pylabrobot

pylabrobot

Overview

PyLabRobot is an open-source Python library that abstracts liquid handling robot hardware behind a unified API. Write a protocol once and run it on any supported robot — Hamilton STAR, Tecan Freedom EVO, Opentrons OT-2, or a simulated backend — without changing the protocol code. PyLabRobot handles deck layout, resource management, and aspirate/dispense operations through a clean, async-first interface.

When to Use

• Writing portable liquid handling protocols: You want a single Python script that works across Hamilton, Tecan, Opentrons, and a simulator without code changes.
• Developing and testing protocols before robot time: Use the simulation backend to validate logic, volumes, and deck layouts without occupying physical hardware.
• Automating plate reformatting and cherry-picking: Transfer specific wells between plates based on upstream data (e.g., hit compounds from a screen).
• Building serial dilution curves: Systematically aspirate and dispense across a plate with precise volume steps.
• Integrating liquid handling into Python data pipelines: Trigger robot actions from analysis code, LIMS queries, or machine learning models.
• Rapid method development: Iterate quickly in Python rather than in vendor-specific scripting environments.
• For Opentrons-specific features (temperature module control, built-in app integration), use the opentrons Python SDK instead; for multi-vendor portability use PyLabRobot.

Prerequisites

• Python packages: pylabrobot
• Optional backends: pylabrobot[hamilton] for Hamilton STAR, pylabrobot[opentrons] for OT-2
• Data requirements: None — deck resources are defined in Python
• Environment: Python 3.9+; physical robot drivers installed separately per vendor docs

pip install pylabrobot
pip install "pylabrobot[hamilton]"   # add Hamilton USB driver
pip install "pylabrobot[opentrons]"  # add Opentrons REST driver

Quick Start

import asyncio
from pylabrobot.liquid_handling import LiquidHandler
from pylabrobot.liquid_handling.backends import SimulatorBackend
from pylabrobot.resources import Deck, Cos_96_Rd, HTF_L

async def main():
    backend = SimulatorBackend(open_browser=False)
    lh = LiquidHandler(backend=backend, deck=Deck())
    await lh.setup()

    plate = Cos_96_Rd(name="plate")
    tips  = HTF_L(name="tips")
    lh.deck.assign_child_resource(plate, rails=2)
    lh.deck.assign_child_resource(tips,  rails=5)

    await lh.pick_up_tips(tips["A1"])
    await lh.aspirate(plate["A1"], vols=50)
    await lh.dispense(plate["B1"], vols=50)
    await lh.drop_tips(tips["A1"])
    await lh.stop()
    print("Transfer complete: 50 uL from A1 -> B1")

asyncio.run(main())

Core API

Module 1: LiquidHandler — Setup and Teardown

The LiquidHandler class is the central controller. It wraps a backend and a Deck.

import asyncio
from pylabrobot.liquid_handling import LiquidHandler
from pylabrobot.liquid_handling.backends import SimulatorBackend
from pylabrobot.resources import Deck

async def main():
    backend = SimulatorBackend(open_browser=False)
    lh = LiquidHandler(backend=backend, deck=Deck())
    await lh.setup()      # connect to hardware / start simulator
    print("LiquidHandler ready:", lh)
    await lh.stop()       # disconnect cleanly

asyncio.run(main())

# Connecting to a real Hamilton STAR
from pylabrobot.liquid_handling.backends.hamilton import STAR

async def main():
    backend = STAR()
    lh = LiquidHandler(backend=backend, deck=Deck())
    await lh.setup()
    # lh is now connected to physical hardware
    await lh.stop()

Module 2: Deck and Resource Assignment

Resources (plates, tip racks, reservoirs) are placed on the deck by rail position.

