Search Results for "convert python to c" - Page 11
Sort By:
Showing 3404 open source projects for "convert python to c"
View related business solutions-
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
LibPQ.jl
A Julia wrapper for libpq
LibPQ.jl is a Julia wrapper for the PostgreSQL libpq C library. -
2
gopy
gopy generates a CPython extension module from a go package
This is an improved version that works with current versions of Go (e.g., 1.15 -- should work with any future version going forward), and uses unique int64 handles to interface with python, so that no pointers are interchanged, making everything safe for the more recent moving garbage collector. It also supports python modules having any number of Go packages, and generates a separate .py module file for each package, which link into a single common binding library. It has been tested... -
3
Tarsier
Vision utilities for web interaction agents
... as buttons, links, or input fields that are visible on the page; Tarsier can also tag all textual elements if you pass tag_text_elements=True. Furthermore, we've developed an OCR algorithm to convert a page screenshot into a whitespace-structured string (almost like ASCII art) that an LLM even without vision can understand. Since current vision-language models still lack fine-grained representations needed for web interaction tasks, this is critical. -
4
ffmpeg.wasm
FFmpeg for browser, powered by WebAssembly
ffmpeg.wasm is a pure WebAssembly (and JavaScript/TypeScript) port of FFmpeg that enables in-browser media recording, conversion, and streaming—letting developers perform video/audio processing entirely client-side without server uploads. -
Turn Your Content into Interactive Magic - For FreeTransform anything you share into an engaging digital experience - for free. Instantly convert your PDFs, slides, and files into dynamic, interactive sessions with built-in collaboration tools, activities, and real-time assessment. From teaching to training to team building, make every presentation unforgettable. Used by millions for education, business, and professional development.
-
5
PocketSVG
Easily convert your SVG files into CGPaths, CAShapeLayers, etc.
A simple toolkit for displaying and manipulating SVGs on iOS and macOS in a performant manner. The goal of this project is not to be a fully compliant SVG parser/renderer. But rather to use SVG as a format for serializing CG/UIPaths, meaning it only supports SVG features that can be represented by CG/UIPaths. Thoroughly documented. -
6
QPanda 2
QPanda 2 is an open source quantum computing framework
QPanda2 is an open source quantum computing framework developed by Origin Quantum, which can be used to build, run and optimize quantum algorithms. QPanda2 is the basic library of a series of software developed by Origin Quantum, which provides core components for QRunes, Qurator and quantum computing services. -
7
PikaPython
An ultra-lightweight Python interpreter that runs with only 4KB of RAM
An ultra-lightweight Python interpreter that runs with only 4KB of RAM, and zero dependencies. It is ready to use out of the box without any configuration required and easy to extend with C. Similar projects: MicroPython, JerryScript. -
8
Hy
A dialect of Lisp that's embedded in Python
... thing a Python programmer will notice about Hy is that it has Lisp’s traditional parenthesis-heavy prefix syntax in place of Python’s C-like infix syntax. As in other Lisps, the value of a simplistic syntax is that it facilitates Lisp’s signature feature, metaprogramming through macros, which are functions that manipulate code objects at compile-time to produce new code objects, which are then executed as if they had been part of the original code. -
9
AsyncAPI
Allows you to create machine-readable definitions of asynchronous APIs
... to understand the capabilities of an event-driven API without requiring access to the source code, documentation, or inspecting the network traffic. It allows you to define your API structures and formats, including channels the end user can subscribe to and the message formats they receive. You can develop, validate, and convert the AsyncAPI document to the latest version or preview your AsyncAPI document in a more readable way using the AsyncAPI Studio. -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
10
Easy3D
Efficient library for processing 3D data
Easy3D is a lightweight, easy-to-use, and efficient library for processing and rendering 3D data, implemented in C++ with Python bindings. It is designed for tasks such as 3D modeling, geometry processing, and rendering, emphasizing simplicity and efficiency. Easy3D serves as a valuable tool for research, education, and the development of sophisticated 3D applications, providing a solid foundation for handling 3D data. -
11
QtAwesome
Iconic fonts in PyQt and PySide applications
QtAwesome enables iconic fonts such as Font Awesome and Elusive Icons in PyQt and PySide applications. It started as a Python port of the QtAwesome C++ library by Rick Blommers. QtAwesome identifies icons by their prefix and their icon name, separated by a period (.) character. Use Font Awesome, Elusive Icons, Material Design Icons, Phosphor, Remix Icon or Microsoft's Codicons. QtAwesome comes bundled with Font Awesome, Elusive Icons, Material Design Icons, Phosphor, Remix Icon and Microsoft's... -
12
EnvPool
C++-based high-performance parallel environment execution engine
EnvPool is a fast, asynchronous, and parallel RL environment library designed for scaling reinforcement learning experiments. Developed by SAIL at Singapore, it leverages C++ backend and Python frontend for extremely high-speed environment interaction, supporting thousands of environments running in parallel on a single machine. It's compatible with Gymnasium API and RLlib, making it suitable for scalable training pipelines. -
13
torchtext
Data loaders and abstractions for text and NLP
We recommend Anaconda as a Python package management system. Please refer to pytorch.org for the details of PyTorch installation. LTS versions are distributed through a different channel than the other versioned releases. Alternatively, you might want to use the Moses tokenizer port in SacreMoses (split from NLTK). You have to install SacreMoses. To build torchtext from source, you need git, CMake and C++11 compiler such as g++. When building from source, make sure that you have the same C... -
14
TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing models
... with a powerful Machine Learning tool set without reinventing the wheel. Since the APIs are kept as similar as possible you can immediately adapt any existing TensorFlow code in C# or F# with a zero learning curve. Take a look at a comparison picture and see how comfortably a TensorFlow/Python script translates into a C# program with TensorFlow.NET. -
15
Recognizers-Text
Recognition and resolution of numbers, units, date/time, etc.
