alonsoir

---
Query original:

SELECT
u.user_id,u.username,u.email, COALESCE(SUM(o.total_amount), 0) AS total_ spent, COUNT(DISTINCT o. order_id) AS total_orders,
ROUND (AVG(o. total_amount, 2) AS avg_order_value,
MAXo. total amount) AS max order_value,
RANK() OVER (ORDER BY SUM(o. total_amount) DESC) AS spending_rank,
SELECT MAX(02. order_date)
FROM orders 02

alonsoir

#!/bin/bash

# Prompt the user for a link
echo "Please enter the link to scan:"
read link

# Output the entered link
echo "You entered: $link"

curl -s "https://crt.sh/?q=%25.$link&output=json" | jq -r '.[].name_value' | sed 's/\*\.//g' | sort -u

alonsoir

from openai import OpenAI
import requests
from dotenv import load_dotenv
import time
import os
import json

load_dotenv()
client = OpenAI()

alonsoir

# pip install openai
# para probarlo, me bajo el libro Moby Dick, lo divido en 72 secciones y envio cada seccion gpt-4.
# Hay que tener cuidado con los parametros MAX_TOKENS_PER_CHUNK y SUMMARY_TOKEN_LIMIT para no molestar a openAI.
from openai import OpenAI
import requests
from dotenv import load_dotenv

load_dotenv()
client = OpenAI()

alonsoir

public class ListaDobleEnlazada<T> {
    private Nodo<T> cabeza;
    private Nodo<T> cola;

    // Clase interna Nodo
    private static class Nodo<T> {
        T dato;
        Nodo<T> siguiente;
        Nodo<T> anterior;

alonsoir

from rembg import remove
from PIL import Image

## Path for input and output image
input_img = 'spiderman_with_bg.jpeg'
output_img = 'spiderman_without_bg.png'

## loading and removing background
inp = Image.open(input_img)
output = remove(inp)

alonsoir

import PyPDF2
import subprocess

# Open the PDF file (Enter Path To Your PDF)
file = open('fullnotes_lagrangiano_modelo_estandar.pdf', 'rb')
readpdf = PyPDF2.PdfReader(file)

# Iterate over each page in the PDF
for pagenumber in range(len(readpdf.pages)):
    # Extract text from the page

alonsoir

import webbrowser

with open('links.txt') as file:
    links = file.readlines()
    for link in links:
        link = link.strip()  # Remove any whitespace or newline characters
        print(link)
        webbrowser.open(link)  # Use the actual link, not the string 'link'

alonsoir

import pandas as pd
from faker import Faker
import random

fake = Faker()


def generate_fake_data(num_entries=10):
    data = []

alonsoir

import os
import subprocess

def analyze_code(directory):
    # List Python files in the directory
    python_files = [file for file in os.listdir(directory) if file.endswith('.py')]

    if not python_files:
        print("No Python files found in the specified directory.")
        return