Sno Station
Sno Station은 AI 에이전트를 하나의 팀으로 묶는 오픈소스 워크스테이션으로, 로컬 머신에서 에이전트 협업을 가능하게 함
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1분 만에 확인하기Apache Airflow 3 provider to run Python callables, Bash commands and Pixi tasks in Pixi environments, on workers or in Kubernetes pods.
저장소 README에서 가져옴
README 전체를 불러오는 중입니다. 아래는 저장된 발췌입니다.
An Apache Airflow 3 provider that runs tasks inside Pixi-managed environments,
on the worker or in a Kubernetes pod, so a task can use conda-forge and PyPI packages that are not
installed on the worker.
Documentation: https://danplischke.github.io/apache-airflow-providers-pixi/
(for LLMs and coding agents: llms.txt)
Requires Apache Airflow 3.1.2 or newer and Python 3.10 to 3.14 (3.14 needs Airflow 3.2). The
workers need pixi 0.81.0 or newer on PATH; the provider
never installs it. See Requirements
and the deployment guide.README 전문 보기 ↗An Apache Airflow 3 provider that runs tasks inside Pixi-managed environments, on the worker or in a Kubernetes pod, so a task can use conda-forge and PyPI packages that are not installed on the worker.
Documentation: https://danplischke.github.io/apache-airflow-providers-pixi/ (for LLMs and coding agents: llms.txt)
pip install apache-airflow-providers-pixi
pip install "apache-airflow-providers-pixi[cncf.kubernetes]" # adds PixiKubernetesPodOperator
Requires Apache Airflow 3.1.2 or newer and Python 3.10 to 3.14 (3.14 needs Airflow 3.2). The
workers need pixi 0.81.0 or newer on PATH; the provider
never installs it. See Requirements
and the deployment guide.
from airflow.sdk import dag, task
@dag
def my_dag():
@task.pixi(dependencies={"python": "3.12.*"}, pypi_dependencies=["pandas>=2"])
def summarize(n: int) -> float:
import pandas as pd # imports go inside the function: it runs in the Pixi environment
return float(pd.Series(range(n)).mean())
summarize(3)
my_dag()
Pass pixi_project_path or pixi_toml_path instead to use an existing Pixi project. The
Pixi Operator guide
covers the ways to choose an environment, arguments and return values, the Airflow context,
environment variables, errors, timeouts and caches.
| Class / decorator | What it does |
|---|---|
PixiOperator / @task.pixi | runs a Python callable in a Pixi environment on the worker |
PixiBashOperator / @task.pixi_bash | runs a Bash command in a Pixi environment |
PixiTaskOperator | runs a task from the manifest's [tasks] |
PixiKubernetesPodOperator / @task.pixi_kubernetes | runs a Python callable in a Pixi environment in a Kubernetes pod |
PixiBranchOperator / @task.pixi_branch | chooses the downstream tasks to follow |
PixiShortCircuitOperator / @task.pixi_short_circuit | skips downstream tasks when the callable returns a falsy value |
PixiSensor / @task.pixi_sensor | waits until the callable returns a truthy value |
Credentials for private conda channels and PyPI indexes go in a
pixi connection.
Other providers can build on these operators; see
Building on the Pixi Operator.
With uv, just and pixi installed:
just dev installs the package with the dev and docs groups and the pre-commit hooks.just test runs the unit tests, with a fake pixi.just check runs what CI runs: lint, unit tests, docs build, package build and smoke test.just standalone starts a local Airflow at http://localhost:8080 with the DAGs in dev/dags.just lists the other recipes. Integration, system and compatibility tests are described in
System Tests and
Installing from sources.
MIT