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# Copy paste this gist in a Google Collab cell
# Go to your Kaggle competition page -> data, scroll below to see the kaggle api command which looks similar to below line
# !kaggle competitions download -c competitive-data-science-predict-future-sales -p data
# Replace that line accordingly in the below code
# Run the cell

!pip install kaggle

from google.colab import files
files.upload()

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#!/usr/bin/env python
import requests
import sys
import getpass
username = input('Enter username: ')
pa = str(getpass.getpass(prompt='Enter password: '))

with requests.session() as s:
	try:
		page = s.post('https://netaccess.iitm.ac.in/account/login' , data={ 'userLogin':username, 'userPassword':pa, 'submit':''}, verify=False)

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// ==UserScript==
// @name        Mangasee123 Fast Scroll
// @namespace   http://tampermonkey.net/
// @version     0.2
// @description Simulate Option + Down arrow when I just press down arrow on mangasee123.com with smooth scrolling. 
// @author      You
// @match       https://mangasee123.com/*
// @grant       none
// ==/UserScript==

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// ==UserScript==
// @name        Mangasee123 Auto Scroll
// @namespace   http://tampermonkey.net/
// @version     0.7
// @description Auto scroll on mangasee123.com with smooth scrolling, toggle key, and notifications. Defaults are for 67% zoomed mangasee.
// @author      You
// @match       https://mangasee123.com/*
// @grant       none
// ==/UserScript==

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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE keyboard SYSTEM "file://localhost/System/Library/DTDs/KeyboardLayout.dtd">
<keyboard group="0" id="5000" name="QWERTY no option" maxout="1">
	<layouts>
		<layout first="0" last="0" modifiers="48" mapSet="312" />
	</layouts>
	<modifierMap id="48" defaultIndex="0">
		<keyMapSelect mapIndex="0">
			<modifier keys="" />
		</keyMapSelect>

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{
  "mcpServers": {
    "Google Docs": {
      "url": "https://mcp.composio.dev/googledocs/REDACTED"
    },
    "Slack": {
      "url": "https://mcp.composio.dev/slack/REDACTED"
    },
    "fetch": {
      "command": "uvx",

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#!/bin/bash

# Script to automatically upload all environment variables from .env to Cloudflare Pages

echo "Uploading environment variables to Cloudflare Pages project:"

# Read each non-comment line from the .env file
while IFS= read -r line || [[ -n "$line" ]]; do
  # Skip empty lines or comments
  if [[ -z "$line" || "$line" == \#* ]]; then

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{
  "questions": [
    {
      "type": "guesstimate",
      "role": "APM",
      "difficulty": "medium",
      "text": "Could you estimate the number of burgers a McDonald's outlet sells in a day?",
      "context": "This is an average McDonald's outlet, not in a specific location like an airport. Only considering in-restaurant purchases.",
      "referenceAnswer": "To estimate the number of burgers a McDonald's outlet sells in a day, I'll use a structured approach:\n\n1. Restaurant capacity: An average McDonald's has about 50 seats\n2. Operating hours: Typically open from 10 am to 10 pm (12 hours)\n3. Peak vs. non-peak consumption patterns:\n   - Peak hours (12-2pm, 6-8pm): 80-90% occupancy\n   - Regular hours: 30-40% occupancy\n4. Average meal time: 20-30 minutes\n5. Burger consumption: About 70% of customers order a burger\n\nCalculation:\n- Peak hours (4 hours): 50 seats × 0.85 occupancy × (4 hours × 60 min / 25 min per customer) × 0.7 burger rate ≈ 714 burgers\n- Regular hours (8 hours): 50 seats × 0.35 

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Running LangGraph Dev with UV

This is a concise guide on setting up and running the LangGraph development server (langgraph dev) using uv as the package manager and runner.

Prerequisites

1. Python: Ensure you have Python 3.11+ installed.
2. UV: Install uv: curl -LsSf https://astral.sh/uv/install.sh | sh (or other methods from astral.sh/uv).
3. .env file: Have your necessary API keys (e.g., OPENAI_API_KEY) in a .env file in your project root.
4. LangGraph Agent: Have your LangGraph agent code (e.g., in agent.py) defining a compiled graph (e.g., graph).

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import argparse
import json
import os
import sys

def jsonl_to_json(jsonl_file_path: str, json_file_path: str):
    """
    Converts a JSONL file to a JSON file.

    Args: