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cli-commands

Use for dora CLI command questions. Triggers on: dora run, dora build, dora start, dora stop, dora new, dora up, dora destroy, dora list, dora ps, dora logs, dora check, dora graph, dora daemon, dora coordinator, CLI命令, 命令行, 运行数据流, 构建, 启动, 停止

Quellinformationen

Repository
ZhangHanDong/dora-skills
Letzte Quellaktivität
21. Januar 2026 um 16:16
Erkannte Sprache von SKILL.md
Englisch
Sterne
7
Forks
1

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Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
cli-commands
description
Use for dora CLI command questions. Triggers on: dora run, dora build, dora start, dora stop, dora new, dora up, dora destroy, dora list, dora ps, dora logs, dora check, dora graph, dora daemon, dora coordinator, CLI命令, 命令行, 运行数据流, 构建, 启动, 停止
globs
["**/dataflow.yml","**/dataflow.yaml"]
source
https://dora-rs.ai
# Dora CLI Commands > Complete reference for the dora command-line interface ## Installation ```bash # Via pip (recommended) pip install dora-rs-cli # Via cargo cargo install dora-cli # Via shell installer (macOS/Linux) curl --proto '=https' --tlsv1.2 -LsSf \ https://github.com/dora-rs/dora/releases/latest/download/dora-cli-installer.sh | sh ``` ## Command Overview | Command | Description | |---------|-------------| | `dora new` | Create new dataflow, node, or operator | | `dora build` | Build nodes in a dataflow | | `dora run` | Run dataflow (standalone mode) | | `dora up` | Start coordinator and daemon | | `dora start` | Start dataflow on daemon | | `dora stop` | Stop running dataflow | | `dora list` / `dora ps` | List running dataflows | | `dora logs` | View node logs | | `dora destroy` | Stop coordinator and daemon | | `dora check` | Check system status | | `dora graph` | Generate dataflow visualization | ## Creating Projects ### New Dataflow ```bash # Create new dataflow project dora new my_project --kind dataflow # With Python language dora new my_project --kind dataflow --lang python # With Rust language dora new my_project --kind dataflow --lang rust ``` ### New Node ```bash # Create new Python node dora new my_node --kind node --lang python # Create new Rust node dora new my_node --kind node --lang rust ``` ### New Operator ```bash # Create new operator dora new my_operator --kind operator --lang rust ``` ## Building ```bash # Build all nodes in dataflow dora build dataflow.yml # Build with uv (faster Python packages) dora build dataflow.yml --uv # Build specific node dora build dataflow.yml --node camera ``` ## Running Dataflows ### Standalone Mode (dora run) ```bash # Run dataflow directly (no daemon) dora run dataflow.yml # Run with uv for Python packages dora run dataflow.yml --uv # Run from URL dora run https://example.com/dataflow.yml ``` ### Daemon Mode ```bash # Step 1: Start coordinator and daemon dora up # Step 2: Start dataflow dora start dataflow.yml # Step 3: Check status dora list # Step 4: Stop dataflow dora stop <dataflow-id> # Step 5: Shutdown daemon dora destroy ``` ## Monitoring ### List Running Dataflows ```bash # List all running dataflows dora list # or dora ps ``` ### View Logs ```bash # View logs for a node dora logs <dataflow-id> <node-id> # Follow logs (like tail -f) dora logs <dataflow-id> <node-id> --follow ``` ### Check System Status ```bash # Check dora system status dora check # or dora system status ``` ## Visualization ```bash # Generate Mermaid diagram dora graph dataflow.yml # Output to file dora graph dataflow.yml > graph.md ``` Example output: ```mermaid flowchart TB camera[camera] detector[detector] plot[plot] camera -- image --> detector camera -- image --> plot detector -- bbox --> plot ``` ## Distributed Mode ### Coordinator ```bash # Start coordinator on custom port dora coordinator --port 6012 ``` ### Daemon ```bash # Connect daemon to remote coordinator dora daemon --coordinator-addr 192.168.1.100:6012 ``` ### Remote Dataflow ```yaml # dataflow.yml with deployment config nodes: - id: camera path: camera_node.py _unstable_deploy: machine: robot-1 - id: processor path: processor_node.py _unstable_deploy: machine: server-1 ``` ## Common Workflows ### Development Workflow ```bash # 1. Create project dora new my_robot --kind dataflow # 2. Edit dataflow.yml and create nodes # 3. Build dora build dataflow.yml --uv # 4. Run and test dora run dataflow.yml --uv # 5. Stop with Ctrl+C ``` ### Production Workflow ```bash # 1. Start services dora up # 2. Deploy dataflow dora start dataflow.yml # 3. Monitor dora list dora logs <id> <node> # 4. Update (stop and restart) dora stop <id> dora start dataflow.yml # 5. Shutdown dora destroy ``` ### Remote Dataflow ```bash # On coordinator machine dora coordinator # On each robot/server dora daemon --coordinator-addr <coordinator-ip>:6012 # Deploy dataflow dora start dataflow.yml ``` ## Environment Variables | Variable | Description | |----------|-------------| | `DORA_COORDINATOR_ADDR` | Coordinator address | | `DORA_DAEMON_ADDR` | Daemon address | | `DORA_OTLP_ENDPOINT` | OpenTelemetry endpoint | | `DORA_JAEGER_TRACING` | Enable Jaeger tracing | ## Troubleshooting ### Common Issues **"Daemon not running"** ```bash # Start the daemon dora up ``` **"Port already in use"** ```bash # Kill existing processes dora destroy # Then restart dora up ``` **"Build failed"** ```bash # Check build output dora build dataflow.yml --uv 2>&1 | tee build.log ``` ### Debug Mode ```bash # Run with debug output RUST_LOG=debug dora run dataflow.yml ``` ## Related Skills - **dataflow-config** - YAML configuration - **node-api-rust** - Rust node development - **node-api-python** - Python node development
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