{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Installation\n", "\n", "**Step 1.** If you do not have Python installed, we recommend using the [Miniconda distribution](https://docs.anaconda.com/free/miniconda/). Please install miniconda and create a new environment:\n", "```bash\n", "conda create -n ppiref python=3.11\n", "conda activate ppiref\n", "```\n", "\n", "**Step 2.** Then, you can clone and install the complete PPIRef package by running\n", "```bash\n", "git clone https://github.com/anton-bushuiev/PPIRef.git\n", "cd PPIRef; pip install -e .\n", "```\n", "Alternatively, if you are not interested in using the complete repository, including datasets, external software (`./external`), scripts (`./scripts`) or tests (`./tests`), you can simply install PPIRef as a package without cloning the repository:\n", "```bash\n", "pip install git+https://github.com/anton-bushuiev/PPIRef.git\n", "```\n", "This is suitable when you are using the PPIRef code as a dependency and will only install Python source code and download basic data files (data splits and example files from `ppiref/data`).\n", "\n", "**Step 3 (optional).** Please see the `PPIRefexternal/README.md` directory or the corresponding documentation in the \"API Reference\" section for the details on how to install the external software for comparing PPIs and calculating buried surface area (BSA)." ] } ], "metadata": { "language_info": { "name": "python" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }