bash_kernel
yq
bash_kernel | yq | |
---|---|---|
5 | 66 | |
674 | 10,802 | |
- | - | |
5.0 | 9.2 | |
about 2 months ago | 10 days ago | |
Python | Go | |
BSD 3-clause "New" or "Revised" License | 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.
bash_kernel
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Runme – Interactive Runbooks Built with Markdown
For those who don't know, Jupyter has a bash kernel: https://github.com/takluyver/bash_kernel
And you can run Jupyter notebooks from the CLI with Ploomber: https://github.com/ploomber/ploomber
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Ask HN: Is there a Jupyter Notebook for terminal/shell
Something like this? https://github.com/takluyver/bash_kernel
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Simple Jupyter kernel for Crystal with 140 lines
I wrote a Crystal kernel for Jupyter, just a modified bash_kernel, 140 lines of code, but it was tiring because I don't have enough Python ability. icrystal is the widely used Jupyter kernel for Crystal, which uses ICR . On the other hand, this crystal_kernel uses the official crystal interpreter.
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SPyQL – SQL with Python in the Middle
Thank you! One of my main goals was making data processing in the command-line more accessible and intuitive. If you use a shell you can leverage an extensive array of tools. please take a look at the recipes in the Readme. The shell is many times underrated for data processing!
Right now you can use it in Jupiter Notebooks using a shell kernel like: https://github.com/takluyver/bash_kernel
On the mid-term, developing a spyql kernel is appealing because of syntax highlighting, code autocompleting, and more. But unless several people show interest on this, I should tackle other features first.
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How does your team organize/manage their runbooks?
I recently learned of jupyter+bash and it seemed like a step toward rundeck.
yq
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Show HN: Flatito, grep for YAML and JSON files
What I often use to just get the full key paths is yq (https://github.com/mikefarah/yq), piping into grep when necessary
yq -o=props
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Command line tools I always install on Ubuntu servers
For more information about this command visit https://github.com/mikefarah/yq
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Runtime error with plugin that uses io.popen to run executable during plugin startup
I've been trying to install and config a plugin (papis.nvim) for a couple of days and am having issues with a function that uses io.popen to run yq to convert yaml files to json. I know my install of yq is fine- I can run yq -oj info.yaml from the command line with no issue and it produces the correct json output. I know the function can find the yq executable, but it returns nil. I've saved the error from the yq golang code: panic: runtime error: invalid memory address or nil pointer dereference
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Jaq – A jq clone focused on correctness, speed, and simplicity
- yq has no if-then-else https://github.com/mikefarah/yq/issues/95 which is a poor design (or omission) in my opinion
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HTTPie Desktop: cross-platform API testing client for humans
After which, I use openapi-generator to make a yaml output.
https://gist.github.com/freshteapot/3637e8d2b5ecdf01b7d25246...
- yq version 3.4.1 (Worth noting, the example uses an out of date yq, so a few modifictaions might be needed)
https://github.com/mikefarah/yq
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jq 1.7
For those pining for a similar yaml query tool for working through acres of config: https://github.com/mikefarah/yq
jq is awesome and thanks to the new team for their recent efforts and energy, it massively appreciated.
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That's a Lot of YAML
For anyone looking for such a script, there's some CLIs that make it easy. One is `yq -o props` [1], another way is to use `yq -j` or `yj` [2] to convert to JSON and pipe it to `gron` [3].
[1] https://github.com/mikefarah/yq
[2] https://github.com/sclevine/yj
[3] https://github.com/tomnomnom/gron