Deep dive into: Python Typing Survey 2025: Code Quality and Flexibility As Top Reasons for Typing Adoption

The 2025 Typed Python Survey, conducted by contributors from JetBrains, Meta, and the broader Python typing community, offers a comprehensive look at the current state of Python’s type system and developer tooling. With 1,241 responses (a 15% increase from last year), the survey captures the evolving sentiment, challenges, and opportunities around Python typing in the open-source ecosystem. In this blog we’ll cover a summary of the key findings and trends from this year’s results.

The survey was initially distributed on official social media accounts by the survey creators, and subsequently shared organically across further platforms including Reddit, email newsletters, Mastodon, LinkedIn, Discord, and Twitter. When respondents were asked which platform they heard about the survey from, Reddit emerged as the most effective channel, but significant engagement also came from email newsletters and Mastodon, reflecting the diverse spaces where Python developers connect and share knowledge.

The respondent pool was predominantly composed of developers experienced with Python and typing. Nearly half reported over a decade of Python experience, and another third had between five and 10 years. While there was representation from newcomers, the majority of participants brought substantial expertise to their responses. Experience with type hints was similarly robust, with most respondents having used them for several years and only a small minority indicating no experience with typing.

The survey results reveal that Python’s type hinting system has become a core part of development for most engineers. An impressive 86% of respondents report that they “always” or “often” use type hints in their Python code, a figure that remains consistent with last year’s Typed Python survey. 

For the first time this year the survey also asked participants to indicate how many years of experience they have with Python and with Python typing. We found that adoption of typing is similar across all experience levels, but there are some interesting nuances:

Overall, the data shows that type hints are widely embraced by the Python community, with strong support from engineers at all experience levels. However, we should note there may be some selection bias at play here, as it’s possible developers who are more familiar with types and use them more often are also more likely to be interested in taking a survey about it.

When asked what developers loved about the Python type system there were some mixed reactions, with a number of responses just stating, “nothing” (note this was an optional question). This indicates the presence of some strong negative opinions towards the type system among a minority of Python users. The majority of responses were positive, with the following themes emerging prominently:

In addition to assessing positive sentiment towards Python typing, we also asked respondents what challenges and pain points they face. With over 800 responses to the question, “What is the hardest part about using the Python type system?” the following themes were identified:

A little less than half of respondents had suggestions for what they thought was missing from the Python type system, the most commonly requested features being:

Analysis & Development

The developer tooling landscape for Python typing continues to evolve, with both established and emerging tools shaping how engineers work.

Mypy remains the most widely used type checker, with 58% of respondents reporting using it. While this represents a slight dip from 61% in last year’s survey, Mypy still holds a dominant position in the ecosystem. At the same time, new Rust-based type checkers like Pyrefly, Ty, and Zuban are quickly gaining traction, now used by over 20% of survey participants collectively.

When it comes to development environments, VS Code leads the pack as the most popular IDE among Python developers, followed by PyCharm and (Neo)vim/vim. The use of type checking tools within IDEs also mimics the popularity of the IDE themselves, with VS Code’s default (Pylance/Pyright) and PyCharm’s built-in support being the first and third most popular options respectively.

When it comes to learning about Python typing and getting help, developers rely on a mix of official resources, community-driven content, and AI-powered tools, a similar learning landscape to what we saw in last year’s survey.

Official documentation remains the go-to resource for most developers. The majority of respondents reported learning about Python typing through the official docs, with 865 citing it as their primary source for learning and 891 turning to it for help. Python’s dedicated typing documentation and type checker-specific docs are also heavily used, showing that well-maintained, authoritative resources are still highly valued.

Blog posts have climbed in popularity, now ranking as the second most common way developers learn about typing, up from third place last year. Online tutorials, code reviews, and YouTube videos also play a significant role.

Community platforms are gaining traction as sources for updates and new features. Reddit, in particular, has become a key channel for discovering new developments in the type system, jumping from fifth to third place as a source for news. Email newsletters, podcasts, and Mastodon are also on the rise.

Large language models (LLMs) are now a notable part of the help-seeking landscape. Over 400 respondents reported using LLM chat tools, and nearly 300 use in-editor LLM suggestions when working with Python typing. 

Future Impact

The 2025 Python Typing Survey highlights the Python community’s sustained adoption of typing features and tools to support their usage. It also points to clear opportunities for continued growth and improvement, including:

To learn more about Meta Open Source, visit our website, subscribe to our YouTube channel, or follow us on Facebook, Threads, X, Bluesky and LinkedIn.

Thanks to everyone who participated! The Python typing ecosystem continues to evolve, and your feedback helps shape its future.

Meta believes in building community through open source technology. Explore our latest projects in Artificial Intelligence, Data Infrastructure, Development Tools, Front End, Languages, Platforms, Security, Virtual Reality, and more.

Engineering at Meta is a technical news resource for engineers interested in how we solve large-scale technical challenges at Meta.

To help personalize content, tailor and measure ads and provide a safer experience, we use cookies. By clicking or navigating the site, you agree to allow our collection of information on and off Facebook through cookies. Learn more, including about available controls: Cookie Policy

Source: View Original