Recognizers-Text is a multilingual text recognition library that extracts structured information such as dates, numbers, and currency values from unstructured text. -
16
TEN
Open-source framework for conversational voice AI agents
TEN (Transformative Extensions Network) is an open source framework designed to empower developers to build real-time multimodal AI agents capable of voice, video, text, image, and data-stream interaction with ultra-low latency. It includes a full ecosystem, TEN Turn Detection, TEN Agent, and TMAN Designer, allowing developers to rapidly assemble human-like, responsive agents that can see, speak, hear, and interact. With support for languages like Python, C++, and Go, it offers flexible... -
17
fastdup
An unsupervised and free tool for image and video dataset analysis
fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale. -
18
Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
... memory in its default configuration. It will likely only work on an RTX 3090, an RTX 2080 Ti, or high-end enterprise GPUs. Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding. -
19
CatBoost
High-performance library for gradient boosting on decision trees
CatBoost is a fast, high-performance open source library for gradient boosting on decision trees. It is a machine learning method with plenty of applications, including ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. CatBoost offers superior performance over other GBDT libraries on many datasets, and has several superb features. It has best in class prediction speed, supports both numerical and categorical features, has a fast and scalable GPU... -
20
TensorFlow Addons
Useful extra functionality for TensorFlow 2.x maintained by SIG-addons
TensorFlow Addons is a repository of contributions that conform to well-established API patterns but implement new functionality not available in core TensorFlow. TensorFlow natively supports a large number of operators, layers, metrics, losses, and optimizers. However, in a fast-moving field like ML, there are many interesting new developments that cannot be integrated into core TensorFlow (because their broad applicability is not yet clear, or it is mostly used by a smaller subset of the... -
21
mlpack
mlpack: a scalable C++ machine learning library
mlpack is an intuitive, fast, and flexible C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers. In addition to its powerful C++ interface, mlpack also provides command-line programs, Python bindings, Julia bindings, Go bindings and R bindings. Written in C++ and built on the Armadillo linear... -
22
PyTorch Geometric
Geometric deep learning extension library for PyTorch
... of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations. -
23
Go Ethereum
Go implementation of the Ethereum protocol
Go Ethereum is the Golang implementation of the Ethereum protocol, a decentralized computing platform that runs smart contracts and applications. There are three original implementations of Ethereum and along with C++ and Python, Go Ethereum is one of them, written in Go. Go Ethereum comes with several wrappers/executables. It is fully open source and available as a standalone client called Geth that you can install on just about any operating system, or as a library that you can embed... -
24
BitNet
Inference framework for 1-bit LLMs
BitNet (bitnet.cpp) is a high-performance inference framework designed to optimize the execution of 1-bit large language models, making them more efficient for edge devices and local deployment. The framework offers significant speedups and energy reductions, achieving up to 6.17x faster performance on x86 CPUs and 70% energy savings, allowing the running of models such as the BitNet b1.58 100B with impressive efficiency. With support for lossless inference and enhanced processing power,... -
25
PyTorch/XLA
Enabling PyTorch on Google TPU
PyTorch/XLA is a Python package that uses the XLA deep learning compiler to connect the PyTorch deep learning framework and Cloud TPUs. You can try it right now, for free, on a single Cloud TPU with Google Colab, and use it in production and on Cloud TPU Pods with Google Cloud. Take a look at one of our Colab notebooks to quickly try different PyTorch networks running on Cloud TPUs and learn how to use Cloud TPUs as PyTorch devices. We are also introducing new TPU VMs for more transparent...
