sq
textql
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sq
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Show HN: I built jq-like scriptable tool to query CSV and JSON with SQLite
Is this related to the other SQ? https://github.com/neilotoole/sq
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Best way to introduce a linter?
For my main OSS project, sq, its .golangci.yml is a lightly customized version of this gist from maratori. I found it to be a good starting point.
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Go port of SQLite without CGo
Thankfully I no longer need to maintain xcgo, but even today, the sq pipeline is still complex with lots of platform-dependent bits.
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Beginner interested in learning SQL. Have a few question that I wasn’t able to find on google.
Through more magic, you COULD of course use stuff like Spark, or easier with programs like TextQL, sq, OctoSQL.
- sq: swiss-army knife for data
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sq: swiss-army knife to inspect, query, join, import, and export data
Available on Git? Absolutely. https://github.com/neilotoole/sq
textql
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Jaq – A jq clone focused on correctness, speed, and simplicity
I like textql [0] better for this use case, as it's simpler in my mind.
[0] https://github.com/dinedal/textql
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Can SQL be used without an RDBMS?
Primarily, you are right. SQL is for working with structured data and that largely covers RDBs. However, there are tools (like textql) that allow you to query CSV files and the effort works with most other text files that have some kind of structure.
- Textql: Execute SQL against structured text like CSV or TSV
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Show HN: ClickHouse-local – a small tool for serverless data analytics
As the author of textql ( https://github.com/dinedal/textql ) - thanks for the shoutout!
Looks great, I love more options in the space for CLI based data analysis tools! Fantastic work!
- Using Commandline To Process CSV files
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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
Reminds me of the textQL extension that's available in Asciidoc.
Point it to an external CSV file, enable TextQL, and bam, there's your query returned as a table. Handy for parts lists, inventory, that kind of crap.
https://github.com/dinedal/textql
https://gist.github.com/mojavelinux/8856117
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Beginner interested in learning SQL. Have a few question that I wasn’t able to find on google.
Through more magic, you COULD of course use stuff like Spark, or easier with programs like TextQL, sq, OctoSQL.
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textql VS trdsql - a user suggested alternative
2 projects | 25 Jun 2022
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Xlite: Query Excel, Open Document spreadsheets (.ods) as SQLite virtual tables
Somewhat-kinda related, the textql extension for Asciidoctor is so dang useful it should be in core.
https://gist.github.com/mojavelinux/8856117
I use this as a "centralized parts repository" for big ol' maintenance manuals. Refresh from PDM/PLM/LSA/Whatever. Rebuild for new parts data.
Built on TextQL, natch
https://github.com/dinedal/textql
What are some alternatives?
unioffice - Pure go library for creating and processing Office Word (.docx), Excel (.xlsx) and Powerpoint (.pptx) documents
q - q - Run SQL directly on delimited files and multi-file sqlite databases
omniparser - omniparser: a native Golang ETL streaming parser and transform library for CSV, JSON, XML, EDI, text, etc.
go-duckdb - go-duckdb provides a database/sql driver for the DuckDB database engine.
csvdecoder - Go library for parsing and deserialising CSV files into Go objects
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
csv-sql - Command-line tool to load csv and excel (xlsx) files and run sql commands
cq - Query CSVs using SQL
dsq - Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.
querycsv - QueryCSV enables you to load CSV files and manipulate them using SQL queries then after you finish you can export the new values to a CSV file
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.