wsjq
q
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| wsjq | q | |
|---|---|---|
| 2 | 46 | |
| 13 | 10,109 | |
| - | - | |
| 6.8 | 3.6 | |
| about 1 month ago | 3 months ago | |
| jq | Python | |
| Mozilla Public License 2.0 | GNU General Public License v3.0 only |
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wsjq
- Zq: An Easier (and Faster) Alternative to Jq
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An Introduction to JQ
jq is unsurprisingly Turing complete, so I wrote a Whitespace interpreter[0] in jq. It is able to handle real-time I/O by requesting lines on-demand from stdin, which is the main input source, with `input` and outputting strings in a stream.
With a relatively large jq program like that, it is critical that the main recursive loop run efficiently, so it's annoying that there's no way to detect whether tail call optimization was applied, other than benchmarking. It would also be nice if object values were lazily evaluated so that it would be possible to create ad hoc switches.
[0]: https://github.com/andrewarchi/wsjq
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?
kubectl-jq - Kubectl plugin that works like "kubectl get" but runs everything through a JQ program you provide
textql - Execute SQL against structured text like CSV or TSV
rb - Turns Ruby into a versatile command line utility
csvq - SQL-like query language for csv
json-logs - A tool to pretty-print JSON logs, like those from zap or logrus.
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
howto - Documenting useful things, lest I forget, and sharing is caring
InquirerPy - :snake: Python port of Inquirer.js (A collection of common interactive command-line user interfaces)
gron - Make JSON greppable!
xsv - A fast CSV command line toolkit written in Rust.
jid - json incremental digger
ledger - Double-entry accounting system with a command-line reporting interface