EmbedIO
NumPy
EmbedIO | NumPy | |
---|---|---|
3 | 272 | |
1,430 | 26,510 | |
0.6% | 1.4% | |
0.0 | 10.0 | |
12 months ago | 6 days ago | |
C# | Python | |
GNU General Public License v3.0 or later | 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.
EmbedIO
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Make MAUI app run a Web API Controller
I haven't used it, but EmbedIO looks like it's another option: https://github.com/unosquare/embedio
- There is framework for everything.
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C# web framework without .net??
You could do something like EmbedIO or self-host an OWIN endpoint. But it's not going to "strip away all the magic" so you can learn C# or .Net or all the other stuff easier. You're just moving the goalpost a bit.
NumPy
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
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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
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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:
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Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
- help with installing numpy, please
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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.
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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.
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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?
Kestrel
SymPy - A computer algebra system written in pure Python
BeetleX - high performance dotnet core socket tcp communication components, support TLS, HTTP, HTTPS, WebSocket, RPC, Redis protocols, custom protocols and 1M connections problem solution
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
UploadStream - high performance file upload streaming for dotnet
blaze - NumPy and Pandas interface to Big Data
XSP - Mono's ASP.NET hosting server. This module includes an Apache Module, a FastCGI module that can be hooked to other web servers as well as a standalone server used for testing (similar to Microsoft's Cassini)
SciPy - SciPy library main repository
NetCoreServer - Ultra fast and low latency asynchronous socket server & client C# .NET Core library with support TCP, SSL, UDP, HTTP, HTTPS, WebSocket protocols and 10K connections problem solution
Numba - NumPy aware dynamic Python compiler using LLVM
NancyFx - Lightweight, low-ceremony, framework for building HTTP based services on .Net and Mono. Note: This project is no longer maintained and has been archived.
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).