{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Esempi sulle liste\n", "\n", "Da ora in poi la maggior parte dei nostri esercizi consisterà nella scrittura di funzioni piuttosto che di programmi completi. Le funzioni potremo chiamarle successivamente da altre celle del notebook per testarne il funzionamento." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Funzioni che usano le liste solo in lettura" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### La funzione `somma_lista`\n", "\n", "**Scrivere una funzione `somma_lista(l)` che somma tutti i numeri presenti nella lista l restituisce il risultato della somma.**\n", "\n", "Ad esempio, se `somma_list([1, 2, 10, 18] = 31`.\n", "\n", "Notare che in Python esiste già una funzione che fa questo lavoro: la funzione `sum`." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "def somma_lista(l):\n", " \"\"\"Restituisce la somma degli elementi di l.\"\"\"\n", " # la variabile somma contiene la somma parziale degli elementi di l\n", " somma = 0\n", " # il ciclo for scorre gli elementi di l mettendoli uno alla volta dentro\n", " # la variabile\n", " for e in l:\n", " # il valore corrente di l viene aggiunto a somma\n", " somma += e\n", " # restituisce il valore di somma\n", " return somma" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "10" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "somma_lista([1,2,3,4])" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "57" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "somma_lista([3, 12, 42])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### La funzione `max_lista`\n", "\n", "**Scrivere una funzione `max_lista(l)` che restituisce il valore massimo presente nella lista l.**\n", "\n", "Esempio:\n", "```\n", "max_lista([2, 10, 4]) = 4\n", "```\n", "\n", "Notare che in Python esiste già una funzione che fa questo lavoro: la funzione `max`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Proviamo prima questa soluzione che **è sbagliata**." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "def max_lista(l):\n", " \"\"\"\n", " Restituisce il valore massimo di l.\n", " \"\"\"\n", " # La variabile massimo_attuale contiene il valore massimo trovato fino al\n", " # momento attuale. La inizializzo a 0 (e questo è un errore).\n", " massimo_attuale = 0\n", " # Esamino un elemento di l alla volta\n", " for e in l:\n", " # Se l'elemento corrente è maggiore del massimo_attuale, aggiorna la variabile\n", " if e > massimo_attuale:\n", " massimo_attuale = e\n", " return massimo_attuale" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "La funzone così scritta va bene se fornisco numeri positivi." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "15" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "max_lista([4, 15, 10])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ma se la lista contiene solo valori negativi, il risultato è sbagliato: restituisce 0 invece del massimo." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# il massimo è -2, ma restituisce 0\n", "max_lista([-2, -10, -4])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "L'errore è nella inizializzazione di massimo_attuale: 0 non va bene, dobbiamo inizializzarlo con un valore che fa parte della lista `l`." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "def max_lista(l):\n", " \"\"\"\n", " Restituisce il valore massimo di l se la lista non è vuota, altrimenti genera un errore.\n", " \"\"\"\n", " # La variabile massimo_attuale contiene il valore massimo trovato fino al\n", " # momento attuale. La inizializzo con il primo elemento di l (cosa che genera\n", " # errore se la lista è vuota). Non posso inizializzarlo a 0 altrimenti, se\n", " # l contiene solo valori negativi, il risultato è scorretto.\n", " massimo_attuale = l[0]\n", " for e in l:\n", " if e > massimo_attuale:\n", " massimo_attuale = e\n", " return massimo_attuale" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "-2" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "max_lista([-2, -10, -4])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notare che siccome non c'è nulla nel codice di `max_lista` che è limitato all'uso nei numeri interi, la funzione opera correttamente anche su liste che contengono valori di altro tipo (come le stringhe) purché si possano confrontare tra di loro con l'operazione relazionale `>`. " ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'zuzzurellone'" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "max_lista([\"amico\", \"ciao\", \"zuzzurellone\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`max_lista` non funziona correttamente se la lista contiene valori di tipo divero che non si possono confrontare tra loro." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "ename": "TypeError", "evalue": "'>' not supported between instances of 'int' and 'str'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m/home/amato/Nextcloud/Didattica/programmazione-python/notebooks/programmazione/notebook_231116.ipynb Cell 20\u001b[0m line \u001b[0;36m1\n\u001b[0;32m----> 1\u001b[0m max_lista([\u001b[39m\"\u001b[39;49m\u001b[39mciao\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39m10\u001b[39;49m])\n", "\u001b[1;32m/home/amato/Nextcloud/Didattica/programmazione-python/notebooks/programmazione/notebook_231116.ipynb Cell 20\u001b[0m line \u001b[0;36m1\n\u001b[1;32m 9\u001b[0m massimo_attuale \u001b[39m=\u001b[39m l[\u001b[39m0\u001b[39m]\n\u001b[1;32m 10\u001b[0m \u001b[39mfor\u001b[39;00m e \u001b[39min\u001b[39;00m l:\n\u001b[0;32m---> 11\u001b[0m \u001b[39mif\u001b[39;00m e \u001b[39m>\u001b[39;49m massimo_attuale:\n\u001b[1;32m 12\u001b[0m massimo_attuale \u001b[39m=\u001b[39m e\n\u001b[1;32m 13\u001b[0m \u001b[39mreturn\u001b[39;00m massimo_attuale\n", "\u001b[0;31mTypeError\u001b[0m: '>' not supported between instances of 'int' and 'str'" ] } ], "source": [ "max_lista([\"ciao\", 10])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "E non funziona neanche per le liste vuote (giustamente, un insieme vuoto di elementi non ha un massimo)." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "ename": "IndexError", "evalue": "list index out of range", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m/home/amato/Nextcloud/Didattica/programmazione-python/notebooks/programmazione/notebook_231116.ipynb Cell 13\u001b[0m line \u001b[0;36m1\n\u001b[0;32m----> 1\u001b[0m max_lista([])\n", "\u001b[1;32m/home/amato/Nextcloud/Didattica/programmazione-python/notebooks/programmazione/notebook_231116.ipynb Cell 13\u001b[0m line \u001b[0;36m2\n\u001b[1;32m 1\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mmax_lista\u001b[39m(l):\n\u001b[0;32m----> 2\u001b[0m massimo_attuale \u001b[39m=\u001b[39m l[\u001b[39m0\u001b[39;49m]\n\u001b[1;32m 3\u001b[0m \u001b[39mfor\u001b[39;00m i \u001b[39min\u001b[39;00m l:\n\u001b[1;32m 4\u001b[0m \u001b[39mif\u001b[39;00m i \u001b[39m>\u001b[39m massimo_attuale:\n", "\u001b[0;31mIndexError\u001b[0m: list index out of range" ] } ], "source": [ "max_lista([])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notare che anche la funzione predefinita `max` di Python restituisce un errore se la lista è vuota." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "ename": "ValueError", "evalue": "max() iterable argument is empty", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m/home/amato/Nextcloud/Didattica/programmazione-python/notebooks/programmazione/notebook_231116.ipynb Cell 24\u001b[0m line \u001b[0;36m1\n\u001b[0;32m----> 1\u001b[0m \u001b[39mmax\u001b[39;49m([])\n", "\u001b[0;31mValueError\u001b[0m: max() iterable argument is empty" ] } ], "source": [ "max([])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### La funzione `argmax_lista`\n", "\n", "La funzione `max_lista` restituisce l'elemento massimo, ma talvolta siamo più interessati alla *posizione* del massimo nella lista più che il suo valore. Ad esempio, se `l = [4, 78, 2, 34]`, magari vogliamo sapere che il massimo è in posizione `1`. La funzione `max_lista` non va bene per questo scopo, ce ne serve una nuova." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Scrivere una funzione `argmax_lista(l)` che restituisce la posizione nella lista che contiene il valore massimo.**\n", "\n", "Esempio:\n", "```\n", "argmax_lista([4, 78, 2, 34]) = 1\n", "argmax_lista([\"ciao\", \"dado\", \"via\", \"bau\"]) = 2\n", "```\n", "\n", "A differenza che con le funzioni viste prima, Python non ha nessuna funzione predefina equivalente a `argmax_lista`." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "def argmax_lista(l):\n", " \"\"\"\n", " Restituisce la posizione del massimo in `l`, se `l` non è vuoto, altrimenti genera un errore.\n", " \"\"\"\n", " # Invece di memorizzare il massimo attuale, memorizziamo in questa variabile la posizione\n", " # nella lista l in cui si trova il massimo che abbiamo trovato fin'ora. Come per la funzione\n", " # max, consideriamo che il massimo sia inizialmente in posizione 0.