{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Il programma fattoriale"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vediamo brevemente una soluzione all'esercizio 1 del 30 ottobre 2023. Vogliamo scrivere un programma che prende in input un numero *n*, e visualizza il *fattoriale di n*, ovvero il prodotto dei numeri da 1 ad *n*. Il fattoriale di un numero *n* si indica di solito in simboli con n!\n",
    "\n",
    "Ad esempio:\n",
    "* 4 ! = 1 × 2 × 3 × 4 = 24\n",
    "* 5 ! = 1 × 2 × 3 × 4 × 5 = 120\n",
    "\n",
    "Supponiamo di dover calcolare il fattoriale di 5 avendo a disposizione solo una calcolatrice che esegue una moltiplicazione alla volta. Allora la procedura sarebbe la seguente:\n",
    "\n",
    "* calcolo 1 × 2 = 2\n",
    "* prendo il risultato del calcolo precedente (2) e lo moltiplico per 3, ottenendo 2 × 3 = 6\n",
    "* prendo il risultato del calcolo precedente (6) e lo moltiplico per 4, ottenendo 6 × 4 = 24\n",
    "* prendo il risultato del calcolo precedente (24) e lo moltiplico per 5, ottenendo 24 × 5 = 120\n",
    "\n",
    "In pratica, ad ogni passo estendo il prodotto precedente con un nuovo fattore. Volendo scrivere uno pseudo-codice per il nostro programma, potremmo ottenere:\n",
    "\n",
    "* leggi *n* da tastiera\n",
    "* fattoriale_parziale = 1\n",
    "* fattoriale_parziale = fattoriale_parziale * 2\n",
    "* fattoriale_parziale = fattoriale_parziale * 3\n",
    "* fattoriale_parziale = fattoriale_parziale * 4\n",
    "*  .......\n",
    "* fattoriale_parziale = fattoriale_parziale * n\n",
    "* stampa fattoriale_parziale\n",
    "\n",
    "Non è uno pseudo-codice del tutto convincente, per via dei puntini. Questa bozza mostra però che c'è una istruzione che va ripetuta tutte le volte in maniera praticamente uguale, tranne per il fattore con cui moltiplicare `fattoriale_parziale`, che cambia di volta in volta. Una versione migliore dello pseudo-codice è questa:\n",
    "\n",
    "\n",
    "* leggi *n* da tastiera\n",
    "* fattoriale_parziale = 1\n",
    "* per tutti i valori della variabile i da 2 fino ad n ripeti questa istruzione:\n",
    "  * fattoriale_parziale = fattoriale_parziale * i\n",
    "* stampa fattoriale_parziale\n",
    "\n",
    "A questo punto, siamo quasi pronti a convertire questo pseudo-codice in programma Python. Dobbiamo solo capire come realizzare la ripetizione \"per tutti i valori di variabile i da 2 fino ad n\". In questo momento, l'unico modo che conosciamo per ripetere delle istruzioni è l'uso del ciclo `while`. In particolare, usiamo un ciclo `while` controllato da contatore. La struttura standard di questo ciclo è:\n",
    "```python\n",
    "i = v1\n",
    "while i <= v2:\n",
    "  # qui faccio quello che voglio\n",
    "  i += 1\n",
    "```\n",
    "In questo modo viene eseguito il corpo del ciclo tante volte: la prima volta con `i=v1`, poi con `i=v1+1`, quindi `i=v1+2` e così via fino a `i=vn`. Possiamo quindi scrivere finalmente il nostro programma fattoriale. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Il fattoriale di 6 è 720\n"
     ]
    }
   ],
   "source": [
    "n = int(input(\"Immetti numero: \"))\n",
    "fattoriale_parziale = 1\n",
    "i = 2\n",
    "while i <= n:\n",
    "    fattoriale_parziale *= i\n",
    "    i += 1\n",
    "print(f\"Il fattoriale di {n} è {fattoriale_parziale}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# L'istruzione for ... range"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Per l'implementazione di cicli controllati da contatore, il Python mette a disposizione una istruzione specifica:\n",
    "```python\n",
    "for i in range(a, b):\n",
    "    # suite\n",
    "```\n",
    "esegue le istruzioni presenti nella suite ripetutamente, con valori diversi per la variabile `i`. La prima volta viene eseguita con `i` uguale a `a`, poi con `i` uguale ad `a+1` e cosi via, fino a `i` uguale a `b-1`. Il valore `b` è infatti escluso dal range. In totale, la suite viene eseguita `b-a` volte."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n",
      "5\n",
      "6\n",
      "7\n",
      "8\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "# Questo programma esegue l'istruzione print con i valori di i compresi tra 0 e 9.\n",
    "for i in range(0, 10):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "3\n",
      "4\n",
      "5\n",
      "6\n",
      "7\n",
      "8\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "# Questo programma esegue l'istruzione print con i valori di i compresi tra 2 e 9.\n",
    "for i in range(2, 10):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Se fornisco un solo argomento a range, l'estremo inferiore è assunto implicitamente pari a 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n",
      "5\n",
      "6\n",
