xc
bash_kernel
xc | bash_kernel | |
---|---|---|
9 | 5 | |
993 | 674 | |
- | - | |
7.2 | 5.0 | |
2 months ago | about 2 months ago | |
Go | Python | |
MIT License | BSD 3-clause "New" or "Revised" 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.
xc
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Runme – Interactive Runbooks Built with Markdown
Nice!
Xc is another doing a similar job
https://xcfile.dev/
- Self-documenting task runner, define tasks in the README
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Can you help me make my makefile for go projects better or suggest an alternative?
For task management, I like to use xc instead of a Makefile. https://github.com/joerdav/xc
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Show HN: Xc – A Markdown Defined Task Runner
I had exactly the same idea regarding ```python fences. I filed an issue if you wanna give it a thumbs up: https://github.com/joerdav/xc/issues/42
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.
What are some alternatives?
taskflow - Create build pipelines in Go [Moved to: https://github.com/goyek/goyek]
icr - Interactive console for Crystal programming language
runme - DevOps Workflows Built with Markdown
spyql - Query data on the command line with SQL-like SELECTs powered by Python expressions
mage - a Make/rake-like dev tool using Go
crystal_kernel - Python wrapper kernel for Crystal
Task - A task runner / simpler Make alternative written in Go
yq - yq is a portable command-line YAML, JSON, XML, CSV, TOML and properties processor
jsonata-playbook - practical examples of jsonata [go-jsonata 1.5.4]
Gauge - Light weight cross-platform test automation
livebook - Automate code & data workflows with interactive Elixir notebooks