Search Results for "dashboards"

Flask-SocketIO is an extension for the Flask web framework that enables real-time bi-directional communication between clients and servers using WebSockets or long-polling fallbacks, making it possible to build interactive applications like chat systems, live dashboards, and collaborative tools. It abstracts the complexities of asynchronous sockets by providing a familiar Flask-style API where developers can define event handlers that trigger on client messages, broadcast to connected users, and manage namespaces and rooms. The extension supports multiple asynchronous workers through integrations with popular async servers like eventlet or gevent, allowing scalable handling of concurrent connections. ...

...Unlike simple sample repositories, it focuses on production-oriented use cases such as data pipelines, machine learning workflows, infrastructure automation, and security management. The repository contains a wide variety of projects, including tools for validating data migrations, generating large datasets for testing, building analytics dashboards, and automating policy enforcement in cloud environments. These solutions are intended to serve as blueprints that organizations can adapt and extend for their own needs rather than turnkey products. It also includes reusable utilities, helper scripts, and example architectures that demonstrate best practices for building scalable and maintainable systems on Google Cloud.

Grafanalib is a Python library for building Grafana dashboards programmatically, allowing users to automate dashboard creation and configuration.

Whisper is one of three components within the Graphite project. Whisper is a fixed-size database, similar in design and purpose to RRD (round-robin-database). It provides fast, reliable storage of numeric data over time. Whisper allows for higher resolution (seconds per point) of recent data to degrade into lower resolutions for long-term retention of historical data. Copies data from src in dst, if missing. Unlike whisper-merge, don't overwrite data that's already present in the target...

...It lays out common use cases (plot types, styling, figure configuration, saving/exporting, subplot layout, etc.) in a concise and organized format — often serving as a “cheat sheet” for rapid look-up. For practitioners working on data-heavy projects, dashboards, or research code where plotting is frequent, it helps speed up development by reducing context-switching and documentation navigation overhead. It is especially useful when you know roughly what you want (e.g. “I need a scatter + histogram marginal plot”) but don’t remember the exact Matplotlib call.