Installation¶

This guide will help you install Dango on macOS, Linux, or Windows.

Prerequisites¶

Python 3.10-3.12 (Required)¶

Check if you have Python:

# Try these commands in order:
python3.12 --version  # Check for Python 3.12
python3.11 --version  # Check for Python 3.11
python3.10 --version  # Check for Python 3.10

# If any show "3.10" or higher, you're good!

python --version     # Should show 3.10 or higher

Install Python if needed:

sudo apt update
sudo apt install python3.11 python3.11-venv python3-pip

sudo dnf install python3.11

Docker Desktop (Required)¶

Install Docker Desktop:

1. Download from docs.docker.com/desktop
2. Install for your platform (macOS, Linux, or Windows)
3. Start Docker Desktop
4. Verify installation:

docker --version

Disk Space Requirements¶

Data Storage (varies by data volume):

• Small datasets (< 100K rows): < 100MB
• Medium datasets (100K - 1M rows): 100MB - 1GB
• Large datasets (> 1M rows): 1GB+

Supported Platforms¶

• macOS (Intel and Apple Silicon)
• Linux (Ubuntu 20.04+, Debian 11+, Fedora 35+)
• Windows 10/11

Verify Prerequisites¶

Before installing, verify you have everything:

# Check Python (any of these should work):
python3.12 --version  # 3.12.x ✓
python3.11 --version  # 3.11.x ✓
python3.10 --version  # 3.10.x ✓

# Check Docker (required):
docker --version

# Check disk space:
df -h .

python --version     # Should show 3.10 or higher
docker --version

Installation Methods¶

Quick Install (Recommended)¶

The bootstrap installer creates a project directory, sets up a virtual environment, and installs Dango automatically.

curl -sSL https://getdango.dev/install.sh | bash

irm https://getdango.dev/install.ps1 | iex

The installer will:

1. Create a project directory
2. Set up an isolated virtual environment
3. Install Dango from PyPI
4. Initialize your project interactively

What the Installer Does¶

The installer detects your situation and responds appropriately:

You'll be prompted at each decision point—nothing runs without your confirmation.

Security-Conscious Installation¶

If you prefer to inspect the installer first:

# Download the installer
curl -sSL https://getdango.dev/install.sh -o install.sh

# Review what it does
cat install.sh

# Run when ready
bash install.sh

# Download the installer
Invoke-WebRequest -Uri https://getdango.dev/install.ps1 -OutFile install.ps1

# Review what it does
Get-Content install.ps1

# Run when ready
.\install.ps1

View the installer source: install.sh | install.ps1

Manual Installation¶

If you prefer to set things up yourself:

# Create project directory
mkdir my-analytics
cd my-analytics

# Create virtual environment
python3 -m venv venv
source venv/bin/activate

# Install Dango
pip install getdango

# Initialize project
dango init

# Create project directory
New-Item -ItemType Directory -Path my-analytics
Set-Location my-analytics

# Create virtual environment
python -m venv venv
.\venv\Scripts\Activate.ps1

# Install Dango
pip install getdango

# Initialize project
dango init

Verify Installation¶

After installation, verify Dango is working:

# Activate virtual environment (if not already active)
cd my-analytics
source venv/bin/activate

# Check version
dango --version
# Should show: dango, version X.X.X

# Check installation
dango validate

# Activate virtual environment (if not already active)
cd my-analytics
.\venv\Scripts\Activate.ps1

# Check version
dango --version
# Should show: dango, version X.X.X

# Check installation
dango validate

Upgrading Dango¶

Automatic Upgrade (Recommended)¶

If you installed with the bootstrap script:

cd your-project
curl -sSL https://getdango.dev/install.sh | bash
# Select [u] to upgrade when prompted

Manual Upgrade¶

cd your-project
source venv/bin/activate

# Upgrade to latest version
pip install --upgrade getdango

# Verify new version
dango --version

cd your-project
.\venv\Scripts\Activate.ps1

# Upgrade to latest version
pip install --upgrade getdango

# Verify new version
dango --version

After Upgrading¶

# Validate project still works
dango validate

# Restart the platform
dango stop
dango start

Uninstall¶

Virtual Environment Installation¶

If you installed in a virtual environment (recommended), simply delete the project directory:

rm -rf my-analytics/

Remove-Item -Recurse -Force my-analytics

That's it! Everything (venv, data, config) is contained in the project directory.

Global Installation¶

If you installed globally:

Step 1: Find which Python has Dango

# Check each Python version
python3.11 -m pip list | grep getdango
python3.10 -m pip list | grep getdango
python3 -m pip list | grep getdango

# Or find the command location
which dango
# Example output: /Users/you/Library/Python/3.11/bin/dango
# This means use python3.11

# Check Python versions
python -m pip list | findstr getdango
py -3.11 -m pip list | findstr getdango

Step 2: Uninstall Dango

# Use the Python version that has it (e.g., python3.11)
python3.11 -m pip uninstall getdango

python -m pip uninstall getdango

Remove Docker Containers (Optional)¶

If you're done with Dango entirely:

# List running containers
docker ps

# Stop Metabase container
docker stop <metabase-container-id>

# Remove Metabase image (saves disk space)
docker rmi metabase/metabase

Next Steps¶

Now that Dango is installed:

1. Quick Start - Get your first pipeline running
2. Troubleshooting - If you encounter issues
3. Core Concepts - Learn about Dango's architecture

Need Help?¶

If installation fails:

1. Check the Troubleshooting guide
2. Search GitHub Issues
3. Open a new issue with your error message