Random generator tools for learning 🇪🇸

random-tools.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def remove_duplication(arr):\n",
    "  if not arr:\n",
    "    return []\n",
    "  \n",
    "  result = [arr[0]]\n",
    "  for i in range(1, len(arr)):\n",
    "      if arr[i] != arr[i - 1]:\n",
    "          result.append(arr[i])\n",
    "  \n",
    "  return result\n",
    "\n",
    "# Function to normalize the probabilities\n",
    "def normalize_weights(weights):\n",
    "    total = sum(weights.values())\n",
    "    return {letter: weight / total for letter, weight in weights.items()}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[18, 39, 79, 27, 64, 21, 66, 85, 65, 63, 87, 70, 85, 26, 62, 27, 92, 85, 73, 53, 69, 45, 92, 93, 88]\n",
      "[78, 67, 79, 16, 78, 64, 36, 90, 79, 89, 73, 39, 28, 52, 74, 70, 10, 58, 62, 57, 69, 72, 66, 49, 80]\n",
      "[20, 56, 74, 37, 68, 72, 83, 68, 71, 72, 81, 25, 71, 53, 84, 33, 43, 23, 71, 75, 72, 67, 18, 75, 46]\n",
      "[39, 75, 23, 79, 56, 69, 28, 83, 99, 53, 72, 20, 77, 72, 47, 37, 57, 55, 28, 34, 54, 13]\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "\n",
    "number_weights = { n: 1 for n in range(10, 100) }\n",
    "for i in range(60, 80):\n",
    "    number_weights[i] = 3\n",
    "\n",
    "for i in range(15, 20):\n",
    "    number_weights[i] = 3\n",
    "\n",
    "# Generate 100 random numbers between 10 and 100\n",
    "random_numbers = random.choices(\n",
    "    population=list(number_weights.keys()), \n",
    "    weights=list(number_weights.values()),\n",
    "    k=100\n",
    ")\n",
    "random_numbers = remove_duplication(random_numbers)\n",
    "\n",
    "# Print the random numbers\n",
    "for i in range(0, 100, 25):\n",
    "    print(random_numbers[i:i+25])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 8:23   12:08   14:01    0:41   11:24   16:34   19:27   18:28    8:39   14:42    5:52   21:24    9:55   13:40    1:42\n",
      "13:07   21:58    5:36    1:24   14:59   21:02   16:13   13:45   17:24   22:51   14:06   23:49   22:54    4:32    6:47\n",
      "16:24    1:50   23:19   20:33   10:41    9:46   22:31    5:39    8:17   12:03    3:56   16:19    6:20   23:28    9:43\n",
      " 1:00   13:21   13:15    0:14   13:09   18:24   19:08    3:38   22:34    2:07   15:47   16:25   12:34   22:56   17:28\n",
      "18:57    9:29    6:32    4:05   10:34   14:03   22:30    7:56    5:26   10:38    6:41    6:39   11:35   20:02    6:29\n",
      " 4:12    6:38   22:10   19:11   20:39   23:14    2:57   21:26   19:55    1:17   14:58    4:04   10:37   14:35   15:05\n",
      "16:59   12:22    9:20   13:06    3:44   11:14   16:00    2:11   18:51\n"
     ]
    }
   ],
   "source": [
    "# Generate 100 random hours between 0 and 23\n",
    "random_times = [f\"{random.randint(0, 23):2d}:{random.randint(0, 59):02d}\" for _ in range(100)]\n",
    "random_times = remove_duplication(random_times)\n",
    "\n",
    "# Print the random times with n times per line\n",
    "n = 15\n",
    "for i in range(0, 100, n):\n",
    "    print(\"   \".join(random_times[i:i+n]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 57,50 €     83,70 €     73,68 €     54,77 €     64,73 €     65,63 €     65,21 €     38,09 €     83,23 €     65,68 €     73,05 €     32,45 €     49,68 €     60,91 €     65,32 €\n",
      " 17,62 €     74,41 €     89,38 €     75,12 €     70,38 €     73,85 €     78,79 €     30,18 €     69,41 €     59,80 €     72,64 €     27,15 €     90,66 €     80,55 €     38,98 €\n",
      " 77,72 €     63,75 €     60,77 €     84,76 €     13,26 €     77,62 €     77,54 €     36,16 €     30,74 €     17,51 €     61,66 €     25,07 €     65,67 €     16,26 €     73,18 €\n",
      " 77,67 €     20,28 €     76,25 €     80,25 €     15,71 €     52,56 €     66,48 €     16,32 €     65,94 €     11,68 €     16,05 €     13,09 €     92,28 €     91,67 €     77,15 €\n",
      " 71,41 €     44,97 €     57,63 €     91,72 €     74,60 €     70,30 €     62,44 €     54,62 €     64,95 €     75,53 €     58,50 €     96,57 €     16,60 €     90,84 €     46,64 €\n",
      " 19,25 €     88,78 €     33,97 €     62,09 €     15,11 €     72,02 €     90,72 €     18,88 €     64,25 €     56,63 €     78,61 €     35,63 €     23,79 €     70,62 €     48,74 €\n",
      " 97,34 €     28,75 €     65,82 €     51,65 €     17,20 €     68,71 €     17,01 €     71,47 €     92,67 €     72,59 €\n"
     ]
    }
   ],
   "source": [
    "euro_weights = { n: 1 for n in range(10, 100) }\n",
    "for i in range(60, 80):\n",
    "    euro_weights[i] = 3\n",
    "\n",
    "for i in range(15, 20):\n",
    "    euro_weights[i] = 3\n",
    "\n",
    "cent_weights = { n: 1 for n in range(0, 99) }\n",
    "for i in range(60, 80):\n",
    "    cent_weights[i] = 3\n",
    "\n",
    "cent_weights[100] = 3\n",
    "\n",
    "# Normalize the initial weights\n",
    "euro_normalized_weights = normalize_weights(euro_weights)\n",
    "cent_normalized_weights = normalize_weights(cent_weights)\n",
    "\n",
    "def random_euro():\n",
    "    return random.choices(\n",
    "        population=list(euro_normalized_weights.keys()), \n",
    "        weights=list(euro_normalized_weights.values()), \n",
    "        k=1\n",
    "    )[0]\n",
    "\n",
    "def random_cent():\n",
    "    return random.choices(\n",
    "        population=list(cent_normalized_weights.keys()), \n",
    "        weights=list(cent_normalized_weights.values()), \n",
    "        k=1\n",
    "    )[0]\n",
    "\n",
    "# Generate 100 random prices between 10 and 100\n",
    "random_prices = [f\"{random_euro():3d},{random_cent():02d} €\" for _ in range(100)]\n",
    "\n",
    "# Print the random times with n times per line\n",
    "n = 15\n",
    "for i in range(0, 100, n):\n",
    "    print(\"    \".join(random_prices[i:i+n]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r, l, ñ, d, r, q, g, j, h, t, n, j, d, j, g, a, v, c, ñ, b, i, u, g, u, m\n",
      "e, t, o, l, g, x, a, u, j, i, e, v, j, d, i, d, s, l, v, q, n, f, a, q, n\n",
      "j, x, h, j, o, v, d, v, l, b, l, f, p, q, h, n, g, v, a, y, t, w, v, k, u\n",
      "y, n, q, a, y, o, g, b, s, t, j, p, z, v, b, r, l, n, m, i\n"
     ]
    }
   ],
   "source": [
    "import string\n",
    "\n",
    "# Define the letters including ñ\n",
    "letters = list(string.ascii_lowercase) + ['ñ']\n",
    "\n",
    "# Initialize the probabilities map with ones\n",
    "letter_weights = {letter: 1 for letter in letters}\n",
    "letter_weights['j'] = 3\n",
    "\n",
    "# Normalize the initial weights\n",
    "normalized_weights = normalize_weights(letter_weights)\n",
    "\n",
    "# Generate 100 random letters based on the normalized probabilities\n",
    "random_letters = random.choices(\n",
    "    population=list(normalized_weights.keys()), \n",
    "    weights=list(normalized_weights.values()), \n",
    "    k=100\n",
    ")\n",
    "\n",
    "random_letters = remove_duplication(random_letters)\n",
    "\n",
    "# Print the random letters with 25 letters per line\n",
    "for i in range(0, 100, 25):\n",
    "    print(\", \".join(random_letters[i:i+25]))"
   ]
  }
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