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Mike Waters mikewaters

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@steve-jansen
steve-jansen / export-zone.sh
Created December 15, 2014 19:11
Export DNS records from Rackspace Cloud DNS to zone files on disk
#!/bin/bash
# exports DNS records from Rackspace Cloud DNS to text files
# Depends on https://github.com/wichert/clouddns/blob/master/src/clouddns.py
set -e
me=export-zone
base_domain=
rackspace_region=
rackspace_rate_limit_delay=3
@spartanatreyu
spartanatreyu / init.lua
Last active August 13, 2024 16:31
Personal Window Management script (hammerspoon)
--Hammerspoon config to replace Cinch & Size-up (Microsoft Windows style) window management for free
--Windows Vista/7's Areo Snap on MacOS
--By Jayden Pearse (spartanatreyu)
-------------------------------------------------------------------
--Options, feel free to edit these:
-------------------------------------------------------------------
--Set this to true to snap windows by dragging them to the edge of your screen
enable_window_snapping_with_mouse = true
@rmcdongit
rmcdongit / macOS_SytemPrefs.md
Last active September 7, 2025 02:56
Apple System Preferences URL Schemes

macOS 10.15 System Preference Panes

Below are a list of System Preference pane URLs and paths that can be accessed with scripting to assist users with enabling macOS security settings without having to walk them through launching System Preferences, finding panes, and scrolling to settings. Not all panes have an accessible anchor and some are OS specific.

To find the Pane ID of a specific pane, open the System Preferences app and select the desired Preference Pane. With the pane selected, open the ScriptEditor.app and run the following script to copy the current Pane ID to your clipboard and display any available anchors:

tell application "System Preferences"
	set CurrentPane to the id of the current pane
	set the clipboard to CurrentPane
@scpedicini
scpedicini / transcribe.py
Last active July 20, 2025 01:43
Python Dictation Transcription Application
# This script will transcribe an audio file (mp3, wav, etc.) to text and then clean the text using a local LLM model via Ollama. Technically, this script will work with any LLM that supports the standard OpenAI bindings with minor adjustments.
# GETTING STARTED:
# 1. Install required python packages (pip install openai python-dotenv)
# 2. Git clone a copy of ggerganov/whisper (https://github.com/ggerganov/whisper.cpp)
# 3. Build the whisper binary (see the whisper.cpp README for instructions)
# 4. Download one of the whisper models (largev2 is the most accurate for all languages, though the base model works reasonably well for English).
# 5. Install ffmpeg (brew install ffmpeg on macOS, apt-get install ffmpeg)
# 6. Install ollama (https://ollama.com/download)
# 7. Download an LLM model (https://ollama.com/library)