Search Results for "python framework" - Page 10
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Showing 607 open source projects for "python framework"
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FuzzBench
FuzzBench - Fuzzer benchmarking as a service
FuzzBench is a large-scale, open research platform developed by Google to evaluate and benchmark fuzzers — automated software testing tools that detect vulnerabilities through randomized input generation. It provides a standardized, reproducible environment for comparing the performance and effectiveness of different fuzzing algorithms on real-world software targets. FuzzBench integrates with the OSS-Fuzz infrastructure, allowing it to run experiments on authentic open source projects and... -
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Neomake
Asynchronous linting and make framework for Neovim/Vim
Neomake is an asynchronous linting and build framework for Vim and Neovim that predates and inspires newer tooling in this space. It runs “makers” (linters, compilers, format checkers, test commands) in the background and surfaces results as signs, virtual text, or via quickfix/location lists. The system is highly configurable: you can define per-filetype makers, chain multiple tools, and control when they run (on save, on write, on cursor hold, or manually). Run several makers concurrently... -
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Splinter
Splinter - Python test framework for web applications
Splinter is a Python test framework for web applications, providing a simple and consistent API for browser automation and testing. -
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Yapsy
A fat-free DIY Python plugin management toolkit.
...Yapsy v2+ supports Python 3 and it's development happens now on https://github.com/tibonihoo/yapsy/ Usage samples, advices and developer's documentations are available on the main website. -
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Rocketry
Modern scheduling library for Python
Scheduler to power your Python apps. Rocketry is a modern statement-based scheduling framework for Python. It is simple, clean and extensive. It is suitable for small and big projects. Unlike the alternatives, Rocketry's scheduler is statement-based. Rocketry natively supports the same scheduling strategies as the other options, including cron and task pipelining, but it can also be arbitrarily extended using custom scheduling statements. -
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UnionML
Build and deploy machine learning microservices
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. -
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OpsManage
Automated operation and maintenance platform
...If you need to quote the project code in your own project, please declare the agreement and copyright information in the project. Programming language, Python3.6 + HTML + JScripts. Front-end web framework, Bootstrap. Backend Web Framework, Django. Backend Task Framework, Celery + Redis. Programming language is Python 3.6. Operating System is CentOS 6+. Ansible version 2.6+. Deployment platform and node server Rsync 3+. -
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Scripting Language Bindings
A port of WFOPT to the several scripting languages
This project contains bindings for various scripting languages to the Wheefun Options Parsing Library. It is meant to provide parity with the C implementation so .NET languages can take advantage of WFOPT. For more information, please see the main page. -
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BEVFormer
Implementation of BEVFormer, a camera-only framework
3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV... -
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Opta
The next generation of Infrastructure-as-Code
Opta is an infrastructure-as-code framework. Rather than working with a low-level cloud configuration, Opta enables you to work with high-level constructs. Opta high-level constructs produce Terraform configuration files. This helps you avoid lock-in to Opta. You can write custom Terraform code or even take the Opta-generated Terraform and go your own way. Opta is a new kind of Infrastructure-as-Code (IaC) framework that lets engineers work with high-level constructs instead of getting lost... -
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Jraph
A Graph Neural Network Library in Jax
Jraph (pronounced “giraffe”) is a lightweight JAX library developed by Google DeepMind for building and experimenting with graph neural networks (GNNs). It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time... -
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codecat
static code analysis, to find/track sinks and bugs
CodeCat is a open source tool to help you in static code analysis, to find/track sinks and bugs, this points follow regex rules... -
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Amazon Braket Ocean Plugin
A Python plugin for using Ocean with Amazon Braket
The Amazon Braket Ocean Plugin is an open-source library in Python that provides a framework that you can use to interact with Ocean tools on top of Amazon Braket. Before you begin working with the Amazon Braket Ocean Plugin, make sure that you've installed or configured the following prerequisites. Download and install Python 3.7.2 or greater from Python.org. If you are using Windows, choose Add Python to environment variables before you begin the installation. ... -
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Blankly
Easily build, backtest and deploy your algo in just a few lines
Blankly is a live trading engine, backtest runner and development framework wrapped into one powerful open-source package. Models can be instantly backtested, paper traded, sandbox tested and run live by simply changing a single line. We built blankly for every type of quant including training & running ML models in the same environment, cross-exchange/cross-symbol arbitrage, and even long/short positions on stocks (all with built-in WebSockets). Blankly is the first framework to enable... -
