ddh0

import os
import torch
import psutil
import datasets
import glob

from transformers import (
    AutoTokenizer, LlamaConfig, LlamaForCausalLM, Trainer, TrainingArguments,
    DataCollatorForLanguageModeling
)

VictorTaelin

THE PROBLEM

🌲 Invert a binary tree! 🌲

Except with 3 catches:

1. It must invert the keys ("bit-reversal permutation")
2. It must be a dependency-free, pure recursive function
3. It must have type Bit -> Tree -> Tree (i.e., a direct recursion with max 1 bit state)

JarbasAl

from typing import Tuple, Dict, List

import spacy
from spacy.cli import download
from spacy.tokens import Token


class DependencyParser:
    def __init__(self):
        self.NEGATION = {"no", "not", "n't", "never", "none"}

hdary85

import tkinter as tk
from tkinter import simpledialog, messagebox

class NestedDictManager:
    def __init__(self, root, data):
        self.root = root
        self.root.title("Nested Dictionary Manager")

        self.data = data  # Use the provided dictionary
        self.tree = tk.ttk.Treeview(self.root)

hdary85

import tkinter as tk
from tkinter import simpledialog, messagebox

class NestedDictManager:
    def __init__(self, root):
        self.root = root
        self.root.title("Nested Dictionary Manager")

        self.data = {
            'key1': 'value1',

rain-1

The reverse turing test

I asked GPT-4 to come up with 10 questions to determine if the answerer was AI or human.

I provided my own answers for these questions and I also asked ChatGPT to answer them.

The result is that GPT-4 was able to correctly differentiate between AI and Human.

mfischr

#!/usr/bin/env bash
set -e

# pj-append.bash is a timestamped log file for you, a human.  Set up a cron job to launch it every
# hour to note what you were working on, or append lines from the terminal whenever you're chewing
# on a hard problem.
#
# Use the data to build a picture of what you worked on during the last week, or grep
# last quarter's log to find out why you decided to use library A instead of library B.
#

amunchet

// ==UserScript==
// @name         noVNC Paste for Proxmox
// @namespace    http://tampermonkey.net/
// @version      0.2a
// @description  Pastes text into a noVNC window (for use with Proxmox specifically)
// @author       Chester Enright
// @match        https://*
// @include      /^.*novnc.*/
// @require http://code.jquery.com/jquery-3.3.1.min.js
// @grant        none

utkarsharma2

"""Dag Factory"""
from datetime import datetime
from airflow import DAG

def create_dag(schedule, default_args, definition):
    """Create dags dynamically."""
    with DAG(
        definition["name"], schedule_interval=schedule, default_args=default_args
    ) as dag:

tykurtz

GROKKING NOTES

I liked the way Grokking the coding interview organized problems into learnable patterns. However, the course is expensive and the majority of the time the problems are copy-pasted from leetcode. As the explanations on leetcode are usually just as good, the course really boils down to being a glorified curated list of leetcode problems.

So below I made a list of leetcode problems that are as close to grokking problems as possible.

Pattern: Sliding Window

• https://leetcode.com/problems/maximum-subarray/ # Close enough
• https://leetcode.com/problems/minimum-size-subarray-sum/