Search Results for "python programming language" - Page 5
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Showing 5254 open source projects for "python programming language"
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curlconverter
Convert curl commands to Python, JavaScript, Go, PHP, etc.
curlconverter transpiles curl commands into programs in other programming languages. You can choose the output language by passing --language <language>. The options are Python python (the default), JavaScript browser node node-request, Go go, Rust rust, PHP php, Java java, R r, Elixir elixir, Dart dart, MATLAB matlab and a few more. The JavaScript API is a bunch of functions that can take either a string of Bash code or an array. curlconverter requires Node 12+. -
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AICGSecEval
A.S.E (AICGSecEval) is a repository-level AI-generated code security
AICGSecEval is an open-source benchmark framework designed to evaluate the security of code generated by artificial intelligence systems. The project was developed to address concerns that AI-assisted programming tools may produce insecure code containing vulnerabilities such as injection flaws or unsafe logic. The framework constructs evaluation tasks based on real-world software repositories and known vulnerability cases derived from CVE records. By simulating realistic development... -
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CodeGeeX
CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)
CodeGeeX is a large-scale multilingual code generation model with 13 billion parameters, trained on 850B tokens across more than 20 programming languages. Developed with MindSpore and later made PyTorch-compatible, it is capable of multilingual code generation, cross-lingual code translation, code completion, summarization, and explanation. It has been benchmarked on HumanEval-X, a multilingual program synthesis benchmark introduced alongside the model, and achieves state-of-the-art... -
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Xi Programming Language
A general-purpose, mutliparadigm language.
Xi is a programming language which attempts to play a similar role to languages such as C, C++, or D. It is initially designed to leverage the procedural and object-oriented paradigms. It aims to provide an expressive language based off of a simple, LL(1) grammar with a comprehensive class library. -
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SGLang
SGLang is a fast serving framework for large language models
SGLang is a fast serving framework for large language models and vision language models. It makes your interaction with models faster and more controllable by co-designing the backend runtime and frontend language. -
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how-to-optim-algorithm-in-cuda
How to optimize some algorithm in cuda
how-to-optim-algorithm-in-cuda is an open educational repository focused on teaching developers how to optimize algorithms for high-performance execution on GPUs using CUDA. The project combines technical notes, code examples, and practical experiments that demonstrate how common computational kernels can be optimized to improve speed and memory efficiency. Instead of presenting only theoretical explanations, the repository includes hand-written CUDA implementations of fundamental operations... -
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JILL.py
A cross-platform installer for the Julia programming language
The enhanced Python fork of JILL, Julia Installer for Linux (and every other platform), Light. -
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LOTUS
AI-Powered Data Processing: Use LOTUS to process all of your datasets
LOTUS is an open-source framework and query engine designed to enable efficient processing of structured and unstructured datasets using large language models. The system provides a declarative programming model that allows developers to express complex AI data operations using high-level commands rather than manually orchestrating model calls. It offers a Python interface with a Pandas-like API, making it familiar for data scientists and engineers already working with data analysis libraries. ... -
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Playground Cheatsheet for Python
Playground and cheatsheet for learning Python
...The design supports “learn by doing”: you can modify the code, run the tests, see how behavior changes, and thus internalize Python language features, idioms, and good style practices (including linting and PEP8). Because it is organized in bite-sized chunks, it’s ideal for beginners or people refreshing their Python skills who want to revisit syntax and common patterns before moving into larger frameworks or applications. It also supports usage as a reference: if you forgot how a list comprehension works or how decorators behave, you can quickly open the relevant script. -
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ECMAScript
Status, process, and documents for ECMA-262
...It contains the content of the most recent yearly snapshot plus any finished proposals (those that have reached Stage 4 in the proposal process and thus are implemented in several implementations and will be in the next practical revision) since that snapshot was taken. This Ecma Standard defines the ECMAScript 2022 Language. It is the twelfth edition of the ECMAScript Language Specification. Since publication of the first edition in 1997, ECMAScript has grown to be one of the world's most widely used general-purpose programming languages. It is best known as the language embedded in web browsers but has also been widely adopted for server and embedded applications. ... -
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Chez Scheme
A programming language and an implementation of that language
Chez Scheme is both a programming language and an implementation of that language, with supporting tools and documentation. As a superset of the language described in the Revised6 Report on the Algorithmic Language Scheme (R6RS), Chez Scheme supports all standard features of Scheme, including first-class procedures, proper treatment of tail calls, continuations, user-defined records, libraries, exceptions, and hygienic macro expansion. -
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Magicoder
Empowering Code Generation with OSS-Instruct
Magicoder is an open-source family of large language models designed specifically for code generation and software development tasks. The project focuses on improving the quality and diversity of code generation by training models with a novel dataset construction approach known as OSS-Instruct. This technique uses open-source code repositories as a foundation for generating more realistic and diverse instruction datasets for training language models. -
