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Products that do what numeth does
Python package to use numerical method algorithms in 1 line
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Dec 2025 · coe.psu.ac.th
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Credit goes to the contributors of https://github.com/enjeck/num2math for making the tool's core.
2024 · scientific.place
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2020 · mathtocode.com
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Greetings! A 2.5 weekends project to teach myself newer Python features (>= 3.10). Conditions are written as Lambda expressions that annotate parameters and return types, and coexist with type annotations. Symbols to share values between conditions are also supported to a limited extend.
2022 · github.com
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2017 · github.com
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This is a Python package that allows you to write function signatures to define LLM queries. This makes it easy to mix regular code with calls to LLMs, which enables you to use the LLM for its creativity and reasoning while also enforcing structure/logic as necessary. LLM output is parsed for you according to the return type annotation of the function, including complex return types such as streaming an array of structured objects. I built this to show that we can think about using LLMs more fluidly than just chains and chats, i.e. more interchangeably with regular code, and to make it…
2023 · github.com
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2021 · projectlovelace.net
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Hi HN! Erik here from Banana (formerly the serverless GPU platform), excited to show you what we’ve been working on next: Fructose Fructose is a python package to call LLMs as strongly typed functions. It uses function type signatures to guide the generation and guarantee a correctly typed output, in whatever basic/complex python datatype requested. By guaranteeing output structure, we believe this will enable more complex applications to be built, interweaving code with LLMs with code. For now, we’ve shipped Fructose as a client-only library simply calling gpt-4 (by default) with json…
2024 · github.com
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2012 · github.com
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2018 · github.com
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Iḿ developing a python package which allows to develop digital circuits. It currently has modules for logic gates, multiplexers and latches; and the next version will include adders, shift registers, and even a simple ALU! Check it out on github.
2022 · github.com
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There is a mobile game called DragonBox. It sort of tricks you into learning algebra by starting with very abstract manipulations of a puzzle that must follow rules... gradually the game teaches you more and more rules and also strips out the more abstract elements until on the last levels you are finally solving real equations. I loved it, it taught my kids algebra.... and it was just fun. Over the years I often thought that there should be a calculator for Algebra that works this way... something where you can drag terms around and cancel & distribute with gestures, but most importantly…
Jul 2026 · github.com
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Hey HN, I’m a physicist turned quant. Some friends and I 'built' SymDerive because we wanted a symbolic math library that was "Agent-Native" by design, but still a practical tool for humans. It boils down to two main goals: 1. Agent Reliability: I’ve found that AI agents write much more reliable code when they stick to stateless, functional pipelines (Lisp-style). It keeps them from hallucinating state changes or getting lost in long procedural scripts. I wanted a library that enforces that "Input -> Transform -> Output" flow by default. 2. Easing the transition to Python: For many…
Feb 2026
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Hi all, we recently open sourced the first version of Hashquery, a Python library which lets you model analytics, DRY up common logic, and execute it against a database or warehouse. We were originally rendering SQL directly for all our queries, but that spiraled out of control with more complex analysis; the SQL needed to be changed sporadically for each new database dialect (BigQuery, Redshift, Aethena, Postgres, etc etc) and the SQL fragments were very challenging to reuse (and so fragments were copy-pasted all over). ~~~ Advantages we think it has over writing SQL by hand: - Queries are…
2024 · hashquery.dev
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2021 · everydayanchovies.github.io
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Hello everyone! I've been working on this project for a few months as part of my thesis in Machine Learning. It's meant to be a library that provides an easy-to-use but flexible API to design and train Diffusion Models. I decided to make it because I wanted to quickly prototype a Diffusion Model but there were no good tools to do it with. I think it really can help people prototype their own Diffusion Models a lot faster and only in a few lines of code. The base idea is to have a Model class that takes different modules corresponding to the different aspects of the Diffusion Model process…
2023 · github.com
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2022 · github.com
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We’ve just open-sourced Vicinity, a lightweight approximate nearest neighbors (ANN) search package that allows for fast experimentation and comparison of a larger number of well known algorithms. Main features: - Lightweight: the base package only uses Numpy - Unified interface: use any of the supported algorithms and backends with a single interface: HNSW, Annoy, FAISS, and many more algorithms and libraries are supported - Easy evaluation: evaluate the performance of your backend with a simple function to measure queries per second vs recall - Serialization: save and load your index for…
2024 · github.com
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