Alternatives
Products that do what Bridge-ds – Dataset handling for any modality a la Pandas does
Hi everyone, I'd like to share my project, bridge-ds - a lightweight Python framework that simplifies how ML practitioners manage and interact with datasets. Why bridge-ds? It abstracts the repetitive parts of dataset handling in real-world ML workflows, but remains lean enough as to not force opinionated workflow or unnecessary dependencies. bridge-ds uses two complementary approaches: - Macro-level: Treat your entire dataset like a DataFrame—filter, sort, and modify with familiar, intuitive operations. - Micro-level: Efficiently handle individual samples with lazy loading, caching, remote…
- 1BA
2019 · bamboolib.com
- 2DA
Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…
2020
- 3UD
I've been working a fair bit with DSPy lately, and I did some work in combining the benefits of vector search and LLMs (via a DSPy pipeline) to disambiguate records with a high degree of accuracy to help enrich a dataset. The blog post shows how this approach scales well, is very cost-effective and super concise - all it takes is < 100 lines of DSPy code and it all runs async. The code to reproduce is in this repo if anyone's interested (all tools are 100% free and open source, and the methodology will work with open weight LLMs too).…
2025 · blog.kuzudb.com
- 4IM
2020 · github.com
- 5II
Two weeks ago I was on my babymoon in Corfu, Greece. While in transit, I was overseeing a GSoC intern submit an important feature to my array database library, Xarray-SQL. He added `to_dataset()`, which completed the roundtrip between thinking of array data in a tabular model simultaneously as gridded rasters (the premise of the project is that every Nd array can be mapped to 2d, where orthogonal dims of the Nd array are just primary keys of a tabular representation). We discussed in chat, now that this feature existed, what demos could we make that would prove this data model works? With…
Jul 2026 · github.com
- 6SP
Hi HN, Over the past 6 months I've been working on a technical book focused on helping aspiring data scientists to get hands-on experience with cloud computing environments using the Python ecosystem. The book is targeted at readers already familiar with libraries such as Pandas and scikit-learn that are looking to build out a portfolio of applied projects. To author the book, I used the Leanpub platform to provide drafts of the text as I completed each chapter. To typeset the book, I used the R bookdown package by Yihui Xie to translate my markdown into a PDF format. I also used Google docs…
2020
- 7DC
2016 · datasets.co
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- 10AP
2020 · github.com
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- 13DT
Sep 2025 · github.com
- 14SF
I've made a small Python library, designed for quick-and-easy prototyping of machine learning models. It's built on top of scikit-learn, to serialize and deserialize data from the forms you're likely to have, to the format used in scikit-learn. https://github.com/madman-bob/Smart-Fruit It's pretty bare-bones at the moment, but I thought I'd see if there was any interest before spending too much time on it. Let me know what you think.
2018
- 15DA
For the past few weeks, I've been working on DataBridge, an open-source solution for easy data ingestion and querying. We support text, PDFs, images, and as of recently, we've added a video parser that can analyze and work well over frames and audio. We are also adding object tracking to improve video ingestion and context, and plan to do this for various data types. To get started, you can find the installation section in our docs at https://databridge.gitbook.io/databridge-docs/getting-starte.... There are a bunch of other useful functions and examples available there.…
2024 · github.com
- 16CM
2019 · github.com
- 17DA
Hi. :) I’m Andrey, the creator of dstack. I started this project while I was working at JetBrains where I helped the PyCharm team to improve support for Jupyter notebooks. As I was in close contact with many ML devs (who used PyCharm) I was able to see their struggle with running ML workflows. Unlike traditional dev workflows, ML workflows are difficult to run on a local machine (due to the lack of memory, more CPUs/GPUs, etc). This is why people often have to use remote machines (e.g. via SSH), or adopt one of the end-to-end MLOps platforms. Using remote machines is not difficult but…
2022 · github.com
- 18RA
2022 · github.com
- 19MM
Hi HN, we're Arnav and Adi, and we're building DataBridge - a multi-modal database built from the ground up with AI use cases in mind. We recently launched support for ColPali-style image embeddings and late-interaction retrieval. We've implemented a hamming distance version of retrieval which helps this approach scale significantly more when compared with the regular late-interaction similarity scoring. These embeddings provide a significantly better retrieval accuracy, with ColQwen achieving around an 89% average score on the ViDoRe benchmark, compared to around 67% for traditional parsing…
2025 · github.com
- 20DA
Hi there, I tried to build a CLI tool to edit and visualize Excel/CSV files directly in the terminal, I called it "dss". I did it for fun to tweak spreadsheet formulas without leaving my terminal or opening heavy GUI apps. It is an interactive editor of sheets with charts and formula engine diretly in TUI. The formula engine is handmaded but I'd like to improve it. I copied a lot from my previous Datacmd project and from Termdash repo. Hoping to receive some feedback.
Apr 2026 · github.com
- 21IE
Hey HN, We built a library to interactively explore unstructured datasets directly from a dataframe: https://github.com/Renumics/spotlight Some background: We have worked on different ML solutions over the years, mainly in the industrial AI space. A crucial step for us is always to inspect and explore the data interactively with the team and the customer. This is true throughout the dev process: During EDA, model debugging, model comparison and monitoring. We have tried many different options for visualizing unstructured datasets in the past: Notebooks, dash apps, custom…
2023 · github.com
- 22PIPandas in JS▲14
2017 · stratodem.github.io
- 23EP
2021 · hairysun.com
- 24IB
Hey HN! Over the past few weeks, I’ve been working on DataBridge, an open-source solution for data ingestion and querying across text, PDFs, images, and videos. In our latest update, we’ve added a fully local deployment option: - No internet required – Runs entirely offline. - Customizable Models – Supports any LLM and embedding model via Ollama (with options for any other private providers) - Extensibility – You can plug in your own models or tools easily. This local-first approach ensures better privacy, security, and flexibility, especially for teams dealing with sensitive data. You can…
2025 · github.com
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