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use clap::Parser;
use cpal::traits::{DeviceTrait, HostTrait, StreamTrait};
use cpal::{FromSample, Sample};
use std::fs::File;
use std::io::BufWriter;
use std::sync::{Arc, Mutex};

#[derive(Parser, Debug)]
#[command(version, about = "CPAL record_wav example", long_about = None)]
struct Opt {

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"""
virtualenv env
source env/bin/activate
pip install --upgrade pip setuptools
pip install python-dotenv
pip install requests
python3 scripts/main.py
"""

import requests

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date:

Habit 1: Be Proactive

Reflective Questions:

• How do you take responsibility for your actions and reactions?
• When faced with a challenging situation, do you focus on what you can control?
• Can you recall a recent instance where you chose a proactive response over a reactive one?

Prompts:

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Debugging questions for entrepreneurs, creators and high performers

Do solo or with someone.

When you’re going through these prompts, ask people at the beginning to write down anything that’s currently on their mind and might distract them and put it aside mentally. Between every prompt, shake out or get up briefly.

Hamming Prompts

• What's your top 3 most harmful habits? When your monkey brain takes over your rational brain?
• What keep you stuck in this local maxima ?

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Oral Health Cheatsheet

Step	Description	Frequency	Source
Waterpik	Uses a high-pressure stream of water to remove food, plaque, and bacteria from hard-to-reach places.	Morning & night	Amazon
Floss	Removes plaque and debris. Recommended: Dr. Tongue's floss

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from scapy.all import *
from openai import OpenAI

client = OpenAI(
    base_url='http://localhost:11434/v1/',
    api_key='ollama',
)

def analyze_packet(packet):
    packet_data = hexdump(packet, dump=True)

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🔄 Weekly Retrospective Template

This template is designed to help you reflect on your past week, plan for the upcoming week, and align your activities with your broader life themes and goals. It's structured to encourage thoughtful consideration of your personal and professional development.

📅 Recent Weekly Retrospectives

To begin, review your recent retrospectives to understand your progress and patterns over time.

🗓 Weekly Retrospective - {{date:DDMMYY}}

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Consideration	RAG	Fine-Tuning	Notes
Data Requirements	Less reliant on domain-specific training data	Requires substantial domain-specific training data	RAG adapts easily to new data; fine-tuning is best for stable knowledge bases.
Model Adaptability	More flexible to new, unseen data	Less flexible, tailored to the training data	RAG

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def generateParityBits(data):
    """
    Generates parity bits for the given 4-bit data.
    """
    p1 = data[0] ^ data[1] ^ data[3]
    p2 = data[0] ^ data[2] ^ data[3]
    p3 = data[1] ^ data[2] ^ data[3]
    return p1, p2, p3

def encodeHamming(data):

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Skill	Level	Notes
Ruby	Basic
React, Typescript, Tailwind	Expert
ReScript	Not familiar
Rust	Advanced	Love it!
PostgreSQL	Advanced	Used many times in production, did a lot of optimization