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Anaconda.org

Anaconda.org is a public package hosting service, established and maintained by Anaconda. It is a web-based repository that provides a method for hosting your packages so they can be publicly accessed and used. For more information and usage instructions, see Anaconda.org.

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Anaconda Client CLI

The Anaconda Client command line interface (CLI) allows you to log in to Anaconda.org directly from your terminal window and manage your account. It is not necessary for downloading or installing packages from Anaconda.org.

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Anaconda Distribution

A downloadable, open-source, high-performance, optimized Python distribution with 300+ packages automatically included. Anaconda Distribution provides the option to easily install an additional 7,500+ open-source packages for data science, including advanced and scientific analytics. Anaconda Distribution includes conda, Python, Anaconda Navigator, and over 300 additional data science and machine learning packages. Anaconda Distribution is available for Windows, macOS, and Linux. After installing Anaconda Distribution, you can install thousands of additional open source packages contained in the Anaconda repository with the following command: 
# Replace <PACKAGE> with the name of the desired package
conda install <PACKAGE>
For more information on Anaconda Distribution, see Anaconda Distribution. For information on licensing, see our Terms of Service.

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Anaconda metapackage

A collection of packages at specific versions that are associated with Anaconda 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. For more information on the Anaconda metapackage, see Anaconda metapackage. For more information about the distinctions between Anaconda Distribution and the Anaconda metapackage, see the Anaconda blog, What’s in a Name? Clarifying the Anaconda Metapackage.

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Anaconda Navigator

A desktop graphical user interface (GUI) included in all versions of Anaconda that allows you to easily manage conda packages, environments, channels, and notebooks without the need to use the command line interface (CLI). For more information on Anaconda Navigator, see Anaconda Navigator.

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Anaconda Notebooks

Anaconda Notebooks is a hosted JupyterLab service, powered by PythonAnywhere, that enables you to run JupyterLab notebooks reliably online. The Notebooks service provides you with a hosted JupyterLab instance running in a dedicated JupyterHub environment, persistent cloud storage, pre-configured conda environments with common data science packages, and the ability to create your own custom environments.

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Anaconda’s premium repository

A curated package repository that contains all of the packages in Anaconda’s public repository, but with added security and governance features, including:
  • Identification of packages with known CVEs, with scores and Anaconda-assigned statuses
  • Ongoing tracking of CVEs
  • Anti-tampering package signatures
  • Package software bills of materials (SBOMs)

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Anaconda Prompt

Anaconda provides a set of command line interface (CLI) applications with Windows installations of Anaconda Distribution and Miniconda that open with conda’s base environment activated by default for ease of use.
  • Instead of Command Prompt, use Anaconda Prompt.
  • Instead of Powershell, use Anaconda Powershell Prompt.
If you prefer to continue to use Command Prompt or Powershell instead of the Anaconda supplied shell applications, you can activate conda in your shell by running one of the following commands, depending on your installation: 
# Replace <PATH-TO-CONDA> with the path to your conda installation
<PATH-TO-CONDA>\anaconda3\Scripts\activate.bat

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Channels

A channel is a location in a repository where conda searches for packages to install in environments. Channels can be defined as either URLs or file paths, depending on your setup.

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Command line interface (CLI)

A CLI is a text-based method for interacting with software or a computer system. CLIs let you run programs by entering commands that the computer executes, as opposed to using graphical elements such as buttons or windows. Conda itself is a CLI tool, meaning you can interact with it through shell applications like Anaconda Prompt (Terminal on macOS/Linux).

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Conda

Conda is an open-source package and environment manager included with Anaconda Distribution and Miniconda. It installs, updates, and removes packages—along with their dependencies—inside isolated environments that it creates, allowing you to use multiple versions of the same software without conflicts. You can interface with conda at the command line or by using Anaconda Navigator. For detailed technical information about conda, see the official conda documentation.

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Conda-build

A command line tool for building conda packages from recipes.

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Conda recipe

Instructions used to tell conda-build how to build a package.

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Conda repository

A cloud-based repository that contains 720+ open source certified packages that are easily installed locally via the conda install command. Can be viewed directly at https://repo.anaconda.com/pkgs/ and used within Anaconda Navigator when downloading and installing packages from the Environments tab, or by using conda commands in a CLI.

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Common Vulnerabilities and Exposures (CVEs)

A CVE is a public identifier for a known security vulnerability in software. Each CVE entry provides a standardized reference that makes it easier to share data across security tools and organizations. CVEs are paired with a severity score to help prioritize fixes. To learn more about CVE’s and how Anaconda mitigates and manages them, watch the State of Data Science webinar.

