conda-tasks#
Project-scoped task runner for conda, with pixi task compatibility.
Define tasks, wire up dependencies between them, and run everything through
conda task. conda-tasks reads conda.toml, pixi.toml, pyproject.toml,
or .condarc and runs commands in your existing conda environments — no new
package manager, no extra solver, just tasks on top of the tools you already
use.
Install#
conda install -c conda-forge conda-tasks
pixi global install conda-tasks
Define tasks#
Create a conda.toml in your project root:
[tasks]
build = "python -m build"
test = { cmd = "pytest tests/ -v", depends-on = ["build"] }
lint = "ruff check ."
[tasks.check]
depends-on = ["test", "lint"]
Then run your tasks:
conda task run check # resolves dependencies, runs build → lint → test
conda task run test # builds first, then tests
conda task list # shows all available tasks
Or use the ct shortcut for quicker typing:
ct run check
ct list
Tasks are executed in your current conda environment by default, or target
any environment with -n myenv. Dependencies are resolved with topological
ordering so everything runs in the right order.
Why conda-tasks?#
pixi introduced an excellent task runner model, but it brings its own environment management. conda-tasks reuses that same task format while delegating execution to conda’s existing infrastructure.
This means:
Tasks read from
conda.toml,pixi.toml,pyproject.toml, or.condarc— one definition, multiple toolsTask dependencies with topological ordering (
depends-on)Jinja2 templates in commands (
{{ conda.platform }}, conditionals)Task arguments with defaults, input/output caching, and per-platform overrides
Ships as a conda plugin (
conda task) and a standalonectCLI
Read more in Motivation.
Install conda-tasks and define your first task in under a minute.
Step-by-step guides: your first project, migrating from pixi, CI setup.
Dependencies, templates, caching, arguments, platform overrides, environment targeting, and more.
All task fields, file formats (conda.toml,
pixi.toml, pyproject.toml, .condarc), and examples.
Complete conda task command-line documentation.
Python API for models, parsers, graph resolution, caching, and template rendering.