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Source channel @githubtrending · Post #15513 · Feb 20

#python#agents#claude#cursor#databricks#vibecoding The Databricks AI Dev Kit enhances AI-driven development by providing your coding assistant (Claude Code, Cursor, etc.) with trusted Databricks knowledge and best practices. It includes a Python library, MCP server with 50+ tools, markdown skills teaching Databricks patterns, and a web-based builder app. You can build Spark pipelines, jobs, dashboards, knowledge assistants, and deploy ML models faster and smarter. The benefit is that your AI coding assistant gains direct access to Databricks functionality and patterns, enabling you to develop data and AI applications more efficiently with built-in governance and best practices. https://github.com/databricks-solutions/ai-dev-kit

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djangoproject

@djangoproject · Post #99 · 07/14/2016, 04:57 AM

https://github.com/daleroberts/tv tv ("#textview") is a small tool to quickly view high-resolution multi-band imagery directly in your terminal. It was designed for working with (very large) #satellite imagery data over a low-bandwidth connection. For example, you can directly visualise a Himawari 8 (11K x 11K pixel) image of the Earth directly from its URL: It is built upon the wonderful #GDAL library so it is able to load a large variety of image formats (GeoTiff, PNG, Jpeg, NetCDF, ...) and subsample the image as it reads from disk so it can handle very large files quickly. It has the ability to read filenames (or URLs) from stdin and load files directly from URLs without writing locally to disk. Command line options are styled after gdal_translate such as: -b to specify the bands (and ordering) to use, -srcwin xoff yoff xsize ysize to view a subset of the image, -r to specify the subsampling algorithm (nearest, bilinear, cubic, cubicspline, lanczos, average, mode).