A compiler for liquid handling. Describe experiments in Python, check the protocol, and produce a document or a robot program.
Lab Compiler is the Python compiler for laboratory work. A Protocol records materials, wells, steps, and optional sample identities and lineage. Compilation checks volumes, units, bindings, and sample declarations, then writes a printable document and code for the liquid handler you name.
Protocol containers, steps, and decks are expressed in Lab types. A Deck holds shared container requirements and can include a DeckLayout for each liquid handler. Compilation selects the layout, checks the handler's capabilities, and translates Lab equipment and placements into Opentrons or PyLabRobot configuration. Supported presets handle simple layouts. You do not need to construct SDK deck objects.
Install the lab-compiler distribution with Python 3.11 or 3.12, and import it as lab:
pip install lab-compilerThe base package compiles printable documents. Install the optional SDK for your robot target:
pip install "lab-compiler[opentrons]" # OT-2 and Flex
pip install "lab-compiler[star]" # Hamilton STARUse "lab-compiler[opentrons,star]" to install both SDKs.
A Protocol records what a scientist would write at the bench: the plates, what starts in each well, and every transfer and mix. This one prepares a two-fold dilution series of fluorescein in PBS, the standard curve for a plate reader.
from lab import Protocol, compile, uL
from lab.deck import Container, Deck, DeckSite
from lab.equipment import LiquidHandler
from lab.labware import PLATE_96
protocol = Protocol("fluorescein serial dilution")
sources = protocol.plate("sources", capacity=360 * uL)
assay = protocol.plate("assay", capacity=360 * uL)
fluorescein, pbs, waste = sources["A1"], sources["A2"], sources["A3"]
protocol.load(fluorescein, "10 µM fluorescein in PBS", volume=150 * uL)
protocol.load(pbs, "PBS", volume=300 * uL)
dilutions = [assay[f"A{column}"] for column in range(1, 7)]
protocol.transfer(fluorescein, dilutions[0], volume=100 * uL)
protocol.distribute(pbs, dilutions[1:], volume=50 * uL)
# Carry 50 µL down the row, mixing each well before the next transfer.
for previous, current in zip(dilutions, dilutions[1:]):
protocol.transfer(previous, current, volume=50 * uL)
protocol.mix(current, volume=40 * uL, cycles=3)
protocol.transfer(dilutions[-1], waste, volume=50 * uL)
protocol.manual("Read fluorescence at 485 nm excitation and 525 nm emission.")
deck = Deck(
containers=(
Container(id="sources", labware=PLATE_96, site=DeckSite.PLATES),
Container(id="assay", labware=PLATE_96, site=DeckSite.PLATES),
)
)
compiled = compile(protocol, deck=deck, liquid_handler=LiquidHandler.FLEX)compile() checks every volume against the wells and the pipette, then writes a printable protocol and an Opentrons Flex program. The deck only says both plates sit in open plate positions; the Flex preset chooses the slots, tip rack, and pipette. Wells A1–A6 of the assay plate each finish with 50 µL.
A DeckLayout states the equipment and positions instead of leaving them to a preset. This OT-2 deck places the dilution protocol's sources and assay plates in slots 1 and 2, a 300 µL tip rack in slot 3, and a P300 pipette on the left mount. It uses the same equipment and placement types as the deck layouts example.
from lab.deck import Deck, DeckLayout, Pipette, Placement, Slot, TipRack
from lab.equipment import LabwareModel, LiquidHandler, Mount, PipetteModel, TipRackModel
from lab.labware import PLATE_96, ContainerSpec
deck = Deck(
containers=(
ContainerSpec(id="sources", labware=PLATE_96),
ContainerSpec(id="assay", labware=PLATE_96),
),
layouts=(
DeckLayout(
liquid_handler=LiquidHandler.OT2,
placements=(
Placement(
container="sources",
model=LabwareModel.CORNING_96_360_UL,
location=Slot("1"),
),
Placement(
container="assay",
model=LabwareModel.CORNING_96_360_UL,
location=Slot("2"),
),
),
tip_racks=(
TipRack(
id="tips",
model=TipRackModel.OPENTRONS_300_UL,
location=Slot("3"),
),
),
pipettes=(
Pipette(
model=PipetteModel.P300_SINGLE_GEN2,
mount=Mount.LEFT,
tip_racks=("tips",),
),
),
),
),
)Compile the dilution protocol for that robot:
compiled = compile(protocol, deck=deck, liquid_handler=LiquidHandler.OT2)Use DeckLayout when equipment or placement needs to be explicit. Each layout names its LiquidHandler and places the same shared containers. All objects below belong to Lab:
| Object | Purpose |
|---|---|
Placement |
A container's physical labware model, position, and optional well mapping |
Slot, Rail, HolderSite |
A deck slot, carrier rail, or indexed site on a named holder |
Carrier, Module |
Equipment that occupies a position and holds other resources |
TipRack |
A tip model and its position |
Pipette, Channel |
A mounted pipette or independent channel, with its assigned tip racks |
Equipment models are typed identifiers from lab.equipment; each backend resolves the models it supports. A STAR layout can place a carrier at Rail(20) and a plate at HolderSite("plates", 3). An Opentrons layout can place the same logical container at Slot("2") or on a named module. The shared model does not impose one thermal device on every handler. Targets enforce their supported device counts, models, locations, and module footprints.