\n", " posizione_massimo_attuale = 0\n", " # Ora scorriamo tutti gli elementi di l, ma lo facciamo a partire dalle posizioni, in modo\n", " # da sapere ogni elemento in che posizione si trova. Quindi questo `for` fa variare `i` da 0\n", " # all'ultima posizione di `l`\n", " for i in range(len(l)):\n", " # se l'elemento nella posizione corrente è maggiore dell'elemento massimo\n", " if l[i] > l[posizione_massimo_attuale]:\n", " # aggiorno la posizione del massimo con quella attuale\n", " posizione_massimo_attuale = i\n", " # restituisce la posizione del massimo\n", " return posizione_massimo_attuale" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "argmax_lista([4, 78, 2, 34])" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "argmax_lista([\"ciao\", \"dado\", \"via\", \"bau\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notare che il `range(len(l))` nel for si potrebbe rimpiazzare con `range(2, len(l))`. È inutile controllare il primo elemento nella lista, visto che assumiamo quello come massimo di partenza. Sarebbe sensato fare la stessa ottimizzazione per `max_lista`, ma con il tipo di `for` usato lì non è altrettanto facile." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In generale, in molte circostante si può riscontrare questo dualismo tra funzioni che retituiscono un valore preso da una lista (come `max_lista`) e funzioni che restituiscono la *posizione* di un elemento (come `argmax_lista`)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### La funzione cerca\n", "\n", "**Scrivere una funzione `cerca(x, l)` che restituisce la posizione nella lista l dell'elemento x, o -1 se x non è presente in l.**\n", "\n", "Esempio:\n", "```\n", "cerca(3, [\"ciao\", 2, 76, 3, \"abc\"]) = 3\n", "cerca(3, [\"ciao\", 2, 76, \"abc\"]) = -1\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Python mette a disposizione il metodo `index` per gli oggetti di tipo lista che è molto simile alla funzione `cerca`, ma genera un errore se `x` non è presente nella lista." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "l = [\"ciao\", 2, 76, 3, \"abc\"]\n", "l.index(\"ciao\")" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "ename": "ValueError", "evalue": "54 is not in list", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m/home/amato/Nextcloud/Didattica/programmazione-python/notebooks/programmazione/notebook_231116.ipynb Cell 35\u001b[0m line \u001b[0;36m1\n\u001b[0;32m----> 1\u001b[0m l\u001b[39m.\u001b[39;49mindex(\u001b[39m54\u001b[39;49m)\n", "\u001b[0;31mValueError\u001b[0m: 54 is not in list" ] } ], "source": [ "l.index(54)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Questo è il codice della funzione." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "def cerca(x, l):\n", " \"\"\"\n", " Restituisce la posizione di x in l se esiste, altrimenti restituisce -1.\n", " \"\"\"\n", " # Scorro tutti gli elementi di l tramite la posizione\n", " for i in range(len(l)):\n", " # Se l'elemento nella posizione corrente è uguale ad x\n", " if l[i] == x:\n", " # Retituisco la posizione corrente\n", " return i\n", " # Se sono arrivato qui con l'esecuzione, vuol dire che non ho trovato `x`\n", " # all'interno della lista, quindi restituisco -1.\n", " return -1" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cerca(3, [\"ciao\", 2, 76, 3, \"abc\"])" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "-1" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cerca(3, [\"ciao\", 2, 76, \"abc\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Vi faccio vedere subito un tipico errore che gli studenti commettono in un programma come questo. Considerate la segute versione della funzione **cerca**." ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "def cerca_bacata(x, l):\n", " \"\"\"\n", " Restituisce la posizione di x in l se esiste, altrimenti restituisce -1.\n", " \"\"\"\n", " for i in range(len(l)):\n", " if l[i] == x:\n", " return i\n", " else:\n", " return -1\n", " return -1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "L'errore consiste nel mettere il `return -1` nel ramo `else` dell'if. Il ragionamento è questo: se l'elemento in posizione `i` non è `x`, vuol dire che non trovato `x`, quindi restituisco `-1`. Ma in il ragionamento è sbagliato. In questo modo il programma controlla solo il primo elemento di `l`, quando `i=0`. Se il primo elemento è uguale ad `x`, restituisce `0`, ma se il primo elemento non è uguale ad `x`, restituisce `-1` (sbagliato, dovrebbe continuare a cercare `x` nelle altre posizioni).