shortthirdman

## --- Imports ---
import requests
import pandas as pd
import numpy as np
import yfinance as yf
from sklearn.tree import DecisionTreeClassifier, plot_tree
import matplotlib.pyplot as plt
import re

# --- Step 1: Download and save financial statements to Excel ---

shortthirdman

@RestController
@RequestMapping("/api/upload")
public class ChunkedUploadController {

    private final Path storagePath = Paths.get("uploads");

    @PostMapping("/chunk")
    public ResponseEntity<String> uploadChunk(
            @RequestParam("file") MultipartFile chunk,
            @RequestParam("chunkNumber") int chunkNumber,

shortthirdman

shortthirdman

shortthirdman

import java.util.*;
import java.util.stream.Collectors;

/**
 * TransactionType enum as an example.
 * In your challenge environment, this might be pre-defined.
 */
enum TransactionType {
    P2P,
    P2M,

shortthirdman

import functools
import time
import random
import asyncio

def async_retry(max_retries=3, start_delay=2, backoff_factor=2, exceptions=(Exception,)):
    """Retry decorator for async functions with exponential backoff."""
    def decorator(func):
        @functools.wraps(func)
        async def wrapper(*args, **kwargs):

shortthirdman

import asyncio
import aiohttp
import random
from bs4 import BeautifulSoup

class AsyncScraper:
    def __init__(self, max_concurrency=20):
        self.semaphore = asyncio.Semaphore(max_concurrency)
        self.user_agents = [
            "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",

shortthirdman

# clearly makes git better
[column]
	ui = auto
[branch]
	sort = -committerdate
[tag]
	sort = version:refname
[init]
	defaultBranch = main
[diff]

shortthirdman

public class LRUCache {
    private int capacity;
    private Map<Integer, Integer> cache;
    private LinkedHashMap<Integer, Long> accessTime;
    
    public LRUCache(int capacity) {
        this.capacity = capacity;
        this.cache = new HashMap<>();
        this.accessTime = new LinkedHashMap<>();
    }

shortthirdman

def permuteUnique(nums):
    def backtrack(path, used):
        if len(path) == len(nums):
            result.append(path[:])
            return
        for i in range(len(nums)):
            if used[i]:
                continue
            # Skip duplicates
            if i > 0 and nums[i] == nums[i - 1] and not used[i - 1]: