Step 1: Installation

The aiqclib library can be installed using several popular Python package managers. Standard installation methods using pip or conda are fully supported.

Standard Approaches

You can use one of the following standard methods to install aiqclib.

Using pip

You can install aiqclib directly from PyPI using pip.

Note

It is highly recommended to install the package inside a virtual environment (like venv or virtualenv) to avoid conflicts with other projects or system packages. This is crucial for managing Python dependencies effectively.

pip install aiqclib

Using conda or mamba

The aiqclib package is available on the conda-forge channel, which is the recommended community-maintained channel for Conda packages. You can use either conda or mamba to install it.

# Using conda (creates a new environment if ``aiqclib`` does not need to be found globally)
conda install -c conda-forge aiqclib

# Or using mamba (for a faster installation and better dependency resolution)
mamba install -c conda-forge aiqclib

Using uv

If you prefer to use uv for both creating virtual environments and installing packages, follow these steps. This method is an excellent pure-Python alternative for environment and package management.

Step 1: Create and activate a virtual environment with uv

uv will create a new virtual environment in a .venv directory within your current working directory by default.

# Create a virtual environment
uv venv

# Activate it (on Linux/macOS):
source .venv/bin/activate
# On Windows (in Command Prompt/PowerShell):
.venv\Scripts\activate

Step 2: Install aiqclib

Once your uv-managed virtual environment is activated, proceed with the installation:

uv pip install aiqclib

Recommended Approach for Development: uv with mamba

This method is highly recommended for all users, especially those managing multiple projects or complex dependencies.

Tip

You can use Miniforge to install both conda and mamba together.

Step 1: Install `uv` into your base mamba environment

This makes the uv command available globally without cluttering your base environment.

mamba activate base
mamba install -n base -c conda-forge uv

Step 2: Obtain the source code from GitHub

git clone https://github.com/AIQC-Hub/aiqclib.git

Step 3: Navigate to the project root and create the virtual environment

cd ./aiqclib
uv venv

Step 4: Activate the uv virtual environment

source .venv/bin/activate

Step 5: Install the dependencies

uv sync

Step 6: Install the project

This command installs the library in “editable” mode (-e).

uv pip install -e .

Next Steps

You have now successfully installed the aiqclib library! The next step in your journey is to understand how to prepare your raw data into a format suitable for model training.

Proceed to the next tutorial: Step 2: Dataset Preparation.