\n", "\n", "In generale, è molto probabile che se dentro un for c'è un `if` in cui sia il ramo `then` che quello `else` contengono un `return`, il programma sia sbagliato. Questo perché un tale `if` fa uscire immediatamente dalla funzione, e quindi dal ciclo `for`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Funzioni che restituiscono stringhe" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### La funzione `reverse`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Scrivere una funzione `reverse(l)` che restituisce una nuova lista ottenuta dall'ultimo elemento di al primo**\n", "```\n", "reverse([4, 87, \"ciao\"]) = [ \"ciao\", 87, 4 ] \n", "```\n", "\n", "In Python esiste un metodo `reverse` per le liste, ma esegue l'operazione *sul posto*. Il significato di questa affermazione la vedremo in una prossima lezione." ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "def reverse(l):\n", " \"\"\"\n", " Restituisce una nuova lista ottenuta da l ma procedendo dall'ultimo al primo elemento.\n", " \"\"\"\n", " # L'idea è di partire da una lista vuota, e mano a mano aggiungere a questa lista gli elementi\n", " # che compongono l, dall'ultimo al primo.\n", " risultato = []\n", " # Scorro le posizioni della lista `l` dall'ultima alla prima. Le posizioni da scorrere sono\n", " # len(l)-1 (l'ultima), len(l)-2, len(l)-3 .... fino alla posizione 0. Per scrivere questa\n", " # sequenza con un range:\n", " # * il primo parametro di range è il primo elemento della sequenza, quindi len(l)-1\n", " # * il secondo parametro di range come sappiamo non è l'ultimo elemento della sequenza, ma il\n", " # successivo dell'ultimo. Quando la sequenza è crescente, il successivo è l'ultimo + 1, ma\n", " # quando la sequenza è decrescente, il successivo è l'ultimo - 1. Nel nostro caso 0 - 1 = -1.\n", " # * il terzo parametro di range è il passo della sequenza: cioè la differenza tra un valore della\n", " # sequenza e il precedente. In questo caso, essendo la sequenza decrescente, il passo è -1.\n", " for i in range(len(l)-1, -1, -1):\n", " # prendo l'elemento corrente di i (l[i]) e lo aggiungo in coda a risultato\n", " risultato.append(l[i])\n", " # restituisco il risultato\n", " return risultato" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['io', 'sono', 'ciao']" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "reverse([\"ciao\", \"sono\", \"io\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Per capire cosa sta facendo la funzione può essere utile, mentre la si progetta, mettere qualche print di debugging. Per esempio, considerate questa variante." ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "def reverse_debug(l):\n", " \"\"\"\n", " Restituisce una nuova lista ottenuta da l ma procedendo dall'ultimo al primo elemento.\n", " \"\"\"\n", " risultato = []\n", " for i in range(len(l)-1, -1, -1):\n", " risultato.append(l[i])\n", " print(i, l[i]) # print di debugging\n", " # restituisco il risultato\n", " return risultato" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "L'unica differenza con la versione precedente è una print dentro il for, che ci fa vedere in che ordine vengono esaminate le posizioni di `l` e come viene costruita passo passo la variabile `risultato`." ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2 io\n", "1 sono\n", "0 ciao\n" ] }, { "data": { "text/plain": [ "['io', 'sono', 'ciao']" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "reverse_debug([\"ciao\", \"sono\", \"io\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Un'altra implementazione per reverse\n", "\n", "L'implementazione che abbiamo scritto parte da una lista vuota che viene gradualmente ingrandita con l'aggiunta di nuovi elementi. Tuttavia, aggiungere nuovi elementi ad una lista è relativamente lento rispetto a modificare un elemento già presente. Un approccio diverso è quindi quello di creare inizialmente una lista `risultato` della stessa lunghezza di `l` (riempita come si vuole), e poi mettere dentro `risultato` gli stessi valori di `l` ma al contrario." ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": [ "def reverse2(l):\n", " \"\"\"\n", " Restituisce una nuova lista ottenuta da l ma procedendo dall'ultimo al primo elemento.\n", " \"\"\"\n", " # Prendo la lista [0] e la ripeto len(l) volte. Il risultato è una lista\n", " # di len(l) elementi, tutta riempita con 0. Al posto di 0 avrei potuto mettere\n", " # qualunque altro elemento, il valore iniziale è del tutto ininfluente.\n", " risultato = [0] * len(l)\n", " # Scorro gli elementi di l uno alla volta, sulla base della posizione\n", " for i in range(len(l)):\n", " # Il primo elemento di l (posizione 0) deve essere messo nella ultima di risultato (la posizione len(l)-1)\n", " # l'elemento in posizione 1 deve essere messo nella penultima posizione di risultato (la posizione len(l)-2)\n", " # abbiamo quindi\n", " # 0 => len(l) - 1\n", " # 1 => len(l) - 2\n", " # 2 => len(l) - 3\n", " # ...