Installing CryoViT ======================== CryoViT is a Python application, and is installable via :ref:`pip `. For most users, this is the recommended installation method. If you plan on using CryoViT for complicated experiments, or want to extend its functionality, you may want to install it :ref:`from source `. .. highlight:: console After installation, you can check that CryoViT is available by running :: $ cryovit --help This should display the basic usage information for the CryoViT command-line interface (CLI). .. tip:: For local development or even usage, it is recommended to install CryoViT into a separate non-global environment (e.g., using `venv`_ or `conda`_ environments). This prevents dependency conflicts with other Python packages you may have installed. The authors recommend using `miniforge`_, a lightweight version of conda, to manage environments and dependencies. .. _venv: https://docs.python.org/3/library/venv.html .. _conda: https://conda.io/projects/conda/en/latest/user-guide/getting-started.html .. _miniforge: https://github.com/conda-forge/miniforge ======================== PyPI package ======================== CryoViT is available on the `Python Package Index`_ (PyPI). The preferred tool for installing packages from PyPI is **pip**, which is included by default with all modern versions of Python. .. _Python Package Index: https://pypi.org/project/cryovit/ To install the latest stable release of CryoViT, run :: $ pip install -U cryovit Installing from PyPI will naturally give access to all features covered in :ref:`the user guide `, including the CLI and napari plugin. However, some advanced features, such as training on clusters and large-scale experiments, require building from source, as described below. ======================== Installation from Source ======================== You can install CryoViT directly from a clone of the `Git repository`_. This requires having `git`_ installed on your system, as well as a conda-based Python distribution such as `miniforge`_. .. _Git repository: https://github.com/VivianDLi/CryoVIT .. _git: https://git-scm.com/downloads .. _miniforge: https://github.com/conda-forge/miniforge First, clone the repository: :: $ git clone https://github.com/VivianDLi/CryoVIT.git $ cd CryoVIT Next, create a conda environment based on the provided environment file: :: $ conda env create -f environment.yaml This will create a conda environment named `cryovit_env` with all required dependencies. The final step is then to activate the environment and install CryoViT in editable mode: :: $ conda activate cryovit_env $ pip install -e . This will track any changes you make to the source code, allowing you to use CryoViT for development and testing.