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 3.8 to 3.12

Python Environment Setup 🐍

1. Installing Python

📌 Run these commands in your terminal:

# Check if Python is installed
python --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

📌 Run these commands in your terminal:

# Create a new virtual environment:
python -m venv .venv

# Activate the environment:

# On Windows:
.venv\Scripts\activate  

# On macOS/Linux:
# source .venv/bin/activate

# Install ipykernel for Jupyter notebook support:
pip install ipykernel

SDK Installation Guide 📦

1. Basic Installation

Select the correct Python interpreter

📌 Important: After activating the virtual environment, make sure to select the .venv kernel in your Jupyter notebook:

1. Click on "Kernel" in the top menu
2. Select "Change kernel"
3. Choose .venv from the list
4. Verify the kernel is selected (top right corner should show .venv)

There are two ways to add Python packages to your active .venv:

Option 1: Install package for active venv on terminal

Open terminal and run:

# Activate the virtual environment first
.venv\Scripts\activate  # Windows
# or
source .venv/bin/activate  # macOS/Linux

# Install the package
pip install dtlpy

# Verify installation
pip show dtlpy

Option 2: Run directly from Jupyter notebook

# Install the Dataloop SDK
!pip install dtlpy

# Verify installation
!pip show dtlpy

2. Validation

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

Best Practices & Tips 👑

1. API Keys (For Automated / Headless Workflows) 🔑

For interactive use, dl.login() (covered in the next chapter) is the simplest way to authenticate — it opens a browser window and handles everything for you.

For automated or headless environments (CI/CD pipelines, remote servers, scheduled scripts), use an API key instead:

How to Create an API Key:

1. Navigate to your project dashboard
2. Go to the API Keys tab
3. Click "Create New Key"
4. Store it securely in a .env file to avoid exposing sensitive information

Using API Keys Securely:

Use python-dotenv and .env files to load the API key:

🔒 Best Practices for .env Files:

1. Add .env to your .gitignore file to prevent committing sensitive data
2. Create a .env.example file with dummy values as a template
3. Never commit real credentials to version control
4. Use strong, unique API keys
5. Regularly rotate your API keys

📚 Learn more about environment variable best practices and python dotenv here

# Install python-dotenv
!pip install python-dotenv

from dotenv import load_dotenv
import os

# Load environment variables from .env file
load_dotenv()

# Access your API key securely
api_key = os.getenv('DTLPY_API_KEY')

# Initialize Dataloop with the API key
dl.login_api_key(api_key=api_key)

# DON'T: Hardcode credentials
# api_key = "your-api-key"  # ❌
# Always use environment variables instead

Validation Checklist ✅

Before proceeding, ensure:

• Python version between 3.8 and 3.12 is installed
• Virtual environment is created and activated
• Dataloop SDK is installed
• Installation is verified
• Environment variables are set
• Test import is successful

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