Search Results for "testing" - Page 3
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Showing 319 open source projects for "testing"
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Werkzeug
The comprehensive WSGI web application library
Werkzeug is a comprehensive WSGI web application library. It began as a simple collection of various utilities for WSGI applications and has become one of the most advanced WSGI utility libraries. Werkzeug doesn’t enforce any dependencies. It is up to the developer to choose a template engine, database adapter, and even how to handle requests. Includes an interactive debugger that allows inspecting stack traces and source code in the browser with an interactive interpreter for any frame in... -
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The Falcon Web Framework
The no-nonsense REST API and microservices framework
...Easy access to headers and bodies through request and response objects. DRY request processing via middleware components and hooks. Strict adherence to RFCs. Idiomatic HTTP error responses. Straightforward exception handling. Snappy testing with WSGI/ASGI helpers and mocks. CPython 3.5+ and PyPy 3.5+ support. No reliance on magic globals for routing and state management. Stable interfaces with an emphasis on backward compatibility. Simple API modeling through centralized RESTful routing. Highly-optimized, extensible code base. -
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DrissionPage
Python based web automation tool. Powerful and elegant
DrissionPage is a Python-based automation framework that blends the capabilities of Selenium for browser automation with Requests-HTML for fast, headless web data extraction. It enables seamless switching between browser-controlled and headless HTTP sessions within the same interface. Ideal for web scraping, testing, and automation, DrissionPage is lightweight and highly efficient, offering more flexibility than standard Selenium or Requests usage alone. -
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HTTPie CLI
Modern, user-friendly command-line HTTP client for the API era
HTTPie (pronounced aitch-tee-tee-pie) is a command-line HTTP client. Its goal is to make CLI interaction with web services as human-friendly as possible. HTTPie is designed for testing, debugging, and generally interacting with APIs & HTTP servers. The HTTP & HTTPS commands allow for creating and sending arbitrary HTTP requests. They use simple and natural syntax and provide formatted and colorized output. -
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Metarget
Framework for automatic construction of vulnerable infrastructures
Metarget = meta- + target, a framework providing automatic constructions of vulnerable infrastructures, used to deploy simple or complicated vulnerable cloud native targets swiftly and automatically. During security research, we might find that the deployment of a vulnerable environment often takes much time, while the time spent on testing PoC or ExP is comparatively short. In the field of cloud-native security, thanks to the complexity of cloud-native systems, this issue is more terrible. There are already some excellent security projects like Vulhub, and VulApps in the open-source community, which pack vulnerable scenes into container images so that researchers could utilize them and deploy scenes quickly. ... -
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NGINX Admin’s Handbook
How to improve NGINX performance, security, and other important things
nginx-admins-handbook is a practical, in-depth guide for configuring, securing, and operating NGINX across real-world deployments. It distills years of research, notes, and field experience into a single handbook that complements the official docs with concrete rules, explanations, and curated external references. The handbook spans fundamentals and advanced topics alike, from HTTP and SSL/TLS basics to reverse proxy patterns, performance tuning, debugging workflows, and hardening... -
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Claude Code Templates
CLI tool for configuring and monitoring Claude Code
...It lets you quickly scaffold domain-specific AI agents (like security auditors, performance optimizers, or database architects), fill in consistent project configurations, and embed automated workflows without reinventing the wheel for each new project. The templates and components are organized by workflow so teams can adopt best practices for testing, deployment, documentation, DevOps automation, and more, all powered by Claude’s agent SDK. Interactive installation commands and a marketplace-style interface make it easy to browse and apply components, and the tool also includes development utilities like analytics and conversation monitoring. -
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PydanticAI
Agent Framework / shim to use Pydantic with LLMs
When I first found FastAPI, I got it immediately. I was excited to find something so innovative and ergonomic built on Pydantic. Virtually every Agent Framework and LLM library in Python uses Pydantic, but when we began to use LLMs in Pydantic Logfire, I couldn't find anything that gave me the same feeling. PydanticAI is a Python Agent Framework designed to make it less painful to build production-grade applications with Generative AI. Built by the team behind Pydantic (the validation layer... -
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Gretel Synthetics
Synthetic data generators for structured and unstructured text
...Synthesize and transform multiple tables or entire relational databases. Mitigate GDPR and CCPA risks, and promote safe data access. Accelerate CI/CD workflows, performance testing, and staging. Augment AI training data, including minority classes and unique edge cases. Amaze prospects with personalized product experiences. -
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CO3D (Common Objects in 3D)
Tooling for the Common Objects In 3D dataset
...Each of the thousands of sequences in CO3Dv2 captures a common object (from categories like cars, chairs, or plants) from multiple real-world viewpoints. The dataset includes RGB images, depth maps, masks, and camera poses for each frame, along with pre-defined training, validation, and testing splits for both few-view and many-view reconstruction tasks. -
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Synthetic Data Vault (SDV)
Synthetic Data Generation for tabular, relational and time series data
The Synthetic Data Vault (SDV) is a Synthetic Data Generation ecosystem of libraries that allows users to easily learn single-table, multi-table and timeseries datasets to later on generate new Synthetic Data that has the same format and statistical properties as the original dataset. Synthetic data can then be used to supplement, augment and in some cases replace real data when training Machine Learning models. Additionally, it enables the testing of Machine Learning or other data dependent software systems without the risk of exposure that comes with data disclosure. Underneath the hood it uses several probabilistic graphical modeling and deep learning based techniques. To enable a variety of data storage structures, we employ unique hierarchical generative modeling and recursive sampling techniques. -
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Django Rules
Awesome Django authorization, without the database
