|about 23 hours ago||7 days ago|
|Apache License 2.0||Apache License 2.0|
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Open source Business intelligence platform made with Python
7 projects | news.ycombinator.com | 28 Nov 2021
Rows.com: Spreadsheets on Steroids
5 projects | news.ycombinator.com | 10 Nov 2021
Standalone Python virtual server example https://github.com/finos/perspective/tree/master/examples/to...
JupyterLab demo on Binder https://mybinder.org/v2/gh/finos/perspective/master?urlpath=...
DuckDB-WASM: Efficient Analytical SQL in the Browser
2 projects | news.ycombinator.com | 29 Oct 2021
Show HN: Vizzu – Open-source charting library focused on animating charts
5 projects | news.ycombinator.com | 17 Oct 2021
The best example of WASM being used to render to canvas (it's also visualizations) I've seen is "Perspective":
"Perspective is an interactive analytics and data visualization component, which is especially well-suited for large and/or streaming datasets. Originally developed at J.P. Morgan and open-sourced through the Fintech Open Source Foundation (FINOS), Perspective makes it simple to build user-configurable analytics entirely in the browser, or in concert with Python and/or Jupyterlab. Use it to create reports, dashboards, notebooks and applications, with static data or streaming updates via Apache Arrow."
Open Source Is Finally Coming to Financial Services
3 projects | news.ycombinator.com | 15 Oct 2021
Man the a16z marketing machine is working hard unfortunately at cost of quality.
For those interested in FS and open source today, especially with a capital markets lens check out:
Lots of great projects, one I used recently and a favourite was this:
Perspective 1.0.0, an open source BI tool built on WebAssembly
2 projects | reddit.com/r/programming | 15 Oct 2021
As far as customizing the Perspective datagrid, the story on this is evolving :) . With the 1.0 release, we've released an NFT demo with a more current version of the plugin API, as well as new plugin API docs. Replacing innerHTML is only costly if you trigger a relayout before the replacement, which you'd want to avoid - check the pudgy-penguins demo source for examples which replaces these with without the intermediate DOM tree being rendered (though this is brower-dependent). If you can't, e.g. the replacement is async or whatever, the underlying regular-table component has an API that allows you to return the DOM elements themselves per cell, but you'd need to write a simple plugin to integrate this as Perspective's version provides its own dataListener.2 projects | reddit.com/r/programming | 15 Oct 2021
2 projects | reddit.com/r/Python | 13 Oct 2021
By the way, the link to the blog on the project website results in a 404.2 projects | reddit.com/r/Python | 13 Oct 2021
1 project | news.ycombinator.com | 13 Oct 2021
pigeon-rs: Open source email automation written in Rust
5 projects | reddit.com/r/rust | 20 Nov 2021
Connectorx is using arrow2 data format for fetching from a database. This data format is optimized for columnar data :
Introducing tidypolars - a Python data frame package for R tidyverse users
9 projects | reddit.com/r/rstats | 10 Nov 2021
I think having a basic understanding of pandas, given how broadly it's used, is beneficial. That being said, polars seems to be matching or beating data.table in performance, so I think it'd be very worth it to take it up. Wes McKinney, creator of pandas, has been quite vocal about architecture flaws of pandas -- which is why he's been working on the Arrow project. polars is based on Arrow, so in principle it's kinda like pandas 2.0 (adopting the changes that Wes proposed).9 projects | reddit.com/r/rstats | 10 Nov 2021
So the question is really - how is polars so fast? Polars is packed by Apache Arrow, which is a columnar memory format that is designed specifically for performance.
Comparing SQLite, DuckDB and Arrow
5 projects | news.ycombinator.com | 27 Oct 2021
The Data Engineer Roadmap 🗺
12 projects | dev.to | 19 Oct 2021
C++ Jobs - Q4 2021
4 projects | reddit.com/r/cpp | 2 Oct 2021
Technologies: Apache Arrow, Flatbuffers, C++ Actor Framework, Linux, Docker, Kubernetes
How to use Spark and Pandas to prepare big data
3 projects | dev.to | 21 Sep 2021
Pandas user-defined function (UDF) is built on top of Apache Arrow. Pandas UDF improves data performance by allowing developers to scale their workloads and leverage Panda’s APIs in Apache Spark. Pandas UDF works with Pandas APIs inside the function, and works with Apache Arrow to exchange data.
2 projects | reddit.com/r/rust | 7 Sep 2021
arrow-odbc allows you to iterate over an ODBC data source as sequence of Apache Arrow record batches.
CuVec: Unifying Python/C++/CUDA memory
2 projects | news.ycombinator.com | 18 Jul 2021
IIRC Apache Arrow  promised similar goal and it seems covers CUDA as well . I wonder how these relates in the big picture. This one seems much simpler than arrow, which is probably a good thing in terms of the differentiation?
Recommendation for a Database for analysis
5 projects | reddit.com/r/algotrading | 13 May 2021
What you need for your use case is a column-oriented store. I recommend explore bcolz or apache arrow for a column file-based systems. These are very fast, support memory mapping, uses compression and SSD speed (and even CPU architecture, in case of arrow) optimally almost out of the box, and has good interfaces to Numpy and Pandas (in case you are using Python for final data consumption and analysis). The columnar structure makes it easy to add or delete a column easily (or even dynamically). If you need a more scalable (albeit at the cost of speed) solution, you can devise a schema over a regular columnar db or an nosql db - see arctic from Man group for an example.
What are some alternatives?
h5py - HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format.
polars - Fast multi-threaded DataFrame library in Rust and Python
arquero - Query processing and transformation of array-backed data tables.
ta-lib - Python wrapper for TA-Lib (http://ta-lib.org/).
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Apache HBase - Apache HBase
spark-rapids - Spark RAPIDS plugin - accelerate Apache Spark with GPUs
arrow-rs - Official Rust implementation of Apache Arrow
docker - These are the official Dockerfiles for https://github.com/orgs/tripl-ai/packages
Arrow.jl - Pure Julia implementation of the apache arrow data format (https://arrow.apache.org/)
cylon - Cylon is a fast, scalable, distributed memory, parallel runtime with a Pandas like DataFrame.