Search Results for "converting c++ code to python"
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Showing 16 open source projects for "converting c++ code to python"
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Intelligent testing agents | Checksum.aiCoding agents write the code. Checksum runs it—continuously testing against real APIs, real data, real edge cases—before it ever reaches production.
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Google Open Source Project Style Guide
Chinese version of Google open source project style guide
Each larger open source project has its own style guide, a series of conventions on how to write code for the project (sometimes more arbitrary). When all the code maintains a consistent style, it is more important when understanding large code bases. easy. The meaning of "style" covers a wide range, from "variables use camelCase" to "never use global variables" to "never use exceptions". The English version of the project maintains the programming style guidelines used in Google. If the... -
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rust-by-practice
Challenging examples, exercises and projects
rust-by-practice is a hands-on, exercise-oriented learning resource for the Rust programming language that takes users beyond theory into real code challenges and practical patterns. Rather than simply listing Rust syntax or language features, it structures its content around progressively complex problems, each designed to illustrate a core Rust concept such as ownership, borrowing, lifetimes, traits, concurrency, zero-cost abstractions, and safe systems programming idioms. The repository... -
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LeetCode Book
Comprehensive study guide for coding interviews
LeetCode-Book is a comprehensive study guide for coding interviews that consolidates algorithm patterns, data-structure templates, and worked LeetCode solutions. It organizes problems by topic—arrays, linked lists, stacks/queues, trees/graphs, dynamic programming, greedy, backtracking, and math—so you can study systematically. Explanations are concise but intentional, highlighting why a pattern fits, how to reason about boundary cases, and the time/space trade-offs. Many entries include... -
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Build your own X
Master programming by recreating your favorite technologies
build-your-own-x is a massive, community-curated roadmap of hands-on tutorials that teach you to re-implement complex systems from scratch—things like databases, compilers, operating systems, interpreters, web servers, neural networks, regex engines, and more. Rather than offering abstract theory, it organizes step-by-step guides by topic and by programming language, so you can pick a project that fits your stack and skill level. The focus is on demystifying internals: you don’t just use a... -
CompanyCam is a photo-based solution created for contractors, by contractors.Take unlimited photos—which are location and time-stamped, sent to the cloud, and stored securely. Every photo is organized by project and instantly available to your team, allowing you to see what’s going on anytime, anywhere. Annotate photos with drawings, arrows, comments, tags, and voice notes, and create project timelines, photo galleries, reports, and transformation photos through the app. Sharing photos with customers and insurance adjusters has never been easier, and keeping your entire process organized has never been simpler.
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Simulation of Urban MObility
SUMO is a microscopic, multi-modal traffic simulation.
SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians and comes with a large set of tools for scenario creation. The code and the issue tracker can be found at https://github.com/eclipse-sumo/sumo/ The documentation can be found at https://sumo.dlr.de/docs/ -
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Prime number ( primenumbers )
Benchmark for 50 000 000 prime numbers as single and multicore
Simple source files and compiled JAR Java programs, for benchmark 50 000 000 cycle finding prime numbers. On Intel(R) Core(TM) i5-8600K CPU, Windows 10 20H2, i have 39 second on single core and 7,6 second on multi core. (PS: C++ multicore 6 second). Added C files for gcc compiler in Windows 10 and for Xcode C command line project in MacOS ( tested on Mac mini M2 with single core 16 to 25 sec and multicore 2,3 to 5 second by compiler -O switch). Surprise, same code in JavaScript for M2 chip in Safari: 12,5 sec single core and 3,3 sec multi core. Python version with numba and numpy on MacOS with M2: 3,78 sec, Intel Ultra 5 225F Linux Fedora 43 GNOME(*Intel): 3,64 sec., W11Intel: 3,73; Faster style in python, MacOS M2: 1,81 sec, *Intel & W11Intel: 2,02 sec.; Ultra faster style in python, MacOS M2: 1,24 s - 1,26 s - 1,34 s, *Intel: 1,48 s - 1,50 s, W11Intel: 1,53 - 1,63. -
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clavirio
Learn touch typing without leaving the terminal
A free, open-source typing tutor for the terminal. Progressive lessons, practice modes, real-time stats, and a virtual keyboard with finger hints — for QWERTY, Dvorak, and Colemak. Methodology Research on typing skill suggests that skilled typing relies more on implicit procedural control than on explicit knowledge of key locations. The paper also suggests that the keyboard is represented in terms of its row-and-column structure, not as a memorized list of individual... -
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The Art of Programming
A collection of practical tips can be found at the bottom of this page
The Art of Programming (Second Edition) is a curated collection of programming problems and solutions originally derived from the Microsoft 100 Interview Questions blog series, later refined into a long-running tutorial and ultimately a published book. Created by July, the series began in 2010 and has since evolved into an in-depth exploration of algorithmic thinking, data structures, and coding interview preparation. The repository brings together 42 classic programming problems from the... -
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Hello AI World
Guide to deploying deep-learning inference networks
...In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train your own DNN models onboard Jetson with PyTorch. Ready to dive into deep learning? It only takes two days. We’ll provide you with all the tools you need, including easy to follow guides, software samples such as TensorRT code, and even pre-trained network models including ImageNet and DetectNet examples. ... -
Taking the Paper Out of WorkThe Square 9 AI-powered intelligent document processing platform takes the paper out of work and makes it easier to get things done with digital workflows.
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wav2letter++
Facebook AI research's automatic speech recognition toolkit
First, install Flashlight (using the 0.3 branch is required) with the ASR application. This repository includes recipes to reproduce the following research papers as well as pre-trained models. All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run... -
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FFmpeg libav tutorial
FFmpeg libav tutorial
FFmpeg libav tutorial, learn how media works from basic to transmuxing, transcoding and more. Most of the code in here will be in C but don't worry: you can easily understand and apply it to your preferred language. FFmpeg libav has lots of bindings for many languages like python, go and even if your language doesn't have it, you can still support it through the ffi (here's an example with Lua). We'll start with a quick lesson about what is video, audio, codec and container and then we'll go to a crash course on how to use FFmpeg command line and finally we'll write code, feel free to skip directly to the section Learn FFmpeg libav the Hard Way. ... -
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A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
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fPotencia
Power flow library in C++
...After observing the lack of ready-to-implement libraries for power system analisys, and that the existing ones focus on command line workflow, I decided myself to start a project to fill the gap. Since Power system simulations have started needing to be executed in parallel, the old C-like designs are outdated; modular design is now needed to launch many simulations at the same time based on a base circuit. fPotencia is programmed in C++, but my intention is to bring JAVA, C#, Python and perhaps MATLAB versions of it. All of them in native code and whenever possible with the same modular structure. -
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Mac OS X and Windows OpenGL 3D Engine tools, content and code to create games and applications. Newton physics, OpenAL sound with OGG Vorbis, Lua, Revolution, written in C.
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python-in-scheme is a scheme library that allows you to run python code within scheme. It uses the Python/C API to embed a python interpreter.
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Institute of Technology, Blanchardstown Computer Science code by the class of 2007-2011 on course BN104. In this project we are open sourcing all of our project work to the public in the hopes it can be reused, built-upon, and used in education.
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