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🐍 What is Pyvider?

Pyvider is a Python framework for building Terraform providers. It implements the Terraform Plugin Protocol v6, allowing you to create custom Terraform providers using pure Python.

🤖 AI-Generated Content

This documentation was generated with AI assistance and is still being audited. Some, or potentially a lot, of this information may be inaccurate. Learn more.

🎯 What Problem Does It Solve?

Traditionally, Terraform providers must be written in Go. This creates barriers for teams and individuals who:

  • Prefer Python over Go
  • Already have Python expertise in-house
  • Want to leverage Python's ecosystem (thousands of libraries for APIs, databases, cloud services)
  • Need rapid prototyping without learning a new language
  • Have existing Python infrastructure code they want to wrap as Terraform providers

Pyvider removes these barriers by letting you write providers in Python while maintaining full Terraform compatibility.

🤔 Who Should Use Pyvider?

Perfect For:

  • Python developers wanting to create custom Terraform providers
  • DevOps/Platform engineers automating internal infrastructure
  • Teams with existing Python codebases to expose via Terraform
  • Educators teaching infrastructure-as-code concepts
  • Rapid prototyping of provider ideas before committing to Go

Not Ideal For:

  • Public, high-traffic providers (Go may be more performant)
  • Teams already proficient in Go with existing Go provider codebases
  • Extremely latency-sensitive operations (though Pyvider is quite fast)

🚀 Key Features

  • Pure Python: Write providers using familiar Python patterns
  • Protocol v6: Latest Terraform plugin protocol
  • Async by default: Built on modern async/await Python
  • Type-safe: Leverages Python type hints and attrs
  • Decorator-based: Simple registration system
  • Well-tested: Comprehensive test suite

⚠️ Current Status

Alpha Software

Pyvider is in alpha (v0.0.1000) - please be aware:

  • APIs may change before the 1.0 release without prior notice
  • Best suited for internal tooling, experimentation, and learning
  • Not yet recommended for public or production-critical providers
  • Some documented features may not be fully implemented yet
  • Active development toward 1.0 release with community feedback

Recommended Use Cases: - Internal company tooling and automation - Rapid prototyping of provider concepts - Educational and learning projects - Wrapping existing Python APIs for Terraform

See the Roadmap for feature status and future plans.