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SharPyShell
Tiny and obfuscated ASP.NET webshell for C# web applications
SharPyShell is a tiny and obfuscated ASP.NET web shell that executes commands received by an encrypted channel compiling them in memory at runtime. SharPyShell supports only C# web applications that run on .NET Framework >= 2.0. SharPyShell is a post-exploitation framework written in Python. The main aim of this framework is to provide the penetration tester with a series of tools to ease the post-exploitation phase once exploitation has been successful against an IIS webserver. This tool is not intended as a replacement for the frameworks for C2 Server (i.e. ... -
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Django REST Framework User
This Django User Model is customised user model
This Django User Model is a customized user model keeping in mind the practical need. JWT Support (Using Simple JWT) Mobile Number, single field for full name, REST API to register, REST API to login, MultiModelBackend: User can login using either of mobile, email or username. REST API to login with OTP (Same API endpoint as for OTP Verification; Set is_login: true while sending JSON request). OTP Verification for mobile and email, API to register / login with OTP (no pre-registration... -
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pyTorch Tutorials
Build your neural network easy and fast
pyTorch Tutorials is an open-source collection of hands-on tutorials designed to teach developers how to build neural networks with the PyTorch framework. It covers the fundamentals of PyTorch from basic tensor operations to constructing full neural network models, making it suitable for beginners and intermediate learners alike. The project is structured around clear, executable Python scripts and Jupyter notebooks that demonstrate regression, classification, convolutional networks, recurrent networks, autoencoders, and generative adversarial networks, which gives learners practical exposure to real machine learning tasks. ... -
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OpenPrompt
An Open-Source Framework for Prompt-Learning
Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks, which modifies the input text with a textual template and directly uses PLMs to conduct pre-trained tasks. OpenPrompt is a library built upon PyTorch and provides a standard, flexible and extensible framework to deploy the prompt-learning pipeline. OpenPrompt supports loading PLMs directly from huggingface transformers. In the future, we will also support PLMs implemented by other... -
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V2RayCloudSpider
V2RayCloudSpider
V2RSS is an "ecological mining machine" that can perform vertical mining on global providers based on the SSPanel-Uim framework; it can generate bottom-up "aggregation collection" tasks for mainstream protocol headers; it can self-digest and Compared with proxypool , the output is purer and more reliable proxy nodes; it has powerful production features such as self-discovery and service self-healing. -
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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Jupyter Dash
Dash v2.11+ has Jupyter support built in
Dash 2.11 and later supports running Dash apps in classic Jupyter Notebooks and in JupyterLab without the need to update the code or use the additional JupyterDash library. If you are using an earlier version of Dash, you can run Dash apps in a notebook using JupyterDash. This page documents additional options available when running Dash apps in notebooks as well as troubleshooting information. -
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Kalliope
Kalliope is a framework to create your own personal assistant
Kalliope is a modular always-on voice-controlled personal assistant designed for home automation. Kalliope is a framework that will help you to create your own personal assistant. The concept is to create the brain of your assistant by attaching an input signal (vocal order, scheduled event, MQTT message, GPIO event, etc..) to one or multiple actions called neurons. You can create your own Kalliope bot, by simply choosing and composing the existing neurons without writing any code. But, if... -
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Spyne
A transport agnostic sync/async RPC library
Spyne is a Python RPC toolkit that makes it easy to expose online services that have a well-defined API using multiple protocols and transports. It integrates with popular Python web frameworks as well as libraries like SQLAlchemy to keep your code as DRY as possible. Spyne aims to save the protocol implementers the hassle of implementing their own remote procedure call api and the application programmers the hassle of jumping through hoops just to expose their services using multiple protocols and transports. ... -
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Model Search
Framework that implements AutoML algorithms
Model Search is an AutoML research system for discovering neural network architectures with minimal human intervention. Instead of hand-crafting models, you define a search space and objectives, then the system explores candidate architectures using controllers and population-based strategies. It supports multiple tasks (such as vision or text) by letting you express reusable building blocks—layers, cells, and topologies—that the search can recombine. Training, evaluation, and promotion of... -
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SBW (Systems Biology Workbench)
Framework for Systems Biology
The Systems Biology Workbench(SBW) is a framework for application intercommunications. It uses a broker-based, distributed, message-passing architecture, supports many languages including Java, C++, Perl & Python, and runs under Linux,OSX & Win32. It comes with a large number of modules, encompassing the whole modeling cycle: creating computational models, simulating and analyzing them, visualizing the information, in order to improve the models.
