Alternatives
Products that do what Manifold-BT does
Fast backtesting for Python traders, powered by Rust
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We think backtesting is too difficult, this is our attempt to make it much easier and more fun - let us know what you think!
2012 · quantblocks.com
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Hi HN, I'm a solo dev and for the last few months I've been building Hikaro, a tool to find statistically significant trading signals for [e.g., US equities, crypto, forex]. I built this to solve my own problem: I was tired of backtests that looked great on paper but failed in practice. Simple metrics like "win rate" can be misleading, so I wanted a way to quickly tell if a signal's performance was genuine or just noise. Hikaro ingests daily market data and runs statistical analysis on various trading signals. The goal is to surface signals with strong properties, like: Low p-value: Evidence…
Sep 2025 · hikaro.app
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Describe, backtest, and automate your trading strategy
5d ago · hey-traders.com
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I built TradeSight (https://tradesight.live) as a lightweight market risk indicator that combines real-time data with AI insights. The backend is written in Rust, with a vanilla JS frontend for maximum performance. It aggregates data from multiple sources (FRED API, Yahoo Finance) and uses Claude's API to provide detailed market analysis. Technical stack: - No login required - static page with hourly updates - Rust backend for efficient data aggregation - Vanilla JavaScript frontend for minimal overhead - Claude API integration for real-time market analysis - Data sources: FRED…
2024 · tradesight.live
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Quick note on how it works and how I've done my batch embedding engine IgniteMS. The whole thing runs as one process using Rust, reading input, tokenizing, packing batches, keeping the queue full. TensorRT handles inference. Python is only as a wrapper. I built it this way because when you use more than couple of GPUs, the GPUs stop being the problem. CPU cannot feed them fast enough. One A100 can go through batches faster than Python can tokenize and feed, so the GPU just sits there idle waiting for work. Most of my time went into optimizing this. At 8 GPUs that was basically the entire…
Jun 2026 · github.com
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I built a Rust drop-in replacement for svelte-check that's 10-30x faster for Svelte 5 projects. What it does: - Parses Svelte files with a custom Rust parser - Transforms them to TSX in parallel using Rayon - Runs type-checking via Microsoft's tsgo (the native Go port of TypeScript) - Maps errors back to original .svelte locations via source maps Why it's fast: The official svelte-check uses TypeScript's Language Service API optimized for IDEs with persistent connections. Great for autocomplete but slow for batch CLI checks. svelte-check-rs writes real TSX files to disk and runs tsgo as a…
Jan 2026 · svelte-check-rs.vercel.app
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Hi HN, We’ve all accepted the "Python tax"—you trade execution speed for developer happiness. But what if that trade-off was a thing of the past? I just came across BustAPI, and it’s basically a "cheat code" for Python web services. It’s not just another wrapper; it’s a hybrid engine that embeds a Rust (Actix-Web) core directly into the Python runtime. Is this the end of the "slow Python" era? The benchmarks are pretty shocking. I’d love to see someone stress-test this against a production-grade Go or Node.js setup. Repo: https://github.com/GrandpaEJ/BustAPI Benchmarks:…
Dec 2025 · github.com
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I've just released rust-loguru, a logging library for Rust that aims to combine intuitive API design (inspired by Go/Python's Loguru) with Rust's performance characteristics. Some highlights: - Consistently outperforms the standard log crate by 50-80% in benchmarks. - Multiple log levels and an extensible handler system -File rotation with better performance than log4rs and other alternatives - Error handling utilities and context helpers I built this because I wanted a logger that was both ergonomic to use and high-performance. The benchmarks comparing it to slog, log, and tracing are…
2025 · crates.io
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Backtesting & live execution infra for AI trading agents
9d ago · emidlabs.com
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Hey HN! We built Achilles, a tool that automatically accelerates your Python code. It identifies performance bottlenecks, rewrites those functions in optimized C++, and seamlessly patches them into your running program—without you changing a single line of code. In CPU-intensive, loop-heavy tasks, we've observed performance improvements of 100-1000x. Achilles can be installed via pip and works with just a single command. We'd appreciate your feedback, and feel free to give us a star if you find it interesting!
2025 · github.com
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Hello, I have several years of experience as a Python developer, and during that time, I've worked on intricate applications dealing with large volumes of data. One frequent challenge I faced was benchmarking the application and identifying performance bottlenecks. While there are some excellent Python profiling tools available, they can be quite daunting for beginners. The utility I have developed simplifies this process, making it as straightforward as possible to transition from slow code to a detailed flame chart. I would greatly appreciate your feedback!
2023 · github.com
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Hello HN. I built my own automated Bitcoin trading bot and noticed that many others want to do the same thing, but lack the coding skills required for the harder stuff, like order execution and backtesting. I like the idea of making automated trading more accessible to existing day traders as well as newcomers. Hopefully this will also inspire some people to learn to code. We’re currently in private beta, but please check out the site below. Feedback is more than welcome. http://tradewave.net
2014
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Read the full blogpost at https://rach.codes/blog/Introducing-Bhumi (click on reader to see the technical breakdown!) AI inference should be fast, but in practice it’s painfully slow. Inference bottlenecks slow down LLM-powered chatbots and AI workflows everywhere. I built Bhumi to fix that. Bhumi is a Python library designed for developers, yet its performance-critical core is implemented in Rust (via PyO3) for near-native speed. This hybrid approach delivers up to 2.5x faster response times across providers like OpenAI, Anthropic, and Gemini—without changing the…
2025 · bhumi.trilok.ai
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Built an AI code reviewer using Letta (Python) that I can call natively from Rust applications. The interesting part: real-time streaming works perfectly across the language boundary with zero hassle using RunAgent. The agent runs in Python with persistent memory, leverages the best in house agentic memory management with Letta (Pythonic AI agent framework), and my rust code just uses it (kinda) natively, though Letta has no Rust bindings. And, streaming works like magic. No FFI, no complex bridges - just native async/streaming that feels like calling any Rust librar, but without…
2025 · medium.com
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Witchcraft is from-scratch Rust reimplementation of Stanford's XTR-Warp (SIGIR'25, https://arxiv.org/abs/2501.17788 ) multi-vector semantic search engine. Witchcraft runs out of a single SQLite database, is blazing-fast (21ms p.95 end-to-end search latency on NFCorpus on a MacBook Pro), accurate (33% NDCG@10), and easy to deploy in your own apps. The Witchcraft repo also comes with Pickbrain, a sample app and agent skill that you can use to instantly query across all your Claude Code and Codex CLI sessions, effectively giving your agents global long-term memory. Please…
Apr 2026 · github.com
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2017 · hackernoon.com
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I built Hermes, an open-source Python framework for multi-agent financial research. Most AI “equity research” demos stop at generating text. In practice, real workflows require pulling structured XBRL financials from SEC filings, extracting labeled sections like MD&A and Risk Factors, merging macro and market data, building actual Excel models with formulas, and generating investment memos in Word or PDF. Hermes is designed to handle that full pipeline end to end. It includes 35 financial data tools covering SEC EDGAR (via edgartools), FRED, Yahoo Finance market data, and RSS-based financial…
Feb 2026 · github.com
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Hi HN – this is Peter from DBOS here with Qian (qianli_cs) and Jeremy (jedberg). We’re building an open-source, lightweight durable workflows library on top of Postgres. Ever since we first launched on HN last year, we’ve been blown away by the support, feedback, and response we’ve received from the community. We've realized durable workflows are critical for everything from business processes to AI automation to data pipelines, but most existing durable orchestration tools are either too heavy or too complicated for most applications. Instead, we're building something lightweight, simple,…
2025 · github.com
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