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#!/usr/bin/env python3
"""
Batch-convert .mov/.MOV QuickTime videos in the current directory:

1. Find all .mov/.MOV files.
2. For each:
   - Convert to MP4 (H.264, no audio, slightly reduced quality).
   - Generate a high-quality GIF from the MP4.
   - Extract JPEG screenshots from the GIF every 1 second.
   - If everything succeeds, delete the original .mov/.MOV file.

basperheim

Ultimate Python Venv Tutorial and Guide

This is a practical, opinionated guide to Python virtual environments on POSIX/macOS/Linux with a few Windows notes. It shows the cleanest workflows that don't bite you later: create/activate, install via pip and requirements.txt, run scripts with reliable logging/printing, deactivate/uninstall/remove, common gotchas, when to upgrade pip/setuptools/wheel, and a Zsh prompt that shows the active venv in red. It also explains what a venv does and doesn't do (spoiler: you can still build Go, run Docker, etc.).

---

Why venvs (in one paragraph)

Python versions and packages vary per project. A venv creates an isolated interpreter + site-packages so each project can pin its own dependencies without polluting system or Homebrew installs. On macOS/Homebrew you usually only have python3 globally; once you activate a venv, you get a project-local python.

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Ollama: Practical Reference (macOS · Linux · Windows)

Local LLMs with a Docker-like CLI. This doc shows how to install, run, manage RAM/disk usage, and clean up.

TL;DR (cheat-sheet)

# install (mac)
brew install --cask ollama-app   # or: brew install ollama

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Vosk Transcriber (MP3/WAV → Text)

A small Python CLI that transcribes audio using Vosk. If you pass an .mp3, it automatically converts to a 16 kHz mono WAV via ffmpeg and then transcribes. If you pass a .wav, it transcribes directly.

• Input: .mp3 or .wav
• Output: .txt with the same base name as the input (e.g., audio.mp3 → audio.txt)
• Engine: Vosk offline speech recognition

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git_diff_filtered — focused diffs for humans and LLMs

A small Bash function that prints only the meaningful parts of your Git diff, skipping asset/vendor directories and binary-ish files. Output is grouped by file with a clear header, making it ideal for quickly reviewing changes or pasting compact, high-signal code context into LLM prompts.

Why

• Less noise, more signal. Excludes node_modules/, .yarn, .astro, and common binary/extensions by default.
• LLM-friendly. Keeps diffs tight to save tokens and reduce hallucinations; per-file headers help models understand boundaries.
• Convenient. One call prints all filtered diffs, or you can narrow to a path.

basperheim

#!/usr/bin/env python3
# Tetris clone in Python + Pygame
# No assets needed. Run: python tetris.py
# Controls:
#   Left/Right: move
#   Down: soft drop
#   Up / X: rotate CW
#   Z: rotate CCW
#   Space: hard drop
#   P: pause

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detailed_tree.sh

A robust, cross-platform shell function for quickly sharing a directory’s structure and previewing file contents.
Ideal for collaborating with others, sharing context with ChatGPT or other LLMs, or just auditing a codebase without manually sifting through files.

---

Features

• Smart Exclusions

basperheim

#!/usr/bin/env python3
import argparse
import os
import sys
import re

# directories to skip entirely
EXCLUDE_DIRS = {'node_modules', 'target', 'bin', '__pycache__', 'build', 'dist'}

MARKDOWN_LINK = re.compile(r'(!?\[.*?\])\((.*?)\)')  # matches [text](url) and ![alt](url)

basperheim

import os
import re
import argparse
from collections import defaultdict

# ---------------------------------------------------------
# Step 0: Utility Functions
# ---------------------------------------------------------
def find_parent_method(lines, call_line_num):
    """

basperheim

keyword,searches,visits
Chatgpt,24900000,8092500
chaat gbt,24900000,8092500
chaat gpt,24900000,8092500
chact gpt,24900000,8092500
chadgbt,24900000,8092500
chag gpt,24900000,8092500
chap gpt,24900000,8092500
chast gpt,24900000,8092500
chatb gpt,24900000,8092500