howto
miller
| howto | miller | |
|---|---|---|
| 1 | 63 | |
| 38 | 8,559 | |
| - | - | |
| 0.0 | 9.0 | |
| almost 4 years ago | 7 days ago | |
| Go | ||
| - | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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howto
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An Introduction to JQ
If there's an API for working with data that you know well already, it's somewhat pointless to learn the (quite esoteric) jq one.
Just pipe curl to node (https://github.com/jareware/howto/blob/master/Replacing%20jq...) or Python or Ruby or whatever you already know!
miller
- Qsv: Efficient CSV CLI Toolkit
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jq 1.7 Released
jq and miller[1] are essential parts of my toolbelt, right up there with awk and vim.
[1]: https://github.com/johnkerl/miller
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Perl first commit: a “replacement” for Awk and sed
> This works really well if your problem can be solved in one or two liners.
My personal comfort threshold is around the 100-line mark. It's even possible to write maintainable shell scripts up to 500 lines, but it mostly depends on the problem you're trying to solve, and the discipline of the programmer to follow best practices (use sane defaults, ShellCheck, etc.).
> It go bad very quickly when, say, you have two CSV files and want to join them the sql-way.
In that case we're talking about structured data, and, yeah, Perl or Python would be easier to work with. That said, depending on the complexity of the CSV, you can still go a long way with plain Bash with IFS/read(1) or tr(1) to split CSV columns. This wouldn't be very robust, but there are tools that handle CSV specifically[1], which can be composed in a shell script just fine.
So it's always a balancing act of being productive quickly with a shell script, or reaching out for a programming language once the tools aren't a good fit, or maintenance becomes an issue.
[1]: https://miller.readthedocs.io/
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Need help on cleaning this data!!
where mlr is from https://github.com/johnkerl/miller
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Running weekly average
if this class of problems (i.e., csv/tsv data) is your main target you may find miller (https://github.com/johnkerl/miller) much more useful in the long run
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GQL: A new SQL like query language for .git files written in Rust
That said, you may be interested in Miller (https://github.com/johnkerl/miller) which provides similar capabilities for CSV, JSON, and XML files. It doesn't use a SQL grammar, but that's just the proverbial lipstick on the thing. I'm not the author, but I have used it and I see some parallels in use cases at the very least.
- johnkerl/miller: Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON
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Any cli utility to create ascii/org mode tables?
worth giving Miller a shot
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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
- Miller: Like Awk, sed, cut, join, and sort for CSV, TSV, and tabular JSON
What are some alternatives?
kubectl-jq - Kubectl plugin that works like "kubectl get" but runs everything through a JQ program you provide
visidata - A terminal spreadsheet multitool for discovering and arranging data
wsjq - Whitespace interpreter and debugger in jq
xsv - A fast CSV command line toolkit written in Rust.
json-logs - A tool to pretty-print JSON logs, like those from zap or logrus.
jq - Command-line JSON processor [Moved to: https://github.com/jqlang/jq]
jiq - jid on jq - interactive JSON query tool using jq expressions
dasel - Select, put and delete data from JSON, TOML, YAML, XML and CSV files with a single tool. Supports conversion between formats and can be used as a Go package.
fx - Terminal JSON viewer & processor
csvtk - A cross-platform, efficient and practical CSV/TSV toolkit in Golang
gron - Make JSON greppable!
yq - yq is a portable command-line YAML, JSON, XML, CSV, TOML and properties processor