Dev tools · alternatives · 2026
24 alternatives to Visions – User defined data type systems
Visions is a python library for working with user defined data type systems. Out of the box, it provides type inference and automated data cleaning of sequence data with backend specific implementations for pandas, spark, python, and numpy. We often use it as a first pass cleaning step when working with tabular data and to simplify the backend logic of both pandas-profiling[1] and our tabular data compression library compressio[2]. Because data types are user defined, we can build user customizable libraries based around types without adding code complexity. In the case of compressio that…
Visions is a Python library that enables type inference and automated data cleaning for sequence data across pandas, Spark, Python, and NumPy backends. It uses user-defined data type systems to simplify tabular data… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Visions – User defined data type systems launched in 2022; newer entries below may have overtaken it.
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A container for dataclasses with multi-indexing and bulk operations. - joshlk/dataclassframe
2020 · github.com · its alternatives →
- 2
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 · its alternatives →
- 3
Hello! I'm James and I am working on VisionScript. With VisionScript, I want to empower people -- including everyone without any prior programming experience -- to build cool apps with vision. This weekend, I recorded a demo for VisionScript, in which I made apps that count how many cats are in an image and hides people in a video. Each app was < 10 lines of code. https://vimeo.com/856043804 VisionScript is built for the 10 year old inside of me who would have loved more visual programming languages with which to play. I want to show people the potential of programming and how…
2023 · github.com · its alternatives →
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Like a Python list but better. Contribute to Lauriat/funct development by creating an account on GitHub.
2021 · github.com · its alternatives →
- 6
Hi HN, We're Anna, Adrian, Marcin and Matt, developers of dlt. dlt is an open source library to automatically create datasets out of messy, unstructured data sources. You can use the library to move data from about anywhere into most of well known SQL and vector stores, data lakes, storage buckets, or local engines like DuckDB. It automates many cumbersome data engineering tasks and can by handled by anyone who knows Python. Here’s our Github: https://github.com/dlt-hub/dlt Here’s our Colab demo:…
2023 · colab.research.google.com · its alternatives →
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Hi HN, Over the past few months, I've been building `dsc`, a tensor library from scratch in C++/CUDA. My main focus has been on getting the basics right, prioritizing a clean API, simplicity, and clear observability for running small LLMs locally. The key features are: - C++ core with CUDA support written from scratch. - A familiar, PyTorch-like Python API. - Runs real models: it's complete enough to load a model like Qwen from HuggingFace and run inference on both CUDA and CPU with a single line change[1]. - Simple, built-in observability for both Python and C++. Next on the roadmap is…
2025 · github.com · its alternatives →
- 8
I am excited to announce the release of TabPFN v2, a tabular foundation model that delivers state-of-the-art predictions on small datasets in just 2.8 seconds for classification and 4.8 seconds for regression compared to strong baselines tuned for 4 hours. Published in Nature, this model outperforms traditional methods on datasets with up to 10,000 samples and 500 features. The model is available under an open license: a derivative of the Apache 2 license with a single modification, adding an enhanced attribution requirement inspired by the Llama 3 license:…
2025 · nature.com · its alternatives →
- 9DA
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 · its alternatives →
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Hey all, I just released v2.0.0 of FilterQL, a query language and TypeScript library. This version adds support for Operations, which allow you to transform the data after filtering. If you think this would be useful in a project you're working on, give it a try and let me know what you think!
2025 · github.com · its alternatives →
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Python library for creating data pipelines with chain functional programming - EntilZha/PyFunctional
2017 · github.com · its alternatives →
- 12BA
2019 · bamboolib.com · its alternatives →
- 13DD
Gleb, Alex, Erez and Simon here – we are building an open-source tool for comparing data within and across databases at any scale. The repo is at https://github.com/datafold/data-diff, and our home page is https://datafold.com/. As a company, Datafold builds tools for data engineers to automate the most tedious and error-prone tasks falling through the cracks of the modern data stack, such as data testing and lineage. We launched two years ago with a tool for regression-testing changes to ETL code…
2022 · its alternatives →
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A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile - target/matrixprofile-ts
2019 · github.com · its alternatives →
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:panda_face: Bringing the python data stack to the shell prompt - robdmc/pandashells
2015 · github.com · its alternatives →
- 16AV
2021 · all.vision · its alternatives →
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A grid library for instant big data processing
2022 · datatable.dev · its alternatives →
- 18DC
2016 · datasets.co · its alternatives →
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A scalable general purpose micro-framework for defining dataflows. THIS REPOSITORY HAS BEEN MOVED TO www.github.com/dagworks-inc/hamilton - stitchfix/hamilton
2021 · github.com · its alternatives →
- 20SA
Hi HN, I’m Tullie, founder of Shaped. Previously, I was a researcher at Meta AI, worked on ranking for Instagram Reels, and was a contributor to PyTorch Lightning. We built ShapedQL because we noticed that while retrieval (finding 1,000 items) has been commoditized by vector DBs, ranking (finding the best 10 items) is still an infrastructure problem. To build a decent for you feed or a RAG system with long-term memory, you usually have to put together a vector DB (Pinecone/Milvus), a feature store (Redis), an inference service, and thousands of lines of Python to handle business logic…
Jan 2026 · playground.shaped.ai · its alternatives →
- 21HA
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 · its alternatives →
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This C library is part of a main project aimed at providing a reactive key-value (KV) database. The data is typed (numbers, strings, dates, or booleans) and can include formulas with references to other entries. Clients connected to this database receive a real-time data stream with updates to the subscribed keys, allowing them to react to changes and their dependencies. Essentially, it’s like building a distributed Excel, where data and formulas dynamically update across the system. I couldn’t find any libraries that offered the full set of features I needed for evaluating expressions, so I…
2024 · github.com · its alternatives →
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Python stream processing for humans. Contribute to omegaml/minibatch development by creating an account on GitHub.
2020 · github.com · its alternatives →
- 24
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 →
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