Automation Cloud-Native Development Continuous Integration Continuous Delivery Continuous Deployment Continuous Testing Continuous Refactoring Continuous Configuration Automation Continuous Software Engineering DevOps Infrastructure as Code Agile Dynamic Project Management Template Repository Python Package Skeleton Sphinx Website Testing Infrastructure FAIR Software GitHub Actions Bot

PyPackIT [ˈpaɪˌpækɪt] is a comprehensive cloud-based automation tool for production of FAIR and professional applications on GitHub, in accordance with the latest software engineering best practices and standards. PyPackIT is a ready-to-use software suite that streamlines the initiation, configuration, development, publication, management, and maintenance of high-quality Python applications. By taking charge of repetitive tasks and automatically enforcing best practices throughout the software development life cycle, PyPackIT enables users to solely focus on the creative aspects of their projects, while improving quality and lowering production costs. Using latest tools and methodologies, PyPackIT offers a robust project infrastructure, including a build-ready Python package skeleton, a fully operational test suite, an automated documentation website, and a comprehensive control center according to Infrastructure-as-Code and Continuous Configuration Automation practices to enable dynamic project management and customization. PyPackIT establishes a complete cloud development environment on GitHub, integrating with its version control system, issue tracker,and pull-based model to provide a fully automated software development workflow with issue management, branching model, and versioning scheme. Leveraging GitHub Actions, PyPackIT implements a cloud-native Agile development process using Continuous software engineering, containerization, and DevOps methodologies, with a full set of Continuous Integration, Deployment, Testing, Refactoring, and Maintenance pipelines. PyPackIT is a free and open-source software suite that readily integrates with both new and existing projects to ensure their long-term sustainability and high quality, enabling software projects to rapidly implement their ideas and easily maintain their products.

Highlights

PyPackIT is fully preconfigured and easily installable in both new and existing repositories via a GitHub repository template. Most users only need to invest a few minutes filling project-specific information in the provided configuration files. PyPackIT then takes over, setting up the repository and generating a complete infrastructure and fully automated development workflow for the project. This leaves users with only few tasks throughout the software development life cycle, such as adding application code, unit-tests, and minimal documentation content.

PyPackIT is a cloud-based solution that integrates with GitHub and uses GitHub Actions to automate the entire software development process. It provides a cloud-native development environment that eliminates the need for initial setup and configuration, enabling users to immediately begin with the actual implementation of software, even directly from the web browser. All integration, testing, and deployment tasks are automatically carried out on the cloud, facilitating Agile development and ensuring the consistent enforcement of best practices.

PyPackIT offers a centralized user interface for automatic configuration, customization, and management of the entire project, and even multiple projects at once. Based on DevOps practices like Infrastructure-as-Code, PyPackIT's control center consolidates all project configurations into a unified data structure, supporting both declarative definitions and dynamic data generation at runtime via built-in templating, scripting, and online retrieval features. Configurations are automatically applied to related components, eliminating redundancy and rendering the entire project dynamic.

PyPackIT's CI/CD pipelines automate tasks such as code analysis, style formatting, type checking, refactoring, testing, dependency monitoring, versioning, build, containerization, release, and distribution, with support for multiple indexing repositories including PyPI, Anaconda, Zenodo, GitHub Releases, and all Docker registries. These Continuous software engineering pipelines eliminate the need for dedicated integration and deployment teams, while increasing control, integrity, scalability, security, and transparency of the Agile development process.

PyPackIT provides Continuous pipelines that periodically perform automated testing, refactoring, and maintenance tasks such as testing previous releases with up-to-date dependencies, refactoring code according to the latest standards, upgrading development tools and project infrastructure, and cleaning up the repository and its development environment. PyPackIT can automatically submit issue tickets and pull requests for applying updates and fixes, thus maintaining the health of the project and ensuring its long-term sustainability.

PyPackIT automatically maintains the project's issue tracking system, providing type-specific submission forms that are kept up-to-date with project information. These collect user inputs in a structured format, allowing PyPackIT to automate issue management activities such as ticket formatting, labeling, bug triage, task assignment, documentation, issue–commit linkage, and progress reports. Users can also command PyPackIT to perform specific tasks using semantic comments and labels, eliminating all repetitive issue management activities.

PyPackIT fully integrates with Git and GitHub to automate version control tasks like branching, versioning, tagging, commit management, and merging. Based on well-established models such as Git Flow, PyPackIT adopts a specialized branching strategy and version scheme for simultaneous development and deployment of multiple orthogonal release candidates, PyPackIT's strategy enables rapid project evolution according to Agile and Continuous software engineering methodologies, while ensuring availability and long-term support of earlier releases.

PyPackIT supports Python applications with extension modules and non-Python dependencies. It enables deployment as a Python package, a Conda package, and/or a Docker image to cloud services such as PyPI, Anaconda, Docker registries, and BinderHub instances. PyPackIT includes a build-ready package skeleton with essential source files and automatically maintained configuration files customized for the project. Users only need to add application code in the provided source files, while PyPackIT automates all integration, packaging, and deployment tasks.

PyPackIT's fully automated testing infrastructure enables the immediate adoption of test-driven development methodologies, requiring users to only provide test cases in the provided skeleton files. Testing is then automatically performed at various phases of the development life cycle, while generating comprehensive reports and coverage metrics to improve awareness of software health status. The test suite is automatically packaged and distributed along each release, allowing for local verification of software functionality and performance by its users.

PyPackIT includes a fully designed website filled with automatically generated documentation such as project information, package metadata, installation guides, API reference, changelogs, release notes, contribution guides, and citation data. The website is automatically deployed to GitHub Pages and Read The Docs platforms, and can be easily customized via the control center with no web development knowledge. PyPackIT can also dynamically generate standalone documents in various Markdown formats, such as READMEs for different repositories.

PyPackIT incorporates the System Package Data Exchange (SPDX) license standard and supports all SPDX License List licenses and exceptions, as well as user-defined ones. Projects can define complex licenses simply by providing an SPDX license expression. PyPackIT will then automatically retrieve the necessary data from the SPDX database, customize it with project-specific information, generate visually appealing and syntactically valid license files and copyright notices, and integrate license information into all project components and releases.

PyPackIT improves project security while supporting community collaboration by incorporating security measures like branch and tag protection rulesets, vulnerability scanning, dependency monitoring, and private security advisories. All provided GitHub Actions workflows and applications are developed according to the latest security standards to prevent unauthorized access, data breaches, and code injection attacks. To ensure that PyPackIT is highly secure and transparent, most of its infrastructure is natively implemented and self-contained.

Upcoming Release

0.0.0 major 2025-04-14

Project Initialization

This is an initial emtpy release.

Latest Developmental Release

Requirements

⚙️ Operating System any

Python 3.10 | 3.11 | 3.12 | 3.13 any

📦 Dependencies any

Interfaces

API pypackit

pypackit

Statistics

Acknowledgements

PyPackIT was developed in Volkamer Lab.

Filters