A cloud package repository hosting service at https://www.anaconda.org. With a free account, you can publish packages you create to be used publicly.
Open-source repository of hundreds of popular data science packages, along with the conda package and virtual environment manager for Windows, macOS, and Linux. Conda makes it quick and easy to install, run, and upgrade complex data science and machine learning environments like scikit-learn, TensorFlow, and SciPy.
A software platform for developing, governing, and automating data science and AI pipelines from laptop to production. Enterprise enables collaboration between teams of thousands of data scientists running large-scale model deployments on high-performance production clusters.
A collection of packages at specific versions that are associated with Distribution installers. Anaconda metapackage is used to pull all of the other packages into the installer. It contains several core, low-level libraries, including compression, encryption, linear algebra, and some GUI libraries.
The Anaconda metapackage is useful for creating environments that have all of the Anaconda Distribution packages in them and it has strong effects on conda’s solver behavior.
Read more about the Anaconda metapackage. Read more about the distinctions between Anaconda Distribution and the Anaconda metapackage.
A desktop Graphical User Interface (GUI) included in Anaconda Distribution that allows you to easily use and manage IDEs, conda packages, environments, channels, and notebooks without the need to use the Command Line Interface (CLI).
A location in a repository where conda looks for packages.
Channels may point to a Cloud repository or a private location
on a remote or local repository that you or your organization created.
conda channel command has a default set of channels to search
beginning with https://repo.anaconda.com/pkgs/. You may override
the default channels to, for example, maintain a private or internal
channel. In conda commands and in the
.condarc file, these default
channels are referred to by the channel name
An open-source package and environment manager bundled with Anaconda Distribution that finds, installs, and updates conda packages and their dependencies. Conda also lets you easily switch between conda environments on your local computer.
A tool used to buid conda packages from recipes.
A superset of Python virtual environments, conda environments make it easy to create projects with different versions of Python and avoid issues related to dependencies and version requirements. A conda environment maintains its own files, directories, and paths so that you can work with specific versions of libraries and/or Python itself without affecting other Python projects. For example, you may use one conda environment for only Python 2.7 and Python 2.7 packages, and maintain another conda environment with only Python 3.5 and Python 3.5 packages.
A binary tarball file containing system-level libraries, Python and R modules, executable programs, or other components. Conda tracks dependencies between specific packages and platforms, making it simple to create operating system-specific environments using different combinations of packages.
Instructions used to tell conda-build how to build a package.
A minimal installer for conda. Like Anaconda Distribution, Miniconda is a
free software package that includes the Anaconda Distribution and conda.
Miniconda does not include any packages other than those dependencies needed
to install it. After installing Miniconda, you can install additional conda
packages directly from the command line using
Software files and information about the software, such as its name, the specific version, and a description, that are bundled into a file that can be installed and managed by a package manager. While packages are generally used for files, they can also be used for metadata alone. When it is, it is called a metapackage.
Any storage location from which software or software assets may be retrieved and installed on a local computer.