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Source channel @githubtrending · Post #15404 · Jan 9

#shell Superpowers turns a coding agent into a disciplined helper that first clarifies what you want, then designs, plans, and implements features using clear steps and strict test‑driven development. It automatically manages branches, breaks work into tiny tasks, uses sub‑agents with built‑in reviews, and enforces quality checks before merging. You benefit by getting more reliable code, less babysitting of the AI, safer experimentation in isolated branches, and a repeatable workflow that feels like working with a careful junior engineer who always follows best practices. https://github.com/obra/superpowers

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Interesting Planet 🌍

@interesting_planet_facts · Post #1053 · 11/19/2025, 06:11 PM

🌎 In 1977, the Soviet Venera 14 probe recorded mysterious low-frequency “thunder”-like sounds on Venus. Scientists now attribute these to seismic activity or wind interacting with the planet’s dense atmosphere. Venus’s surface winds move slowly, but thick air carries sound much farther than on Earth. ✨ #Venus⚡#sounds⚡#space 👉subscribe Interesting Planet 👉more Channels ​

djangoproject

@djangoproject · Post #255 · 02/02/2017, 06:57 PM

https://github.com/tyiannak/pyAudioAnalysis #pyAudioAnalysis is a Python library covering a wide range of audio analysis tasks. Through pyAudioAnalysis you can: Extract #audio features and representations (e.g. mfccs, spectrogram, chromagram) Classify unknown #sounds Train, parameter tune and evaluate classifiers of audio segments Detect audio events and exclude silence periods from long recordings Perform supervised segmentation (joint segmentation - classification) Perform unsupervised segmentation (e.g. speaker diarization) Extract audio thumbnails Train and use audio regression models (example application: emotion recognition) Apply dimensionality reduction to visualize audio data and content similarities