Showing 29 open source projects for "router data usage"

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  • 1
    Data Contract CLI

    Data Contract CLI

    Enforce Data Contracts

    Data Contract CLI is an open-source command-line tool and Python library for creating, validating, testing, importing, exporting, and enforcing data contracts. It uses YAML-based contract files to define the structure, meaning, quality rules, service levels, and connection details for a data product. The tool can connect to real data sources and check whether the actual dataset matches the schema, constraints, and quality expectations described in the contract. It supports both the Data...
    Downloads: 0 This Week
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  • 2
    SDGym

    SDGym

    Benchmarking synthetic data generation methods

    The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking.
    Downloads: 0 This Week
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  • 3
    Comprehensive Python Cheatsheet

    Comprehensive Python Cheatsheet

    Comprehensive Python Cheatsheet

    ...The project is designed to help developers quickly recall language features without digging through full documentation, making it especially useful for both beginners and experienced programmers. It covers a broad range of topics including data structures, control flow, functions, object-oriented programming, standard library usage, and common patterns. The repository includes both web and printable versions, allowing users to access the material in multiple formats depending on their workflow. Because it is continuously maintained, the cheatsheet reflects modern Python usage and practical conventions. ...
    Downloads: 2 This Week
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  • 4
    Robusta KRR

    Robusta KRR

    Prometheus-based Kubernetes Resource Recommendations

    Robusta KRR (Kubernetes Resource Recommender) is a CLI tool for optimizing resource allocation in Kubernetes clusters. It gathers pod usage data from Prometheus and recommends requests and limits for CPU and memory. This reduces costs and improves performance.
    Downloads: 0 This Week
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  • 5
    PaddleX

    PaddleX

    PaddlePaddle End-to-End Development Toolkit

    PaddleX is a deep learning full-process development tool based on the core framework, development kit, and tool components of Paddle. It has three characteristics opening up the whole process, integrating industrial practice, and being easy to use and integrate. Image classification and labeling is the most basic and simplest labeling task. Users only need to put pictures belonging to the same category in the same folder. When the model is trained, we need to divide the training set, the...
    Downloads: 1 This Week
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  • 6
    Kaggle CLI

    Kaggle CLI

    The official CLI to interact with Kaggle

    ...Its main value is turning Kaggle’s web-based data science platform into a scriptable developer workflow.
    Downloads: 5 This Week
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  • 7
    Groq Python

    Groq Python

    The official Python Library for the Groq API

    ...Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and supports both synchronous and asynchronous usage patterns depending on your application needs. This makes it easy to integrate Groq-powered AI capabilities into backend services, data pipelines, research notebooks, or applications written in Python. For those building AI-based tooling, automation scripts, or ML-backed backends, groq-python abstracts away HTTP request plumbing and exposes a clean API, accelerating development and reducing boilerplate.
    Downloads: 2 This Week
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  • 8
    learn_python3_spider

    learn_python3_spider

    Python crawler tutorial series, learning Python crawlers from 0 to 1

    ...It introduces request capture, browser and mobile traffic inspection, and core scraping libraries such as Requests, BeautifulSoup, Selenium, Appium, and Scrapy. Lessons also cover JSON parsing, regular expressions, concurrency, proxy usage, login handling, and CAPTCHA-related techniques. Data can be stored with CSV, MySQL, or MongoDB examples. More advanced material explores anti-scraping defenses, JavaScript analysis, WebSocket data, and distributed crawlers. The repository includes practical source-code examples for scraping several real-world websites and services.
    Downloads: 0 This Week
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  • 9
    LocalGPT

    LocalGPT

    Chat with your documents on your local device using GPT models

    LocalGPT is a private, on-premises document intelligence platform for questioning, summarizing, and analyzing files with locally hosted language models. Its data remains on the user’s machine, making it suitable for confidential or offline workflows. The retrieval system combines semantic similarity, keyword matching, late chunking, contextual enrichment, and sentence-level pruning. A smart router chooses between retrieval-augmented generation and direct model responses for each query. An independent verification pass is intended to improve answer reliability before results are returned. ...
    Downloads: 0 This Week
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  • 10
    DrissionPage

    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.
    Downloads: 2 This Week
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  • 11
    DeepEP

    DeepEP

    DeepEP: an efficient expert-parallel communication library

    ...Its core role is to implement high-throughput, low-latency all-to-all GPU communication kernels, which handle the dispatching of tokens to different experts (or shards) and then combining expert outputs back into the main data flow. Because MoE architectures require routing inputs to different experts, communication overhead can become a bottleneck — DeepEP addresses that by providing optimized GPU kernels and efficient dispatch/combining logic. The library also supports low-precision operations (such as FP8) to reduce memory and bandwidth usage during communication. ...
    Downloads: 0 This Week
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  • 12
    RecBole

    RecBole

    A unified, comprehensive and efficient recommendation library

    A unified, comprehensive and efficient recommendation library. We design general and extensible data structures to unify the formatting and usage of various recommendation datasets. 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.
    Downloads: 0 This Week
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  • 13
    mobsfscan

    mobsfscan

    Static analysis tool that can find insecure code patterns in code

    mobsfscan is a fast and powerful static analysis tool for identifying security vulnerabilities in mobile app source code. It supports Android, iOS, and Flutter codebases and helps developers secure apps before deployment.
    Downloads: 0 This Week
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  • 14
    Homemade Machine Learning

    Homemade Machine Learning

    Python examples of popular machine learning algorithms

    homemade-machine-learning is a repository by Oleksii Trekhleb containing Python implementations of classic machine-learning algorithms done “from scratch”, meaning you don’t rely heavily on high-level libraries but instead write the logic yourself to deepen understanding. Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. The purpose is pedagogical: you’ll see linear regression, logistic regression, k-means clustering, neural nets, decision trees, etc., built in Python using fundamentals like NumPy and Matplotlib, not hidden behind API calls. It is well suited for learners who want to move beyond library usage to understand how algorithms operate internally—how cost functions, gradients, updates and predictions work.
    Downloads: 0 This Week
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  • 15
    Boltons

