/benchling-integration

name: benchling-integration
description: "Benchling R&D Python SDK: CRUD on registry entities (DNA, RNA, proteins, custom), inventory, ELN, workflow automation. Needs Benchling account and API key. Use biopython for local sequence analysis; pubchem for chemical DBs."
license: "Apache-2.0"

Benchling Integration — R&D Platform SDK

Overview

Benchling is a cloud platform for life sciences R&D. The Python SDK provides programmatic access to registry entities (DNA, proteins), inventory, electronic lab notebooks, and workflows. All operations require a Benchling tenant URL and API key or OAuth credentials.

When to Use

• Creating, updating, or querying biological sequences (DNA, RNA, proteins) in Benchling registry
• Automating inventory operations (containers, boxes, locations, sample transfers)
• Creating or querying electronic lab notebook (ELN) entries programmatically
• Building workflow automations (task creation, status updates, bulk operations)
• Bulk importing entities from FASTA files or spreadsheets into Benchling
• Exporting Benchling data to CSV or external databases for analysis
• Syncing Benchling with external systems via event-driven integrations
• For **local sequence analysis** (BLAST, alignment), use biopython instead
• For **chemical compound databases**, use pubchem-compound-search instead

Prerequisites

pip install benchling-sdk

**Authentication setup**: Obtain an API key from Benchling Profile Settings. Store securely in environment variables — never commit to version control.

import os
from benchling_sdk.benchling import Benchling
from benchling_sdk.auth.api_key_auth import ApiKeyAuth

benchling = Benchling(
    url="https://your-tenant.benchling.com",
    auth_method=ApiKeyAuth(os.environ["BENCHLING_API_KEY"])
)

**OAuth (for multi-user apps)**:

from benchling_sdk.auth.client_credentials_oauth2 import ClientCredentialsOAuth2

benchling = Benchling(
    url="https://your-tenant.benchling.com",
    auth_method=ClientCredentialsOAuth2(
        client_id=os.environ["BENCHLING_CLIENT_ID"],
        client_secret=os.environ["BENCHLING_CLIENT_SECRET"]
    )
)

**API rate limits**: Benchling enforces per-tenant rate limits. The SDK automatically retries on 429 responses with exponential backoff (up to 5 retries by default). For bulk operations, add `time.sleep(0.5)` between batches.

Quick Start

from benchling_sdk.benchling import Benchling
from benchling_sdk.auth.api_key_auth import ApiKeyAuth
from benchling_sdk.models import DnaSequenceCreate
import os

benchling = Benchling(
    url="https://your-tenant.benchling.com",
    auth_method=ApiKeyAuth(os.environ["BENCHLING_API_KEY"])
)

# Create a DNA sequence
seq = benchling.dna_sequences.create(
    DnaSequenceCreate(name="GFP-insert", bases="ATGGTGAGCAAGGGC", is_circular=False, folder_id="fld_abc123")
)
print(f"Created: {seq.name} ({seq.id})")

Core API

1. Registry — Entity CRUD

Registry entities include DNA sequences, RNA sequences, AA sequences, custom entities, and mixtures. All entity types follow the same create/read/update/archive pattern.

from benchling_sdk.models import DnaSequenceCreate, DnaSequenceUpdate

# Create
sequence = benchling.dna_sequences.create(
    DnaSequenceCreate(
        name="My Plasmid",
        bases="ATCGATCG",
        is_circular=True,
        folder_id="fld_abc123",
        schema_id="ts_abc123",
        fields=benchling.models.fields({"gene_name": "GFP"})
    )
)
print(f"Created: {sequence.id}")

# Read
seq = benchling.dna_sequences.get_by_id(sequence.id)
print(f"Name: {seq.name}, Length: {len(seq.bases)} bp")

# Update (partial — unspecified fields unchanged)
updated = benchling.dna_sequences.update(
    sequence_id=sequence.id,
    dna_sequence=DnaSequenceUpdate(
        name="Updated Plasmid",
        fields=benchling.models.fields({"gene_name": "mCherry"})
    )
)

# Archive
benchling.dna_sequences.archive(ids=[sequence.id], reason="RETIRED")

# Register entity in registry (with auto-generated ID)
registered = benchling.dna_sequences.create(
    DnaSequenceCreate(
        name="Production Plasmid",
        bases="ATCGATCG",
        is_circular=True,
        folder_id="fld_abc123",
        entity_registry_id="src_abc123",
        naming_strategy="NEW_IDS"  # or "IDS_FROM_NAMES"
    )
)
print(f"Registry ID: {registered.entity_registry_id}")

# Entity types available via SDK:
# benchling.dna_sequences, benchling.rna_sequences,
# benchling.aa_sequences, benchling.custom_entities, benchling.mixtures

2. Registry — Listing and Pagination

All list operations return paginated generators for memory efficiency.

# List with pagination
sequences = benchling.dna_sequences.list()
total = sequences.estimated_count()
print(f"Total sequences: {total}")

for page in sequences:
    for seq in page:
        print(f"  {seq.name} ({seq.id}): {len(seq.bases)} bp")

# Filter by schema
filtered = benchling.dna_sequences.list(schema_id="ts_abc123")
for page in filtered:
    for seq in page:
        print(f"  {seq.name}")

3. Inventory Management

Manage physical samples, containers, boxes, and locations.

from benchling_sdk.models import ContainerCreate, BoxCreate

# Create container (sample tube)
container = benchling.containers.create(
    ContainerCreate(
        name="Sample Tube 001",
        schema_id="cont_schema_abc123",
        parent_storage_id="box_abc123",
        fields=benchling.models.fields({"concentration": "100 ng/uL"})
    )
)
print(f"Container: {container.id}, Barcode: {container.barcode}")

# Create box
box = benchling.boxes.create(
    BoxCreate(
        name="Freezer Box A1",
        schema_id="box_schema_abc123",
        parent_storage_id="loc_abc123"
    )
)

# Transfer container to new location
benchling.containers.transfer(
    container_id=container.id,
    destination_id="box_xyz789"
)
print(f"Transferred {container.name} to new box")