Building trading platform and develop tools

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Bo Nguyen • Peerlist

The UI framework for AI coding agents, on Svelte 5: one typed vocabulary across every component, docs generated from the types, and errors that say how to fix them. Accessible, consistent and polished by default, with five built-in design languages behind one theme engine.Status: alpha. Install it with npm install sveltier. The API may still change between releases.<ul><li>Docs: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="http://sveltier.com">sveltier.com</a></li><li>For agents: <a target="_blank" rel="nofollow" class="break-all link-break text-gray-500 hover:underline" href="https://sveltier.com/llms.txt">llms.txt</a> and <a target="_blank" rel="nofollow" class="break-all link-break text-gray-500 hover:underline" href="https://sveltier.com/llms-full.txt">llms-full.txt</a></li><li>What the package offers and how to set it up: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://github.com/sveltier/sveltier/blob/main/packages/sveltier#readme">packages/sveltier</a></li></ul>

Sveltier: the UI framework

<h3>Averosi is a free AI-powered Applicant Tracking System (ATS) designed for headhunters and recruitment agencies. It streamlines the hiring process by leveraging artificial intelligence to assess CV suitability against job descriptions and generate relevant interview questions.</h3><ul><li>AI-Powered CV Matching: Averosi's AI reads CVs and scores their match percentage with the Job Description (JD), helping you prioritize candidates. It highlights strengths with supporting evidence from the CV and identifies areas that require further verification.</li><li>Interview Guidance: Receive up to three suggested interview questions tailored to the candidate's CV and the JD's requirements, focusing on areas needing clarification.</li><li>Streamlined Workflow: Manage your entire recruitment pipeline, from screening to offer, within a single platform. Features include a customizable pipeline (Table &amp; Kanban views), bulk actions, and email BCC for efficient communication.</li><li>Automated CV Parsing: Upload CVs in PDF or DOCX format, and Averosi automatically extracts key information like name, email, phone number, LinkedIn profile, job title, experience, skills, and salary expectations (using AI credits).</li><li>Client Collaboration: Share blind profiles with clients for review, with options for them to accept or reject. Links are time-bound for security.</li><li>Team Collaboration &amp; Job Sharing: Invite team members, manage roles, and securely share job openings with other headhunters and agencies on the platform to collaborate on difficult-to-fill roles and share referral fees.</li><li>Customizable Career Pages: Create a dedicated career page for your agency to attract candidates directly. Shareable across social media platforms.</li><li>Reporting &amp; Analytics: Gain insights into conversion rates at each stage of the pipeline, identify effective candidate sources, and track time-to-hire metrics.</li><li>Data Privacy &amp; Security: Averosi ensures data isolation per agency and implements candidate consent mechanisms. AI processing is opt-in, with automatic anonymization of sensitive data.</li></ul>Averosi is committed to providing a free, efficient, and intelligent solution for recruitment professionals, allowing them to focus more on candidates and clients.

Averosi — AI ATS free headhunters & agencies

<h3>About densa</h3>densa is a Rust toolkit designed for applications that need to display a large amount of live, dynamic data with exceptional performance. It focuses on keeping live data in order as it changes and rendering it on the GPU at the display's refresh rate, ensuring a smooth experience from data stream to pixel. This toolkit is ideal for software where every pixel carries critical, rapidly updating information.<ul><li>Live Tables: Efficiently upsert Arrow record batches by key. Views can be sorted, filtered, and aggregated, with changes reflected incrementally without full recomputation. Batches are shared, not copied, and reading a view never allocates memory. Selections remain with their data as it moves.</li><li>Widgets: A retained tree of widgets, laid out using flexbox, that handles pointer, keyboard, and input method events. This system can run without a window, allowing interfaces to be built, driven, and tested headless. Features include labels, buttons, text inputs, scroll views, splitters, panels, and docking capabilities.</li><li>Data Grid and Charts: A high-performance data grid and chart component that tracks live data, offering zoom and pan functionality. Charts can be linked to grids, displaying data for selected instruments in real-time.</li><li>Rendering: Utilizes a batched rendering approach, combining rectangles and glyphs into a single instanced draw call per frame. The data grid directly accesses cell data, eliminating the need for model copying. Charts draw lines efficiently, and glyph atlases grow dynamically.</li><li>Text Rendering: Paragraphs are shaped, wrapped, and aligned, sharing a glyph atlas with the grid. Supports bidirectional text, colored spans, and various alignments. Features include click-to-caret selection, keyboard navigation, and input method editing (IME).</li><li>Data Handoff: Implements a wait-free data hand-off mechanism between producer and UI threads, ensuring that the UI thread always picks up the newest data snapshot once per frame without blocking.</li><li>Engineering Guarantees: The project emphasizes reliability through rigorous testing, including no allocation per frame, no locks between threads, correct pixel rendering verification, and thorough checking of unsafe code.</li></ul>densa is open source under the MIT or Apache-2.0 license and supports Linux, macOS, and Windows. It requires Rust 1.90+ and a GPU with Vulkan, DX12, or Metal support.

densa: Rs libraries for data-dense interfaces

<h3>TradeCanvas is a powerful and flexible charting library designed for web applications, enabling the creation of sophisticated trading interfaces. It leverages both Canvas 2D and WebGL for rendering, ensuring high performance and smooth visuals even with large datasets. The library boasts an extensive feature set, including 18 different chart types, 111 built-in technical indicators, and 69 drawing tools, allowing users to perform in-depth market analysis.</h3><ul><li>Real-time Data: Connect to live exchange feeds to display up-to-the-minute market data.</li><li>Interactive Trading: Place and manage orders directly on the chart, with visual representation of positions and stop-loss/take-profit levels.</li><li>Advanced Analysis: Utilize a wide array of indicators and drawing tools, such as Fibonacci levels, trend lines, and harmonic patterns, with customizable settings and alerts.</li><li>Historical Data &amp; Replay: Step through historical price data bar by bar, with indicators, drawings, and orders dynamically updating to simulate past trading scenarios.</li><li>Performance: Optimized for speed, capable of rendering up to 1 million bars at 60 frames per second using WebGL, and efficiently handling large datasets with Canvas 2D fallback.</li><li>Framework Integration: Offers dedicated wrappers for popular frameworks like React, Vue, and Svelte, facilitating seamless integration into existing projects.</li><li>Extensibility: Allows developers to register custom indicators, drawing tools, and chart types, tailoring the library to specific needs.</li><li>Multi-language Support: Available in 30 languages, making it accessible to a global audience.</li><li>Zero Dependencies: Built with a focus on minimal dependencies, ensuring easier integration and smaller bundle sizes.</li><li>Open Source: Licensed under MIT, providing freedom for commercial and non-commercial use.</li></ul>TradeCanvas provides a comprehensive solution for building feature-rich trading platforms, from basic charting to complex analytical and trading functionalities.