The deck layouts example prepares duplicate BSA standards and purified protein samples in a flat-bottom assay plate using a reservoir of prepared BCA working reagent. protocol() describes the transfers; deck() shares the container requirements and calls opentrons_layout() for OT-2 and Flex and hamilton_layout() for STAR. The logical source wells map to physical wells B1–B12 on each handler; STAR also specifies carriers, rails, and occupied carrier sites. Mixing, incubation, and absorbance reading remain an explicit operator handoff following the Pierce BCA guide. The example imports only Lab types and the Python standard library, with layouts to adapt to installed equipment.
from examples.deck_layouts import deck, protocol
from lab import compile
from lab.equipment import LiquidHandler
compiled = compile(protocol(), deck=deck(), liquid_handler=LiquidHandler.STAR)The compiler rejects missing layouts, conflicting placements, invalid holder references, incompatible labware, and unsupported target features. It preserves the authored Lab deck in plan.json alongside the resolved backend configuration. Physical geometry comes from the selected equipment definitions; the STAR backend constructs and serializes the PyLabRobot resource hierarchy internally.
For Opentrons, place thermal labware on a supported Module. STAR layouts currently support one independent Channel and external thermal integration. Declare thermal containers in DeckLayout.external_thermal_resources and supply the async thermocycle callback when the generated run() executes. The callback is responsible for controlling the device and returning the plate to its original position. Compilation checks the declaration; the software preview only reports the request. On-deck Module models are not yet supported by the STAR backend.
By default, thermocycling matches the lid target to each block target within the device's heated lid range and turns lid heating off below that range. On Opentrons, the lid follows block targets at 37 °C and above; colder holds turn off the lid heater. Persistent thermocycler holds use the same rule, including setup and plating. An explicit lid_temperature keeps the lid at a fixed target throughout a profile. Successful profiles keep their final temperature settings; a failed Opentrons profile shuts down both controllers. External STAR thermal callbacks follow the same contract when lid_temperature=None.
The examples live in the source repository. With uv installed, set up Python 3.12 and both optional SDKs:
git clone https://github.com/MyersResearchGroup/LabCompiler.git
cd LabCompiler
uv sync --locked --all-extras --python 3.12
uv run --no-sync python -m examples.cloning --target manual
uv run --no-sync python -m examples.cloning --target ot2
uv run --no-sync python -m examples.deck_layouts --target star
uv run --no-sync python -m examples.deck_layouts --target ot2
uv run --no-sync python -m examples.deck_layouts --target flexUse manual or ot2 for the cloning example. Its assembly recipe includes transfers below the current Flex preset's supported pipetting range. The deck layouts example supports ot2, flex, and star.
The cloning example writes separate assembly, transformation, and plating bundles under build/cloning/<target>, including for the manual target. The deck layouts example writes to build/decks/<target>. Both accept --out to choose a different output directory. Compilation never connects to hardware.
compile() writes the bundle to ~/.lab/<protocol>/<target>/. LAB_HOME replaces ~/.lab, and to chooses another directory. to=None returns the compilation without writing. Compiling the same protocol and target again replaces that bundle.
Compilation.write() writes these files to a chosen directory:
| File | Contents | When written |
|---|---|---|
protocol.html |
Printable protocol and setup instructions | Every compilation |
plan.json |
Recorded protocol, sample declarations, target configuration, bindings, and final volumes | Every compilation |
manifest.json |
Planned output samples and logical placements | When the protocol declares outputs |
protocol.py |
Generated robot program | Robot targets |
The manifest uses logical container and well names; physical bindings remain in plan.json. Rewriting an identical bundle succeeds. If any generated file would replace different contents, write() rejects the write before changing any bundle files.
