7 个仓库
Frameworks optimized for building data-centric applications and dashboards without requiring front-end languages.
Distinct from Python Web Frameworks: Distinct from general Python web frameworks as it is specifically geared towards data apps and interactive dashboards.
Explore 7 awesome GitHub repositories matching web development · Data App Frameworks. Refine with filters or upvote what's useful.
Dash is a Python-based framework for building analytical web applications and reactive data dashboards. It allows developers to connect data science and machine learning code to interactive web interfaces without writing JavaScript, serving as a backend-driven tool for defining layouts and managing state. The framework integrates the Plotly charting engine to render a wide variety of complex charts and financial graphs. It distinguishes itself through a reactive callback system that links user input components to data visualizations, enabling the creation of business intelligence dashboards a
Provides a framework for building analytical web applications and interactive dashboards using Python without writing JavaScript.
Bokeh is a Python data visualization library and interactive plotting framework used to create high-performance graphics and data dashboards that render in web browsers. It serves as a tool for generating standalone HTML documents, embedded components for digital notebooks, and full-stack web applications powered by a Python backend. The project distinguishes itself through its ability to handle large or streaming datasets while maintaining smooth interactivity. It enables linked brushing across multiple views, allowing data selected in one plot to automatically highlight corresponding data i
Facilitates the development of full-stack web applications with a Python backend to power dynamic data visualizations.
GreptimeDB is a distributed, open-source time-series database built for unified observability. It stores and queries metrics, logs, and traces together in a single columnar engine, supporting both SQL and PromQL for analysis. The database is designed as a Kubernetes-native operator with a decoupled compute and storage architecture, enabling horizontal scaling and multi-region deployment. What distinguishes GreptimeDB is its role as a multi-protocol ingestion gateway, accepting data through OpenTelemetry, Prometheus Remote Write, InfluxDB, Loki, Elasticsearch, Kafka, and MQTT protocols without
Connects to Streamlit via SQL for building interactive data applications.
dtale 是一个基于 Web 的 pandas 数据框交互式网格与可视化工具,设计为探索性数据分析工具。它提供了一个基于浏览器的界面用于分析表格数据结构,允许用户在无需编写手动代码的情况下计算统计数据、检测异常值并计算相关性。 该项目作为嵌入式数据查看器运行,可通过 iframe 或自定义路由集成到 Web 应用中,并对 Django、Flask 与 Streamlit 提供特定支持。它通过交互式数据网格与能够生成直方图、箱线图与 3D 散点图的数据可视化库的组合,实现了对数据集的探索。 该平台涵盖了广泛的数据管理与分析能力,包括表格数据清理、重塑与交互式过滤。它包括用于缺失数据分析、相关性计算与预测能力评分的观测工具。对于会话管理,它支持多实例追踪与跨并发工作进程的状态持久化。 该界面受用户名与密码认证保护,并支持从分隔文件、电子表格与 ArcticDB 数据存储中进行数据摄入。
Integrates the data analysis interface into Streamlit applications by routing requests through a container.
Preswald 是一个 WebAssembly 数据应用框架,用于构建完全在浏览器中运行的 Python 交互式数据应用。它提供了一个基于浏览器的数据栈,包括 SQL 和 Python 执行环境,无需后端服务器即可离线运行。 该框架包含一个静态数据应用打包器,可将数据工作流和可视化结果打包成单个可共享的文件。这些自包含的应用实现了无服务器数据可视化和可分发的数据工作流打包。 该系统利用响应式数据仪表板界面,根据底层数据的变化自动更新特定的屏幕元素。它涵盖了本地优先的状态管理和客户端 SQL 执行,以保持浏览器会话中的操作连续性。
Provides a framework optimized for building interactive data-centric applications and dashboards without requiring front-end languages.
Leafmap is a Python geospatial visualization library designed for creating interactive maps and performing geospatial analysis within Jupyter environments. It provides a comprehensive set of tools for building interactive map interfaces, browsing and visualizing SpatioTemporal Asset Catalog items, and connecting to PostGIS databases for spatial data rendering. The project distinguishes itself through a backend-agnostic rendering system that allows users to switch between different mapping engines while maintaining a consistent API. It features specialized capabilities for Cloud Optimized GeoT
Displays interactive maps directly within Streamlit web applications as functional UI components.
Vizro is a low-code Python framework for building production-ready data visualization applications. It functions as a UI orchestrator that allows users to define multi-page analytical dashboards through structured configurations in Python, YAML, or JSON, reducing the need for extensive frontend engineering. The project distinguishes itself through generative AI integration, utilizing a model context protocol server to translate natural language descriptions into validated dashboard configurations, charts, and layouts. It also features a decoupled data cataloging system that separates data sou
Provides a framework for building data-centric dashboards without requiring advanced frontend engineering or design expertise.