Showing 301 open source projects for "logging"

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  • 1
    Loguru

    Loguru

    Python logging made (stupidly) simple

    Loguru is a Python library designed to simplify logging for developers. It offers easy setup with no configuration, support for multiple sinks (console, file, etc.), structured logging, formatting, rotation, and exception handling—all in an intuitive API.
    Downloads: 3 This Week
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  • 2
    BruteForceAI

    BruteForceAI

    Advanced LLM-powered brute-force tool combining AI intelligence

    ...It combines that analysis layer with automated credential testing workflows, framing itself as a more adaptive alternative to older brute-force tooling that depends heavily on manual configuration. The repository emphasizes features such as threaded execution, logging, and notification integrations, which position it as an automation-oriented project for controlled security assessment environments. From a software design perspective, its distinguishing idea is the use of language models as a front-end analysis layer that interprets a target page before the rest of the workflow proceeds.
    Downloads: 286 This Week
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  • 3
    FuXi

    FuXi

    FuXi is a fast, self-contained AI coding agent

    ...More than 50 built-in tools cover file operations, shell access, search, diagnostics, Jupyter, browser use, background tasks, and parallel sub-agents. Sessions are persistent, extensible through MCP, hooks, skills, and plugins, and protected by command classification, permissions, and audit logging.
    Downloads: 13 This Week
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  • 4
    FitTrackee

    FitTrackee

    Self-hosted outdoor activity tracker

    FitTrackee is a self-hostable fitness tracking and workout management platform designed to help individuals and small groups monitor physical activity, set goals, and review performance over time with clarity and flexibility. It provides an organized environment for logging workouts, recording metrics like sets, reps, durations, and weights, and visualizing progress through charts and summaries that detail trends in strength, endurance, and consistency. Instead of locking users into proprietary ecosystems or paid plans, FitTrackee lets you keep your own data on your server, giving full control over privacy and longevity of your fitness history. ...
    Downloads: 7 This Week
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  • 5
    Python colorlog

    Python colorlog

    A colored formatter for the python logging module

    Add colors to the output of Python's logging module. This library is over a decade old and supported a wide set of Python versions for most of its life, which has made it a difficult library to add new features to. colorlog 6 may break backward compatibility so that newer features can be added more easily, but may still not accept all changes or feature requests. colorlog 4 might accept essential bug fixes but should not be considered actively maintained and will not accept any major changes or new features.
    Downloads: 4 This Week
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  • 6
    whylogs

    whylogs

    The open standard for data logging

    whylogs is an open-source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (called whylogs profiles) which they can use to track changes in their dataset Create data constraints to know whether their data looks the way it should. Quickly visualize key summary statistics about their datasets. whylogs profiles are the core of the whylogs library.
    Downloads: 4 This Week
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  • 7
    WhatsApp Beacon

    WhatsApp Beacon

    OSINT tool for tracking WhatsApp online status via Web automation

    WhatsApp Beacon is an open source OSINT tool designed to monitor and analyze the online activity status of WhatsApp users through WhatsApp Web. It uses Selenium automation to interact with the web interface and detect when a target account goes online or offline. By continuously monitoring these changes, WhatsApp Beacon records connectivity patterns and builds a historical dataset of activity sessions. The collected information is stored in logs and a local database, allowing users to review...
    Downloads: 89 This Week
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  • 8
    TNT

    TNT

    A lightweight library for PyTorch training tools and utilities

    ...It introduces modular abstractions that allow developers to organize training logic into reusable components such as trainers, evaluators, and callbacks. This design helps separate concerns such as model training, evaluation, logging, and checkpointing, making machine learning experiments easier to manage. The framework is particularly useful for large-scale experiments where maintaining clear training workflows becomes increasingly important. Because it is built on top of PyTorch, the framework integrates naturally with existing deep learning models and datasets.
    Downloads: 2 This Week
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  • 9
    Google Toolbox for Mac