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Deployment

A deployed Anaconda project containing a Notebook, web app, dashboard, or machine learning model (exposed via an API). When you deploy a project, Data Science & AI Workbench builds a container with all the required dependencies and runtime components—the libraries on which the project depends in order to run—and launches it with the security and access permissions defined by the user. This allows you to easily run and share the application with others.

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Environments

Environments in conda are self-contained, isolated spaces where you can install specific versions of software packages, including dependencies, libraries, and Python versions. This isolation helps avoid conflicts between package versions and ensures that your projects have the exact libraries and tools they need.

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Graphical user interface (GUI)

A program with graphic images, icons, and menus into which commands are entered by clicking with a mouse and/or entering text in edit boxes. Anaconda Navigator is a graphical user interface that overlays the conda utility.

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Interactive data application

Visualizations with sliders, dropdowns, and other widgets that allow users to interact with them. Interactive data applications can drive new computations, update plots, and connect to other programmatic functionality.

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Integrated development environment (IDE)

A suite of software tools that combines everything a developer needs to write and test software. It typically includes a code editor, a compiler or interpreter, and a debugger that the developer accesses through a single Graphical User Interface (GUI). An IDE can be installed locally, or it can be included as part of one or more existing and compatible applications accessed through a web browser.

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Label

Part of the URLs on Anaconda.org where conda looks for packages. Labels are searched only if you specify a label. The default label is main, so packages that are uploaded without specifying a label are automatically labeled main. The version labeled main is also downloaded by default, unless you specify a different label. For example, the following repositories are equivalent: 
https://anaconda.org/sean/labels/main
https://anaconda.org/sean
Commands such as conda install can be used with a channel or used with a channel and a label: 
conda install --channel sean selenium
conda install --channel sean/label/dev selenium
conda install --channel sean/label/stable selenium

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Miniconda

Miniconda is a lightweight version of Anaconda Distribution run from a CLI that only includes conda, Python, and their dependencies. Once Miniconda is installed, you can install additional conda packages directly from the CLI with the following command: 
# Replace  <PACKAGE> with the name of the package you want to install in your environment
conda install <PACKAGE>
For more information on Miniconda, see Miniconda. For information on licensing, see our Terms of Service.

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Mirror

Mirroring is the process of copying data from a source and then storing it in a new location, often on a scheduled basis. When the mirror’s source updates its contents, the mirror’s contents update to match the next time it runs. It is possible to mirror just a subset of the source’s contents as well, if the source contains more data than you need or can store.

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Namespace

Each user and organization has their own location called a “namespace” where they can host packages. You can view the public packages in a user or organization’s namespace by navigating to their user page. EXAMPLE: The travis user namespace located at https://anaconda.org/travis contains packages that were uploaded and shared by the user whose account is named travis.

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Noarch package

Noarch packages are not built specific to a particular CPU architecture or operating system, so they can be installed on any machine.

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Packages

Packages are bundles of software files along with information about the software, such as its name, version, and description, that can be installed and managed by a package manager. Some packages consist only of metadata, with no software of their own. These are called metapackages. Their role is to pull in related packages so they can be installed and managed together.

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Package manager

A collection of software tools that automates the process of installing, updating, configuring, and removing packages. Also known as a package management system. Anaconda Navigator includes the conda package manager with a GUI overlay for ease of use. Anaconda.org supports two package managers: conda and pip.

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Parameters

Model parameters are the weights and biases it learns during training. The more parameters a model has, the better its ability to learn, but the more tightly it will conform to its training data.

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Project template

Contains all the base files and components to support a particular programming environment. For example, a Python Spark project template contains everything you need to write Python code that connects to Spark clusters. When creating a new project, you can select a template that contains a set of packages and their dependencies.

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Quantization Method

Quantization balances a model’s parameters. This is done to make the model either more efficient in terms of memory usage, or more robust and accurate. Think of this like taking a 300-page manual and condensing it down to 100, 50, or 30 pages of the most important information.

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R package

An R package is a bundle of code, data, and documentation written in the R language that extends its functionality. For more information about R, see Using R language with Anaconda.

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Repository

Any storage location from which software or software assets, like packages, can be retrieved and installed on a local computer. See also: Anaconda Premium Repository and conda repository.

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REST API

A common way to operationalize a machine learning model is through a REST API. A REST API is a web server endpoint, or callable URL, which provides results based on a query. REST APIs allow developers to create applications that incorporate machine learning and prediction, without having to write models themselves.

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Session

A time-bounded context that keeps user identity and state across requests. A session starts when a user (or service) authenticates or starts a runtime, and ends at sign-out, timeout, or termination. Sessions can hold permissions, environment settings, and runtime/process information.

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Token

A token is a randomly generated string used for authentication or access control. It represents proof of identity and permissions, allowing systems to access resources such as repository channels or APIs.