Search Results for "debug"
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Showing 79 open source projects for "debug"
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Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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httpdbg
Tool for Python developers to easily debug the HTTP(S) client requests
httpdbg is a tool for Python developers to easily debug the HTTP(S) client requests in a Python program. -
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Strawberry GraphQL
A GraphQL library for Python that leverages type annotations
Python GraphQL library based on dataclasses. Strawberry's friendly API allows to create GraphQL API rather quickly, the debug server makes it easy to quickly test and debug. Django and ASGI support allow having your API deployed in production in a matter of minutes. The quick start method provides a server and CLI to get going quickly. Strawberry comes with a mypy plugin that enables statically type-checking your GraphQL schema. A Django view is provided for adding a GraphQL endpoint to your application. ... -
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yt-dlp-gui
A cross-platform GUI wrapper for yt-dlp written in PySide6
yt-dlp-gui is a cross-platform graphical interface for the popular command-line video downloader yt-dlp, created to make video and audio downloads from sites like YouTube, Vimeo, Twitch, and others easier for everyday users without needing to work directly with command-line arguments. Written in PySide6 (Python with Qt bindings), it wraps the powerful yt-dlp engine in a visual application that lets users paste video URLs, choose formats, apply presets, and start downloads with a click, while... -
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Translate Toolkit
Useful localization tools with Python API for building localization
The localization engineers' Swiss Army Knife. Use it to convert, count, manipulate, review and debug texts. Tools that you can expand, adapt, and grow. Convert between a number of localization, translation and software formats. Allowing you and your translators to work on industry-standard translation formats. Search for pattern matches. Run tests that adapt to languages and source projects. Extract terminology. A large toolset to allow you to increase localization quality. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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Python Fire
Automatically generate CLIs from absolutely any Python object
...It’s a really simple and easy way to create CLI in Python, and can also enable you to explore existing code or turn other people’s code into a CLI. Python Fire lets you call Fire on any Python object: be it functions, classes, objects, modules, lists-- you name it! It will help you develop as well as debug Python code, and make transitioning between Bash and Python a whole lot easier. -
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IceCream
Never use print() to debug again
Do you ever use print() or log() to debug your code? Of course you do. IceCream, or ic for short, makes print debugging a little sweeter. With arguments, ic() inspects itself and prints both its own arguments and the values of those arguments. Just give ic() a variable or expression and you're done. ic() returns its argument(s), so ic() can easily be inserted into pre-existing code. -
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LocalStack
Develop and test your cloud apps offline
LocalStack is a fully functional local AWS cloud stack that enables you to develop and test your cloud and serverless apps offline. It spins up an easy-to-use testing environment on your local machine that has the same APIs and works the same way as the real AWS cloud environment. It can spin up a number of different core Cloud APIs on your local machine, including API Gateway, Kinesis, DynamoDB, Firehose, Lambda and many others. LocalStack was built on some of today’s best-of-breed... -
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AWS SAM CLI
CLI tool to build, test, debug, and deploy Serverless applications
...During deployment, SAM transforms and expands the SAM syntax into AWS CloudFormation syntax, enabling you to build serverless applications faster. To get started with building SAM-based applications, use the SAM CLI. SAM CLI provides a Lambda-like execution environment that lets you locally build, test, debug, and deploy AWS serverless applications. -
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AWS Serverless Application Model
An open-source framework for building serverless applications
...To get started with building SAM-based applications, use the AWS SAM CLI. SAM CLI provides a Lambda-like execution environment that lets you locally build, test, and debug applications defined by SAM templates or through the AWS Cloud Development Kit (CDK). You can also use the SAM CLI to deploy your applications to AWS. SAM and SAM CLI are open-sourced under the Apache 2.0 license. You can contribute new features and enhancements to SAM on GitHub or SAM CLI on GitHub. -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Jinja
Ultra fast and expressive template engine
Jinja is a fast, full-featured and expressive template engine for Python. It offers full unicode support, a sandboxed environment for safe executions, and so much more. Jinja is among the most widely used template engines for Python, and for good reason. It is both beautiful and powerful, and makes a template designer’s job a lot easier. Jinja is inspired by Django's templating system, but steps it up with an expressive language that results in more powerful tools, plus an automatic HTML... -
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...Don’t let friction between development and production slow down the deployment of new data/ML workflows and cause an increase in production bugs. Flyte enables rapid experimentation with production-grade software. Debug in the cloud by iterating on the workflows locally to achieve tighter feedback loops. As your data and ML workflows expand and demand more computing power, your workflow orchestration platform must keep up. If it’s not designed to scale, your platform will require constant monitoring and maintenance. Flyte was built with scalability in mind, ready to handle changing workloads and resource needs.
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Gigi
Framework for rapid prototyping and development of real-time rendering
Gigi is software designed for rapid prototyping and rapid development of real-time rendering techniques. It is meant for use by professionals, researchers, students, and hobbyists. The goal is to allow work at the speed of thought, and then easily use what was created in real applications using various APIs or engines. Gigi is being actively used and developed but is young software. You may hit bugs or missing features. Please report these so we can improve Gigi and push forward in the most... -
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AgentOps
Python SDK for agent monitoring, LLM cost tracking, benchmarking, etc.
