Talk Python to Me• May 15, 2023• 47:51Interview

Future of Pydantic and FastAPI - Talk Python to Me Ep. 415

From Talk Python to Me

Samuel Colvin and Sebastián Ramírez•Creator of Pydantic and Creator of FastAPI

Executive Summary

Samuel Colvin has raised venture capital from investors including Sequoia to form a company around the Pydantic open-source project, with the team currently focused on releasing Pydantic V2.
Pydantic V2, rewritten in Rust, offers a significant performance boost, with benchmarks showing it to be ~22x faster than V1.
This is expected to provide a 10-20x performance improvement for FastAPI users.
The migration from Pydantic V1 to V2 is designed to be mostly transparent for common use cases, though some breaking changes exist, such as stricter type coercion (e.g., integers are no longer coerced to strings).
The Python typing system continues to evolve, with features like `typing.Annotated` being adopted by FastAPI and Pydantic to improve developer experience and enable more powerful, declarative APIs.

12 quotes

Concerns Raised

Migration from Pydantic V1 to V2 may involve subtle breaking changes for edge cases.
APIs may change behavior due to stricter type coercion in Pydantic V2 (e.g., no longer coercing integers to strings).

Opportunities Identified

Massive performance improvements (10-20x) for FastAPI and other dependent libraries.
New commercial services and products to be built around the Pydantic ecosystem.
Simplified and more elegant code in downstream libraries due to Pydantic V2's enhanced serialization.
Improved developer experience and API design through the adoption of `typing.Annotated`.

Key Themes

Commercialization of Open Source

Samuel Colvin discusses raising a funding round led by Sequoia to build a commercial entity around the Pydantic library. This move allows for a full-time dedicated team to accelerate development, starting with the V2 release, before moving on to unannounced commercial products.

This highlights a growing trend of venture capital investment in foundational open-source projects, providing a path to sustainability and accelerated growth for critical developer infrastructure.

Performance Revolution with Pydantic V2

Pydantic V2 represents a ground-up rewrite with a core implemented in Rust, leading to massive performance gains in data validation and serialization. This speedup has a cascading effect, significantly boosting the performance of dependent libraries like FastAPI, LangChain, and others in the ecosystem.

This demonstrates the impact of leveraging high-performance languages like Rust within the Python ecosystem to overcome performance bottlenecks, directly benefiting applications that handle large volumes of data.

Ecosystem Impact and Migration Strategy

The upgrade to Pydantic V2 will have a broad impact, particularly for its largest dependent, FastAPI. The speakers discuss the migration path, aiming for a smooth transition for most users while acknowledging subtle breaking changes and the need for developers to adapt to a stricter validation model.

This provides a case study in managing major version changes in a foundational library, balancing the introduction of powerful new features and performance gains with the need for a clear and manageable upgrade path for the community.

The Evolution of Python's Typing System

The discussion highlights the increasing sophistication and practical application of Python's typing system. Features like `typing.Annotated` are enabling libraries like FastAPI and Pydantic to create more expressive and type-safe APIs, separating metadata from function logic in a clean, standard way.

This shows how the Python language is co-evolving with its most popular libraries, with new typing features being driven by real-world needs, leading to better tooling, static analysis, and overall developer experience.

Advanced Serialization and Customization

Pydantic V2 introduces a highly capable serialization engine that can serialize directly to JSON using Rust's Serde library. It also allows for per-field customization and can output a 'JSON-able' Python dictionary, which simplifies integration with other data formats like XML or YAML.

These new capabilities provide developers with more granular control and higher performance for data output, simplifying API response generation and enabling more efficient data interchange.

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Topics

Pydantic FastAPI Python Typing Performance Optimization Rust Open Source Venture Capital Sequoia Capital API Development Data Validation Serialization typing.Annotated LangChain Developer Experience Library Migration

Processed May 4, 2026 yt-dlp + mlx-whisper + Gemini

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