Search Results for "python-gtksourceview2" - Page 6
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Showing 713 open source projects for "python-gtksourceview2"
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LIEF
LIEF - Library to Instrument Executable Formats (C++, Python, Rust)
LIEF (Library to Instrument Executable Formats) is a cross-platform library that enables parsing, modifying, and abstracting executable formats such as ELF, PE, and Mach-O. It's widely used in reverse engineering and binary analysis. -
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Stanza
Stanford NLP Python library for many human languages
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. ... -
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UCO3D
Uncommon Objects in 3D dataset
...The repository includes automated downloaders with checksum verification, fine-grained controls to fetch only selected modalities or super-categories, and a lightweight Python API for loading frames, geometry, and splats on demand. Metadata is indexed in SQLite for quick queries at scale, and helper builders handle alignment, undistortion, frame extraction from videos, and cropping around the object. -
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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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Recommenders 2023
Best Practices on Recommendation Systems
Recommenders objective is to assist researchers, developers and enthusiasts in prototyping, experimenting with and bringing to production a range of classic and state-of-the-art recommendation systems. Recommenders is a project under the Linux Foundation of AI and Data. -
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Pants Build System
The Pants Build System
Pants 2 is a fast, scalable, user-friendly build system for codebases of all sizes. It's currently focused on Python, Go, Java, Scala, Kotlin, Shell, and Docker, with support for other languages and frameworks coming soon. A lot of effort has gone into making Pants easy to adopt, easy to use and easy to extend. We're super excited to bring Pants' distinctive features to Go, Java, Python, Scala, Kotlin, and Shell users. Pants requires very minimal BUILD file metadata/boilerplate. ... -
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Boltons
250+ constructs, recipes, and snippets which extend the Python library
Boltons is a set of pure-Python utilities in the same spirit as, and yet conspicuously missing from, the standard library. Due to the nature of utilities, application developers might want to consider other integration options. Boltons is tested against Python 2.6-2.7, 3.4-3.7, and PyPy. The majority of boltons strive to be “good enough” for a wide range of basic uses, leaving advanced use cases to Python’s myriad specialized 3rd-party libraries. -
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Public APIs
A collective list of free APIs
public-apis is a collaboratively maintained repository that provides an extensive, categorized list of publicly available APIs for developers. Curated by community contributors and the team at APILayer, it serves as a centralized resource for discovering APIs across a wide range of domains, including data, machine learning, weather, entertainment, and finance. The project aims to make API exploration and integration more accessible by offering a single, organized index of open and... -
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spaCy
Industrial-strength Natural Language Processing (NLP)
spaCy is a library built on the very latest research for advanced Natural Language Processing (NLP) in Python and Cython. Since its inception it was designed to be used for real world applications-- for building real products and gathering real insights. It comes with pretrained statistical models and word vectors, convolutional neural network models, easy deep learning integration and so much more. spaCy is the fastest syntactic parser in the world according to independent benchmarks, with an accuracy within 1% of the best available. ... -
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LLM CLI
Access large language models from the command-line
A CLI utility and Python library for interacting with Large Language Models, both via remote APIs and models that can be installed and run on your own machine. -
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Semantix
Non-Pydantic, Non-JSON Schema, efficient AutoPrompting
Semantix empowers developers to infuse meaning into their code through enhanced variable typing (semantic typing). By leveraging the power of large language models (LLMs) behind the scenes, Semantix transforms ordinary functions into intelligent, context-aware operations without explicit LLM calls. -
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Pymunk
Pymunk is a easy-to-use pythonic 2d physics library
Pymunk is an easy-to-use Pythonic 2D physics library that can be used whenever you need 2D rigid body physics from Python. Perfect when you need 2D physics in your game, demo or simulation! It is built on top of the very capable 2D physics library Chipmunk2D. The first version was released in 2007 and Pymunk is still actively developed and maintained today, more than 15 years of active development. Pymunk has been used with success in many projects, big and small. -
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Netron
Visualizer for neural network, deep learning, machine learning models
...Netron has experimental support for TensorFlow, PyTorch, TorchScript, OpenVINO, Torch, Arm NN, BigDL, Chainer, CNTK, Deeplearning4j, MediaPipe, ML.NET, scikit-learn, TensorFlow.js. There is an extense variety of sample model files to download or open using the browser version. It is supported by macOS, Windows, Linux, Python Server and browser. -
