Alternatives
Products that do what dstack – an open-source tool to build data applications easily does
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…
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2020 · dstack.ai
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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
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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
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Hi HN! I’m Alex from Parabola (https://parabola.io). Parabola is a visual programming tool for creating functional data flows that everyone can use. It’s entirely drag-and-drop, handles data sizes much larger than a traditional spreadsheet, calculates everything live, and can run your flows on a schedule of your choosing. I used to work in strategy consulting, doing data analytics for SMBs and Fortune 500 companies. The amount of time wasted on menial tasks was astounding. Things like cleaning data, generating custom reports, creating human workflows to solve shortcomings in third…
2018 · parabola.io
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Hello Hacker News! We are Rick & Yannick from Orchest (https://www.orchest.io - https://github.com/orchest/orchest). We're building a visual pipeline tool for data scientists. The tool can be considered to be high-code because you write your own Python/R notebooks and scripts, but we manage the underlying infrastructure to make it 'just work™'. You can think of it as a simplified version of Kubeflow. We created Orchest to free data scientists from the tedious engineering related tasks of their job. Similar to how companies like Netflix, Uber and Booking.com…
2020
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2014 · callmeed.github.io
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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
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I've already posted yesterday, but I'd really love to get comments, any kind of questions, suggestions and help would be greatly appreciated as it's an Open Source project of mine (and was for others during my studies at the University of Konstanz 6 years ago). Since then I spent countless ours to bring forth the idea of a versioned storage system, especially well suited for analytical tasks for timd-varying data. Especially I'd love to discuss what documentation you need, which next steps are necessary (JSON, Cloud...), API additions or changes... I've updated the README quiet a bit, such…
2018
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2020 · github.com
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Hi Show HN, we are Dave, Marcin, Alena, and Adrian, authors of data load tool (dlt), a Python library that automatically creates datasets from any kind of messy, unstructured data. We launched dlt on HN 7 months ago with a mission to make getting datasets fast and easy. Now dlt helps its users to code around a thousand new data sources each month and to maintain many thousands of live datasets in production. Today we are releasing *dlt-init-openapi,* a Python CLI tool that generates a dlt data pipeline from any OpenAPI spec. It brings the time to create a dataset down to a few minutes.…
2024 · colab.research.google.com
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2019 · github.com
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2019 · github.com
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Hi HN! I am an undergrad student trying to build interesting things with AI. Recently, I was looking for a dataset I could use for a new project. I realized that it is really frustrating to go through all the government websites (with terrible UX) just to find some usable dataset. I set out to build a GitHub for datasets, named DataHub. Right now, we have more than 1000 datasets from Montréal and New York City, with more cities coming soon (and possible government agencies). All of this is wrapped into a powerful search. It's a breeze to find a dataset to work on. I'd be interested to know…
2017
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2016 · vpj.github.io
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2015 · getdatajoy.com
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Hey HN! We just released the open-source version of Renumics Spotlight, a data exploration and analysis tool for multimodal datasets. Spotlight integrates seamlessly with pandas and supports rich data types like images, videos, and meshes. You can load anything that fits in a DataFrame and view it through a customizable GUI featuring multiple interactive widgets: a data table, similarity map, histograms, scatter plots, and more. In the past, we have used Spotlight for exploratory data analysis and tackling various model and data-related problems in our machine learning projects. What are…
2023 · renumics.com
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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
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Hello HN. We're happy to show to the world a platform that we've created to help our students get started with Data Science: https://notebooks.rmotr.com/ We know how hard it is to start working with Data Science tools: setting up local environment, installing dependencies, keeping projects organized, etc. RMOTR Notebooks has Jupyter Lab already preinstalled + the ability to upload datasets. Our platform is now open to everybody for free, and we are thinking about adding paid tiers in the future with better hardware, GPU support, pro features, etc. We've also worked on a…
2018
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