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Dev tools · alternatives · 2026

24 alternatives to DSAlgo

Data Structures and Algorithms concepts and solutions.

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. DSAlgo launched in 2023; newer entries below may have overtaken it.

  1. 1

    🥞Data Structures and Algorithms explained and implemented in JavaScript + eBook - amejiarosario/dsa.js-data-structures-algorithms-javascript

    2019 · github.com · its alternatives →

  2. 2

    🥞Data Structures and Algorithms explained and implemented in JavaScript + eBook - amejiarosario/dsa.js-data-structures-algorithms-javascript

    2019 · github.com · its alternatives →

  3. 3

    Problem Solving. Contribute to sangupta/ps development by creating an account on GitHub.

    2016 · github.com · its alternatives →

  4. 4DA

    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 →

  5. 5

    A container for dataclasses with multi-indexing and bulk operations. - joshlk/dataclassframe

    2020 · github.com · its alternatives →

  6. 6NL

    Link: https://www.nlpdemystified.org/ Hi HN: After a year of work, I've published my free NLP course. The course helps anyone who knows Python and a bit of math go from the basics to today's mainstream models and frameworks. I strive to balance theory and practice, so every module consists of detailed explanations and slides along with a Colab notebook putting the ideas into practice (in most modules). The notebooks cover how to accomplish everyday NLP tasks including extracting key information, document search, text similarity, text classification, finding topics in…

    2022 · its alternatives →

  7. 7

    Visual explanations of Algorithms and Data structures

    2020 · chrislaux.com · its alternatives →

  8. 8DA
  9. 9

    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 →

  10. 10

    Hi HN: I published part one of my free NLP course. The course is intended to help anyone who knows Python and a bit of math go from the very basics all the way to today's mainstream models and frameworks. I strive to balance theory and practice and so every module consists of detailed explanations and slides along with a Colab notebook (in most modules) putting the theory into practice. In part one, we cover text preprocessing, how to turn text into numbers, and multiple ways to classify and search text using "classical" approaches. And along the way, we'll pick up useful bits on how to use…

    2022 · nlpdemystified.org · its alternatives →

  11. 11

    An on-disk B+tree for Python 3. Contribute to NicolasLM/bplustree development by creating an account on GitHub.

    2018 · github.com · its alternatives →

  12. 12

    Python library for creating data pipelines with chain functional programming - EntilZha/PyFunctional

    2017 · github.com · its alternatives →

  13. 13

    Hey HN – Stefan and Elijah here from DAGWorks (http://dagworks.io/, YC W23). If you don’t remember us from our previous HN launch (https://news.ycombinator.com/item?id=35056903), we’re the authors of Hamilton (https://github.com/dagworks-inc/hamilton), an open-source library for building self-documenting, modular dataflows in python that works for data, ML, LLM pipelines, & even web-workflows. We’ve been developing this UI for a while and we’re excited to say we open-sourced it! It comes out of the box with the following capabilities, and…

    2024 · github.com · its alternatives →

  14. 14

    The data community's workbench

    2018 · its alternatives →

  15. 15

    Like a Python list but better. Contribute to Lauriat/funct development by creating an account on GitHub.

    2021 · github.com · its alternatives →

  16. 16

    teaching data structures and algorithms to web engineers - j4orz/iruka

    2020 · github.com · its alternatives →

  17. 17

    Computer Science Data Structures and Algorithms in JavaScript ( Node.JS, ES ) in simple, clean, reusable code - crisdosaygo/cs.js

    2021 · github.com · its alternatives →

  18. 18

    Data Science and Python, starting at zero

    2015 · joelgrus.com · its alternatives →

  19. 19

    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…

    2022 · github.com · its alternatives →

  20. 20DC
  21. 21

    Learn data structures and algorithms

    2025 · its alternatives →

  22. 22

    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…

    2024 · github.com · its alternatives →

  23. 23DS
  24. 24

    Play with data structures and algorithms

    2025 · dsalgolabs.com · 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 →