josephyooo

#!/usr/bin/env python3
"""
Minimal live viewer for Claude Code sessions.
Landing page is a project/session picker; picked session opens a live viewer
that renders assistant text with Markdown + KaTeX.

Usage:
    claude-live.py                         # start server, use picker
    claude-live.py --port 7777             # custom port
"""

josephyooo

For those who want to backup their MacOS system using Time Machine but don't have an external storage drive. This is a self-contained guide, heavily based on fragmented information found online.

Disclaimers:

• Extra steps will be needed if you want to connect through the internet. I could not get this to work.
• Backing up systems greater than 64 GB may be challenging (see 2.b.6).

0. Prerequisites

1. A MacOS system (this guide tested on a Macbook Air M3 (2024) running Sonoma 14.3)
2. A Windows system (tested on an AMD system running Windows 11 Pro 23H2)
3. Administrative permissions on both systems

josephyooo

if [[ $(pmset -g|grep "lowpowermode"|tail -c 2) == 0 ]]
then
    sudo pmset -a lowpowermode 1
else
    sudo pmset -a lowpowermode 0
fi

josephyooo

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josephyooo

from random import shuffle # for unsorted list

def bubble_sort(arr):
    n = len(arr)

    # run n-1 to ensure array is sorted
    for j in range(n-1):
        for i in range(n-1):
            if arr[i] > arr[i+1]:
                arr[i], arr[i+1] = arr[i+1], arr[i]

josephyooo

def highlight(s):
    return f"\033[36m{s}\033[0m"

def switch_elements(l, i1, i2):
    # switch elements of list in-place
    l[i1], l[i2] = l[i2], l[i1]

def visualize_selection_sort(l):
    # l: list of characters to be sorted
    l = [ord(c) for c in l]

josephyooo

from math import sqrt, pi, e, ceil

# NUMERICAL INTEGRATIOn
def trapezoidal(f, a, b, n):
    # init h and x_j
    h = (b - a) / n
    x = lambda j: a + j * h
    # compute and return quadrature
    return h / 2 * (f(a) + 2 * sum([f(x(j)) for j in range(1, n)]) + f(b))

josephyooo

def newton(f, f_prime, lambda_0, epsilon, maxits=25):
    lambdas = [lambda_0]
    for i in range(maxits):
        lambda_0 = lambdas[-1]
        lambda_1 = lambdas[-1] - f(lambdas[-1]) / f_prime(lambdas[-1])
        lambdas.append(lambda_1)
        if abs(lambda_1 - lambda_0) < epsilon:
            return lambdas
    return lambdas