\n", " # len(l) -1 => 0\n", " # Non è difficile rendersi conto che se i è la posizione nella lista l, nella lista\n", " # risultato quell'elemento va messo in posizione len(l) - 1 - i, da cui:\n", " risultato[len(l)-i-1] = l[i]\n", " # Notare che se invece uso risultato[i]=l[i], alla fine risultato sarà uguale ad l.\n", " # Restituisco il risultato\n", " return risultato" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[5, 4, 2]" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "reverse2([2,4,5])" ] }, { "attachments": { "image.png": { "image/png": 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pQkKC6f+n51i2t7fn3XffZe7cuaa24OBgUwCKjo7mypUrFCxYkFatWnH06FEOHz5sGnfLli3Aw25PlqZs2bJUqFABHx+fZMO6du2KtbU1Xl5eaZ6fl5cX58+fJzAwEHj4DU50dDTz589n3rx5zJs3j9dee419+/Zl2jpkpvQcV4+eX1OT2rGW1YxGI3FxcQQFBeHu7o6HhwcRERGcOnUKeHgh/ttvv5nu5j9rSW9G+v7777Nl+SLPq7S81S8z3vx39epVJk6cyLhx48zu6teoUYNx48YxYcIEvbIzJ7GxsWHAgAHMmzePL7/8ks6dO2MwGEyv8LSzs2PgwIFUqlTJNM2ff/7JBx98gNFoJDY2luHDh5vuRq9YsYKtW7cC4O7uzoQJEwDzPv0AM2bMMKujVq1aKV4NBgUFsWzZMqKiojAajdSoUYM333wz07dDSp60Ldq0acP169d59913cXBwwN3dnREjRmR4eZk9v8yUtP+srKyoU6cOw4cPNw17tE9/sWLFGDVqFAA///wzu3fvJj4+nly5cpnW53Hr6ujoyKxZs/j+++9ZvXo11tbW2NnZMWzYsGR1jRo1ip9++omhQ4diZ2eHi4sLnTp1okGDBmk6lv+tevXqeHp6cu3aNeDhm6W2b9+OwWAgISGBdu3amY7RmTNnMmfOHBYtWoS9vT3ly5fns88+M5vfp59+anoDS+PGjalSpUqyPv3NmjUzfdWaXR7tVz1w4MBk4/Tr14/33nuPli1bmrXnyZOHqVOnpnuZH374oelbn127diX71qhZs2aMGjXK1MXn0W3Zo0ePdC8zs6TnuHr0/Jqaxx1rWSUmJoYxY8Zw69YtWrdubbpx4+3tzdy5c01vSuvQoUOWfbOa0rGX9ArXJK1bt+aXX37B39+f6tWrZ0kdIpIxRYoUYd68eSm+lrN27dqpDssMhujoaGOWzDmLhYWFPfWdchERERERS1XRqQkGrDBgUPceERERERFLp9AvIiIiImLhFPpFRERERCycQr+IiIiIiIVT6BcRERERsXAK/SIiIiIiFk6hX0RERETEwunHuURERJ7A4f1d2V3CU4n+unl2lyAi2UyhX0RE5AkUmkXkeafuPSIiIiIiFk6hX0RERETEwj3X3XuuX7+e3SWIiIiIiDwVW1tb4uLisnQZutMvIiIiImLhFPpFRERERCycQr+IiIiIiIVT6BcRERERsXAK/SIiIiIiOdydO3eYPXs2sbGxGZpeoV9EREREJIdzdXWlVKlSzJgxI0PB/7l+ZWdmGzduHAkJCUyZMsXU9t1333Hp0iUmTZoEwJ49e1i4cCHlypXD29vbNN6wYcO4ceMGAM7OztSoUYP+/ftjb2/PwoULCQwMZNq0aQAYjUbef/99wsPDGTNmDFWrVgXgwIEDzJs3DwA7OzuKFi1Kr169KFeuHLdv3+a9995jxIgR1KxZ07TcpPZHLV68mIiICH766SfOnDmDnZ0dpUuXZtCgQTg6OmbylhMRERGRrPbqq69iZWXFzJkzGT58OHZ2dmme1uJC/507d3B1dc3QOA0aNGDlypXcunWL/Pnzk5CQwIkTJ2jfvr1pnIMHD1KsWDECAwO5ffs2efPmNQ1r2LAhLVu25NSpU6xbt46CBQvSpUuXZMs5d+4cUVFRuLu7c/ToUVPoTzJp0iTu3r3LDz/8wLJly5g4ceIT17tbt254enqa/raxsWHOnDk8ePCAfv36kZiYyK1btxT4RURERJ5j7dq1w8rKii+//JLhw4dja2ubpuksrnvPnDlz2LlzZ6rDfXx8WLRoUYrDGjZsiMFg4Pjx48DDcH737l3q168PQEREBGfOnKFXr15YWVlx9OhRs+nz5ctH+fLl6dKlC/nz5ycsLCzF5Rw8eJDKlStTv359fH19SUxMNBteuHBhKlWqRIECBfDw8EjTehcrVoyKFSua/gMIDg6mbNmyNGzYkBdeeIEOHTqkaV4iIiIiknN5eXlRo0YNvvrqqzRPY3Gh/8MPP+SPP/5IMfhv3ryZkydP8u6776Y4rZubG2XLljWFfj8/Pzw9PSlQoAAAhw8fJnfu3FSqVImKFSty5MgRs+nv3LlDSEgIe/fuJSwsjMqVKydbRkJCAkePHqVWrVrUrFmTqKgozpw5YzZO//796dWrF3/99Reurq4YjcYnrveMGTPo0aMHPXr04IsvvsBgMFC/fn327dvHRx99xJo1a7hz584T5yMiIiIiOZ+VlVW6+vZbXPceR0dHxowZwxdffAFAy5YtAdi2bRsBAQGMHDnysf2fGjZsyIoVK7h//z5+fn688sorpmEHDx6kaNGinD17lgIFCrB3714iIiLIkycPAPv372f//v0AtG7dmhdeeCHZ/E+dOkVUVBQODg7ExcVha2vLkSNHzC4QvvjiC6ytrdm5cydbtmyhatWqFC1a9LHr/e/uPc7OzgAMHjyYF154gV27drF161a2b9/OlClTKFiw4BO3o4iIiIjkTDt27ODw4cOMGjUqzdNYXOgHyJUrF6NHjzYF/8TERPz9/RkxYsQTH3ioX78+y5YtY+PGjYSHh5u69ty8eZPz588DD4N7El9fX9OFxSuvvEK3bt0YMWIEV69eTXH+Bw8eBDA9sJs0j379+pn+zp8/P/b29nTq1Ilff/2Vy5cvPzH0J3XveVT16tWpXr06Fy5cYNy4cZw6dYpmzZo9dl4iIiIikjPt2LGDQ4cOMXr0aBwcHNI8nUWGfgAHBwdGjRrFjBkzsLOzS/ODDnny5KFChQps27aNihUrmu7iHzx4kFy5cvHdd99hY/Nws40bN44jR46YQj+AtbU1r7/+OnPmzOHEiRNmb9qJi4vDz8+P7t27065dOwBOnDjBjBkzOHv2rGm8GzduYGtry+HDhwEoW7asadilS5dMOzhv3rzY29sDcOXKFZycnEzjeXp68sMPP5A/f348PDzw9/cHeOLFg4iIiIjkTDt27ODAgQOMGTMmXYEfLDj0w8PgP27cuHRP17BhQ86cOUODBg1MbYcOHaJGjRqmwA9Qp04dfvnlFyIiIsymb9CgAVu2bGHZsmVmb+Y5ceIE0dHR1K5d29RWpUoVHBwcOHLkiKl7zscff4y1tTUFChTgrbfewtPTk9u3bwOwevVq07TNmzenU6dOAKxcudKshvnz5xMXF8euXbuIiooif/78vPXWW5QrVy7d20NEREREstedO3fw8/Nj9OjR5MqVK93TG6Kjo5/8lGgOFBYWRlxcXHaXISIiIiLyVGxtbbMk1zYt0w0DVhgwWN7be0RERERExJxCv4iIiIiIhVPoFxERERGxcAr9IiIiIiIWTqFfRERERMTCKfSLiIiIiFi45/o9/YUKFcruEkREREREnkpYWFiWL0N3+kVERERELJxCv4iIiIiIhXuuu/eIiIiIiPzXxMfHYzQazdqsra2xskr9fr5Cv4iIiIjIc2LLli2sXr3arM1oNFK8eHEmTZqU6nQWF/rt7e2zuwQRERERkRTFxMRkeNrNmzfz+++/M2fOHFxdXU3tkZGRjB49+rHTWlzoFxERERGxNEmBf+zYsabAbzQaGTJkCHZ2diQkJJCQkIC1tXWK0+tBXhERERGRHGzz5s3s27ePTz75hNy5c5vaDQYDs2fP5u233+b+/fvMmjUrWV//JAr9IiIiIiI51ObNm9m7dy9jx44lT548yYbb2tpStGhRnJ2duXfvHvv27UtxPhbfvedp+k1lttOnT1OpUqXsLkOyiPavZdP+tWzavyKSXs/iOdJNmzaxd+9exo0bl2LgT3Ljxg1sbGzo1q0bq1ev5uWXX042ju70i4iIiIjkMFu3bmXPnj2MGzeOvHnzpjrexYsXmTVrFn369KFw4cKEh4enOJ5Cv4iIiIhIDhMcHEyZMmUee4f/4sWLTJs2jb59+1KvXj2uXbtGwYIFUxxXoV9E5Bm6e/cucXFx2V2GZJOlS5fSvHlzjh8/nt2liEgO99ZbbxEZGcmCBQtSfDj38uXLTJs2jT59+lCvXj2MRiMbN26kQYMGKc7P4vv0P4969OjB9evX6dmzJ/369TO1h4eH89prr9G6dWtGjRqVjRVapri4OIKCgqhYsWKWLeONN94gNDQ01eHLli2jSJEiWbZ8yXrh4eEsW7YMX19fwsLCyJ07N5UrV+a9994z9bcsUqQICxcuzO5SJZ0GDx7MuXPnmDx5MvXr1ze137x5k+7du1O7dm2++OKLbKxQRCyJnZ0dI0aMYPr06SxYsIC3334bg8EAQEhICFOnTqVt27bUrl2b4OBgfvnlFwwGQ4r9+UF3+nO0VatWERwcbPo7tVcwSebYunUrc+fOzdJltGjRgvbt29O+fXvy5csHYPq7ffv2ODo6ZunyJWvFxMQwYsQINm3aRN68eXnppZfIly8fp0+fxtXVFTs7O9zd3XVh95xq1qwZAAcOHDBr/+OPPwBo3rz5M69JRCybnZ0dI0eO5ObNm6Y7/kl3+KtXr87OnTvp168fc+bMoWLFigwbNgwrq5Tjve7051COjo48ePCAL7/8ktmzZ5uu7CRrxMXFsXLlSkJDQzl69Cj16tXLkuW89dZbpv9/4cIFwsPD+fDDD7NkWfLs/fnnn4SEhNCiRQs+/vjjZMOtra1ZtGhRNlQmmeHll1/mu+++49ChQxiNRtN5ef/+/dja2vLiiy9mc4UiYomSgv+0adP45ptv+Pvvv+ndu3eq3XhSo9CfQ7m7u1OrVi3Wrl3L5s2bad++fbJxTp06xfLlywkKCuL+/fuULl2agQMHUqVKFQCGDRsGQLly5di9ezdWVlZ07tyZChUqMH/+fC5evEi5cuUYNWoU7u7uAAQFBfHtt9/y999/kydPHrp27UqHDh2e3Ypnk61bt5q63SxdujTLQv+TzJ8/nzVr1vDRRx/Rrl07AL766is2b97M4sWL2bNnD7/++itdu3Zl7dq1REdH07RpU9555x3s7OwA2Lt3LytWrODKlSsUL16cQYMGUb169WxZn/+a+Ph44OHn6Pz585QpUybZOM2bN6d8+fLMmzePsWPHcvjwYbPhzs7ObNy40TSf/+LnMafKnz8/1apVw9/fn7Nnz1KxYkUiIiI4efIkL774Ik5OToSGhvLjjz/i7+/P7du3KViwIN26dcPLyyvFee7YsYNp06aZPvP37t3j1VdfpVatWkyfPh3QcSAiD18POmrUKBYtWkTv3r0zlFPUvScH69+/P+7u7ixYsICwsLBkw+/du0dkZCQvvfQS9erVIzAwkP/7v//j/v37pnH8/f3Zt28fVatW5d69e8yfP5+xY8dSrFgxihQpwp9//mnq0nLr1i0++ugjU//UPHny8PXXX3P06NFnts7ZIekuf5IzZ85k2zondR/w8/MztR05coSyZctSrFgx4OG7eNetW0ejRo1wc3Nj/fr1LF68GICDBw8yceJEnJ2defPNN4mIiGDcuHHcvn37ma/Lf1GdOnUoV64cwcHBvPPOO/Tu3ZtVq1aZfSb/rWXLlvTv35/+/fubLtYbNWoE/Hc/jzndo118Dhw4gNFoNLU7ODhw9uxZqlWrRosWLbh79y4zZ87k1KlTGVqejgMRSeLg4MC7776b4RuTCv05mIODAx999BH37t1j7ty5yfr0169fn3nz5vH+++/j7e1N69atiYyM5Pz582bj/fjjj4wfP57evXsDDx8mHTNmDF9//TX29vacPn0agG3btnH//n169epFu3btGDx4MACHDh16Bmubff59lz/J0qVLs6UWT09PihUrxvHjx0lISOD8+fOEhobStGlTs/FGjx7NkCFDmDlzJtbW1mzfvh2AtWvXYmVlxUcffUT79u3p0qUL9+/fx9/fPztW5z/H3t6euXPnMm7cOKpUqcLVq1dZsGABvXr1SvEB7pdffpkePXrw0ksvERQURMmSJU3dvf6rn8ecrnHjxtjY2JhC//79+3F0dDR9ze7i4sKiRYsYM2YMw4cPZ8iQIQCcOHEiQ8vTcSAimUXde3K4unXr0rJlS3bu3EnNmjXNhiUkJLBmzRr++OMPrl+/zp07dwBM/5skqd9p0p3ihIQE4GFAcXd3N4WRq1evAjBt2jSz6aOjozN5rXKOuLg4VqxYkaz9zJkzfb+59QAAIABJREFU+Pr6Urdu3WdeU7NmzViyZAlnzpwhICAAINmT+En71MXFhVKlShEUFER8fDzXrl0jMTGRvn37mo1vyfswp7GysqJp06Y0bdqUsLAwpk2bxrFjx/jtt9/o3r17svFjYmL47LPPAPD29jb9wuN/8fP4PHB1daVOnTocPnyYc+fOceLECZo1a2bqXgewb98+tm7dSnBwMBEREQBERUVlaHk6DkQksyj0PwcGDx6Mr68vCxYsMGtftmwZy5Yt46OPPqJx48Zs27aN77//PsPLKVy4MADvvPMO3bp1e6qanxdbtmzh1q1bKQ5bunRptoZ+Pz8/jh8/TsWKFSlUqJDZODExMQA8ePCAkJAQChYsiI2NDYUKFeLmzZt88803WfrqUUlZfHw80dHRODs7A+Dm5kb16tU5duxYqm/fmjVrFsHBwXzyyScUL17c1P5f/Dw+L5o1a8bhw4eZNWsW8fHxpq498PCO/oQJE2jbti0jRowgNDSUoUOHpjovG5uH/wwnhftHjxMdByKSWRT6nwOurq4MHjyYyZMnm7UnhVU/Pz9u377Nzp07n2o5bdu25ZdffmHp0qVcv36dMmXKEBISQseOHfHw8HiqeedEj/blf9Tp06ez5W5/0aJFKVeuHPv27ePy5csMGjQo2ThTp07l5Zdf5uzZs8TFxdGpUycAunbtir+/PxMnTqRly5bkzZuXixcvMnToUL0B6hk4fPgwEyZMoEKFCri7uxMWFsZff/1Frly5aNy4cbLxf/31V3bs2EHBggUJDQ1l1apVALz66qv/uc/j86RRo0bY29ubHqytVauWaVjSeTkwMJDdu3cne1DbxcUFeLjv3dzc8PT0xGAwsHbtWq5du0ZQUJDZ+DoORCSzqE//c6J58+ZmPwYD0Lt3b2rUqMHRo0fZuXMnrVu3fqplFChQgNmzZ1OzZk1+//13fvzxRy5evJjiQ8SW4HF3+ZNkV9/+Zs2acfHiRYxGI02aNEk2vHTp0uzcuZOwsDD69evHa6+9BjwMIxMnTsTNzY1169bx888/Ex4ebupiIFmrSJEitGnThsjISA4cOMClS5eoU6cOM2fOpGjRosnG379/P4Dp/ctJ/92/f/8/93l8nuTKlYuGDRsC0KRJE6ytrU3DmjZtSps2bbh27Rpr166lYsWKFChQwDS8RYsWVK1alYMHD/L7779TrFgxhg4diouLCydPnqRhw4ZUq1bNNL6OAxHJLIbo6Ojn8hefwsLCcHNzS9ae1B82SVI3iJzg9OnTVKpUKbvLkCySmfv30qVL9O3bl2rVqvHVV1+Z2pcuXcqSJUuYPXu26W0v8mzo82vZtH9FJL0ezZxplVI2DQsLIy4u7mlLSqZpmW4YsMKAQXf6RXKipNf7pdQlRERERCS9FPpFcqCdO3diMBj0C58iIiKSKRT6RXKYmzdvEhAQQIUKFcz6AouIiIhklN7eI5LDFCxYkN9++y3FYb179zb9yJqIiIhIWulOv4iIiIiIhVPoFxERERGxcAr9IiIiIiIWTqFfRERERMTCKfSLiIiIiFg4hX4REREREQtniI6ONmZ3ERkRFhaGm5tbsvaM/iSyiIiIiEhWi4mJSdYWFhZGXFxcpi+raZluGLDCgEF3+kVERERELJ1Cv4iIiIiIhVPoFxERERGxcAr9IiIiIiIWTqFfRERERMTCKfSLiIiIiFg4hX4REREREQun0C8iIiIiYuEU+nOYxMREXn/9dbZv357dpUgW0P4VeX5NnjyZF198Mdl/3bt3z+7SRESeyCa7CxBzVlZWtGvXDk9Pz+wuRbJAevdvZGQknTp1YuvWrTg4OGRxdSLyOGPGjGHMmDFmbWPHjqVChQrZVJGISNop9OdAvXv3zu4SJAuld//GxsZmUSUikh5WVuZfjl+/fh1fX19GjRqVTRWJiKSduvfkQD169ODIkSPZXYZkkX/v3127djF69GjGjx+Pl5cXnTt3Zv369aZxX3/9dQDatWunLgQiOcy6deto2rQpefPmze5SRESeSKFfJJudOXOGLl26sHbtWgYOHMiXX37JhQsXAFizZg0AmzdvZuXKldlZpoj8S3R0NJs2baJr167ZXYqISJoo9Itks8KFC1OjRg1y5cpF69atKVWqFOfOncvuskTkMbZv307JkiUpX758dpciIpImCv0iOUy+fPmIj4/P7jJE5DF++eUX3eUXkeeKQr/Ic8BoNGZ3CSLy//n5+REVFUWTJk2yuxQRkTRT6BfJwRwdHbG1tcXPz4/ExMTsLkdEgJ9//plOnTphY6MX4InI80OhXyQHs7W15f3332fq1Kl0796dyMjI7C5J5D/typUr+Pn50aFDh+wuRUQkXQzR0dHPZb+BsLAw3NzckrXb29tnQzUiIiIiIk8WExOTrC0sLIy4uLhMX1bTMt0wYIUBg+70i4iIiIhYOoV+ERERERELp9AvIiIiImLhFPpFRERERCycQr+IiIiIiIWz+JcMp/SEtIiIiIjI03je3hipO/0iIiIiIhZOoV9ERERExMIp9IuIiIiIWDiFfhERERERC6fQLyIiIiJi4RT6RUREREQsnEK/iIiIiIiFU+gXEREREbFwCv05TEJCAj169GDXrl3ZXYpkAaPRSM+ePdm5c2d2lyIiGeDt7U3z5s3N/ps3b152lyUi8kQW/4u8zxtra2u8vLwoW7ZsdpciWcBgMKRr/965c4du3bqxfv16HBwcsrg6EXmS6OhoRo4cSZs2bbK7FBGRdFHoz4F69OiR3SVIFnrzzTfTNX5sbGwWVSIi6RUdHa0LcBF5Lql7Tw7Ur18/fH19s7sMySL/3r979+5l3LhxTJgwgY4dO/LGG2/g4+NjGjfpArBLly706dMnW+oVkf958OABuXLlyu4yRETSTaFfJJudO3eODh06sHLlSt566y2+/vprgoODAVi+fDkAa9euZcmSJdlYpYjAwzv9U6ZMoW3btvTu3ZvFixcTExOT3WWJiDyRuveIZLNChQpRvXp1AFq0aMGqVav4+++/KVmyZPYWJiLJTJ48mTx58mBnZ8e5c+eYOXMmt2/f5qOPPsru0kREHkt3+kVymLx585KQkJDdZYhICooWLYqzszN2dnZUrVqVd999lz179mA0GrO7NBGRx1LoF3kOKFCI5EzW1tbY2dlhMBiyuxQRkcdS6BfJwRwdHbGxseH48eMK/iLZLDIyknXr1nHlyhUePHjA2bNn+e677/Dy8sru0kREnkh9+kVyMBsbG4YMGcKMGTNwdnZmzpw55M6dO7vLEvlPiouL4/z58/z8889ERkZSqFAhvLy86Ny5c3aXJiLyRIbo6Ojn8vZhWFgYbm5uydrt7e3N/n4e36rQr18/Bg8eTN26dbO7FBERERFJwaOZM61SyqZhYWHExcU9bUnJNC3TDQNWGDBk3p3+W7du4evrS1BQEFevXuXevXsAODk5UaRIETw9Palbt26KQV3+Jz4+ntDQUG0nEREREck0Tx36b926xcaNGzl27BhGoxEPDw/Kly+Pi4sLAFFRUVy+fJmNGzfi4+NDnTp16NChg0JtKrZs2ULRokUpVapUdpciIiIiIhbiqUL/4cOHWbVqFQCtWrWicePG5MuXL8Vxw8LC+P3339m3bx8BAQF0796d+vXrP83iLdKxY8eYPn263gQhIiIiIpkmw336t23bho+PD+XKlaNPnz6phv1HhYeHs3jxYgIDA+nQoQNt2rTJyOItuk+/iIiIiORs/4k+/YcOHcLHx4d69erRu3dvrK2tTcOCg4M5duwY169fx8rKisKFC1OvXj2KFCkCQL58+fjggw9YsmQJGzduJG/evLrjLyIiIiKShdId+m/dusXq1atNd/itrB6+6j8xMZFVq1axf/9+AJydnTEYDAQEBLBjxw5atGhBp06dMBgMWFtb06dPHyIiIli5ciVly5bNsj7+Gb0KExERERGxFOkO/evXr8dgMNCvXz9T4AfYsGED+/fvx8PDg549e1KyZEng4Z3/ZcuWsXPnTmxtbWnfvj3w8FcM+/bty4QJE9i4cSP9+/fPnDUSEREREREz6fpF3tDQUE6cOEHTpk3JkyePqf3mzZvs2rULd3d3Ro0aZQr8ACVLlmTUqFEUKFCAX3/9lVu3bpmG5cuXjyZNmuDn50dYWNjTr42IiIiIiCSTrtDv5+cHwEsvvWTW7uvrS2JiIq+99hp2dnbJprO3t+e1114jMTGR48ePmw1r3LgxRqMRX1/f9NYuIiIiIiJpkK7QHxgYiIeHB3nz5jVrv3HjBgCenp6pTluuXDkAbt++bdbu5uaGh4cHgYGB6SlFRERERETSKF2h/8qVK3h4eCRrd3BwAHjsq4YSEhKAlB+sLVq0KFevXk1PKSIiIiIikkbpCv3379/H1dU1WXvx4sUBHttFJ2mYu7t7smEuLi7cu3cvPaWIiIiIiEgapSv0w//u2P9b3bp1cXJyYsOGDVy+fDnZ8MuXL7N+/XqcnZ2pXbt2suGJiYkYjRn6jTAREREREXmCdL2y08nJicjIyGTt9vb29OzZk++//57p06fTtm1bKlasCMDJkyfZvn07iYmJDBo0KMUHfaOionB2ds7gKoiIiIiIyOOkK/QXKVKES5cupTisRo0atGjRgp07d7Jx40Y2btxoNrxp06ZUqFAhxWkvXbpk+sVeERERERHJXOkK/eXLl2fDhg1cv36dQoUKmdofPHjA8uXLOXbsGFZWVpQrV44CBQpgZWXF9evXOX/+PHv27OHatWsMGDDA7K5+WFgY169fp1GjRpm3ViIiIiIiYpKu0F+3bl02btzIvn376NatGwAxMTHMmjWLixcvUq9ePTp37kzu3LnNpouKisLHx4c//viDGTNmMHLkSJycnAD4/fffsbKyom7dupm0SiIiIiIi8m/pepA3X758NGzYkP379xMaGgrAmjVruHjxIq1ataJfv37JAj88fDtPjx496NKlCzdu3GDVqlUAREREsHfvXho1amT2C78iIiIiIpJ50v32ns6dO+Pg4MDChQu5fPkyhw4dokyZMnTs2PGJ07Zo0YKqVavi5+dHcHAw8+fPx9bWNk3TioiIiIhIxqQ79Ds5OdGjRw8uX77MrFmzMBqNtGnTBoPBkKbpW7duDcCcOXMICQmhe/fupq4+IiIiIiKS+dId+gFq1qxJr169uH//PgB58+ZN87Surq5YWVlx7949unXrluJ7+0VEREREJPOk60Hef2vQoAH29vYsW7aMKVOm0KRJE5o0aULBggVTHD8sLIz9+/ezZ88e7O3t6datG/Xr189w4SIiIiIikjYZDv3w8I5/mTJlWLduHXv37mX37t0UKlSIEiVK4OLiAjx8c8+lS5e4du0aBoOBunXr0rlzZ1xdXTNlBURERERE5PEM0dHRxsyYUUREBEeOHCEwMJArV66Yuv44Ojri4eGBp6cn9evXz7S39ISFheHm5pas3d7ePlPmLyIiIiKS2WJiYpK1hYWFERcXl+nLalqmGwasMGDIvND/rCn0i4iIiMjzJrtCf4Ye5BURERERkeeHQr+IiIiIiIVT6BcRERERsXAK/SIiIiIiFk6hX0RERETEwin0i4iIiIhYOIV+ERERERELp9AvIiIiImLhFPpFRERERCycQr+IiIiIiIVT6BcRERERsXAK/SIiIiIiFk6hX0RERETEwin0i4iIiIhYOIV+ERERERELp9AvIiIiImLhFPpFRERERCycQr+IiIiIiIVT6BcRERERsXAK/SIiIiIiFk6hX0RERETEwin0i4iIiIhYOIV+ERERERELZ5PZM9y5cyfr1q0za2vcuDHdu3fP7EWJiIiIiEgaPPWd/nv37pn9HRISAkDJkiUpU6YMtra2prYk9+/ff9rFioiIiIhIGj1V6N+6dSvjx4/nyJEjprYLFy5gb2/PqFGjGDFiBGXKlOHy5cvEx8cD8Oeff+Lt7c3atWufrnIREREREUmTDHfv2bZtG5s2bQJg8eLFnDhxgnbt2hEeHk7ZsmUxGAwAlChRgrNnzxIYGIivry+HDh0C4LfffsNgMNC5c+dMWA0REREREUlNhkL/jh078PHxIU+ePAwcOJA9e/Zw9OhR/vrrL+Bh0E9SrFgxAObNm0d8fDwlS5akW7durFy5kp07d2JlZUXHjh0zYVVERERERCQl6e7eEx8fz+7duwF48803KVmyJP369WPgwIHkypULg8GAp6enafxSpUphZ2eH0WikXbt2jBw5kpIlS9K7d28A/vjjj2TPBYiIiIiISOZJ951+Gxsbevbsydy5c9myZQuVK1fGysqKGjVq4OnpSXR0NG5ubqbx8+XLx9SpU7lz5w7u7u6m9q1btwLw+uuv4+TklAmrIiIiIiIiKcnQg7xVqlShQYMGhISEmMI7gJOTk1ngT5IrVy6zwB8QEMDx48epWbMm9erVy0gJIiIiIiKSRhl+e0/Tpk2xsbFh27ZtXLp0yWzYvXv3OHr0KL6+vty+fdtsWExMDCtXrsTa2ppWrVpldPEiIiIiIpJG6eres3nzZkJCQrhw4YJZP3wbm//N5syZM8yfP5+YmBgAbG1t6d69Ow0bNjSNm5iYSEJCAtOmTcPFxYUSJUpQsmRJXnnllcxYJxERERER+Zd0hf4tW7YA4OrqSo0aNShVqhRly5alcOHCAMTGxvLDDz8A0LFjRxwcHNi6dSsrVqygdOnSuLu7Y21tzbBhwzh79iz//PMP//zzD6dOneLUqVMK/SIiIiIiWSDdD/K6u7vz6aefpjgs