pylabrobot
정보
PyLabRobot는 액체 핸들러, 플레이트 리더, 펌프 등 다양한 실험실 자동화 장비를 통합 인터페이스로 제어하기 위한 벤더 중립적 Python 프레임워크입니다. 복잡한 다중 벤더 워크플로우를 구축하거나 시뮬레이션 기능이 필요한 개발자에게 이상적입니다. 단일 벤더의 공식 API만 사용하는 프로젝트의 경우 더 간단한 통합 방식을 고려하는 것이 좋습니다.
빠른 설치
Claude Code
추천npx skills add K-Dense-AI/claude-scientific-skills -a claude-code/plugin add https://github.com/K-Dense-AI/claude-scientific-skillsgit clone https://github.com/K-Dense-AI/claude-scientific-skills.git ~/.claude/skills/pylabrobotClaude Code에서 이 명령을 복사하여 붙여넣어 스킬을 설치하세요
문서
PyLabRobot
Overview
PyLabRobot is a hardware-agnostic, pure Python Software Development Kit for automated and autonomous laboratories. Use this skill to control liquid handling robots, plate readers, pumps, heater shakers, incubators, centrifuges, and other laboratory automation equipment through a unified Python interface that works across platforms (Windows, macOS, Linux).
When to Use This Skill
Use this skill when:
- Programming liquid handling robots (Hamilton STAR/STARlet, Opentrons OT-2, Tecan EVO)
- Automating laboratory workflows involving pipetting, sample preparation, or analytical measurements
- Managing deck layouts and laboratory resources (plates, tips, containers, troughs)
- Integrating multiple lab devices (liquid handlers, plate readers, heater shakers, pumps)
- Creating reproducible laboratory protocols with state management
- Simulating protocols before running on physical hardware
- Reading plates using BMG CLARIOstar or other supported plate readers
- Controlling temperature, shaking, centrifugation, or other material handling operations
- Working with laboratory automation in Python
Core Capabilities
PyLabRobot provides comprehensive laboratory automation through six main capability areas, each detailed in the references/ directory:
1. Liquid Handling (references/liquid-handling.md)
Control liquid handling robots for aspirating, dispensing, and transferring liquids. Key operations include:
- Basic Operations: Aspirate, dispense, transfer liquids between wells
- Tip Management: Pick up, drop, and track pipette tips automatically
- Advanced Techniques: Multi-channel pipetting, serial dilutions, plate replication
- Volume Tracking: Automatic tracking of liquid volumes in wells
- Hardware Support: Hamilton STAR/STARlet, Opentrons OT-2, Tecan EVO, and others
2. Resource Management (references/resources.md)
Manage laboratory resources in a hierarchical system:
- Resource Types: Plates, tip racks, troughs, tubes, carriers, and custom labware
- Deck Layout: Assign resources to deck positions with coordinate systems
- State Management: Track tip presence, liquid volumes, and resource states
- Serialization: Save and load deck layouts and states from JSON files
- Resource Discovery: Access wells, tips, and containers through intuitive APIs
3. Hardware Backends (references/hardware-backends.md)
Connect to diverse laboratory equipment through backend abstraction:
- Liquid Handlers: Hamilton STAR (full support), Opentrons OT-2, Tecan EVO
- Simulation: ChatterboxBackend for protocol testing without hardware
- Platform Support: Works on Windows, macOS, Linux, and Raspberry Pi
- Backend Switching: Change robots by swapping backend without rewriting protocols
4. Analytical Equipment (references/analytical-equipment.md)
Integrate plate readers and analytical instruments:
- Plate Readers: BMG CLARIOstar for absorbance, luminescence, fluorescence
- Scales: Mettler Toledo integration for mass measurements
- Integration Patterns: Combine liquid handlers with analytical equipment
- Automated Workflows: Move plates between devices automatically
5. Material Handling (references/material-handling.md)
Control environmental and material handling equipment:
- Heater Shakers: Hamilton HeaterShaker, Inheco ThermoShake
- Incubators: Inheco and Thermo Fisher incubators with temperature control
- Centrifuges: Agilent VSpin with bucket positioning and spin control
- Pumps: Cole Parmer Masterflex for fluid pumping operations
- Temperature Control: Set and monitor temperatures during protocols
6. Visualization & Simulation (references/visualization.md)
Visualize and simulate laboratory protocols:
- Browser Visualizer: Real-time 3D visualization of deck state
- Simulation Mode: Test protocols without physical hardware
- State Tracking: Monitor tip presence and liquid volumes visually
- Deck Editor: Graphical tool for designing deck layouts
- Protocol Validation: Verify protocols before running on hardware
Quick Start
To get started with PyLabRobot, install the package and initialize a liquid handler:
# Install PyLabRobot
# uv pip install pylabrobot
# Basic liquid handling setup
from pylabrobot.liquid_handling import LiquidHandler
from pylabrobot.liquid_handling.backends import STAR
from pylabrobot.resources import STARLetDeck
# Initialize liquid handler
lh = LiquidHandler(backend=STAR(), deck=STARLetDeck())
await lh.setup()
# Basic operations
await lh.pick_up_tips(tip_rack["A1:H1"])
await lh.aspirate(plate["A1"], vols=100)
await lh.dispense(plate["A2"], vols=100)
await lh.drop_tips()
Working with References
This skill organizes detailed information across multiple reference files. Load the relevant reference when:
- Liquid Handling: Writing pipetting protocols, tip management, transfers
- Resources: Defining deck layouts, managing plates/tips, custom labware
- Hardware Backends: Connecting to specific robots, switching platforms
- Analytical Equipment: Integrating plate readers, scales, or analytical devices
- Material Handling: Using heater shakers, incubators, centrifuges, pumps
- Visualization: Simulating protocols, visualizing deck states
All reference files can be found in the references/ directory and contain comprehensive examples, API usage patterns, and best practices.