from pylabrobot.resources import (
    Deck,
    Cos_96_Rd,                  # Corning 96-well round-bottom plate
    Cos_384_Sq,                 # Corning 384-well plate
    HTF_L,                      # Hamilton tip rack (filtered, large)
    Trough_1_Row_1_Col_4,       # 4-channel reservoir
)

deck = Deck()
plate_96  = Cos_96_Rd(name="sample_plate")
plate_384 = Cos_384_Sq(name="assay_plate")
tips      = HTF_L(name="tip_rack")
reservoir = Trough_1_Row_1_Col_4(name="buffer")

deck.assign_child_resource(plate_96,  rails=1)
deck.assign_child_resource(plate_384, rails=4)
deck.assign_child_resource(tips,      rails=8)
deck.assign_child_resource(reservoir, rails=11)

print("Deck resources:", [r.name for r in deck.children])

Module 3: Tip Operations

Pick up and drop tips before and after liquid operations.

# Pick up tips from the first column of the tip rack
await lh.pick_up_tips(tips["A1:H1"])   # all 8 tips in column 1

# After liquid operations, drop tips back
await lh.drop_tips(tips["A1:H1"])

# Single tip
await lh.pick_up_tips(tips["A1"])
await lh.drop_tips(tips["A1"])
print("Tip operations complete")

Module 4: Aspirate Operations

Aspirate liquid from wells. Accepts single wells, ranges, or lists.

# Aspirate 100 uL from a single well
await lh.aspirate(plate["A1"], vols=100)

# Aspirate different volumes from multiple wells simultaneously
await lh.aspirate(
    plate["A1:A4"],
    vols=[50, 75, 100, 125],
)
print("Aspiration complete")

from pylabrobot.resources import Coordinate

# Aspirate with flow rate and liquid height control
await lh.aspirate(
    plate["A1"],
    vols=50,
    flow_rates=100,                    # uL/s
    offsets=Coordinate(0, 0, 1),       # 1 mm above well bottom
)

Module 5: Dispense Operations

Dispense liquid into target wells.

# Dispense 100 uL into a single well
await lh.dispense(plate["B1"], vols=100)

# Multi-well dispense with different volumes
await lh.dispense(
    plate["B1:B4"],
    vols=[50, 75, 100, 125],
)
print("Dispense complete")

Module 6: Transfer — High-Level Convenience

transfer combines aspirate and dispense for simple source-to-destination moves.

# Transfer 50 uL from A1 -> B1
await lh.transfer(plate["A1"], plate["B1"], transfer_volume=50)

# Multi-well pairwise transfer
sources      = plate["A1:A8"]
destinations = plate["B1:B8"]
await lh.transfer(sources, destinations, transfer_volume=75)
print("Transfer complete")

Module 7: Simulation Backend

The SimulatorBackend runs a browser-based visualizer for protocol debugging.

from pylabrobot.liquid_handling.backends import SimulatorBackend

# With visual browser (default — opens http://localhost:2121)
backend = SimulatorBackend(open_browser=True)

# Headless simulation (CI/testing)
backend = SimulatorBackend(open_browser=False)

# After setup(), liquid movements are visualized in real time
await lh.setup()
# Check browser for visual confirmation before running on real hardware
print("Simulator running at http://localhost:2121")

Key Concepts

Async-First Design

All robot operations (setup, aspirate, dispense, transfer) are Python async coroutines. Run them inside an async def function using asyncio.run() or Jupyter's top-level await syntax.

import asyncio

async def run_protocol(lh, plate, tips):
    await lh.pick_up_tips(tips["A1"])
    await lh.aspirate(plate["A1"], vols=50)
    await lh.dispense(plate["B1"], vols=50)
    await lh.drop_tips(tips["A1"])
    print("Protocol complete")

asyncio.run(run_protocol(lh, plate, tips))

Well Addressing

Wells are addressed by alphanumeric position ("A1") or slice notation ("A1:H1" for a column, "A1:A12" for a row).

well    = plate["A1"]             # single well
col1    = plate["A1:H1"]          # 8 wells in column 1
row_a   = plate["A1:A12"]         # 12 wells in row A
print(f"Single: {well.name}")
print(f"Column: {len(col1)} wells")
print(f"Row:    {len(row_a)} wells")

