KyPy
@kypython.bsky.social
Lifetime Midwesterner. Python web developer for almost 20 years. @testdouble.bsky.social secret agent and consultant for almost 7 years. To quote Wayne Witzel: “it’s just typing.” Any non-Python content will be over at @kadams54.bsky.social.
Reposted by KyPy
Learn how to normalize inconsistent data structures in Python with Pydantic. This post from Gabriel Côté-Carrier and Kyle Adams guides you through different approaches and pitfalls, using Pydantic's alias path and alias choices features. https://link.testdouble.com/f540d0
November 3, 2025 at 1:57 PM
Learn how to normalize inconsistent data structures in Python with Pydantic. This post from Gabriel Côté-Carrier and Kyle Adams guides you through different approaches and pitfalls, using Pydantic's alias path and alias choices features. https://link.testdouble.com/f540d0
Reposted by KyPy
Python Type System and Tooling Survey 2025 #python
Python Type System and Tooling Survey 2025 #python
Welcome to this annual survey to better understand how Python developers use the type system, type checkers, and integrated development environments (IDEs). The goal of this survey is to gain insights into the tools and practices you use (if any!), the...
docs.google.com
September 16, 2025 at 3:00 AM
Python Type System and Tooling Survey 2025 #python
Reposted by KyPy
You shouldn't have to choose: clean Python code or poorly-named external APIs.
Pydantic field aliases let you have both: Pythonic variable names in your code, whatever naming scheme the API expects on the wire.
No more manual field mapping or workarounds. https://link.testdouble.com/ddffe7
#Python
Pydantic field aliases let you have both: Pythonic variable names in your code, whatever naming scheme the API expects on the wire.
No more manual field mapping or workarounds. https://link.testdouble.com/ddffe7
#Python
September 16, 2025 at 12:03 PM
You shouldn't have to choose: clean Python code or poorly-named external APIs.
Pydantic field aliases let you have both: Pythonic variable names in your code, whatever naming scheme the API expects on the wire.
No more manual field mapping or workarounds. https://link.testdouble.com/ddffe7
#Python
Pydantic field aliases let you have both: Pythonic variable names in your code, whatever naming scheme the API expects on the wire.
No more manual field mapping or workarounds. https://link.testdouble.com/ddffe7
#Python
Reposted by KyPy
Today, we're announcing our first hosted infrastructure product: pyx, a Python-native package registry.
We think of pyx as an optimized backend for uv: it’s a package registry, but it also solves problems that go beyond the scope of a traditional "package registry".
We think of pyx as an optimized backend for uv: it’s a package registry, but it also solves problems that go beyond the scope of a traditional "package registry".
August 13, 2025 at 6:24 PM
Today, we're announcing our first hosted infrastructure product: pyx, a Python-native package registry.
We think of pyx as an optimized backend for uv: it’s a package registry, but it also solves problems that go beyond the scope of a traditional "package registry".
We think of pyx as an optimized backend for uv: it’s a package registry, but it also solves problems that go beyond the scope of a traditional "package registry".
The problem was a large, unruly JSON document, the kind that likely used to be XML. Once you’d gone 4-5 levels deep, it was difficult to hold in your head 1) where you were in the structure, 2) what data was available at the current location, and 3) how to navigate to other pieces of data.
Python type safety lightbulb moment: mypy = compile-time safety Pydantic = runtime safety
Helped a client shift domain knowledge from heads → codebase with this combo. https://link.testdouble.com/769eb9
No more "wait, what does this field contain?" moments 🎯
#python #pydantic
Helped a client shift domain knowledge from heads → codebase with this combo. https://link.testdouble.com/769eb9
No more "wait, what does this field contain?" moments 🎯
#python #pydantic
September 3, 2025 at 1:10 PM
The problem was a large, unruly JSON document, the kind that likely used to be XML. Once you’d gone 4-5 levels deep, it was difficult to hold in your head 1) where you were in the structure, 2) what data was available at the current location, and 3) how to navigate to other pieces of data.