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://raw.githubusercontent.com/getdango/dango/main/install.sh | bash

irm https://raw.githubusercontent.com/getdango/dango/main/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

Security-Conscious Installation¶

If you prefer to inspect the installer first:

# Download the installer
curl -sSL https://raw.githubusercontent.com/getdango/dango/main/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://raw.githubusercontent.com/getdango/dango/main/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://raw.githubusercontent.com/getdango/dango/main/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