Common Workflows

Workflow 1: 96-Well Serial Dilution

Goal: Perform a 2-fold serial dilution across a 96-well plate.

import asyncio
from pylabrobot.liquid_handling import LiquidHandler
from pylabrobot.liquid_handling.backends import SimulatorBackend
from pylabrobot.resources import Deck, Cos_96_Rd, HTF_L, Trough_1_Row_1_Col_4

async def serial_dilution():
    backend = SimulatorBackend(open_browser=False)
    lh = LiquidHandler(backend=backend, deck=Deck())
    await lh.setup()

    plate   = Cos_96_Rd(name="plate")
    tips    = HTF_L(name="tips")
    diluent = Trough_1_Row_1_Col_4(name="diluent")
    lh.deck.assign_child_resource(plate,   rails=1)
    lh.deck.assign_child_resource(tips,    rails=5)
    lh.deck.assign_child_resource(diluent, rails=9)

    # Add 100 uL diluent to columns 2-12
    for col in range(2, 13):
        col_label = f"A{col}:H{col}"
        await lh.pick_up_tips(tips[f"A{col}:H{col}"])
        await lh.aspirate(diluent["A1:H1"], vols=100)
        await lh.dispense(plate[col_label], vols=100)
        await lh.drop_tips(tips[f"A{col}:H{col}"])

    # Serial transfer: col 1 -> 2 -> ... -> 11
    for col in range(1, 12):
        src = f"A{col}:H{col}"
        dst = f"A{col+1}:H{col+1}"
        await lh.pick_up_tips(tips[f"A{col}:H{col}"])
        await lh.aspirate(plate[src], vols=100)
        await lh.dispense(plate[dst], vols=100)
        await lh.drop_tips(tips[f"A{col}:H{col}"])

    print("Serial dilution complete: 12 columns, 2-fold steps")
    await lh.stop()

asyncio.run(serial_dilution())

Workflow 2: Cherry-Picking from a Hit List

Goal: Transfer compounds from specified source wells to a destination plate based on a CSV hit list.

import asyncio
import pandas as pd
from pylabrobot.liquid_handling import LiquidHandler
from pylabrobot.liquid_handling.backends import SimulatorBackend
from pylabrobot.resources import Deck, Cos_96_Rd, HTF_L

async def cherry_pick(hit_list_csv: str, volume: float = 50.0):
    # CSV must have columns: source_well, dest_well
    hits = pd.read_csv(hit_list_csv)
    print(f"Cherry-picking {len(hits)} hits at {volume} uL each")

    backend = SimulatorBackend(open_browser=False)
    lh = LiquidHandler(backend=backend, deck=Deck())
    await lh.setup()

    src  = Cos_96_Rd(name="source")
    dst  = Cos_96_Rd(name="destination")
    tips = HTF_L(name="tips")
    lh.deck.assign_child_resource(src,  rails=1)
    lh.deck.assign_child_resource(dst,  rails=4)
    lh.deck.assign_child_resource(tips, rails=8)

    # Get all well names from tip rack
    tip_wells = [w.name for w in tips.wells]
    for i, row in hits.iterrows():
        await lh.pick_up_tips(tips[tip_wells[i]])
        await lh.transfer(src[row["source_well"]], dst[row["dest_well"]],
                          transfer_volume=volume)
        await lh.drop_tips(tips[tip_wells[i]])

    print(f"Cherry-pick complete: {len(hits)} transfers done")
    await lh.stop()

# asyncio.run(cherry_pick("hits.csv", volume=50))

Key Parameters

Parameter	Module	Default	Range / Options	Effect
vols	aspirate / dispense	required	0 – robot max (µL)	Volume to aspirate or dispense per well
flow_rates	aspirate / dispense	backend default	10 – 1000 µL/s	Speed of liquid movement
blow_out_air_volume	dispense	0	0 – 30 µL	Air volume blown after dispense to empty tip
offsets	aspirate / dispense	Coordinate(0,0,0)	Any Coordinate	Positional offset from well center (x, y, z mm)
open_browser	SimulatorBackend	True	True, False	Open browser-based visual simulator on setup
rails	deck assignment	required	1 – max deck rails	Physical slot on the deck for a resource
transfer_volume	transfer	required	0 – robot max (µL)	Volume for high-level aspirate+dispense transfer

Best Practices

1. Always test with the simulator first: Run your full protocol with SimulatorBackend(open_browser=True) before connecting to physical hardware. The browser visualizer shows deck layout and liquid movements in real time.

