Virtual Environment Creation

virtual-environment-creation

Summary

Create an isolated Python virtual environment using uv or conda to manage dependencies and avoid conflicts when installing ENPKG workflow components. This ensures reproducible, project-specific package versions without contaminating the system Python installation.

When to use

Before installing ENPKG dependencies for the first time, or when setting up the workflow on a new machine or user account. Trigger when you have cloned enpkg_full or enpkg_workflow and need to install runtime and optional development dependencies in isolation.

When NOT to use

• If the ENPKG workflow is already installed and environment is active (re-activation suffices).
• If you are running via a container (Docker, Singularity) that already provides dependency isolation.
• If system-wide Python package management is enforced by institutional policy and project-level isolation is forbidden.

Inputs

• Project root directory (enpkg_full or enpkg_workflow cloned repository)
• pyproject.toml or requirements file with pinned dependencies
• System with Git and Anaconda/Miniconda or uv pre-installed

Outputs

• .venv directory (isolated Python virtual environment)
• Activated shell session with environment variables pointing to .venv/bin
• Installed runtime and optional development packages in .venv/lib/pythonX.Y/site-packages

How to apply

Use the uv package manager (recommended over conda for ENPKG) to create and sync an isolated .venv in the project root by running uv sync to install runtime dependencies, or uv sync --group dev to include development tools like pytest and linters. If uv is not installed, first install it via the documented curl command. Optionally specify a Python version (e.g., uv python install 3.11) before syncing. Activate the environment with source .venv/bin/activate on Linux/macOS or use uv run as a prefix to execute commands without manual activation. The rationale is that ENPKG calls multiple external tools (MZmine, Sirius, GraphDB connectors) and requires precise version pinning; isolation prevents dependency conflicts and ensures reproducibility across environments.

Related tools

• uv (Primary dependency manager for creating and syncing isolated Python environment with pinned versions) — https://docs.astral.sh/uv/latest/
• Anaconda / Miniconda (Alternative package manager and environment creation tool; prerequisite if uv is not used) — https://docs.anaconda.com/free/anaconda/install/index.html
• Git (Required to clone enpkg_full and enpkg_workflow repositories before environment setup) — https://github.com/git-guides/install-git

Examples

curl -LsSf https://astral.sh/uv/install.sh | sh && cd enpkg_full && uv python install 3.11 && uv sync --group dev && source .venv/bin/activate

Evaluation signals

• Verify .venv directory exists in project root and contains bin/, lib/, and include/ subdirectories.
• Confirm environment activation succeeds: source .venv/bin/activate returns no errors and shell prompt changes to show (enpkg_full) or similar.
• Run python --version and pip list within activated environment; verify Python version and installed packages match pyproject.toml or requirements.
• Test environment isolation: which python should point to .venv/bin/python, not system Python.
• Run provided validation checks (e.g., uv run pytest or test suite commands) to confirm all components are correctly configured.

Limitations

• uv must be installed separately before running uv sync; installation requires curl and internet access.
• The .venv directory is not portable across different OS or CPU architectures; re-sync is needed on new machines.
• Optional development dependencies (pytest, linters) are only installed if --group dev is explicitly passed; omitting this flag will not include them.
• Environment variables and machine-specific paths (e.g., PATH_TO_SIRIUS, SIRIUS_USERNAME) are not automatically configured by virtual environment creation; users must separately configure .env file and source it before running workflows.

Evidence

• [readme] We now rely on uv for dependency management. Install it if needed: "We now rely on uv for dependency management. Install it if needed (see the uv docs for alternative methods)"
• [readme] uv sync creates a .venv in the project root with dependencies: "With uv installed, sync the project dependencies into an isolated .venv"
• [readme] Optional dev dependencies included with --group dev flag: "If you also want the development tooling (pytest, linters, etc.), add the dev dependency group: uv sync --group dev"
• [readme] Activate environment or use uv run prefix: "uv sync creates a .venv in the project root. Activate it with: source .venv/bin/activate. You can also run commands without activating by prefixing them with uv run, e.g.: uv run pytest"
• [readme] Prerequisites include Git and Anaconda or Miniconda: "You will need to have Git and Anaconda (or [Miniconda](https://docs.conda.io/en/latest/minico"