Pixi

Pixi Helper

Expert guidance for using Pixi, a fast conda-based package manager for Python projects.

Purpose

Help developers effectively use Pixi for managing conda/PyPI dependencies, running commands in isolated environments, and configuring multi-environment projects.

When to Use

• Working with pixi.toml or pixi.lock files
• Installing or managing packages
• Running commands or tasks in pixi environments
• Setting up development/production environments
• Debugging pixi configuration errors

Quick Command Reference

Essential Commands

# Initialize & install
pixi init [project-name]
pixi install                         # install default environment
pixi install -e dev                  # install dev environment

# Add dependencies
pixi add python=3.11 pytorch pandas  # conda packages
pixi add --pypi transformers         # PyPI packages
pixi add --feature dev pytest ruff   # to dev feature

# Run commands
pixi run python script.py            # use default env
pixi run -e dev pytest               # use dev env
pixi shell                           # interactive shell
pixi shell -e dev                    # dev shell

# Tasks
pixi task add lint "ruff check ."
pixi task list
pixi run lint

# Production
pixi run --frozen --no-install train.py

Key Flags

• -e <env>: Use specific environment
• --frozen: Don't update lock file (reproducible)
• --no-install: Skip installation
• --feature <name>: Target specific feature

Core Concepts

Workspace

Directory with:

• pixi.toml: Configuration (commit this)
• pixi.lock: Lock file (commit this)
• .pixi/: Environment cache (DON'T commit)

Environments

Named dependency sets. Use -e flag to select:

pixi run python script.py       # default
pixi run -e dev pytest           # dev
pixi run -e prod train.py        # prod

Features

Reusable dependency groups that compose into environments.

Tasks

Predefined commands in pixi.toml. Run with pixi run <task-name>.

Command Patterns

When to Use What

Adding Dependencies

Prefer conda first (better compatibility, faster):

pixi add numpy pytorch

Use PyPI when needed:

pixi add --pypi transformers

Why conda first? Pixi resolves conda deps first, then PyPI.

pixi.toml Configuration

Project Metadata

[project]
name = "my-project"
channels = ["conda-forge", "pytorch"]  # order matters
platforms = ["linux-64", "osx-arm64"]

Dependencies

[dependencies]
python = ">=3.10"
numpy = "*"
pytorch = ">=2.0,<3"

[pypi-dependencies]
transformers = "*"
my-pkg = { path = "./local", editable = true }

Tasks

Simple:

[tasks]
test = "pytest tests/"

With environment variables:

[tasks.train]
cmd = "python train.py"
env = { CUDA_VISIBLE_DEVICES = "0,1" }

With dependencies:

[tasks]
clean = "rm -rf __pycache__"
test = { cmd = "pytest", depends-on = ["clean"] }

Multi-line:

[tasks.submit]
cmd = """
python train.py \
  --config config.yaml \
  --output results/
"""

Features

[feature.dev.dependencies]
pytest = "*"
ruff = "*"

[feature.cuda.dependencies]
pytorch-cuda = "12.1"

[environments]
default = []
dev = ["dev"]
gpu = ["cuda"]
dev-gpu = ["dev", "cuda"]

Activation Environment

[activation.env]
CUDA_HOME = "/usr/local/cuda"
PROJECT_ROOT = "$PIXI_PROJECT_ROOT"

Common Workflows

Your Patterns (susser-tod)

Dev testing:

pixi run -e dev pytest ./tests

Type checking:

pixi run typecheck

Profiling:

pixi run -e dev nsys profile python train.py

Troubleshooting

1. Package Not Found

Checks:

1. Channel specified in channels = [...]?
2. Package name correct? Try: pixi search <pkg>
3. Try PyPI: pixi add --pypi <pkg>

2. Environment Not Activated

❌ Wrong: python script.py (bare python) ✅ Correct: pixi run python script.py

4. Lock File Conflicts

After merge conflicts:

pixi install              # regenerate lock
# or
rm pixi.lock && pixi install

5. Environment Variables Not Set

Variables from [activation.env] only work with:

• pixi run <cmd>
• Inside pixi shell

NOT with bare python outside pixi.

6. Dependency Version Conflicts

Use solve-group to isolate environments:

[environments]
default = { solve-group = "group1" }
dev = { features = ["dev"], solve-group = "group1" }  # shared
prod = { solve-group = "group2" }                     # isolated

Best Practices

Dependencies

✅ Conda first, PyPI when needed ✅ Pin critical versions: pytorch = "2.1.*" ✅ Version constraints: python = ">=3.10,<3.12" ❌ Don't mix conda + PyPI for same package

Lock Files

✅ Commit pixi.lock ✅ Use --frozen in CI/production

Environments

✅ Use features to organize deps ✅ Share solve-groups when possible ✅ 2-4 environments is ideal

Reference

• Detailed pixi.toml schema: See REFERENCE.md
• Official docs: https://pixi.sh/latest/
• pixi.toml spec: https://pixi.sh/latest/reference/pixi_toml/

Practical guidance for Pixi. For project-specific patterns, check your CLAUDE.md.