2. Use fresh tips for each transfer when contamination matters: Reusing tips in cherry-picking workflows risks cross-contamination. Track tip consumption against tip rack capacity programmatically.

3. Wrap protocols in try/finally for cleanup: If an exception occurs mid-protocol, always call await lh.stop() to release hardware connections.

   try:
       await run_my_protocol(lh)
   finally:
       await lh.stop()
   

4. Define resources once at the top of your script: Create resource objects and assign them to the deck once. Reassigning the same resource mid-run can desynchronize the robot's internal state tracking.

5. Pre-calculate volume and tip requirements: For high-throughput runs, compute total volume and tip count needed before starting, and assert that resources are sufficient.

Common Recipes

Recipe: Dispense with Post-Dispense Mixing

When to use: Reagent addition to cell culture wells requiring homogeneous mixing.

async def dispense_and_mix(lh, src, dst, tips, volume=50, mix_vol=40, mix_reps=3):
    await lh.pick_up_tips(tips["A1"])
    await lh.aspirate(src["A1"], vols=volume)
    await lh.dispense(dst["A1"], vols=volume)
    for _ in range(mix_reps):
        await lh.aspirate(dst["A1"], vols=mix_vol)
        await lh.dispense(dst["A1"], vols=mix_vol)
    await lh.drop_tips(tips["A1"])
    print(f"Dispensed {volume} uL and mixed {mix_reps}x")

Recipe: Full-Plate Stamp

When to use: Replicate an entire 96-well plate to a second plate.

async def stamp_plate(lh, src_plate, dst_plate, tips, volume=100):
    for col in range(1, 13):
        col_label = f"A{col}:H{col}"
        await lh.pick_up_tips(tips[col_label])
        await lh.aspirate(src_plate[col_label], vols=volume)
        await lh.dispense(dst_plate[col_label], vols=volume)
        await lh.drop_tips(tips[col_label])
    print(f"Full plate stamped: {volume} uL per well, 12 columns")

Expected Outputs

• Robot executes liquid handling operations as scripted (physical or simulated)
• Simulator at http://localhost:2121 shows animated deck with per-well volume tracking
• No file outputs by default; integrate pandas / CSV logging in wrapper code as needed

Troubleshooting

Problem	Cause	Solution
RuntimeError: No backend connected	lh.setup() not awaited before operations	Ensure await lh.setup() completes before any liquid handling call
ResourceNotFoundError	Resource name not assigned to deck	Call deck.assign_child_resource(resource, rails=N) before referencing wells
asyncio.InvalidStateError	Coroutine called outside async context	Wrap top-level calls in async def main() and use asyncio.run(main())
Well address KeyError	Incorrect well label format	Use uppercase letter + integer: "A1", "H12", not "a1" or "A01"
VolumeError: exceeds tip capacity	Requested volume larger than tip max	Use appropriate tip type; HTF_L holds up to 1000 µL
Simulator shows no movement	open_browser=False with no viewer	Set open_browser=True or open http://localhost:2121 manually
ImportError: pylabrobot.hamilton	Backend extras not installed	pip install "pylabrobot[hamilton]"

References

• PyLabRobot Documentation — official docs covering all backends and resources
• PyLabRobot GitHub — source code, examples, and issue tracker
• Azeloglu & Bhatt (2023), Cell Device — PyLabRobot paper — original publication
• PyPI: pylabrobot — installation and version history