Industry-leading developer platform to test and debug AI agents. We built the tools so you don't have to. Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks. -
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mitmproxy
A free and open source interactive HTTPS proxy
mitmproxy is an open source, interactive SSL/TLS-capable intercepting HTTP proxy, with a console interface fit for HTTP/1, HTTP/2, and WebSockets. It's the ideal tool for penetration testers and software developers, able to debug, test, and make privacy measurements. It can intercept, inspect, modify and replay web traffic, and can even prettify and decode a variety of message types. Its web-based interface mitmweb gives you a similar experience as Chrome's DevTools, with the addition of features like request interception and replay. Its command-line version mitmdump allows you to write powerful addons and script mitmproxy so it can automatically modify messages, redirect traffic, and perform many other custom commands. -
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Android Use
Automate native Android apps with AI using accessibility APIs
...The project works by using Android’s accessibility API to extract structured UI state (as XML) from the device, which is then fed to a large language model (LLM) like OpenAI’s models for decision-making, and actions are executed via the Android Debug Bridge (ADB). This approach bypasses expensive vision-based models and provides faster, cheaper automation with fine-grained interaction capabilities (for example, tapping buttons, typing text, navigating screens). -
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GPT PILOT
The first real AI developer
GPT PILOT is an open-source AI developer assistant designed to build full applications by collaborating with a human developer throughout the software lifecycle. Unlike simple autocomplete tools, it aims to function as a true AI engineer that can generate features, set up environments, debug code, and request feedback when necessary. The system works by asking clarifying questions, producing product requirements, and then implementing the application step by step while the user supervises. It powers the Pythagora VS Code extension and relies on coordinated AI agents that mimic roles in a real development workflow. GPT Pilot is intended to automate the majority of routine coding work while leaving strategic decisions and final review to the human developer. ... -
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OpenAI Agents SDK
A lightweight, powerful framework for multi-agent workflows
The OpenAI Agents Python SDK is a powerful yet lightweight framework for developing multi-agent workflows. This framework enables developers to create and manage agents that can coordinate tasks autonomously, using a set of instructions, tools, guardrails, and handoffs. The SDK allows users to configure workflows in which agents can pass control to other agents as necessary, ensuring dynamic task management. It also includes a built-in tracing system for tracking, debugging, and optimizing... -
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Prompt flow
Build high-quality LLM apps
Prompt flow is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, and evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality. -
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Nerfstudio
A collaboration friendly studio for NeRFs
Nerfstudio provides a simple API that allows for a simplified end-to-end process of creating, training, and testing NeRFs. The library supports a more interpretable implementation of NeRFs by modularizing each component. With more modular NeRFs, we hope to create a more user-friendly experience in exploring the technology. This is a contributor-friendly repo with the goal of building a community where users can more easily build upon each other’s contributions. Nerfstudio initially launched... -
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TorchCode
Practice implementing softmax, attention, GPT-2 and more
...The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms, and full transformer architectures. It runs in a Jupyter-based environment, allowing users to write, test, and debug their code interactively while receiving immediate feedback. An automated judging system evaluates correctness, gradient flow, and numerical stability, helping users understand both functional and theoretical aspects of their implementations. -
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PySpur
Visual tool for building, testing, and deploying AI agent workflows
...It addresses common challenges in AI agent development such as prompt tuning difficulties and lack of visibility into workflow execution. By offering a visual representation of workflows, PySpur makes it easier to debug interactions between components and identify failures in complex pipelines. It supports iterative experimentation, allowing developers to rapidly improve agents without rebuilding systems from scratch. PySpur also enables deployment of finalized workflows after testing, making it suitable for both development and production use. ... -
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Anthropic's Original Performance
Anthropic's original performance take-home, now open for you to try
...The project sets up a baseline performance problem where participants work to reduce simulated “clock cycles” required to run a given workload, effectively challenging them to engineer faster code under constraints. This take-home includes starter code, tests, and tools to debug performance, aiming to measure how effectively one can apply algorithmic improvements and optimizations. Because it’s framed around beating baseline scores — and even outperforming previous automated systems — it encourages both deep knowledge of Python and creative problem-solving. -
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FastKoko
Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model
...The server also offers per-word timestamped captions, which makes it useful for creating subtitles or aligning audio with text. A built in web UI, API documentation, and debug endpoints for monitoring system status help users explore voices, test requests, and integrate the service into larger systems. -
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Petastorm
Petastorm library enables single machine or distributed training
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. Petastorm is an open-source data access library developed at Uber ATG. This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. Petastorm supports popular... -
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OpenSRE
Build your own AI SRE agents. The open source toolkit for the AI era
...When an alert is triggered, the system autonomously analyzes correlated signals, identifies anomalies, and generates structured investigation reports with probable causes and recommended actions. Its multi-agent architecture allows parallel reasoning across systems, mimicking how experienced SRE teams debug complex issues. The platform also incorporates memory and knowledge graph capabilities to learn from past incidents and improve future investigations. It is designed to run locally within an organization’s infrastructure, ensuring data privacy and compliance.