    Google Toolbox for Mac

    Google Toolbox for Mac

    ...It consolidates reusable code components drawn from various internal Google projects, offering developers a wide range of tools for building efficient, maintainable Apple platform software. The library includes modules for networking, logging, testing, data handling, and user interface extensions, helping developers avoid reinventing common functionality. Its modular design allows developers to integrate only the components they need, improving project flexibility and performance. With well-documented interfaces and consistent coding standards, Google Toolbox for Mac serves as a reliable foundation for both small and large-scale applications. ...
    Downloads: 7 This Week
    Last Update:
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  • 10
    Django RQ

    Django RQ

    A simple app that provides django integration for RQ

    A simple app that provides django integration for RQ (Redis Queue). Django integration with RQ, a Redis-based Python queuing library. Django-RQ is a simple app that allows you to configure your queues in django's settings.py and easily use them in your project. Django-RQ allows you to easily put jobs into any of the queues defined in settings.py. You can provide your own singleton Redis connection object to this function so that it will not create a new connection object for each queue...
    Downloads: 3 This Week
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  • 11
    verl

    verl

    Volcano Engine Reinforcement Learning for LLMs

    ...Data pipelines treat human feedback, simulated environments, and synthetic preferences as interchangeable sources, which helps with rapid experimentation. VERL is meant for both research and production hardening: logging, checkpointing, and evaluation suites are built in so you can track learning dynamics and regressions over time.
    Downloads: 5 This Week
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  • 12
    Atropos

    Atropos

    Language Model Reinforcement Learning Environments frameworks

    ...This framework facilitates experimentation with RLHF (Reinforcement Learning from Human Feedback), RLAIF, or multi-turn training approaches by abstracting environment logic, scoring, and logging into reusable components.
    Downloads: 2 This Week
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  • 13
    Behaviour Suite Reinforcement Learning

    Behaviour Suite Reinforcement Learning

    bsuite is a collection of carefully-designed experiments

    ...Each experiment in bsuite is meticulously designed to capture key challenges in RL, such as exploration, credit assignment, and stability. The framework supports automated logging and analysis, generating standardized output compatible with Jupyter notebooks for streamlined evaluation. It also integrates easily with existing RL libraries and can be used locally or via cloud computing platforms, including Google Cloud.
    Downloads: 2 This Week
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  • 14
    PyTorch Lightning

    PyTorch Lightning

    The lightweight PyTorch wrapper for high-performance AI research

    ...When you need to scale up things like BERT and self-supervised learning, Lightning responds accordingly by automatically exporting to ONNX or TorchScript. PyTorch Lightning can easily be applied for any use case. With just a quick refactor you can run your code on any hardware, run distributed training, perform logging, metrics, visualization and so much more!
    Downloads: 2 This Week
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  • 15
    alive-progress

    alive-progress

    A new kind of Progress Bar, with real-time throughput, ETA

    ...It includes sophisticated ETA estimation powered by exponential smoothing algorithms, improving prediction accuracy for variable workloads. Developers can easily integrate it into scripts thanks to automatic logging hooks and flexible configuration options. With its emphasis on responsiveness, customization, and developer ergonomics, alive-progress stands out as a modern replacement for conventional Python progress bars.
    Downloads: 0 This Week
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  • 16
    pg_probackup

    pg_probackup

    Backup and recovery manager for PostgreSQL

    pg_probackup is an advanced backup and recovery tool for PostgreSQL developed by PostgresPro. It supports full, incremental, and differential backups with compression and encryption, and provides fine-grained control over backup and restore processes. It’s designed for enterprise-grade backup strategies in PostgreSQL environments.
    Downloads: 3 This Week
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  • 17
    BayesianOptimization

    BayesianOptimization

    A Python implementation of global optimization with gaussian processes

    BayesianOptimization is a Python library that helps find the maximum (or minimum) of expensive or unknown objective functions using Bayesian optimization. This technique is especially useful for hyperparameter tuning in machine learning, where evaluating the objective function is costly. The library provides an easy-to-use API for defining bounds and optimizing over parameter spaces using probabilistic models like Gaussian Processes.
    Downloads: 4 This Week
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  • 18
    Recursive Language Models

