Installation#
SixGman can be installed in several ways depending on your workflow:
Standard Installation (from GitHub)
Editable / Development Installation (recommended for contributors)
Prerequisites#
Python 3.8+ (recommended 3.9 for Conda)
pip and optionally conda
Git installed if installing directly from the repository
1️⃣ Standard Installation (Non-editable)#
You can install the latest version directly from GitHub:
Option 1: Using Python venv (Recommended for lightweight setup)
# Create virtual environment
python -m venv .venv
# Activate it
source .venv/bin/activate # Linux/Mac
.venv\Scripts\activate # Windows
# Install the package
pip install git+https://github.com/OS-ONDT/SixGman.git
Option 2: Using Conda (Recommended for data science users)
# Create a conda environment with Python 3.9+
conda create -n sixgman-env python=3.9 -y
# Activate environment
conda activate sixgman-env
# Install the package
pip install git+https://github.com/OS-ONDT/SixGman.git
This will install SixGman and all required dependencies.
2️⃣ Development / Editable Installation#
If you plan to modify the code or contribute, use editable mode.
Step 1: Clone the repository
git clone https://github.com/OS-ONDT/SixGman.git
cd SixGman
Step 2: Create a virtual environment (Recommended)
Option 1: Using Python venv (Recommended for lightweight setup)
# Create virtual environment
python -m venv .venv
# Activate it
source .venv/bin/activate # Linux/Mac
.venv\Scripts\activate # Windows
# Install in editable mode
pip install -e .
Option 2: Using Conda (Recommended for data science users)
# Create a conda environment with Python 3.9+
conda create -n sixgman-env python=3.9 -y
# Activate environment
conda activate sixgman-env
# Install in editable mode
pip install -e .
This allows local changes to reflect immediately without reinstallation.
Verify Installation#
To check the installation:
python -c "import sixgman; print(sixgman.__version__)"
If no error appears, the package is installed correctly.