Streamlit

DashLit is a self-hosted dashboard for links, tools, and service status. It supports multiple public, authenticated, or private dashboards with configurable rows, columns, and masonry layouts; groups and items can be arranged with drag-and-drop on desktop or touch devices. It also provides URL availability monitoring, keyboard filtering and navigation, item and dashboard shortcuts, icon search, light and dark themes, dashboard import, export and cloning, per-user defaults, and local password or OIDC authentication. DashLit is distributed as a single Go binary with an embedded Svelte frontend, and can run with Docker, Docker Compose, or directly as a systemd service on Linux. Application state, uploaded icons, and the SQLite database are stored in a persistent data directory. The project is available under the MIT License.

Helical Insight is an open-source business intelligence and embedded analytics platform for self-hosted, cloud, on-premises, and hybrid deployments. It combines natural-language, chat-driven AI analytics with bring-your-own-LLM support, automatic SQL generation, report summarization, and insight discovery; interactive dashboards with filters, KPI widgets, drill-down and drill-through interactions, maps, charts, pivot tables, and custom JavaScript visualizations; and paginated, pixel-perfect reports for invoices, financial statements, operational reports, and regulatory reporting. Dashboards, reports, and the AI chatbot can be embedded in web applications, SaaS platforms, customer portals, and enterprise applications. Reports and dashboards can be exported to PDF, Excel, CSV, Word, HTML, JSON, and XML, scheduled for delivery by email, and distributed as personalized reports. The platform supports white labeling, multi-tenancy, row-, column-, and table-level security based on user context, and SSO through JWT, Okta, Keycloak, OAuth, and custom token-based mechanisms. It connects to relational databases, NoSQL and big-data systems, flat files, cloud storage, and APIs through native connectors, JDBC, REST APIs, custom integrations, and uploaded JDBC drivers. Docker, Kubernetes, caching, pagination, virtualization, load balancing, clustering, and REST APIs support deployment and extension, while developers can customize it with Java, JavaScript, CSS, HTML, Liquid Template Language, plugins, and custom workflows. The project states that its enterprise features are available in the free open-source version.

XY is an open-source Python charting library for web applications, notebooks, and static exports. It supports declarative charts and matplotlib-style conventions, with customization through Python, CSS, or Tailwind; outputs include HTML, PNG, SVG, and PDF. For small charts, XY sends individual points to the browser. For large datasets, its Rust core computes the data needed for the current screen resolution and can represent the result as a density surface. Panning, zooming, hovering, and selections rerun the process for the visible range, while selections can return the original data rows. The library is installable with pip or uv and supports interactions such as pan, zoom, hover, crosshairs, callbacks, and linked charts, along with layers, facets, responsive layouts, themes, axes, legends, and tooltips. The repository describes XY as an alpha project and notes that its matplotlib compatibility does not yet cover all charts and functionality.

Project Jupyter is an open-source web-based interactive computing platform centered on notebooks and computational kernels. JupyterLab provides a configurable interface for notebooks, code, and data, while the classic Jupyter Notebook offers a document-oriented web application for creating and sharing computational documents. Notebooks combine executable code with narrative text, equations, visualizations, and rich outputs, and use a JSON-based document format; kernels run code in a selected programming language and communicate with the notebook through a JSON-based interactive computing protocol over ZeroMQ and WebSockets. Jupyter supports more than 40 languages, including Python, R, Julia, and Scala, and includes JupyterHub for centrally deployed multi-user environments and Voilà for turning notebooks into stand-alone web applications.

Gridline is an independent, Excel-inspired browser spreadsheet application built with plain HTML, CSS, and JavaScript. It uses a WebGPU worksheet renderer with a Canvas2D fallback, a formula interpreter with dependency tracking and cached results, transactional editing, and local workbook storage without a framework, CDN, account, application server, or runtime package dependencies. The application supports worksheets, formatting, charts, sorting, filtering, notes, conditional rules, undo/redo, cross-sheet and relative or absolute A1 references, CSV/TSV import and export, native .gridline JSON files, and a documented subset of XLSX. Its engine can also be used directly as an ES module. Local autosaves remain in the current browser profile and origin rather than cloud storage; WebGPU requires a compatible browser and suitable origin, while calculation and serialization run synchronously on the main thread. Gridline is an engineering preview released under the MIT license. XLSX support is not a lossless Excel round trip: pivots, VBA, Power Query, external links, dynamic arrays, advanced formatting, rich text, charts, notes, and conditional rules are not fully supported or exported. The repository reports passing Node and browser test suites, but its release tests did not verify WebGPU pipeline execution or hardware performance.