---

name: domino-python-sdk description: Programmatically interact with Domino using python-domino SDK and REST APIs. Covers authentication, running jobs, managing projects, file operations, model deployment, and automation. Use when automating Domino workflows, integrating with CI/CD, or building custom tooling around Domino.

Domino Python SDK Skill

Description

This skill helps users work with the Domino Python SDK (python-domino) and REST APIs to programmatically interact with Domino.

Activation

Activate this skill when users want to:

• Use the Domino Python SDK
• Make API calls to Domino
• Automate Domino workflows
• Integrate Domino with external systems
• Query Domino programmatically

Overview

Domino provides two main programmatic interfaces:

• python-domino: Python SDK for common operations
• REST API: Full HTTP API for all Domino features

Installation

python-domino

Copy# Install from PyPI
pip install dominodatalab

# Or install with extras
pip install "dominodatalab[data]"

In Domino Environment

Add to requirements.txt:

Copydominodatalab>=1.4.0

Or Dockerfile:

CopyRUN pip install dominodatalab

Authentication

API Key

Get your API key from Domino:

1. Go to Account Settings
2. Click API Keys
3. Generate or copy key

Configure SDK

Copyfrom domino import Domino

# Option 1: Pass credentials directly
domino = Domino(
    host="https://your-domino.com",
    api_key="your-api-key",
    project="owner/project-name"
)

# Option 2: Environment variables
import os
os.environ["DOMINO_API_HOST"] = "https://your-domino.com"
os.environ["DOMINO_USER_API_KEY"] = "your-api-key"

domino = Domino("owner/project-name")

# Option 3: Inside Domino (auto-configured)
domino = Domino("owner/project-name")  # Uses built-in auth

Common Operations

Projects

Copyfrom domino import Domino

domino = Domino()

# Create project
project = domino.project_create(
    project_name="my-new-project",
    owner_name="username"
)

# Get project info
info = domino.project_info()
print(f"Project: {info['name']}")
print(f"ID: {info['id']}")

Jobs (Runs)

Copy# Start a job
run = domino.runs_start(
    command="python train.py --epochs 100",
    hardware_tier_name="medium",
    environment_id="env-id"
)
print(f"Run ID: {run['runId']}")

# Start job with different commit
run = domino.runs_start(
    command="python train.py",
    commit_id="abc123"
)

# Check status
status = domino.runs_status(run['runId'])
print(f"Status: {status['status']}")

# Wait for completion
domino.runs_wait(run['runId'])

# Get logs
logs = domino.runs_get_logs(run['runId'])
print(logs)

# Stop a run
domino.runs_stop(run['runId'])

Workspaces

Copy# Start workspace
workspace = domino.workspace_start(
    hardware_tier_name="medium",
    environment_id="env-id",
    workspace_type="JupyterLab"
)
print(f"Workspace ID: {workspace['workspaceId']}")

# Stop workspace
domino.workspace_stop(workspace['workspaceId'])

Files

Copy# Upload file
domino.files_upload(
    path="local/file.csv",
    dest_path="/mnt/code/data/"
)

# Download file
domino.files_download(
    path="/mnt/code/results/output.csv",
    dest_path="local/output.csv"
)

# List files
files = domino.files_list("/mnt/code/")
for f in files:
    print(f['path'])

Datasets

Copy# Create dataset
dataset = domino.datasets_create(
    name="training-data",
    description="Training dataset"
)

# List datasets
datasets = domino.datasets_list()

# Create snapshot
snapshot = domino.datasets_snapshot(
    dataset_name="training-data",
    tag="v1.0"
)

Environments

Copy# List environments
environments = domino.environments_list()
for env in environments:
    print(f"{env['name']}: {env['id']}")

# Get environment details
env = domino.environment_get("env-id")

Model APIs

Copy# Publish model
model = domino.model_publish(
    file="model.py",
    function="predict",
    environment_id="env-id",
    name="my-classifier",
    description="Classification model"
)
print(f"Model ID: {model['id']}")

