jupyterlite
q
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jupyterlite | q | |
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5 | 46 | |
88 | 10,109 | |
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8.9 | 3.6 | |
7 days ago | 3 months ago | |
TypeScript | Python | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 only |
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jupyterlite
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A fast SQLite PWA notebook for CSV files
This is really wonderful! The discussion about lay people's knowledge of sql reminded me that the Pandas API is often useful for non-sql folk. Likewise there are some projects similar to dirtylittlesql to bring Python data manipulation to the browser.
https://github.com/jtpio/jupyterlite
https://github.com/gzuidhof/starboard-notebook
- IPython running in your browser with JupyterLite
- jtpio/jupyterlite
- WASM powered Jupyter (notebook) running in the browser
q
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I wrote this iCalendar (.ics) command-line utility to turn common calendar exports into more broadly compatible CSV files.
CSV utilities (still haven't pick a favorite one...): https://github.com/harelba/q https://github.com/BurntSushi/xsv https://github.com/wireservice/csvkit https://github.com/johnkerl/miller
- SegĂtsĂ©g kĂ©rĂ©s Excel automatizáláshoz
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Show HN: ClickHouse-local – a small tool for serverless data analytics
I think they're talking about https://github.com/harelba/q, which is not very fast.
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sqly - execute SQL against CSV / JSON with shell
Apparently, there were many who thought the same thing; Tools to execute SQL against CSV were trdsql, q, csvq, TextQL. They were highly functional, hoewver, had many options and no input completion. I found it just a little difficult to use.
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Q – Run SQL Directly on CSV or TSV Files
Hi, author of q here.
Regarding the error you got, q currently does not autodetect headers, so you'd need to add -H as a flag in order to use the "country" column name. You're absolutely correct on failing-fast here - It's a bug which i'll fix.
In general regarding speed - q supports automatic caching of the CSV files (through the "-C readwrite" flag). Once it's activated, it will write the data into another file (with a .qsql extension), and will use it automatically in further queries in order to speed things considerably.
Effectively, the .qsql files are regular sqlite3 files (with some metadata), and q can be used to query them directly (or any regular sqlite3 file), including the ability to seamlessly join between multiple sqlite3 files.
http://harelba.github.io/q/#auto-caching-examples
- PostgreSQL alternative for Large amounts of data
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q VS trdsql - a user suggested alternative
2 projects | 25 Jun 2022
- One-liner for running queries against CSV files with SQLite
What are some alternatives?
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
textql - Execute SQL against structured text like CSV or TSV
Uno Platform - Build Mobile, Desktop and WebAssembly apps with C# and XAML. Today. Open source and professionally supported.
csvq - SQL-like query language for csv
ipycanvas - Interactive Canvas in Jupyter
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
TinyGo - Go compiler for small places. Microcontrollers, WebAssembly (WASM/WASI), and command-line tools. Based on LLVM.
InquirerPy - :snake: Python port of Inquirer.js (A collection of common interactive command-line user interfaces)
jupyterlab_templates - Support for jupyter notebook templates in jupyterlab
xsv - A fast CSV command line toolkit written in Rust.
datastation - App to easily query, script, and visualize data from every database, file, and API.
ledger - Double-entry accounting system with a command-line reporting interface