Environment operations

Regular environments

Environment type	Discover	Create	Select	Delete
Base environment	Yes	No	Yes	No
Named environment	Yes	Yes	Yes	Yes
Project .conda prefix	Yes	Interactive only	Yes	Yes
Other conda prefix	Yes when discovered or resolved	Outside Conda Code	Yes	No
conda installation prefix	Yes when discovered	Outside Conda Code	Yes	No
conda-global tool prefix	No	No	No	No
conda-exec cache prefix	No	No	No	No
.pixi/envs prefix	No	No	No	No

Regular discovery combines these sources:

• the configured executable, its validated installation root, and default environment directories

• ~/.conda/environments.txt

• conda installation roots found through conda executables located inside them, relevant CONDA environment variables, and standard installation locations

• prefixes resolved explicitly from a prefix path or Python executable

• cached conda info --json details when available

For each known installation, Conda Code inspects the installation root and the direct children of its environment directories. It does not recursively scan arbitrary directories.

Ordinary regular discovery is process-free. Unchanged results are reused when the discovery filesystem fingerprint is unchanged, and overlapping refresh requests are coalesced. Missing or stale conda info --json details are loaded as optional background enrichment. Conda Code watches the exact configuration files reported by conda. A live change schedules one forced background enrichment. A lightweight fingerprint of those files, relevant conda environment inputs, and the configured executable detects changes made while VS Code was closed. The 24-hour cache age remains a fallback for sources that conda had not reported.

Conda Code determines a prefix’s owning installation from its installation layout or conda-meta/history. It then applies the same Base, Named, and Prefix classification used by the Python Environments conda provider for ordinary conda environments. The owning installation root is Base, environments named by conda or found directly below an owner’s environment directory are Named, and other owned environments are Prefix. To preserve the Python Environments view behavior, an ownerless discovered environment with Python also appears under Named using its directory name.

An owning conda executable provides conda hook activation from the owner root and handles regular package changes and deletion. A prefix without an owning conda executable remains visible and selectable, but Conda Code refuses to mutate it. The primary configured conda remains the route for creation, workspaces, tasks, and plugin features.

Workspace environments do not participate in ordinary environment classification. conda-global tool prefixes, conda-exec cache prefixes, and Pixi-owned prefixes remain excluded from regular discovery and explicit resolution.

Project environment files are creation inputs, not discovery inputs. See Project creation. After creation, the regular named environment is visible after discovery finds its prefix.

Environments without Python remain visible with a warning. Conda Code reads Python version data from conda-meta rather than starting the interpreter.

SBOM export

Run Conda Code: Export Environment SBOM from the Command Palette to export the selected Conda Code environment. The save dialog proposes <environment>.cdx.json, then Conda Code runs the routed conda executable against the exact installed prefix:

conda export --prefix PREFIX --from-history --format cyclonedx-json-v1.7 --file FILE

This command requires conda-sboms 0.3.0 or newer in the routed conda installation. Regular environments use their owning conda installation and export is refused when no usable owner executable is known. Workspace environments use the configured primary conda installation. Conda Code delegates CycloneDX generation and serialization to the plugin.

Workspace environments

State	Discover	Install through Create	Select	Delete
Installed with Python	Yes	Already installed	Declaring Python project only	Clean prefix
Installed without Python	Yes, with warning	Already installed	Declaring Python project only	Clean prefix
Declared but not installed	No	Yes	No	Not applicable
Prefix claimed by multiple manifests	No	No	No	No

Deleting a workspace environment runs the workspace clean operation. It does not remove the declaration from the manifest.

Creation behavior

Context	Quick Create	Interactive Create
Existing workspace	Install a declared environment	Choose an uninstalled declaration when needed
One recognized project input	Create a named environment from it	Choose the input, workspace, .conda, or named environment
Several recognized project inputs	Fail	Choose an input, workspace, .conda, or named environment
Registered project without an input	Create conda.toml and install its default environment	Choose workspace, .conda, or named environment
Pixi workspace without an input when Pixi Code is installed	Refused	Project .conda or named environment
Global or multiple projects	Create an available named environment	Create a named environment

New regular environments created without a project input and new workspaces include Python unless the requested package list already contains a Python specification.

When conda-workspaces provides a complete snapshot, Quick Create adds Python and other requested packages directly to the selected environment. With the 0.7-compatible metadata, Conda Code can add them only when the environment is backed by exactly one feature. Metadata from 0.7 cannot distinguish a default environment from an isolated environment when its feature list is empty, so zero-feature and composed environments must be edited directly.

CEP 24 inputs supply their own package set and may receive additional creation packages afterward. Exact inputs refuse additional packages and disable configured default packages.

Execution

Regular environments with an identified owner and workspace environments advertise the same conda shell activation and deactivation commands for Bash, Zsh, POSIX sh, Fish, PowerShell Core (pwsh), Git Bash, and Command Prompt. Workspace activation targets the exact installed prefix through the configured conda installation used for workspace discovery.

Direct execution still uses the environment’s absolute Python interpreter. Conda Code does not advertise conda workspace shell because it opens a nested blocking shell.