Kedro
tmux
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Kedro | tmux | |
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29 | 208 | |
9,353 | 32,923 | |
1.5% | 2.2% | |
9.7 | 8.3 | |
9 days ago | 14 days ago | |
Python | C | |
Apache License 2.0 | 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.
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.
Kedro
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Nextflow: Data-Driven Computational Pipelines
Interesting, thanks for sharing. I'll definitely take a look, although at this point I am so comfortable with Snakemake, it is a bit hard to imagine what would convince me to move to another tool. But I like the idea of composable pipelines: I am building a tool (too early to share) that would allow to lay Snakemake pipelines on top of each other using semi-automatic data annotations similar to how it is done in kedro (https://github.com/kedro-org/kedro).
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A Polars exploration into Kedro
# pyproject.toml [project] dependencies = [ "kedro @ git+https://github.com/kedro-org/kedro@3ea7231", "kedro-datasets[pandas.CSVDataSet,polars.CSVDataSet] @ git+https://github.com/kedro-org/kedro-plugins@3b42fae#subdirectory=kedro-datasets", ]
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What are some open-source ML pipeline managers that are easy to use?
So there's 2 sides to pipeline management: the actual definition of the pipelines (in code) and how/when/where you run them. Some tools like prefect or airflow do both of them at once, but for the actual pipeline definition I'm a fan of https://kedro.org. You can then use most available orchestrators to run those pipelines on whatever schedule and architecture you want.
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How do data scientists combine Kedro and Databricks?
We have set up a milestone on GitHub so you can check in on our progress and contribute if you want to. To suggest features to us, report bugs, or just see what we're working on right now, visit the Kedro projects on GitHub.
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How do you organize yourself during projects?
you could use a project framework like kedro to force you to be more disciplined about how you structure your projects. I'd also recommend checking out this book: Edna Ridge - Guerrilla Analytics: A Practical Approach to Working with Data
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Futuristic documentation systems in Python, part 1: aiming for more
Recently I started a position as Developer Advocate for Kedro, an opinionated data science framework, and one of the things we're doing is exploring what are the best open source tools we can use to create our documentation.
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Python projects with best practices on Github?
You can also check out Kedro, it’s like the Flask for data science projects and helps apply clean code principles to data science code.
- Data Science/ Analyst Zertifikate für den Job Markt?
- What are examples of well-organized data science project that I can see on Github?
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Dabbling with Dagster vs. Airflow
An often overlooked framework used by NASA among others is Kedro https://github.com/kedro-org/kedro. Kedro is probably the simplest set of abstractions for building pipelines but it doesn't attempt to kill Airflow. It even has an Airflow plugin that allows it to be used as a DSL for building Airflow pipelines or plug into whichever production orchestration system is needed.
tmux
- Chained ttys for side-by-side reading
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Let's See Your Terminal
This got me thinking about my recent pivot, my switch to Neovim by way of LazyVim to write most of my code, and using tmux to keep terminal states alive after closing a session.
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Just How Much Faster Are the Gnome 46 Terminals?
I use Tmux. It's a terminal-agnostic multiplexer. Gives you persistence and automation superpowers.
https://github.com/tmux/tmux/wiki
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Easy Access to Terminal Commands in Neovim using FTerm
Having a common set of tools already set up in different windows or sessions in Tmux or Zellij is obviously an option, but there is a subset of us ( 👋 ) that would rather just have fingertip access to our common tools inside of our editor.
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Using Shell Scripting to simplify your Shopify App development workflow 🐚
Once you have your Mac or Linux machine ready, make sure to downlaod and install TMUX (Terminal Mulitplexer). A lot of our scripts are going to be running headless inside of a TMUX session as it's an incredibly clean way to manage and organise different workspaces simultaneously. A lot of our scripts will help us to interact with TMUX so don't worry if it looks a little intimidating at first. You can install TMUX using your package manager in the terminal, use whichever applies to you:
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Zellij – A terminal workspace with batteries included (tmux alternative)
After having spent too much time trying to get the simple https://github.com/csdvrx/sixel-tmux/ features into mainline tmux (last November https://github.com/tmux/tmux/issues/3753), maybe it'd be easier to jump ship as use zellij?
Could anyone offer recommendations on "riced" zellij configuations, or just a demo where it shows doing with (say charts of disk usage per folder), watching a movie with mpv + keeping a vim to type on?
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Automating the startup of a dev workflow
Well, I now use tmux and tmuxinator. I have had many failed tmux attempts over the years, but I'm firmly bedded in now.
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Clipboards, Terminals, and Linux
Which leads me to clipboards. Linux has two of them! Adding to the interest, I typically use Neovim remotely, via an SSH connection to a Tmux session. And on my Linux system, I use urxvt as my terminal program. All of these are very UNIX-y tools, and somehow they all need to play nicely together.
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Connecting Debugger to Rails Applications
The downside of overmind is that it requires tmux, which is a terminal multiplexer tool. If you don't already use tmux, I'd say it's probably not worth learning it just for the purposes of using overmind. But if you're like me and already know/use tmux, this can be a great solution to pursue.
- Enchula Mi Consola
What are some alternatives?
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
zellij - A terminal workspace with batteries included
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
kitty - Cross-platform, fast, feature-rich, GPU based terminal
Dask - Parallel computing with task scheduling
tilix - A tiling terminal emulator for Linux using GTK+ 3
cookiecutter-pytorch - A Cookiecutter template for PyTorch Deep Learning projects.
toggleterm.nvim - A neovim lua plugin to help easily manage multiple terminal windows
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
i3 - A tiling window manager for X11
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
Mosh - Mobile Shell