The HTML worksheet shows initial loads, numbered operations, liquid-class settings, and calculated final volumes. Hover or focus a material, location, resource, or liquid class to inspect its recorded details; click to keep the card open and press Escape to dismiss it. Location cards distinguish initial loads, planned final volumes, output samples, and incoming transfers. The first paragraph of Protocol.description is the overview; subsequent paragraphs appear in expandable protocol notes. Styles and interactions are embedded for offline use, with a plain reference section when JavaScript is disabled and a separate print layout.
The worksheet UI guide describes its typed view data, reusable templates, and interactive components.
The preparation preview shows logical plate layouts and reagent inputs. Step through or play the procedure to see source volumes decrease and destination wells fill; a schematic pipette and directional paths show each transfer. Distributions visit each destination, and mixes animate in place. Click a procedure step number to preview that state. Well details and reagent amounts follow the selected step. The preview uses the compiler's volume accounting, with animation timing chosen for readability. It shows planned liquid movement; physical well bindings are available in the detail cards.
Liquid-class cards plot flow rate against time for the selected operation. Aspiration is positive and dispensing negative; mixing repeats those phases. Durations are ideal calculations from nominal volume divided by the recorded rate, excluding robot movement, pauses, ramps, air gaps, and volume correction. These diagrams are not measured device traces. Native Hamilton profiles require rates captured during STAR compilation.
Preparation proceeds across the plate: medium first, then vehicle and each stock, followed by inoculation and mixing. Equal doses from the same source share a distribute() operation and one tip. Unique doses remain individual transfers. Preparing the full supplied layout requires 327 tips, including source resuspension and destination mixing. The worksheet reports the tip count alongside the operation count.
The standalone concentration-series example reads a plate layout and protocol configuration, then records ordinary transfers and mixes. The supplied layout preserves the well coordinates and target concentrations of an LMSF fitness export, with generic strain and plasmid names. Every CSV row is prepared by default: 96 wells covering 24 conditions for each of four plasmid samples. An optional wells list in the configuration selects a subset explicitly. lab.units.dilution_volume() calculates stock volumes; the recipe balances vehicle and medium, inoculates, and mixes. Source identities and volumes, working-stock selection, and liquid classes are explicit. The TOML also declares development OT-2 and STAR deck layouts, parsed directly into Lab's existing Deck types, with reservoir sources and enough tips for the full plate.
main() parses the TOML into ProtocolConfig and the CSV into PlateLayout using Pydantic. The reusable quantity fields and liquid-class schemas come from lab.config, available through lab-compiler[config] and included in development dependencies (uv sync --locked). prepare_wells() checks the inputs together and calculates doses; protocol() consumes those prepared wells and the validated configuration to record operations. The configuration mirrors the TOML: medium.name is config.medium.name, and liquid-class names remain names until protocol construction resolves them. Saved configuration comes from that same model.
uv run --no-sync python -m examples.concentration_series \
--csv examples/concentration_series/layout.csv \
--config examples/concentration_series/config.toml --target manualUse --target ot2 or --target star with the corresponding optional SDK installed. Output goes to build/concentration_series/csv/<target>/; --out selects another directory. Rerunning replaces the generated bundle in that directory. The example ends with an inoculated plate; incubation and measurement need separately specified methods.
LiquidClass supplies unit-checked aspiration and dispense rates on either robot family. HamiltonLiquidClass references a native STAR built-in, whose definition is captured during compilation. Both can be passed as liquid_class= to transfer(), distribute(), and mix(). See liquid classes for examples, settings coverage, calibration boundaries, and the data needed to compare with VENUS.
From the repository root:
uv sync --locked --all-extras --python 3.12
uv run --no-sync ruff check .
uv run --no-sync mypy
uv run --no-sync pytestThe concentration-series tests use the same layout.csv and config.toml as the example. They exercise parsing, dose calculations, compilation, robot simulation, and provenance without additional data files or configuration.
CI runs the OT-2 equivalence tests against a pinned PUDU revision. To compare against another checkout, set PUDU_SOURCE to its src directory. When this variable is set, missing PUDU source or the Opentrons SDK fails the run.
PUDU_SOURCE=/path/to/PUDU/src uv run --no-sync pytest -q tests/test_ot2_equivalence.pySee the release guide for package validation and PyPI publishing, and the release notes for changes and migration guidance.