Linux command
dagster 命令
文本
复制后可按需替换文件名、目录或参数。
常用示例
Start development server
dagster dev
Start with specific module
dagster dev -m [my_project]
Launch daemon for schedules/sensors
dagster-daemon run
Start webserver only
dagster-webserver
Run a job
dagster job execute -m [my_project] -j [job_name]
List jobs
dagster job list -m [my_project]
Scaffold a new project
dagster project scaffold --name [my-project]
Check definitions
dagster definitions validate -m [my_project]
说明
dagster is the CLI for Dagster, a data orchestration platform built around software-defined assets. It manages the development environment, job execution, and infrastructure. dagster dev starts both the webserver (UI) and daemon (schedules, sensors) for local development. In production, run dagster-webserver and dagster-daemon separately. Software-defined assets are the core abstraction—functions that produce data assets with dependencies. Assets form a DAG that Dagster materializes. Jobs group assets for execution. Schedules trigger jobs on cron patterns; sensors trigger based on external events. Both require the daemon process to run. The webserver provides a UI showing asset lineage, run history, logs, and metrics. The asset graph visualizes data dependencies.
参数
- -m, --module _name_
- Python module containing definitions.
- -f, --file _path_
- Python file containing definitions.
- -j, --job _name_
- Job name.
- -p, --port _port_
- Webserver port. Default: 3000.
- -h, --host _host_
- Webserver host. Default: localhost.
- -w, --workspace _file_
- Workspace YAML file.
- -d, --working-directory _path_
- Working directory for code.
FAQ
What is the dagster command used for?
dagster is the CLI for Dagster, a data orchestration platform built around software-defined assets. It manages the development environment, job execution, and infrastructure. dagster dev starts both the webserver (UI) and daemon (schedules, sensors) for local development. In production, run dagster-webserver and dagster-daemon separately. Software-defined assets are the core abstraction—functions that produce data assets with dependencies. Assets form a DAG that Dagster materializes. Jobs group assets for execution. Schedules trigger jobs on cron patterns; sensors trigger based on external events. Both require the daemon process to run. The webserver provides a UI showing asset lineage, run history, logs, and metrics. The asset graph visualizes data dependencies.
How do I run a basic dagster example?
Run `dagster dev` in a terminal, then adjust file names, paths, flags, or remote targets for your system.
What does -m, --module _name_ do in dagster?
Python module containing definitions.