Your First Steps in Dataloop 🎯

What Can You Do? 🌟

With our powerful Python SDK, you'll have full control over your entire AI development lifecycle:

Core Resources 📊

• 📁 Projects - Your high-level workspaces
• 📊 Datasets - Your data collections
• 🖼️ Items - Your individual files
• ✏️ Annotations - Your data labels
• 📝 Metadata - Your custom data attributes

Advanced Features 🚀

• 🤖 Model Management - Train, deploy, and monitor ML models
• 🔄 Pipelines - Build automated AI workflows
• ⚡ FaaS (Function as a Service) - Deploy serverless functions
• 📦 DPKs (Dataloop Package Kit) - Package and share your solutions
• 🎯 Tasks - Manage annotation and review workflows

AI Development Tools 🧠

• 🔍 Model Zoo - Access pre-trained models
• 🎓 Transfer Learning - Fine-tune existing models
• 📈 Model Metrics - Track performance and metrics
• 🔄 Data Versioning - Manage dataset versions

Automation & Integration 🔗

• 🔄 Webhooks - Set up event-driven workflows
• 🌐 REST API - Integrate with external systems
• 🔌 Plugins - Extend platform functionality
• 🤝 Team Collaboration - Manage users and roles

Authentication & Security 🔐

1. Interactive Login

import dtlpy as dl

# Smart login with token handling
if dl.token_expired():
    dl.login()

2. Headless Authentication

# Using API key (recommended for automation)
dl.login_api_key(api_key=os.environ['DTLPY_API_KEY'])

# Using email/password (not recommended for production)
dl.login_m2m(email='your-email@company.com', 
             password=os.environ['DTLPY_PASSWORD'])

3. Token Management

# Check token status
is_expired = dl.token_expired()

# Logout
dl.logout()

Project Management Mastery 🏗️

1. Creating Your First Project

# Create a new project
project = dl.projects.create(project_name='My-Awesome-Project')

# Get existing project
project = dl.projects.get(project_name='My-Awesome-Project')

2. Project Configuration

# Add project members
project.add_member(
    email='teammate@company.com',
    role=dl.MemberRole.Developer
)

3. Project Organization

# List all projects
projects = dl.projects.list()
for project in projects:
    print(f"Project: {project.name}")

Dataset Organization 📊

1. Creating Datasets

# Create a new dataset
dataset = project.datasets.create(dataset_name='training-data')

# Clone an existing dataset
cloned_dataset = dataset.clone(
    clone_name='validation-data'
)

2. Dataset Management

# List all datasets
datasets = project.datasets.list()

# Get dataset by name
dataset = project.datasets.get(dataset_name='training-data')

# Update dataset
dataset.name = 'training-data-v1'
dataset.update()

Team Collaboration Essentials 👥

1. Role Management

# Add team member with role
project.add_member(
    email='annotator@company.com',
    role=dl.MemberRole.Annotator
)

# Update member role
project.update_member(
    email='annotator@company.com',
    role=dl.MemberRole.Developer
)

2. Access Control

# List project members
members = project.members.list()
for member in members:
    print(f"{member.email}: {member.role}")

# Remove member
project.remove_member(email='ex-teammate@company.com')

Best Practices 👑

1. Project Organization

• Use clear naming conventions
• Add detailed descriptions
• Maintain proper documentation
• Tag resources appropriately

2. Security Practices

# Use environment variables
api_key = os.environ.get('DTLPY_API_KEY')

# Regular token refresh
if dl.token_expired():
    dl.refresh_token()

3. Resource Management

# Clean up unused resources
try:
    # Your code here
finally:
    # Logout when done
    dl.logout()

Troubleshooting Guide 🔧

Common Issues:

1. Authentication Failures

   # Check token status
   print(dl.token_expired())
   
   # Force re-authentication
   dl.login_m2m(force=True)

2. Project Access Issues

   # Verify project existence
   try:
       project = dl.projects.get(project_name='My-Project')
   except dl.exceptions.NotFound:
       print("Project not found!")

3. Dataset Operations

   # Handle dataset errors
   try:
       dataset.update(description='New description')
   except dl.exceptions.Forbidden:
       print("Insufficient permissions!")

Ready to start working with data? Let's move on to data management! 🚀