Dev tools · alternatives · 2026

24 alternatives to Opytimizer – A Nature-Inspired Python Optimizer

https://github.com/gugarosa/opytimizer Did you ever reach a bottleneck in your computational experiments? Are you tired of selecting suitable parameters for a chosen technique? If yes, Opytimizer is the real deal! This package provides an easy-to-go implementation of meta-heuristic optimizations. From agents to search space, from internal functions to external communication, we will foster all research related to optimizing stuff. Use Opytimizer if you need a library or wish to: - Create your optimization algorithm; - Design or use pre-loaded optimization tasks; -…

Opytimizer is a Python library for implementing meta-heuristic optimization algorithms. It is designed for researchers and developers who need to optimize computational tasks or create custom optimization methods. The… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Opytimizer – A Nature-Inspired Python Optimizer launched in 2021; newer entries below may have overtaken it.

1
A radically more scalable alternative to Bayesian Optimization▲96
Experimental Global Optimization Algorithm. Contribute to chrisstroemel/Simple development by creating an account on GitHub.
2018 · github.com · its alternatives →
2
TensorZero▲307
Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2025 · github.com · its alternatives →
3
GitHits beta 0.9▲181
It has been almost 10 years since I started the opencv-python packaging project. Scaling it to more than 100 million downloads as a side project showed me how much ease of installation and proper package distribution matter to users. It gave the computer vision ecosystem a noticeable boost. Now I have a new idea that I hope can help even more people across the broader software engineering world. A while ago, I realized I kept giving the same advice to teammates and friends when they ran into a programming issue they couldn't easily solve: go to GitHub and look at how others solved it. There…
Jun 2026 · githits.com · its alternatives →
4
PyBroker – Algotrading in Python with Machine Learning▲70
Hello, I am excited to share PyBroker with you, a free and open-source Python framework that I developed for creating algorithmic trading strategies, including those that utilize machine learning. With PyBroker, you can easily develop and fine-tune trading rules, build powerful ML models, and gain valuable insights into your strategy's performance. Some of the key features of PyBroker include: - A super-fast backtesting engine built using NumPy and accelerated with Numba. - The ability to create and execute trading rules and models across multiple instruments with ease. - Access to…
2023 · github.com · its alternatives →
5
LeanRL: Fast PyTorch RL with Torch.compile and CUDA Graphs▲53
We're excited to announce that we've open-sourced LeanRL, a lightweight PyTorch reinforcement learning library that provides recipes for fast RL training using torch.compile and CUDA graphs. By leveraging these tools, we've achieved significant speed-ups compared to the original CleanRL implementations - up to 6x faster! Reinforcement learning is notoriously CPU-bound due to the high frequency of small CPU operations. PyTorch's powerful compiler can help alleviate these issues, but comes with its own costs. LeanRL addresses this challenge by providing simple recipes to accelerate your…
2024 · github.com · its alternatives →
6
Solid – A comprehensive gradient-free optimization framework in Python▲87
🎯 A comprehensive gradient-free optimization framework written in Python - 100/Solid
2017 · github.com · its alternatives →
7
A weekend replication of STOKE, a stochastic superoptimiser▲58
Haskell re-implementation of STOKE, the stochastic superoptimizer - blaze/notebooks/tutorial.ipynb at master · bollu/blaze
2019 · github.com · its alternatives →
8
Leaping – Debug Python tests instantly with an LLM debugger▲120
Hi HN! We’re Adrien and Kanav. We met at our previous job, where we spent about a third of our lives combating a constant firehose of bugs. In the hope of reducing this pain for others in the future, we’re working on automating debugging. We’re currently working on a platform that ingests logs and then automatically reproduces, root causes and ultimately fixes production bugs as they happen. You can see some of our work on this here - https://news.ycombinator.com/item?id=39528087 As we were building the root-cause phase of our automated debugger, we realized that we developed…
2024 · github.com · its alternatives →
9
Forge Agent▲113
Swarm Agents That Turn Slow PyTorch Into Fast GPU Kernels
Jan 2026 · rightnowai.co · its alternatives →
10
Optimize and serve models with Fable quality at half the cost▲71
Hi HN, we built world-model-optimizer, an open source tool to continually improve a specialized model for an agent. It does this by simulating production tool responses through text world modeling (similar to QwenAgentWorld, summary here https://x.com/silennai/status/2073887455884058814). We can then use this to train a router for frontier, OS, and local models (use defaults or pick which ones to optimize against). wmo ingests agent traces, builds the simulation, embeds the traces, runs different models you choose against the simulation scenarios, and then uses a KNN…
Jul 2026 · github.com · its alternatives →
11BA
Brancher – A user-friendly PyTorch module for probabilistic inference▲96
2019 · brancher.org · its alternatives →
12PA
Python at the Speed of Rust▲68
