Anirudh anirudhXshetty

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Audio Output Switcher

This script will cycle to the next available audio output device. It can be tied to a hotkey to easily be triggered. This is handy, for example, for swapping between HDMI audio and headphones.

Install

Download the audio-device-switch.sh script and place it in /usr/local/bin.
Make the script executable: sudo chmod 755 /usr/local/bin/audio-device-switch.sh.
Open the Keyboard Shortcuts settings page, add a new shortcut, tell it to execute audio-device-switch.sh, and set up your shortcut!
Install the notify-send library if you want to see a popup notification when the audio device switches: sudo apt install libnotify-bin.

Customizations

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Data Structure
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Graph Theory
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SQL

	"""
	The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp

	# remotes::install_github("walkerke/mapgl")
	library(mapgl)

	# CYBERPUNK 2125 - Ultra-striking neon palette
	# Deep blacks + electric neons for that Blade Runner / Akira vibe
	cyberpunk_2125 <- c(
	"#000000", # Pure black (shadows)
	"#0a0e27", # Deep space blue (dark areas)
	"#1a1a2e", # Dark navy (buildings)
	"#16213e", # Midnight blue

	// Simulation parameters
	const ACCOUNTS_TARGET: usize = 20_000;
	const INSTRUMENTS_TARGET: usize = 15;
	// number of events to stdout before the final line
	const TICKS_GENERATED_COUNT: u64 = 1_000_000 - 1;

	// Trading constraints
	const TRADE_MAX_SZ: u64 = 1_000;
	const TRADE_MAX_PX: u64 = 1_000_000;
	const TRADE_MIN_PX: u64 = 100;

	"""
	This script demonstrates how to build a real-time scanner that detects significant
	price movements across all US stocks and ETFs using Databento's market data APIs.

	Features:
	- Handles entire US equities universe of ~9,000 symbols efficiently
	- Median sub-ms feed delay to NY4/5 (WAN-shaped) and ~5s to start scanning
	- Monitors all US stocks and ETFs for price movements exceeding a configurable threshold
	- Compares current prices against previous day's closing prices
	- Displays alerts when significant moves are detected

	#!/usr/bin/env python

	# Building high-frequency trading signals in Python with Databento and sklearn
	#
	# This is a simple example that demonstrates how to build high-frequency trading signals in Python,
	# using order book and market depth data from [Databento](https://databento.com) together with
	# machine learning models from [sklearn](https://scikit-learn.org/).

	import databento as db
	import numpy as np

	library(geojsonsf)
	library(sf)
	library(rayrender)

	#Data source: https://github.com/telegeography/www.submarinecablemap.com
	cables = geojson_sf("cable-geo.json")

	cablescene = list()
	counter = 1
	for(i in 1:length(cables$geometry)) {