⚡️ Instant Boilerplate for Python Projects ⚡️
Fast, easy and reliable project generator for your Python projects.Getting Started • Usage • How to: Custom Projects • AI Agent Harness
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Instant Python replaces extensive manual setup with a simple command to get started quickly. Its motivation is to emulate
commands like `ng new` or `create-react-app`, but for Python projects.
Why use Instant Python? Generating your Python project with Instant Python lets you:
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🚀 Quick Start
Once installed, generating a project takes two commands:
ipy config # answer a few questions through an interactive wizard to create your ipy.yml configuration file
ipy init # generate the project from that configuration file
ipy configasks you about your project (name, Python version, project manager, template, dependencies, and more) and writes anipy.ymlconfiguration file in the current directory.ipy initreads thatipy.ymlfile and generates your new project.
See the First Steps guide for a full walkthrough.
✨ NEW ✨ Create Fully Customized Projects
Take full control of your project generation! With custom templates, you can:
- 🎨 Design your own project structure that matches your architectural patterns (like Hexagonal Architecture)
- 📝 Create reusable file templates with your standardized code and best practices
- 🔄 Enforce consistency across all your Python projects
- ⚡ Eliminate repetitive boilerplate and setup tasks
Whether you have a standardized project structure you always use or specific architectural patterns you want to enforce, custom templates let you generate projects exactly the way you want them. Learn how to create your first custom template and level up your project generation workflow!
🤖 AI Agents Setup
Generate projects with a pre-configured AI agent environment to assist your development workflow. When you include the
ai_agents built-in feature, your project comes with:
AGENTS.md— Project rules and guidelines that configure AI agents to follow your coding standards- Skills — Reusable instruction sets for common tasks: code review, refactoring, story splitting, test analysis, and more
- Commands — On-demand workflows for recurring operations: committing changes, running security reviews, analyzing technical debt
- Architecture Decision Records (ADR) — Templates to document and track technical decisions
- Design Docs — Templates to capture feature requirements and implementation plans
All generated under docs/ and .agents/ directories, ready to use with any AI coding assistant that supports agent configuration.
See all available skills and commands.
Navigation Guide
This section provides a high-level overview of the instant-python documentation
so can quickly find what you need.
For Users
- Installation: begin by learning how to install
instant-python. - First Steps: get started with the basic features of
instant-python. - Privacy & Metrics: learn about the anonymous usage data we collect and how to opt out.
- Advanced Usage and Customization: explore advanced features and customization options.
For Developers
- Contributing: learn how to contribute to
instant-pythondevelopment. - Releases: understand our release process and versioning.
- Security: understand our security policies and reporting procedures.
Need help?
- Join a discussion 💬 on GitHub Discussions
- Raise an issue on GitHub
🔒 Privacy & Usage Metrics
To improve instant-python and provide a better experience, we collect anonymous usage metrics.
No personal or sensitive information is collected.
What we collect:
- Command executed and IPY version
- Operating system type
- Python version, dependency manager, and template choices
- Error types (when commands fail)
What we DON'T collect:
- No file paths, project names, or code content
- No personal information or IP addresses
How to opt out:
Set the environment variable IPY_METRICS_ENABLE=false
For complete details, see our Privacy & Metrics documentation.
1 maintainer
Metadata
1 maintainer
Release files for instant-python 0.27.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| instant_python-0.27.1.tar.gz | 507.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| instant_python-0.27.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 748.9 kB
Release files / instant_python-0.27.1.tar.gz
| Download URL | instant_python-0.27.1.tar.gz |
|---|---|
| Size | 507.1 kB |
| Tags | Source |
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Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / instant_python-0.27.1-py3-none-any.whl
| Download URL | instant_python-0.27.1-py3-none-any.whl |
|---|---|
| Size | 241.8 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 12, 2026.
Transparency log