I’m sure many of you are familiar, but there’s a treacherous gap between finding (or building) a model that works in PyTorch, and getting that deployed into your application, especially in consumer-facing applications. I’ve been very interested in solving this problem with a great developer experience. Over time, I gradually realized that the highest-impact thing to have was a way to go from existing Python code to a self-contained native binary—in other words, a Python compiler. I was already pretty familiar with a successful attempt: when Apple introduced armv8 on the iPhone 5s, they…
2025 · blog.fxn.ai · its alternatives →
13
Minibatch – Python stream processing▲50
Python stream processing for humans. Contribute to omegaml/minibatch development by creating an account on GitHub.
2020 · github.com · its alternatives →
14
A design-by-contract Python package in ~100 lines▲58
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 · its alternatives →
15
Faking SIMD to Search and Sort Strings 5x Faster▲29
I want to share a really dumb, but very practical project I have packaged this summer, to perform operations on strings much faster. I was using Python to work with a multi-terabyte newline-delimited file. Reading, splitting, and shuffling it was a nightmare. So, I wrapped a trivial hardware-friendly heuristic I've been using for the last few years into a CPython library. The part I enjoyed the most is implementing SIMD behavior without SIMD instructions... Using 64-bit words to work at 8-bit granularity. Unlike conventional SIMD, the code would remain the same for ~~almost~~ any hardware.…
2023 · ashvardanian.com · its alternatives →
16
GUIs for Faster ML Prototyping and Sharing▲85
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work! - gradio-app/gradio
2020 · github.com · its alternatives →
17
Gsubpy, an interpreter for subset of Python, written in Go▲65
Recently, I write an interpreter for subset of Python using Go. I haven't seen source code of CPython, all is just written according to my understanding of Python so there may be some unusual things. Hope you can play fun with it. Any suggestion is welcome, glad to get some feedback.
2023 · github.com · its alternatives →
18FA
FunctorFlow – An attempt to re-imagine Python libraries▲40
2019 · functorflow.org · its alternatives →
19
My self-pub book on Evolutionary Algorithms with Python (inc. sample)▲13
A practical book on Evolutionary Algorithms that teaches you the concepts and how they’re implemented in practice.
2021 · datacrayon.com · its alternatives →
20
I Wrote a Book on Evolutionary Algorithms with Python Notebooks▲13
Evolutionary Algorithms (EAs) are a fascinating class of algorithms for meta-heuristic optimisation. Perhaps the most difficult question to answer is where do we start? There is so much to cover, and many potential starting points.
2020 · datacrayon.com · its alternatives →
21
Zipslicer, a library for loading LLM checkpoints on consumer hardware▲38
This is a low-level opensource library I developed for my own use and decided to share, as it makes it possible to process large checkpoints of neural networks without renting high-RAM instances, on a regular PC. It replaces torch.load() with a custom function that produces a dictionary that materializes tensors on the fly. Compared to other solutions it doesn't require sharding or re-encoding checkpoints and uses them completely as-is. It is a foundation to make it possible to run inference and compress language models and other large models one layer at a time - in principle, even one…
2023 · github.com · its alternatives →
22OS
Open-Source AlphaEvolve Clone Using GPT-4.1 and Genetic Programming▲20
Everyone saw the AlphaEvolve hype. I got obsessed with how it might work under the hood and decided to just build it myself. My setup uses GPT-4.1 to mutate matrix multiplication code, guided by a bunch of hand-crafted mutation strategies (loop reordering, tiling, Strassen, etc.). Each candidate is evaluated on both speed and accuracy. Then I apply Pareto selection with crowding distance to evolve better ones over generations. I ran into all the usual LLM reward hacks-returning the input, calling np.dot, etc. So I forced primitive-only implementations and tightly constrained the mutation…
2025 · its alternatives →
23LO
Leaping – Open-source debugging with LLMs▲15
Show HN: Leaping - Open-source debugging with LLMs Hi HN! We’re Adrien and Kanav. We met at our previous job, where we spent about a third of our life combating a constant firehose of bugs. In the hope of reducing this pain for others in the future, we’re working on automating debugging. We started by capturing information from running applications to then ‘replay’ relevant sessions later. Our approach for Python involved extensive monkey patching: we’d use OpenTelemetry-style instrumentation to hook into the request/response lifecycle, and capture anything non-deterministic (random,…
2024 · its alternatives →
24PL
Python library to scan ML models for vulnerabilities▲20
Hi! I’ve been working on this automatic scanner for ML models to detect issues like underperforming data slices, overconfidence in predictions, robustness problems, and others. It supports all main Python ML frameworks (sklearn, torch, xgboost, …) and integrates with the quality assurance solution we are building at Giskard AI (https://giskard.ai) to systematically test models before putting them in production. It is still a beta and I would love to hear your feedback if you have the time to try it out. We have quite a few tutorials in the docs with ready-made colab notebooks to…
2023 · docs.giskard.ai · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →