PyLabRobot

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:

1. Start with Simulation: Use ChatterboxBackend and the visualizer to test protocols before running on hardware
2. Enable Tracking: Turn on tip tracking and volume tracking for accurate state management
3. Resource Naming: Use clear, descriptive names for all resources (plates, tip racks, containers)
4. State Serialization: Save deck layouts and states to JSON for reproducibility
5. Error Handling: Implement proper async error handling for hardware operations
6. Temperature Control: Set temperatures early as heating/cooling takes time
7. Modular Protocols: Break complex workflows into reusable functions
8. 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.