icr
bash_kernel
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| icr | bash_kernel | |
|---|---|---|
| 2 | 5 | |
| 500 | 672 | |
| 0.4% | - | |
| 1.8 | 5.0 | |
| over 2 years ago | about 1 month ago | |
| Crystal | 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.
icr
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Crystal's Interpreter (2021)
it's had an IRB-like REPL for years. It just wasn't built into the language. Admittedly it was limited compared to IRB but it was more than enough to test out quick ideas.
It's called ICR: Interactive Crystal
https://github.com/crystal-community/icr
the first release was back in 2017
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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.
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?
crystal_kernel - Python wrapper kernel for Crystal
spyql - Query data on the command line with SQL-like SELECTs powered by Python expressions
ChakraCore - ChakraCore is an open source Javascript engine with a C API.
charly - 🐈 The Charly Programming Language | Written by @KCreate
yq - yq is a portable command-line YAML, JSON, XML, CSV, TOML and properties processor
fancyline - Readline-esque library with fancy features
runme - DevOps Workflows Built with Markdown
FrameworkBenchmarks - Source for the TechEmpower Framework Benchmarks project
xc - Markdown defined task runner.
kemal - Fast, Effective, Simple Web Framework
livebook - Automate code & data workflows with interactive Elixir notebooks