trdsql
xsv
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trdsql
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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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Run SQL on CSV, Parquet, JSON, Arrow, Unix Pipes and Google Sheet
Nice! Kinds of reminds me of trdsql
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What is the most user friendly way to upload CSV files into a SQL database?
trdsql(https://github.com/noborus/trdsql) is a tool that executes SQL for files such as CSV, but it can also be used by connecting to MySQL. Therefore, SQL such as CREATE TABLE table AS SELECT * FROM csvfile.csv can also be executed.
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textql VS trdsql - a user suggested alternative
2 projects | 25 Jun 2022
trdsql can execute SQL against CSV, LTSV, JSON and TBLN, and the database can also use SQLite,PostgreSQL and MySQL.
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q VS trdsql - a user suggested alternative
2 projects | 25 Jun 2022
trdsql can execute SQL against CSV, LTSV, JSON and TBLN, and the database can also use SQLite,PostgreSQL and MySQL.
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One-liner for running queries against CSV files with SQLite
Check out https://github.com/noborus/trdsql
- trdsql: CLI tool that can execute SQL queries on CSV, LTSV, JSON and TBLN
- Show HN: Trdsql – CLI tool that can execute SQL queries on CSV, LTSV, JSON
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If you want to run SQL queries on CSV files from the command line without installing/opening any DBMS software, use CSVKIT
The trdsql I made is feature-rich and fast (as a similar SQL tool).
xsv
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Show HN: TextQuery – Query and Visualize Your CSV Data in Minutes
I realize it's not really that comparable since these tools don't support SQL, but a more fully functioned CLI tool is - https://github.com/BurntSushi/xsv
They are both fairly good
- Qsv: Efficient CSV CLI Toolkit
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Joining CSV Data Without SQL: An IP Geolocation Use Case
I have done some similar, simpler data wrangling with xsv (https://github.com/BurntSushi/xsv) and jq. It could process my 800M rows in a couple of minutes (plus the time to read it out from the database =)
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Qsv: CSVs sliced, diced and analyzed (fork of xsv)
xsv, which seems to be why qsv was created.
[1] https://github.com/BurntSushi/xsv/issues/267
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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
- Icsp – Command-line iCalendar (.ics) to CSV parser
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ripgrep is faster than {grep, ag, git grep, ucg, pt, sift}
$ git remote -v origin [email protected]:rust-lang/rust (fetch) origin [email protected]:rust-lang/rust (push) $ git rev-parse HEAD 3b0d4813ab461ec81eab8980bb884691c97c5a35 $ time grep -ri burntsushi ./ ./src/tools/cargotest/main.rs: repo: "https://github.com/BurntSushi/ripgrep", ./src/tools/cargotest/main.rs: repo: "https://github.com/BurntSushi/xsv", grep: ./target/debug/incremental/cargotest-2dvu4f2km9e91/s-gactj3ma2j-1b10l4z-2l60ur55ixe6n/query-cache.bin: binary file matches grep: ./target/debug/incremental/cargotest-38cpmhhbdgdyq/s-gactj3luwq-1o12vgp-t61hd8qdyp7t/query-cache.bin: binary file matches grep: ./target/debug/incremental/cargotest-17632op6djxne/s-gawuq5468i-1h69nfw-4gm0s8yhhiun/query-cache.bin: binary file matches grep: ./target/debug/incremental/cargotest-2trm4kt5yom3r/s-gawuq53qqg-bjiezj-lo0gha8ign8w/query-cache.bin: binary file matches grep: ./target/debug/deps/libregex_automata-c74a6d9fd0abd77b.rmeta: binary file matches grep: ./target/debug/deps/libsame_file-a0e0363a2985455d.rlib: binary file matches grep: ./target/debug/deps/libsame_file-a0e0363a2985455d.rmeta: binary file matches grep: ./target/debug/deps/libsame_file-7251d8d3586a319b.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-sysroot/lib/rustlib/x86_64-unknown-linux-gnu/lib/libaho_corasick-999a08e2b700420d.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-sysroot/lib/rustlib/x86_64-unknown-linux-gnu/lib/libregex_automata-0d168be5d25b3ac5.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libregex_automata-7d6bec0156f15da1.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libregex_automata-7d6bec0156f15da1.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-07dee4514b87d99b.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-07dee4514b87d99b.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-999a08e2b700420d.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-999a08e2b700420d.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libregex_automata-0d168be5d25b3ac5.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libregex_automata-0d168be5d25b3ac5.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libaho_corasick-992e1ba08ef83436.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libignore-54d41239d2761852.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libsame_file-9a5e3ddd89cfe599.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libregex_automata-8e700951c9869a66.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libignore-54d41239d2761852.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libaho_corasick-992e1ba08ef83436.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libregex_automata-8e700951c9869a66.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libsame_file-9a5e3ddd89cfe599.rmeta: binary file matches real 16.683 user 15.793 sys 0.878 maxmem 8 MB faults 0
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Any Linux admins willing to try Pygrep?
Unrelated, are you the same burntsushi that wrote xsv?
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Analyzing multi-gigabyte JSON files locally
If it could be tabular in nature, maybe convert to sqlite3 so you can make use of indexing, or CSV to make use of high-performance tools like xsv or zsv (the latter of which I'm an author).
https://github.com/BurntSushi/xsv
https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql...
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What monitoring tool do you use or recommend?
Oh and there's rad cli shit out there for CSV files too, like xsv
What are some alternatives?
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
csvtk - A cross-platform, efficient and practical CSV/TSV toolkit in Golang
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
miller - Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON
gsheet - gsheet is a CLI tool (and Golang package) for piping csv data to and from Google Sheets
ripgrep - ripgrep recursively searches directories for a regex pattern while respecting your gitignore
grafana-sqlite-datasource - Grafana Plugin to enable SQLite as a Datasource
Servo - Servo, the embeddable, independent, memory-safe, modular, parallel web rendering engine
usql - Universal command-line interface for SQL databases
Fractalide - Reusable Reproducible Composable Software
json-watch - A small cli tool for monitoring JSON data for new items
svgcleaner - svgcleaner could help you to clean up your SVG files from the unnecessary data.