proposal-type-annotations
NumPy
proposal-type-annotations | NumPy | |
---|---|---|
101 | 272 | |
4,097 | 26,459 | |
0.7% | 1.1% | |
4.7 | 10.0 | |
about 2 months ago | about 15 hours ago | |
JavaScript | Python | |
- | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
proposal-type-annotations
-
Bun 1.1
That proposal is not fully compatible with Typescript: https://github.com/tc39/proposal-type-annotations?tab=readme...
-
Go 1.22 Release Notes
They held a meeting a few months ago so it's alive but probably still years away.
https://github.com/tc39/proposal-type-annotations/issues/184
-
[AskJS] Kicking a dead horse - TS vs JS
I particularly like this thread in the TC39 types proposal. TypeScript IS a development trojan horse and locks you into the Microsoft Way of being a JS developer.
- Strong static typing, a hill I'm willing to die on...
-
HTML First – Six principles for building simple, maintainable, web software
Edit: There is a proposal to extend JavaScript with type annotations, which would allow ("a reasonably large subset") of TypeScript to run directly in the browser. Yay!
https://github.com/tc39/proposal-type-annotations
-
Building React Components Using Unions in TypeScript
More importantly, TypeScript typically commits to build things into itself when the proposal in JavaScript reaches Stage 3. The pattern matching proposal in JavaScript is Stage 1, but depends on many other proposals as well that may or may not need to be at Stage 3 as well for it to work. This particular proposal is interested on pattern matching on JavaScript Objects and other primitives, just like Python does with it’s native primitives. These are also dynamic types which helps in some areas, but makes it harder than others. Additionally, the JavaScript type annotations proposal needs to possibly account for this. So it’s going to be awhile. Like many years.
-
Show HN: Conway's Game of Life in TypeScript's type system
this is exactly what I want from the _Types as Comments_ proposal[0] as I think it's the only way that types can feasibly become part of the language. It's hard to imagine how all of the concepts TS introduces via special syntax can be covered otherwise.
[0] https://tc39.es/proposal-type-annotations
-
Why Htmx Does Not Have a Build Step
Crossing my fingers that the proposal for allowing (browser-ignored) type annotations in javascript progresses: https://tc39.es/proposal-type-annotations/
Between that, HTTP2/3 and ES modules many of the downsides for building apps with no compile step are almost completely mitigated.
-
TypeScript Without Transpilation
JSDoc can get you pretty far, but it can be clumsy sometimes. There’s a [TC39 proposal](https://github.com/tc39/proposal-type-annotations) to allow types to live in JS code and be treated as comments (similar with Python types today)
- Do you think typescript will ever have native support on brosers? Or we will have only the JS type annotations?
NumPy
-
Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
-
Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.
- JSON dans les projets data science : Trucs & Astuces
-
JSON in data science projects: tips & tricks
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:
-
Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
- help with installing numpy, please
-
A Comprehensive Guide to NumPy Arrays
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.
-
Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
-
NumPy 2.0 development status & announcements: major C-API and Python API cleanup
I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]
What are some alternatives?
astexplorer - A web tool to explore the ASTs generated by various parsers.
SymPy - A computer algebra system written in pure Python
Scala.js - Scala.js, the Scala to JavaScript compiler
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
rescript-compiler - The compiler for ReScript.
blaze - NumPy and Pandas interface to Big Data
Carp - A statically typed lisp, without a GC, for real-time applications.
SciPy - SciPy library main repository
d2-playground - An online runner to play, learn, and create with D2, the modern diagram scripting language that turns text to diagrams.
Numba - NumPy aware dynamic Python compiler using LLVM
proposal-record-tuple - ECMAScript proposal for the Record and Tuple value types. | Stage 2: it will change!
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).