    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. In many cases the respective boltons module...
    Downloads: 1 This Week
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  • 16
    cheat.sh

    cheat.sh

    The only cheat sheet you need

    cheat.sh is a compact, network-accessible cheat-sheet service that serves concise examples and usage notes for hundreds of shell commands, programming languages, and tools via a simple HTTP interface. You can query it from the terminal (for example curl cht.sh/rsync or curl cheat.sh/ls) or browse the web front page; it also supports a shorthand hostname (cht.sh) and provides both online and standalone/local installation modes. The repository contains the server and client code, instructions to run a local standalone instance (including Python virtualenv setup), and tooling to fetch or maintain the upstream cheat-sheet data; installation documentation explains disk-space needs and dependency setup for offline use. ...
    Downloads: 1 This Week
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  • 17
    PoJamas aims to provide a Python and tools for loading, processing, and producing .cr2, pz3 (crz, pzz) files compatible with the SmithMicro (e-frontier) Poser character animation application. PoJamas is composed of: - Python library - Python Wavefront (.obj) 3D viewer based on GLFW - LibreOffice/Python Application (to ease the library and the viewer usage) As of 2020, the project is ported in Python3 As of 2021 this project proposes a 3D viewer for Wavefront files...
    Downloads: 0 This Week
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  • 18
    OpenCarenet CHE

    OpenCarenet CHE

    Enabling community health workers to collect health data efficiently

    OpenCarenet CHE is a robust and user-friendly application tailored for community health workers, facilitating seamless data collection, management, and reporting. With its mobile data collection capabilities, offline functionality, and interoperability with DHIS2, the app empowers health professionals to efficiently track patient information, aggregate primary data, and generate detailed health reports, even in areas with limited internet access. Its multilingual support and configurable language settings enhance communication and usage in diverse cultural contexts, while features such as local patient management, transparent reference and geolocation functionalities contribute to improved patient care and holistic community health management.
    Downloads: 0 This Week
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  • 19
    gradslam

    gradslam

    gradslam is an open source differentiable dense SLAM library

    gradslam is an open-source framework providing differentiable building blocks for simultaneous localization and mapping (SLAM) systems. We enable the usage of dense SLAM subsystems from the comfort of PyTorch. The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. However, learning representations for SLAM has been an open question, because traditional SLAM systems are not end-to-end differentiable. ...
    Downloads: 0 This Week
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  • 20
    TGAN

    TGAN

    Generative adversarial training for generating synthetic tabular data

    We are happy to announce that our new model for synthetic data called CTGAN is open-sourced. The new model is simpler and gives better performance on many datasets. TGAN is a tabular data synthesizer. It can generate fully synthetic data from real data. Currently, TGAN can generate numerical columns and categorical columns. TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid interfering with other software installed in the system where TGAN is run. ...
    Downloads: 0 This Week
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  • 21
    Jupyter Themes

    Jupyter Themes

    Custom Jupyter Notebook Themes

    jupyter-themes brings theme management to classic Jupyter Notebooks with a command-line tool that can restyle the interface, code cells, and UI chrome in seconds. It ships a catalog of popular dark and light themes and lets you customize fonts, font sizes, cell widths, and toolbar visibility so the notebook matches your preferred reading and coding ergonomics. The theming system adjusts CodeMirror syntax highlighting to keep code legible against chosen backgrounds and provides options to...
    Downloads: 1 This Week
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  • 22
    Algorithms in Python

    Algorithms in Python

    Data Structures and Algorithms in Python

    Algorithms in Python is a collection of algorithm and data structure implementations (primarily in Python) meant to serve as both learning material and reference code for engineers. It includes code for graph algorithms, heap data structures, stacks, queues, and more — each implemented cleanly so learners can trace logic and adapt for their problems. The repository is particularly useful for people preparing for competitive programming, job interviews, or building a foundational...
    Downloads: 0 This Week
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  • 23

    mysql2sqlite

    converts mysql database to sqlite database using php, pdo or exe

    Convert a mysql database to a Sqlite database. Includes two projects : A) A php script B) A windows executable, based on a python script Converts data, indexes and foreign key constraints. About the php script : -don't need a lot of memory -good speed Was projected to use on VDS/VPS. Usage: wget https://sourceforge.net/projects/mysql2sqlite/files/mysql2sqlite/download chmod +x mysql2sqlite ./mysql2sqlite About the Windows executable and the Python script : Usage : edit the in i file to fit your system, and just run the exe or the python script.
    Downloads: 6 This Week
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  • 24
    LightProfiler

    LightProfiler

    Profiler for Oracle extended SQL trace files

    ...It generates detailed resource profile for extended SQL trace files (10046 event), containing information about consuming of response time (by events, by cursors, etc.), data files usage, error analysis (SQL, PL/SQL) and much more. Also it contain tools for additional processing of trace files (extract session data, splitting files) and for management of database's sessions (disconnecting, tracing, monitor parameters, blocking locks, events and etc.)
    Downloads: 2 This Week
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  • 25

    Yang XML viewer

    PyGtk2-based application that shows Yang-models as Treeview

    The application uses 'pyang' for creating a XML file and displaying the Yang-model in a Treeview. Additionally it allows to send Netconf requests to a configured target. For this purpose, it uses the Netconf client from [1] or can use an external console too. [1] https://github.com/tail-f-systems/JNC/blob/master/examples/2-junos/netconf-console
    Downloads: 3 This Week
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