Best Practices
When creating laboratory automation protocols with PyLabRobot:
- Start with Simulation: Use ChatterboxBackend and the visualizer to test protocols before running on hardware
- Enable Tracking: Turn on tip tracking and volume tracking for accurate state management
- Resource Naming: Use clear, descriptive names for all resources (plates, tip racks, containers)
- State Serialization: Save deck layouts and states to JSON for reproducibility
- Error Handling: Implement proper async error handling for hardware operations
- Temperature Control: Set temperatures early as heating/cooling takes time
- Modular Protocols: Break complex workflows into reusable functions
- Documentation: Reference official docs at https://docs.pylabrobot.org for latest features
Common Workflows
Liquid Transfer Protocol
# Setup
lh = LiquidHandler(backend=STAR(), deck=STARLetDeck())
await lh.setup()
# Define resources
tip_rack = TIP_CAR_480_A00(name="tip_rack")
source_plate = Cos_96_DW_1mL(name="source")
dest_plate = Cos_96_DW_1mL(name="dest")
lh.deck.assign_child_resource(tip_rack, rails=1)
lh.deck.assign_child_resource(source_plate, rails=10)
lh.deck.assign_child_resource(dest_plate, rails=15)
# Transfer protocol
await lh.pick_up_tips(tip_rack["A1:H1"])
await lh.transfer(source_plate["A1:H12"], dest_plate["A1:H12"], vols=100)
await lh.drop_tips()
Plate Reading Workflow
# Setup plate reader
from pylabrobot.plate_reading import PlateReader
from pylabrobot.plate_reading.clario_star_backend import CLARIOstarBackend
pr = PlateReader(name="CLARIOstar", backend=CLARIOstarBackend())
await pr.setup()
# Set temperature and read
await pr.set_temperature(37)
await pr.open()
# (manually or robotically load plate)
await pr.close()
data = await pr.read_absorbance(wavelength=450)
Additional Resources
- Official Documentation: https://docs.pylabrobot.org
- GitHub Repository: https://github.com/PyLabRobot/pylabrobot
- Community Forum: https://discuss.pylabrobot.org
- PyPI Package: https://pypi.org/project/PyLabRobot/
For detailed usage of specific capabilities, refer to the corresponding reference file in the references/ directory.
GitHub 저장소
연관 스킬
executing-plans
디자인executing-plans 스킬은 검토 체크포인트가 포함된 통제된 배치로 실행할 완전한 구현 계획이 있을 때 사용합니다. 이 스킬은 계획을 불러와 비판적으로 검토한 후, 소규모 배치(기본값 3개 작업)로 작업을 실행하면서 각 배치 사이에 진행 상황을 아키텍트 검토를 위해 보고합니다. 이를 통해 내재된 품질 관리 체크포인트를 갖춘 체계적인 구현이 보장됩니다.
requesting-code-review
디자인이 스킬은 코드 변경 사항을 요구 사항에 따라 분석하기 위해 코드 리뷰어 하위 에이전트를 호출합니다. 작업 완료 후, 주요 기능 구현 후, 또는 메인 브랜치에 병합하기 전에 사용해야 합니다. 이 리뷰는 현재 구현체와 원래 계획을 비교하여 문제를 조기에 발견하는 데 도움이 됩니다.
connect-mcp-server
디자인이 스킬은 개발자들이 HTTP, stdio 또는 SSE 전송 방식을 통해 MCP 서버를 Claude Code에 연결하는 포괄적인 가이드를 제공합니다. GitHub, Notion 및 사용자 정의 API와 같은 외부 서비스를 통합하기 위한 설치, 구성, 인증 및 보안을 다룹니다. MCP 통합 설정, 외부 도구 구성 또는 Claude의 모델 컨텍스트 프로토콜 작업 시 활용하세요.
web-cli-teleport
디자인이 스킬은 작업 분석을 기반으로 개발자가 Claude Code 웹 인터페이스와 CLI 인터페이스 중 선택할 수 있도록 돕고, 두 환경 간 원활한 세션 텔레포트를 가능하게 합니다. 웹, CLI 또는 모바일 환경 전환 시 세션 상태와 컨텍스트를 관리하여 워크플로를 최적화합니다. 다양한 단계에서 서로 다른 도구가 필요한 복잡한 프로젝트에 사용하세요.