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Racket
The Racket repository
Racket is a general-purpose programming language and an ecosystem for language-oriented programming. This repository holds the source code for the core of Racket plus some related packages. The rest of the Racket distribution source code is in other repositories, mostly under the Racket GitHub organization. Racket programmers typically program with functions, records, objects, exceptions, regular expressions, modules, and threads. -
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Odin
Odin Programming Language
Odin is a general-purpose programming language with distinct typing built for high performance, modern systems, and data-oriented programming. Odin has been designed for readability, scalability, and orthogonality of concepts. Simplicity is complicated to get right, clear is better than clever. Odin allows for the highest performance through low-level control over the memory layout, memory management, custom allocators and so much more. -
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YueScript
A Moonscript dialect compiles to Lua
...The original language is getting too hard to adopt new features for those that may break the stability of existing applications. So Yuescript is a new code base for pushing the language to go forward and being a playground to try introducing new language syntax or programming paradigms to make Moonscript language more expressive and productive. -
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Dasar Pemrograman Golang
Source Code E-book Dasar Pemrograman Golang
Goal, or Go is a programming language that was born in 2009. The goal has many advantages, as evidenced by a large number of large companies using this language in the development of their products, up to the level of production of course. This ebook is one of the many references that can be used as learning material for Go programming. The topics provided vary greatly from basic ( from 0), to adventurous chapters. -
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autoMate
AI tool for automating desktop tasks via natural language input
autoMate is an AI-powered local automation tool designed to enable users to control and automate their computers using natural language instructions instead of traditional scripting or rule-based systems. It combines large language models with computer vision techniques to interpret user intent and understand on-screen content, allowing it to interact with graphical interfaces similarly to a human user. autoMate follows an observe-decide-act workflow, where it analyzes the screen, plans... -
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Solidity
The Smart Contract Programming Language
Solidity is a statically-typed curly-braces programming language designed for developing smart contracts that run on Ethereum. Solidity 0.8.4 adds custom structured errors, allows more flexible configuration of the SMTChecker and fixes a bug in the Solidity ABI decoder v2. Read more about the bug here. With v0.8.4, errors can be defined inside and outside of contracts (including interfaces and libraries). -
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sectorlisp
Bootstrapping LISP in a Boot Sector
The sectorlisp project is a minimal implementation of the Lisp programming language designed to fit within extremely constrained environments. It is engineered to run in very small memory footprints, making it suitable for educational purposes and experimentation with low-level programming concepts. The project demonstrates how a functional programming language can be implemented with minimal resources while still retaining core features. -
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rust-analyzer
A Rust compiler front-end for IDEs
rust-analyzer is a modular compiler frontend for the Rust language. It is a part of a larger rls-2.0 effort to create excellent IDE support for Rust. If you want to contribute to rust-analyzer or are just curious about how things work under the hood, check the ./docs/dev folder. If you want to use rust-analyzer's language server with your editor of choice, check the manual folder. It also contains some tips & tricks to help you be more productive when using rust-analyzer. rust-analyzer is an implementation of Language Server Protocol for the Rust programming language. ... -
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Numba CUDA Target
The CUDA target for Numba
Numba CUDA Target is NVIDIA’s maintained CUDA backend for the Numba JIT compiler, enabling developers to write GPU-accelerated code directly in Python. It allows users to define CUDA kernels using Python syntax, which are then compiled into efficient GPU code at runtime using LLVM-based toolchains. This approach significantly lowers the barrier to entry for GPU programming by eliminating the need to write CUDA C++ while still delivering high performance. The project supports the SIMT programming model, allowing developers to control threads, blocks, and memory hierarchies similarly to native CUDA programming. -
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Swift
The Swift Programming Language
Swift is a high-performance, general-purpose programming language built with a modern approach to safety, performance, and software design patterns. With a clean and modern syntax, it offers seamless access to existing C and Objective-C code and frameworks. Swift makes it easy to write software that is incredibly fast and safe by design. It comes packaged with core features like flow control, data structures and functions, with high-level constructs like objects, protocols, closures, and generics. ... -
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Mecha
A parser combinator library for Zig
A parser combinator library for the Zig programming language. Time to make your own parser mech. -
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PyQuil
A Python library for quantum programming using Quil
PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. ... -
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NVIDIA Warp
A Python framework for accelerated simulation, data generation
NVIDIA Warp is a high-performance Python framework developed by NVIDIA for building and accelerating simulation, graphics, and physics-based workloads using GPU computing. It enables developers to write kernel-level code in Python that is automatically compiled into efficient CUDA kernels, combining ease of use with near-native performance. The framework is designed for applications such as robotics, reinforcement learning, physical simulation, and differentiable computing, where performance and flexibility are critical. ...
