .zip file and its dependencies—all with the single conda install [packagename] command. 1.3 Getting started with conda Conda is a powerful package - http://some.custom/channel - file:///some/local/directory - defaults To select channels for a single environment, put a .condarc file in the root directory of that environment (or use the --env option of its values: conda config --remove-key channels To configure channels and their priority for a single environment, make a .condarc file in the root directory of that environment. 1.5.2 Sample .condarc

The metapackage is what allows us to achieve the mutual exclusivity. It unifies the options on a single package name, but with a different build string. Automating the addition of the metapackage with "python", etc. version (Optional) Package version. May include the * wildcard or a version range(s) in single quotes. For example: numpy=1.17.* returns all numpy packages with a version containing "1.17." and namespace and distributed ownership of that namespace. Because of this, it is easier within PyPI to have single sources for a package directly from package maintainers. Conda has unlimited namespaces (channels)

The metapackage is what allows us to achieve the mutual exclusivity. It unifies the options on a single package name, but with a different build string. Automating the addition of the metapackage with "python", etc. version (Optional) Package version. May include the * wildcard or a version range(s) in single quotes. For example: numpy=1.17.* returns all numpy packages with a version containing "1.17." and namespace and distributed ownership of that namespace. Because of this, it is easier within PyPI to have single sources for a package directly from package maintainers. Conda has unlimited namespaces (channels)

Installing conda packages with the system package manager makes it very easy to distribute conda across a cluster of machines running Linux without having to worry about any non-privileged user modifying the installation your project more self-contained as everything, including the required software, is contained in a single project directory. An additional benefit of creating your project’s environment inside a subdirectory of its values: conda config --remove-key channels To configure channels and their priority for a single environment, make a .condarc file in the root directory of that environment. Sample .condarc file

Installing conda packages with the system package manager makes it very easy to distribute conda across a cluster of machines running Linux without having to worry about any non-privileged user modifying the installation your project more self-contained as everything, including the required software, is contained in a single project directory. 4.1. User guide 23 conda, Release 24.5.1.dev1 An additional benefit of creating of its values: conda config --remove-key channels To configure channels and their priority for a single environment, make a .condarc file in the root directory of that environment. Sample .condarc file

The metapackage is what allows us to achieve the mutual exclusivity. It unifies the options on a single package name, but with a different build string. Automating the addition of the metapackage with "python", etc. version (Optional) Package version. May include the * wildcard or a version range(s) in single quotes. For example: numpy=1.17.* returns all numpy packages with a version containing "1.17." and namespace and distributed ownership of that namespace. Because of this, it is easier within PyPI to have single sources for a package directly from package maintainers. Conda has unlimited namespaces (channels)

Installing conda packages with the system package manager makes it very easy to distribute conda across a cluster of machines running Linux without having to worry about any non-privileged user modifying the installation your project more self-contained as everything, including the required software, is contained in a single project directory. 4.1. User guide 23 conda, Release 24.1.2.dev2 An additional benefit of creating of its values: conda config --remove-key channels To configure channels and their priority for a single environment, make a .condarc file in the root directory of that environment. Sample .condarc file

Installing conda packages with the system package manager makes it very easy to distribute conda across a cluster of machines running Linux without having to worry about any non-privileged user modifying the installation your project more self-contained as everything, including the required software, is contained in a single project directory. 4.1. User guide 23 conda, Release 24.3.1.dev2 An additional benefit of creating of its values: conda config --remove-key channels To configure channels and their priority for a single environment, make a .condarc file in the root directory of that environment. Sample .condarc file

Installing conda packages with the system package manager makes it very easy to distribute conda across a cluster of machines running Linux without having to worry about any non-privileged user modifying the installation your project more self-contained as everything, including the required software, is contained in a single project directory. 4.1. User guide 23 conda, Release 24.3.1.dev7 An additional benefit of creating of its values: conda config --remove-key channels To configure channels and their priority for a single environment, make a .condarc file in the root directory of that environment. Sample .condarc file