Installation¶

This page guides you through installing the k-diagram package. Choose the method that best suits your needs.

Requirements¶

Before installing, ensure you have the following prerequisites:

Python: Version 3.6 or higher.
Core Dependencies: k-diagram relies on several standard
scientific Python libraries: * numpy * pandas * scipy * matplotlib * seaborn * scikit-learn

These dependencies are typically installed automatically when you install k-diagram using pip.

Installation from PyPI (Recommended)¶

The easiest and recommended way to install k-diagram is directly from the Python Package Index (PyPI) using pip:

pip install k-diagram

This command downloads and installs the latest stable release of the package along with its required dependencies.

Installation from Source (for Development)¶

If you want to contribute to k-diagram, modify the code, or use the very latest (potentially unstable) version, you can install it from the source repository on GitHub.

Clone the repository: First, clone the repository to your local machine using Git:
```
git clone https://github.com/earthai-tech/k-diagram.git
cd k-diagram
```
Install in editable mode: Install the package in “editable” mode using pip. This links the installed package directly to your cloned source code, so any changes you make are immediately reflected without reinstalling.

It’s also recommended to install the optional development dependencies ([dev]), which include tools for testing and building documentation:
```
pip install -e .[dev]
```
- The -e flag stands for “editable”.
- The . refers to the current directory (the cloned repo root).
- [dev] installs the extra dependencies listed under “dev”
  in setup.py (like pytest, sphinx).

Virtual Environments (Highly Recommended)¶

It is strongly recommended to install Python packages within a virtual environment (using tools like venv or conda). This avoids conflicts between dependencies of different projects.

Note

Using virtual environments keeps your global Python installation clean and ensures project dependencies are isolated.

Using `venv` (Python’s built-in tool):

# Create a virtual environment (e.g., named .venv)
python -m venv .venv

# Activate it (Linux/macOS)
source .venv/bin/activate
# OR Activate it (Windows - Command Prompt)
# .venv\Scripts\activate.bat
# OR Activate it (Windows - PowerShell)
# .venv\Scripts\Activate.ps1

# Now install k-diagram inside the active environment
pip install k-diagram

# Deactivate when finished
# deactivate

Using `conda`:

# Create a new conda environment (e.g., named kdiagram-env)
conda create -n kdiagram-env python=3.9 # Or your preferred Python version

# Activate the environment
conda activate kdiagram-env

# Install k-diagram
pip install k-diagram # Often best to use pip within conda for PyPI packages

# Deactivate when finished
# conda deactivate

Verifying the Installation¶

After installation, you can verify it by importing the package in a Python interpreter or script:

import kdiagram

try:
    print(f"k-diagram version: {kdiagram.__version__}")
except AttributeError:
    print("Could not determine k-diagram version.")

If this runs without errors, the installation was likely successful.

Troubleshooting¶

If you encounter issues during installation:

Ensure you have a compatible version of Python installed and that
pip is up-to-date (pip install --upgrade pip).
Check that you have the necessary build tools if installing from
source or if a dependency requires compilation.
If you face persistent problems, please consult the project’s
GitHub Issues page. Search for similar issues or open a new one with details about your environment and the error message.