      "7\n",
      "8\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "for i in range(10):  # uguale a range(0,10)\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notare che usare `range(0)` non produce nessun output. Infatti `range(0)` indica la sequenza di numeri da 0 fino a 0 (escluso)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(0):\n",
    "    print(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "È possibile fornire un terzo parametro a `range` che indica di quanto incrementare la variabile contatore ogni volta."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "2\n",
      "4\n",
      "6\n",
      "8\n"
     ]
    }
   ],
   "source": [
    "for i in range(0, 10, 2):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "E possibile quindi scrivere una nuova versione del programma fattoriale usando l'istruzione for invece di while, come segue:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Il fattoriale di 6 è 720\n"
     ]
    }
   ],
   "source": [
    "# Versione del programma di calcolo del fattoriale che usa l'istruzione\n",
    "# for invece di while.\n",
    "n = int(input(\"Immetti n: \"))\n",
    "fact = 1\n",
    "# nel for qui sotto metto n+1 come estremo superiore perché l'estremo\n",
    "# superiore è escluso\n",
    "for i in range(2, n+1):\n",
    "    fact *=  i\n",
    "print(f\"Il fattoriale di {n} è {fact}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Un altro esempio di utilizzo dell'istruzione `for` lo vediamo in una nuova variante del programma che calcola la media dei salari visto la volta scorsa a lezione. Questa nuova variante, invece di interrompere l'input quando l'utente inserisce un valore negativo, chiede per prima cosa all'utente quanti salari vuole inserire, e poi con un ciclo `for` ripete l'istruzione di input il numero appropriato di volte.\n",
    "\n",
    "Trovate questa versione nel fle **programma_231031_1_salari.py**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Il programma riconoscimento duplicati"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vediamo brevemente una soluzione all'esercizio 5 del 30 ottobre 2023. L'esercizio chiedeva:\n",
    "\n",
    "Scrivere un programma che prende in input una sequenza di numeri positivi (fermandosi, al solito, appena l'utente inserisce un numero negativo). Ogni volta che l'utente inserisce due valori consecutivi uguali, il programma rende noto questa fatto all'utente. Ad esempio, una possibile interazione con il programma può essere la seguente (in grassetto ciò che è immesso dall'utente):\n",
    "\n",
    "<pre>\n",
    "Inserisci un numero: <b>4</b>\n",
    "Inserisci un numero: <b>3</b>\n",
    "Inserisci un numero: <b>3</b>\n",
    "Hai inserito un numero duplicato\n",
    "Inserisci un numero: <b>7</b>\n",
    "Inserisci un numero: <b>2</b>\n",
    "Inserisci un numero: <b>2</b>\n",
    "Hai inserito un numero duplicato\n",
    "Inserisci un numero: <b>-1</b>\n",
    "</pre>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Una possibile soluzione, che trovate anche sotto forma di file Python col nome **soluzioni_231030_5_duplicati.py** è la seguente:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hai inserito un numero duplicato\n"
     ]
    }
   ],
   "source": [
    "valore = int(input(\"Immetti un numero: \"))\n",
    "while valore > 0:\n",
    "    # Utilizzo la variabile `precedente` per salvare il valore della variabile\n",
    "    # `valore` della vecchia iterazione. Quindi, subito dopo, aggiorno\n",
    "    # `valore` con una nuova lettura.\n",
    "    precedente = valore\n",
    "    valore = int(input(\"Immetti un numero: \"))\n",
    "    if valore == precedente:  # controllo se il nuovo valore e il precedente coincidono\n",
    "        print(\"Hai inserito un numero duplicato\")"
   ]
  },
  {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Questa è una esecuzione passo passo del programma.\n",
    "\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cicli annidati"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nel seguito di questo notebook, scriveremo dei pezzi di codice che stampano righe consecutive di asterischi. In realtà questa cosa è partcolarmente facile in Python, dove possiamo usare l'operazione di ripetizione di stringhe. Ad esempio, per stampare una riga di 10 asterischi possiamo scrivere la seguente:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "**********\n"
     ]
    }
   ],
   "source": [
    "print(\"*\" * 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tuttavia, a scopi didattici, supponiamo che questa cosa non sia possibile, e che una riga di asterischi vada scritta un carattere alla volta. Un primo tentativo potrebbe essere il seguente."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*\n",
      "*\n",
