ramda-cli
q
| ramda-cli | q | |
|---|---|---|
| 2 | 46 | |
| 571 | 10,126 | |
| - | - | |
| 0.0 | 2.1 | |
| over 1 year ago | 11 days ago | |
| LiveScript | Python | |
| ISC License | GNU General Public License v3.0 only |
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.
ramda-cli
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Zq: An Easier (and Faster) Alternative to Jq
Not quite that, but ramda-cli[1] which I've created solves this problem, at least for me, by offering the familiar set of functions from Ramda, and you can create pipelines with those to do operations on your data.
[1]: https://github.com/raine/ramda-cli
- Ramda vs. LiveScript
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
- Segítség kérés 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?
rb - Turns Ruby into a versatile command line utility
textql - Execute SQL against structured text like CSV or TSV
brackit - Query processor with proven optimizations, ready to use for your JSON store to query semi-structured data with JSONiq. Can also be used as an ad-hoc in-memory query processor.
csvq - SQL-like query language for csv
wsjq - Whitespace interpreter and debugger in jq
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
Ponzu - Headless CMS with automatic JSON API. Featuring auto-HTTPS from Let's Encrypt, HTTP/2 Server Push, and flexible server framework written in Go.
InquirerPy - :snake: Python port of Inquirer.js (A collection of common interactive command-line user interfaces)
nq - sed "s/jq .key/nq '({key}) => key'/"
xsv - A fast CSV command line toolkit written in Rust.
jp - Command line interface to JMESPath - http://jmespath.org
ledger - Double-entry accounting system with a command-line reporting interface