# List models
models = domino.models_list()

# Get model info
model_info = domino.model_get("model-id")

REST API

Direct API Calls

Copyimport requests

headers = {
    "X-Domino-Api-Key": "your-api-key",
    "Content-Type": "application/json"
}

# Get projects
response = requests.get(
    "https://your-domino.com/v4/projects",
    headers=headers
)
projects = response.json()

# Start a run
response = requests.post(
    f"https://your-domino.com/v4/projects/{project_id}/runs",
    headers=headers,
    json={
        "command": "python train.py",
        "hardwareTierId": "tier-id"
    }
)
run = response.json()

Common Endpoints

Domino Data API

Separate SDK for data access:

Copyfrom domino_data.data_sources import DataSourceClient

# Initialize client
client = DataSourceClient()

# List data sources
sources = client.list_data_sources()

# Query data source
df = client.get_datasource("my-datasource").query(
    "SELECT * FROM customers WHERE region = 'US'"
)

Automation Examples

CI/CD Integration

Copy# trigger_training.py - Call from CI/CD pipeline
from domino import Domino
import sys

domino = Domino("team/ml-project")

# Start training job
run = domino.runs_start(
    command="python train.py",
    hardware_tier_name="gpu-large"
)

# Wait for completion
result = domino.runs_wait(run['runId'])

if result['status'] != 'Succeeded':
    print(f"Training failed: {result['status']}")
    sys.exit(1)

print("Training completed successfully!")

Batch Job Scheduler

Copy# Run multiple experiments
from domino import Domino
import itertools

domino = Domino("team/experiments")

# Parameter grid
params = {
    "learning_rate": [0.01, 0.001, 0.0001],
    "batch_size": [32, 64, 128]
}

# Generate combinations
combinations = list(itertools.product(*params.values()))
param_names = list(params.keys())

# Submit all experiments
runs = []
for combo in combinations:
    param_str = " ".join(
        f"--{name}={value}"
        for name, value in zip(param_names, combo)
    )
    run = domino.runs_start(
        command=f"python experiment.py {param_str}",
        hardware_tier_name="gpu-small"
    )
    runs.append(run['runId'])
    print(f"Started run {run['runId']} with {param_str}")

# Wait for all to complete
for run_id in runs:
    result = domino.runs_wait(run_id)
    print(f"Run {run_id}: {result['status']}")

Model Deployment Pipeline

Copyfrom domino import Domino

domino = Domino("team/model-deployment")

# 1. Train model
train_run = domino.runs_start(command="python train.py")
domino.runs_wait(train_run['runId'])

# 2. Evaluate model
eval_run = domino.runs_start(command="python evaluate.py")
domino.runs_wait(eval_run['runId'])

# 3. Deploy if evaluation passes
# (Check evaluation results first)
model = domino.model_publish(
    file="serve.py",
    function="predict",
    name="production-model"
)

print(f"Model deployed: {model['id']}")

Error Handling

Copyfrom domino import Domino
from domino.exceptions import DominoException

try:
    domino = Domino("team/project")
    run = domino.runs_start(command="python train.py")
except DominoException as e:
    print(f"Domino error: {e}")
except Exception as e:
    print(f"Unexpected error: {e}")

Best Practices

1. Use Environment Variables

Copyimport os

# Don't hardcode credentials
api_key = os.environ.get("DOMINO_USER_API_KEY")
host = os.environ.get("DOMINO_API_HOST")

2. Handle Rate Limits

Copyimport time
from domino.exceptions import DominoException

def api_call_with_retry(func, max_retries=3):
    for attempt in range(max_retries):
        try:
            return func()
        except DominoException as e:
            if "rate limit" in str(e).lower():
                time.sleep(2 ** attempt)
            else:
                raise
    raise Exception("Max retries exceeded")

3. Log API Calls

Copyimport logging

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def start_run(command):
    logger.info(f"Starting run: {command}")
    run = domino.runs_start(command=command)
    logger.info(f"Run ID: {run['runId']}")
    return run

Detailed API Reference

For comprehensive REST API documentation, see these specialized guides:

Documentation Reference

• API Guide
• REST API Reference
• python-domino Library
• GitHub Repository