    Recursive Language Models

    General plug-and-play inference library for Recursive Language Models

    ...It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom agents, environments, policy networks, and reward structures while leveraging built-in dataset utilities, logging, and checkpointing for reproducible experiments. RLM also includes integration with popular simulation environments and benchmark suites, giving researchers a ready-made playground for algorithm comparison and performance tracking.
    Downloads: 0 This Week
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  • 19
    SleepFM-Clinical

    SleepFM-Clinical

    Improve human sleep through scientifically

    ...Rather than simply playing static white noise or ambient tracks, it uses a closed-loop, frequency-modulated framework that responds to user-specific sleep patterns and physiological signals to tailor sound in ways that can enhance sleep onset and depth. The clinical release includes additional features for controlled experimentation, such as logging capabilities, adjustable parameter sets, and protocols suitable for sleep studies and therapeutic settings. It also integrates tools for clinicians to configure sessions, annotate events, and potentially link with biofeedback data, enabling a more nuanced understanding of sound’s effect on sleep architecture over time.
    Downloads: 0 This Week
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  • 20
    Uncertainty Baselines

    Uncertainty Baselines

    High-quality implementations of standard and SOTA methods

    Uncertainty Baselines is a collection of strong, well-documented training pipelines that make it straightforward to evaluate predictive uncertainty in modern machine learning models. Rather than offering toy scripts, it provides end-to-end recipes—data input, model architectures, training loops, evaluation metrics, and logging—so results are comparable across runs and research groups. The library spans canonical modalities and tasks, from image classification and NLP to tabular problems, with baselines that cover both deterministic and probabilistic approaches. Techniques include deep ensembles, Monte Carlo dropout, temperature scaling, stochastic variational inference, heteroscedastic heads, and out-of-distribution detection workflows. ...
    Downloads: 0 This Week
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  • 21
    Coconut

    Coconut

    Training Large Language Model to Reason in a Continuous Latent Space

    ...It supports training across multiple reasoning paradigms—including standard Chain-of-Thought (CoT), no-thought, and hybrid configurations—using configurable training stages and latent representations. The repository is built with Hugging Face Transformers, PyTorch Distributed, and Weights & Biases (wandb) for logging, supporting large-scale experiments on mathematical and logical reasoning datasets such as GSM8K, ProntoQA, and ProsQA.
    Downloads: 0 This Week
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  • 22
    PaaSTA

    PaaSTA

    An open, distributed platform as a service

    ...Rather than managing Kubernetes YAML files, PaaSTA provides a simplified schema to describe your service and in addition to configuring Kubernetes it can also configure other infrastructure tools to provide monitoring, logging, cost management etc.
    Downloads: 18 This Week
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  • 23
    Tunix

    Tunix

    A JAX-native LLM Post-Training Library

    ...Examples and reference configs demonstrate end-to-end runs for common model families, helping teams reproduce baselines before customizing. Tunix also leans into research ergonomics: logging, checkpointing, and metrics are built in, and the code is written to be hackable rather than monolithic. Overall it aims to shorten the path from an off-the-shelf base model to a well-aligned, task-ready model using scalable JAX primitives.
    Downloads: 0 This Week
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  • 24
    Pearl

    Pearl

    A Production-ready Reinforcement Learning AI Agent Library

    ...Tutorials demonstrate end-to-end workflows on OpenAI Gym tasks and contextual-bandit setups derived from tabular datasets, emphasizing reproducibility and clear baselines. Pearl’s design favors clarity and deployability: metrics, logging, and evaluation harnesses are integrated so you can monitor learning, compare agents, and catch regressions.
    Downloads: 0 This Week
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  • 25
    TensorBoardX

    TensorBoardX

    tensorboard for pytorch (and chainer, mxnet, numpy, etc.)

    ...The class updates the file contents asynchronously. This allows a training program to call methods to add data to the file directly from the training loop, without slowing down training. TensorboardX now supports logging directly to Comet. Comet is a free cloud based solution that allows you to automatically track, compare and explain your experiments. It adds a lot of functionality on top of tensorboard such as dataset management, diffing experiments, seeing the code that generated the results and more. Create special chart by collecting charts tags in ‘scalars’. ...
    Downloads: 0 This Week
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