Before You Begin: Essential Setup 🛠️

Welcome to your Dataloop journey! Let's get your environment perfectly set up for success.

Useful Resources 📚

Before diving into the setup, here are some helpful resources:

1. 🔍 Dataloop Python SDK Cheat Sheet - Quick reference for SDK code examples
2. 💻 Recommended Specifications - System requirements, supported browsers, and file formats
3. 🔑 Sign Up - Create your free Dataloop account
4. 📂 Onboarding Files - Access all onboarding exercise files
5. 📚 In-depth SDK Documentation - Detailed SDK reference

System Requirements 💻

Hardware Requirements

• CPU: 2+ cores recommended
• RAM: 4GB minimum, 8GB+ recommended
• Storage: 1GB+ free space for SDK and dependencies
• Internet: Stable connection required

Software Prerequisites

• Operating System:
  • Windows 10/11
  • macOS 10.14+
  • Ubuntu 18.04+ or other modern Linux distributions
• Python: Version 3.6 or higher
• pip: Latest version recommended

Python Environment Setup 🐍

1. Installing Python

# Check if Python is installed
python --version  # or python3 --version

# If not installed, download from:
# https://www.python.org/downloads/

💡 Pro Tip: Always check "Add Python to PATH" during Windows installation!

2. Setting Up a Virtual Environment

# Create a new virtual environment
python -m venv dataloop-env

# Activate the environment
# On Windows:
dataloop-env\Scripts\activate
# On macOS/Linux:
source dataloop-env/bin/activate

SDK Installation Guide 📦

1. Basic Installation

# Install the Dataloop SDK
pip install dtlpy

# Verify installation
pip show dtlpy

2. Validation

# Test your installation
import dtlpy as dl
print(dl.__version__)

Environment Configuration ⚙️

1. Setting Up Environment Variables

# Windows
set DTLPY_API_KEY=your-api-key

# Linux/macOS
export DTLPY_API_KEY=your-api-key

2. Configuration File Setup

# Create a default configuration
dl.configure()

# Or specify custom settings
dl.configure(api_key='your-api-key',
            environment='prod')

Best Practices & Tips 👑

1. Environment Management

• Always use virtual environments
• Keep dependencies updated
• Document your environment setup

2. Security Best Practices

# DON'T: Hardcode credentials
api_key = "your-api-key"  # ❌

# DO: Use environment variables
import os
api_key = os.environ.get('DTLPY_API_KEY')  # ✅

3. Installation Troubleshooting

Common issues and solutions:

1. SSL Certificate Errors

   # Temporary fix
   pip install --trusted-host pypi.org --trusted-host files.pythonhosted.org dtlpy

2. Dependency Conflicts

   # Clean installation
   pip uninstall dtlpy
   pip cache purge
   pip install dtlpy

3. Version Mismatch

   # Force specific version
   pip install dtlpy==x.y.z

Validation Checklist ✅

Before proceeding, ensure:

• Python 3.8+ is installed
• Virtual environment is created and activated
• Dataloop SDK is installed
• Installation is verified
• Environment variables are set
• Test import is successful

Next Steps 🎯

Once your environment is ready:

1. Configure your credentials
2. Create your first project
3. Start exploring Dataloop's features

🔍 Need Help? Check our troubleshooting guide

Pro Tips 💡

1. IDE Integration

   • Use VS Code or PyCharm for better development experience
   • Install Python extensions for code completion

2. Development Workflow

   import dtlpy as dl
   # Enable debug logging
   dl.verbose.logging_level = "DEBUG"
   

3. Resource Management

   # Always clean up resources
   try:
       # Your code here
   finally:
       dl.logout()

Ready to start your Dataloop journey? Let's move on to authentication and project setup! 🚀