      "*\n",
      "*\n",
      "*\n",
      "*\n",
      "*\n",
      "*\n",
      "*\n",
      "*\n"
     ]
    }
   ],
   "source": [
    "for i in range(10):\n",
    "    print(\"*\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Purtroppo in questo modo la riga di asterischi è verticale. Per farla in orizzontale dobbiamo impedire alla funzione `print` di andare a capo dopo la stampa di un asterisco. Per far ciò, è sufficiente inserire come ultimo argoemento di print  il valore speciale `end=\"\"`. Per ora imparate questa cosa un po' a memoria, tra qualche lezione potremo spiegare meglio di che si tratta. Adesso, per stampare una riga di 10 asterischi orrizontali, possiamo scrivere:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "**********"
     ]
    }
   ],
   "source": [
    "for i in range(10):\n",
    "    print(\"*\", end=\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Supponiamo ora di voler stampare un quadrato 10 x 10 di asterischi. L'idea è che usiamo un ciclo `for` per stampare dieci righe, ognua composta da 10 astrischi.\n",
    "```python\n",
    "for j in range(10):\n",
    "    # stampa un riga composta da 10 asterischi\n",
    "```\n",
    "Per stampare la riga composta di 10 asterischi possiamo usare il `for` di prima: abbiamo così due for uno dentro l'altro. Si parla in questo caso di *cicli annidati*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "**********\n",
      "**********\n",
      "**********\n",
      "**********\n",
      "**********\n",
      "**********\n",
      "**********\n",
      "**********\n",
      "**********\n",
      "**********\n"
     ]
    }
   ],
   "source": [
    "for j in range(10):\n",
    "    # stampa una riga composta da 10 asterischi\n",
    "    for i in range(10):\n",
    "        print(\"*\", end=\"\")\n",
    "    # la print qui sotto serve per andare a capo alla fine di una riga di asterischi\n",
    "    print()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notare che visivamente non abbiamo un quadrato ma un rettangolo, perché il singolo carattere non è quadrato ma è più grande in verticale."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Supponiamo ora di voler stampare un triangolo come il seguente:\n",
    "```\n",
    "*\n",
    "**\n",
    "***\n",
    "****\n",
    "*****\n",
    "******\n",
    "*******\n",
    "********\n",
    "*********\n",
    "**********\n",
    "```\n",
    "La prima riga è formata da un solo asterisco, la seconda da 2, e così via fino alla decima riga che è formata da 10 asterischi. È sufficiente modifica il `range` nel for interno da `range(10)` a `range(j+1)`. In questo modo, quando `j=0` (prima riga), il for interno è un `range(0+1)=range(1)` e viene eseguito una volta, quando `j=9` (ultima riga), il for interno è `range(9+1)=range(10)`  e viene eseguito 10 volte."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*\n",
      "**\n",
      "***\n",
      "****\n",
      "*****\n",
      "******\n",
      "*******\n",
      "********\n",
      "*********\n",
      "**********\n"
     ]
    }
   ],
   "source": [
    "for j in range(10):\n",
    "    # stampa la riga i-esima (riga formata da i asterischi)\n",
    "    for i in range(j+1):\n",
    "        print(\"*\", end=\"\")\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Se ci si dimentica il `+1` nel for interno, la prima riga sarà vuota, e l'ultima avrà 9 asterischi."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "*\n",
      "**\n",
      "***\n",
      "****\n",
      "*****\n",
      "******\n",
      "*******\n",
      "********\n",
      "*********\n"
     ]
    }
   ],
   "source": [
    "for j in range(10):\n",
    "    # stampa la riga i-esima (riga formata da i asterischi)\n",
    "    for i in range(j):\n",
    "        print(\"*\", end=\"\")\n",
    "    print()"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Questa è una esecuzione passo-passo di quest'ultimo programma (quello senza il `+1` nel for interno).\n",
    "\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In alternativa al `+1` nel for interno (e in maniera forse più leggibile), possiamo lasciare il secondo for con il `range(j)`, e modificare il primo da  `range(10)` a `range(1,11)`. In questo modo il ciclo esterno avrà sempre 10 iterazioni (11-1=10), ma i valori assunti da `j` andranno da 1 a 10 invece che da 0 a 9."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*\n",
      "**\n",
      "***\n",
      "****\n",
      "*****\n",
      "******\n",
      "*******\n",
      "********\n",
      "*********\n",
      "**********\n"
     ]
    }
   ],
   "source": [
    "for j in range(1,11):\n",
    "    for i in range(j):\n",
    "        print(\"*\", end=\"\")\n",
    "    print()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}