What problem does it solve?
Conda-environment activation can fail or be inconsistent in non-interactive shells, leading to missing packages or mismatched dependencies. This skill standardizes the activation workflow so the correct environment is always active before running Python commands.
Core Features & Use Cases
- Activation pattern: source the conda setup script (for example, conda.sh) and run conda activate ENV_NAME; supports both Miniconda and Miniforge setups.
- Before running commands: detect whether an environment exists, list available environments, and activate the required one to ensure reproducibility.
- Package installation: prefer conda install, fall back to pip inside the active environment, never install into base, and ensure ipykernel is present for notebook execution.
- One-time configuration: set channel-priority to strict, enable the libmamba solver, and add conda-forge to channels for reliable dependency resolution.
- Environment export: export environments with conda env export --from-history to capture only user-specified packages for portability.
- Shared environments and policies: use a consistent naming convention per project and avoid modifying the base environment.
Quick Start
Source the conda setup script and activate ENV_NAME before running your Python commands.