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hosts
Consolidate and extend hosts files from several well-curated sources
Consolidating and extending hosts files from several well-curated sources. You can optionally pick extensions to block pornography, social media, and other categories. The unified hosts file is optionally extensible. Extensions are used to include domains by category. Currently, we offer the following categories: fakenews, social, gambling, and porn. Extensions are optional, and can be combined in various ways with the base hosts file. The combined products are stored in the alternates... -
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XGBoost
Scalable and Flexible Gradient Boosting
...XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems. XGBoost can be used for Python, Java, Scala, R, C++ and more. It can run on a single machine, Hadoop, Spark, Dask, Flink and most other distributed environments, and is capable of solving problems beyond billions of examples. -
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Music Assistant
Music Assistant is a free, opensource Media library manager
Music Assistant Server is the core backend for Music Assistant, a free and open-source music library manager for local and online music sources. It connects streaming services, local files, metadata providers, and many speaker ecosystems into one centralized music system. The server is designed to run on an always-on device such as a Raspberry Pi, NAS, Intel NUC, or similar home server. It can work as a standalone product, but it is especially tailored for Home Assistant users who want... -
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nuwa-skill
Mental models, decision heuristics, expressing DNA
nuwa-skill is an AI-oriented project focused on defining, managing, and executing modular “skills” that can be used by intelligent agents or automation systems. It provides a framework for organizing capabilities into reusable units that can be invoked dynamically depending on context or user input. The project is designed to integrate with AI systems, enabling them to perform structured tasks such as data retrieval, processing, or interaction with external services. It emphasizes modularity... -
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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
Anomalib is an open-source deep learning library focused on anomaly detection and localization tasks, collecting state-of-the-art algorithms and tools under one modular framework. It provides implementations of leading anomaly detection methods drawn from current research, as well as a full set of utilities for training, evaluating, benchmarking, and deploying these models on both public and private datasets. Anomalib emphasizes flexibility and reproducibility: you can use its simple APIs to... -
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DocTR
Library for OCR-related tasks powered by Deep Learning
DocTR provides an easy and powerful way to extract valuable information from your documents. Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document... -
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DGL
Python package built to ease deep learning on graph
Build your models with PyTorch, TensorFlow or Apache MXNet. Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers.... -
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Copy Fail - CVE-2026-31431
epository that demonstrates and analyzes a Linux kernel vulnerability
Copy Fail - CVE-2026-31431 is a proof-of-concept repository that demonstrates and analyzes a specific Linux kernel vulnerability identified as CVE-2026-31431. The project provides experimental scripts and documentation to reproduce and study the exploit in controlled environments. It is designed for security researchers and engineers who want to understand the mechanics of the vulnerability. The repository includes tested configurations across multiple Linux distributions and kernel... -
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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. -
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Pottery
Redis for humans
Redis is awesome, but Redis commands are not always intuitive. Pottery is a Pythonic way to access Redis. If you know how to use Python dicts, then you already know how to use Pottery. Pottery is useful for accessing Redis more easily, and also for implementing microservice resilience patterns, and it has been battle-tested in production at scale. -
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Open Asset Import Library
The open-asset-importer-library repository
...In the past, it has been used in a wide range of applications. Written in C++, it is available under a liberal BSD license. There is a C API as well as bindings to various other languages, including C#, Python and D. Assimp loads all input model formats into one straightforward data structure for further processing. -
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YOLOv9
Learning What You Want to Learn Using Programmable Gradient Info
YOLOv9 is the official implementation of the paper “YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.” It is a modern object detection repository focused on improving how deep networks preserve useful information during training. The project introduces Programmable Gradient Information and the GELAN architecture to improve gradient flow, parameter efficiency, and train-from-scratch performance. It provides scripts and model assets for training, testing, and...