...Predicates can be any type of callable -- simple functions, lambdas, methods, callable class objects, partial functions, decorated functions, anything really. A good Django citizen. Seamless integration with Django views, templates and the Admin for testing for object-level permissions. Efficient and smart. No need to mess around with a database to figure out whether John really wrote that book. Simple. Dive in the code. You'll need 10 minutes to figure out how it works. Powerful. rules comes complete with advanced features, such as invocation context and storage for arbitrary data, skipping evaluation of predicates. -
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RecBole
A unified, comprehensive and efficient recommendation library
...We implement more than 100 commonly used recommendation algorithms and provide formatted copies of 28 recommendation datasets. We support a series of widely adopted evaluation protocols or settings for testing and comparing recommendation algorithms. RecBole is developed based on Python and PyTorch for reproducing and developing recommendation algorithms in a unified, comprehensive and efficient framework for research purpose. It can be installed from pip, conda and source, and is easy to use. We have implemented more than 100 recommender system models, covering four common recommender system categories in RecBole and eight toolkits of RecBole2.0, including General Recommendation, Sequential Recommendation, Context-aware Recommendation, and Knowledge-based Recommendation and sub-packages. -
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RLax
Library of JAX-based building blocks for reinforcement learning agents
RLax (pronounced “relax”) is a JAX-based library developed by Google DeepMind that provides reusable mathematical building blocks for constructing reinforcement learning (RL) agents. Rather than implementing full algorithms, RLax focuses on the core functional operations that underpin RL methods—such as computing value functions, returns, policy gradients, and loss terms—allowing researchers to flexibly assemble their own agents. It supports both on-policy and off-policy learning, as well as... -
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Courses (Anthropic)
Anthropic's educational courses
...Each course mixes short readings with runnable notebooks and exercises, guiding you through concepts like model parameters, streaming, multimodal prompts, structured outputs, and evaluation. Assignments emphasize realistic tasks such as building small utilities, testing prompts against edge cases, and measuring quality so you learn to ship things that work. The materials are written for developers but remain friendly to newcomers, with clear setup instructions and minimal boilerplate. Because the repo is live and maintained, lessons are updated as the SDK and models evolve, and issues are used to track fixes, clarifications, and new modules. -
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Professional Programming
A collection of learning resources for curious software engineers
Professional Programming is a long-running, curated collection of learning resources aimed at helping software engineers grow into well-rounded professionals. It goes far beyond basic “learn to code” material and covers topics like system design, debugging, testing, performance, security, architecture, and software craftsmanship. The list is organized by themes such as coding, design, operations, communication, and career, making it easy to dive into specific aspects of engineering practice. Each resource is hand-picked by the maintainer, focusing on timeless, high-signal articles, talks, and books rather than trendy or shallow content. ... -
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AWS Chalice
Python Serverless Microframework for AWS
Chalice is a Python microframework for writing and deploying serverless applications on AWS with minimal ceremony. You define routes, event handlers, and background tasks in plain Python, and Chalice turns them into AWS Lambda functions wired to API Gateway, Amazon EventBridge schedulers, S3/SNS/SQS triggers, and more. A single command builds your app, bundles dependencies, generates infrastructure templates, and deploys to your account with sensible defaults. The framework includes local... -
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django-organizations
Multi-user accounts for Django projects
...Users can belong to and own more than one organization (account, group) Invitation and registration functionality works out of the box for many situations and can be extended as needed to fit specific requirements. Start with the base models or use your own for greater customization. Testing each change on all the environments takes some time, you may want to test faster and avoid slowing down development by using pytest against your current environment. -
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SageMaker Spark Container
Docker image used to run data processing workloads
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data... -
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FlowLens MCP
Open-source MCP server that gives your coding agent
FlowLens MCP Server is an open-source tool designed to give AI-powered coding agents (like Claude Code, Cursor, GitHub Copilot / Codex, and others) full, replayable browser context to dramatically improve debugging, bug reporting, and regression testing for web applications. It works together with a companion browser extension: when a user reproduces a bug or a complicated UI interaction, the extension captures a rich session log, including screen/video recording, network traffic, console logs, DOM events, storage changes, and more, and exports it. The MCP server then loads this captured “flow” and exposes it to the AI agent via the Model Context Protocol (MCP), letting the agent examine, search, filter, and reason about the session just as a human developer would, without needing the agent to re-run the flow or rely on minimal reproduction data (logs, screenshots). -
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MASVS
The OWASP MASVS (Mobile Application Security Verification Standard)
The OWASP Mobile Application Security Verification Standard (MASVS) is a comprehensive security standard for mobile applications, providing guidelines and a checklist for secure mobile app development. -
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TextTest is an application-independent tool for text-based functional testing. This means running a batch-mode binary in lots of different ways, and using the text output produced as a means of controlling the behaviour of that application.
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PyNuker
A stress testing tool written in python.
PyNuker is a network stress testing tool written in python. Because it is written in python it should run equally well on any system that has Python version 3.x installed. It infinitely(until stopped) sends a string of text via a UDP packet to a target computer or network device in an effort to flood the target with so much useless traffic that it stops responding to valid requests. -
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Wapiti
Wapiti is a web-application vulnerability scanner
Wapiti is a vulnerability scanner for web applications. It currently search vulnerabilities like XSS, SQL and XPath injections, file inclusions, command execution, XXE injections, CRLF injections, Server Side Request Forgery, Open Redirects... It use the Python 3 programming language. -
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Wifipumpkin3
Powerful framework for rogue access point attack
wifipumpkin3 is powerful framework for rogue access point attack, written in Python, that allow and offer to security researchers, red teamers and reverse engineers to mount a wireless network to conduct a man-in-the-middle attack.
