miller
gdu
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miller | gdu | |
---|---|---|
63 | 37 | |
8,553 | 3,255 | |
- | - | |
9.1 | 8.9 | |
6 days ago | 3 days ago | |
Go | Go | |
GNU General Public License v3.0 or later | MIT License |
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.
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
gdu
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Go: What We Got Right, What We Got Wrong
Not sure these are really popular, but I cannot resist advertising a few utilities written in Go that I regularly use in my daily workflow:
- gdu: a NCDU clone, much faster on SSD mounts [1]
- duf: a `df` clone with a nicer interface [2]
- massren: a `vidir` clone (simpler to use but with fewer options) [3]
- gotop: a `top` clone [4]
- micro: a nice TUI editor [5]
Building this kind of tools in Go makes sense, as the executables are statically compiled and are thus easy to install on remote servers.
[1]: https://github.com/dundee/gdu
[2]: https://github.com/muesli/duf
[3]: https://github.com/laurent22/massren
[4]: https://github.com/xxxserxxx/gotop
[5]: https://github.com/zyedidia/micro
- Gdu – fast disk usage analyzer with console interface written in Go
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Clean mount lists in Linux
For anyone that likes ncdu I would highly recommend gdu. https://github.com/dundee/gdu
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new and interesting file managers or text editors for the cli lately?
gdu is faster
- How to report on usage?
- Why does macOS keep a cache of every wallpaper ever used?
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Midnight Commander is MIA; any command line based twin pane file manager recommendations?
gdu - Just a very fast and cool disk usage explorer
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RPCS3 compile to SD card?
The RPCS3 flatpak lives in /home/deck/.var/app/net.rpcs3.RPCS3. I'd advise you to install a tool like gdu or use something like du -h --max-depth=1 in the console in that directory, to find where the disk usage goes. There are also GUI tools, but I prefer these myself.
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Ncdu – NCurses Disk Usage
While ncdu does the job I've found gdu (similar tool written in Go) significantly faster for larger directories.
https://github.com/dundee/gdu
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Why can i not resize my main partition? I’m running out of space and have no idea why
There's also gdu, which is much faster on SSDs.
What are some alternatives?
visidata - A terminal spreadsheet multitool for discovering and arranging data
higgs - A tiny cross-platform Go library to hide/unhide files and directories
xsv - A fast CSV command line toolkit written in Rust.
duf - Disk Usage/Free Utility - a better 'df' alternative
jq - Command-line JSON processor [Moved to: https://github.com/jqlang/jq]
pathtype - Add a type for paths in Go.
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.
modern-unix - A collection of modern/faster/saner alternatives to common unix commands.
csvtk - A cross-platform, efficient and practical CSV/TSV toolkit in Golang
diskonaut - Terminal disk space navigator 🔭
yq - yq is a portable command-line YAML, JSON, XML, CSV, TOML and properties processor
todotxt - Parser for todo.txt files in Go ✅