6RuAjh070rp1a+Bhf/5FixZx9uxZU79+d3d33N3dadKkCQDffvstAQEBGVwFERERERF5nKf6Rd5HJf0gV0ptiYmJ6ZpOREREREQyR7rv9N+8eZPPP/+cYsWKUbx4cUqVKkXJkiUBKFmyJM7Ozmzfvh0AR0dHNm/ejI2NDVWrVjWbR1BQECEhIVy8eJHLly9nztqIiIiIiEgy6Qr9Xl5eBAcHExISwpUrVzh8+DAA//d//0fhwoWxs7Ojb9++LFy4kA0bNjxcgI0NvXr1In/+/AAkJCQwc+ZM7ty5Azx8zaenp6fpwkFERERERDJXukJ/+/btTf8/JCSEGTNmkJiYSHx8vKm9cuXKfP7555w+fRqj0UilSpVwdnY2DY+Pj8fKygorKyuGDRtG6dKl1b1HRERERCQLZbhP/969e4mPj6dt27YUK1bMbJiTkxN169alXr16ZoEfwN7enu7du5OYmMhvv/2mwC8iIiIiksUyFPpPnTrF4cOHKVGiBF5eXqb2e/fuER4enmz8mJgYQkNDTX9Xq1aNWrVq8eeff+Lr65uREkREREREJI3SHfrj4+NZvnw5AK+88gpWVg9nERAQwIQJExg/frzZ6zfDw8MZM2YMEyZMYNu2baa3+CRdLKxevdrsh75ERERERCRzpTv029jY8PLLLwOwYsUKgoODWbx4Md9++y337t0jMTGRwMBA0/gXLlwgOjoao9GIj48P06dPJzg4mKVLlwLQuHFjnJycMmdtREREREQkmXS/shOgdevWJCYm4uPjw7Rp04CHXXbatWvH5MmTCQ4ONo176dIlAIYMGcKxY8c4cOCAaRovLy+zh4NFRERERCTzZSj0A7Rt25bExER27drFa6+9RsOGDQHIly8fly5dwmg0YjAYCAkJwdramrJly1KxYkVq167NsmXLaNSoEe3atcu0FRERERERkZQZoqOjjU8zg3v37pl1z1m4cCHHjh2jZMmSWFtbc/HiRYoUKcKYMWNM48THx2Njk+HrDQDCwsJwc3NL1m5vb/9U8xURERERySoxMTHJ2sLCwoiLi8v0ZTUt0w0DVhgwZPyVnUke7Y+f9CNbwcHBnD9/nri4OEqUKGE2ztMGfhERERERSbtMT98tWrSgRYsWmT1bERERERHJIIu/5f77779ndwkiIiIikkUaN26c3SU8F566e4+IiIiIiORsCv0iIiIiIhZOoV9ERERExMIp9IuIiIiIWDiFfhERERERC6fQLyIiIiJi4RT6RUREREQsnEK/iIiIiIiFU+gXEREREbFwFv+LvPqVNhERERH5r7MJCwvL7hoy7HmuXUREREQkia2tbZbO38bjsz+zdAFpEf118+wuQURERETEYqlPv4iIiIiIhVPoFxERERGxcJka+q2tDJk5uyeKiIjg9u3bGI3GLF3O9evXuXLlSpYuI71u37792OERERHPqBIRERERyahr165x7tw5oqKiMn3eBv6XzTPt7T15HW1Z/25tXvv+OKFRsZk122QiIiJYsWIFR48exc7ODnt7e8LCwnjhhRfo1asXrq6umb7MKVOmEBMTw7fffovB8GwvbFJy4MABtmzZwqRJk1KsJzo6mg8//JDp06dToECBbKhQRERERB4nICCAuXPn4uTkRO7cuTlz5gz169dnyJAh2NnZZfLSDBh4Z8tT3ybP62jLxsG1Ge/zN/v+Dk/39Gl9kPfs2bNMnTqVfv368dJLL2Fl9fCLitjYWHx8fNi4cSOTJ0+mWLFiKU7v7+/Pd999x507d6hVqxYffPABNjaPv+45cOAA+/btw8nJiYoVK9KqVasn1nnr1i2mT5/O5cuXKVKkCKNGjcq08G00GhkwYACTJ09m1qxZjB07FhcXF9Pw06dPs2fPHsqWLcuZM2f48MMPk81j/fr1bN68mbi4ODp27Ejnzp0zpTYRERHJOrGxsSxbtozDhw8TERFBrly56N69O23btk11muPHj7N27VomTZpEYmIir776Kps3b042ntFo5KeffmLv3r1ERkbi4eHBhAkTyJ07NwCHDx9m3rx5DB48mAYNGqSr7qioKCZMmEB4eDidOnWiXbt2pmHHjh3j+++/586dO1SqVIkRI0aQK1cuwsLC+P777zl79ixRUVGUL1+e4cOHkz9//nQt+3H8/f3ZsGEDf//9N9bW1rRt2xaj0civv/5KQkIC5cqVo2PHjlSvXj3Tlpnk5MmTfPnll0ycOJGiRYsCD/fB6tWrOXToEDNmzMiUt/lUcnqZh4Hf6um79zxt4E+riIgIPv/8cz7++GOaNGliCvwAdnZ2dO3alSFDhvDpp58SFxeXbPrw8HCmTJnCuHHjWLp0KTExMfzwww+PXabRaGTp0qX069ePXr16sWrVqhTn/aixY8fSvn17li9fTuPGjfH29k7/Cqfi/PnzuLu7ExQUhJOTEy4uLvj7+zN37lxCQ0OpUKECJ0+epH79+vj6+iab/sCBA+zZs4e5c+cyZ84cNm/ezOHDhzOtPhEREcl8iYmJDB8+HDs7O2bPns3PP//MzJkzqVmzZqbM//vvvycyMpJ58+bx888/M2zYMHLnzs3du3cZOXIkGzduxNnZOUPz9vHxoUKFCvzwww9mgf/27dtMnz6dzz//nBUrVpA/f36+/vpr4GG28/LyYvHixaxYsYJy5crx7bffZsq6wsPQPXz4cAA6d+5MkyZNWLhwIT/88AMvv/wynTp1Mm3zU6dOZdpyk8yZM4cxY8aYAj+AwWDgjTfewMPDgy1btmTaspL6hKQr9BfJ40CrSuZXWJvfq5PlgR/gp59+om3btpQvXx5fX1+zPuvBwcEEBQXRoEEDPD092bp1a7Lpf/31V1q2bImHhwfW1tYMGDCAbdu2PfZ5gO3bt1O5cmUKFy5Mvnz5eOGFF/Dx8XlsnadPn8bOzo4XX3wRgPbt23Pnzh2CgoIyuObmrl69SokSJQgMDDR90KdPn46TkxNr1qzBysqKGjVqEBAQgIODA9HR0WbT+/j40Lt3bxwcHHB1deWNN95IcXuJiIhIzrFlyxZKlChBr169cHR0BKBAgQIUKlToqed99+5d/vjjDwYNGoS9vT0Gg4ESJUoA4OTkxFtvvcWUKVNwd3fP0PzDw8MpUqRIsvaAgAAqV65MgQIFMBgM9O/fn0OHDvHgwQNcXFyoXr06BoMBBwcHmjdvTnh45mXNPXv2UK1aNby9venSpQsDBgygQIECFChQgP79+9O1a1c+++wzqlSpwu7duzNtuYBpPcqXL5/i8Pbt23PgwIFMXaaBdIb+yAdxjGxVmvbVCpraLt+Oprx7xq780spoNPL777/ToUMHAB48eMDHH39MVFQUV65c4bPPPiMxMRGAV155hX379iWbx4ULF8w2rru7O3Z2dqk+EBsXF8fq1avp2bMnixcvZu7cubzxxhv4+Phw//79VGv9559/qFChgllbpUqVuHTpUrrXOyV2dnbExsbi6OhouvApXLgwy5cvp3Tp0sDDK2dnZ2diY2OTfTX06HaoXLkyFy9ezJTaREREJGv4+fnRpEmTVIdfuXKFESNG0KtXL4YMGcKFCxfSPO+LFy9SvHhxDh48yNixYxk7dixnzpwBHt59Ti2c/ltcXBxz585lwIAB9OrVi59++gmAXbt2sWfPHpYsWcLAgQO5fPmyaZr4+HgePHhg+tvOzg4nJydu3LhhajMajfz9998sWrSI1q1bp3mdniQyMpKCBf+XZ+Pj47lz5w537twhPj7e1F6oUCEiIyMzbbkAd+7cIW/evKkOL1q06BNf2JI+D+/1pyv034tJoOO3x3i/WUlT8O/xw580r+DG4JdLZGJx5m7dukWePHlMXys1btyYLl26MGbMGMaPH8+IESMoV64cAGXLliUkJCTZPJKC8L+5urqmuiM3bNjASy+9RL58+YiLiyM2NhYnJye8vLxYs2ZNqrXevn0bJyenNC8nvcqVK0dAQACNGjVix44dJCYmEhQUxMCBA/H39+fixYucO3eO0qVL4+zsjLW1tdn0ERERZtshM2sTERGRrHH16lXy5Pl/7d1bTFTXGsDx/yA4JcJoEDzCqDGiD1XBCw5GtKQeohmpRlovKOqAJ+oRlcRoQTFUM028gMYYTVTGgug0hRBjEI2Geo2TNqmSCiKgPlQUxcvB8R37AAAIU0lEQVQMGdIwXGfY5wHZMtwvQ057zvo98DB7rb0WQ0i+tfe3vjWq2+vff/89MTExGI1GYmJiOH78eJ/vbbVaqaio4OXLlyQmJhIVFcW+ffuw2Wx9vkdOTg719fVkZGRw+vRpTCYTJpOJiIgIFi5cSGxsLOnp6U7pLMHBwTx58oSSkhKsVis//PADDofDKS7Zu3cvO3fuxGKxuCyVCVqD+fLyciorKzGbzRgMBiRJQpIkDAYDZrOZyspKysvLXfI2pT/ap7AP3qeCL/2+a8fA394isS6jiPApPiQsnOjCSX7i5ubWqUrNjBkzqKmpQalUEhgYKH/u4eGBw+HodA+VSsWff/7p9JnNZutypWWz2bh69SrR0dGdrn399dfcu3ev2xWYSqXqVHKpu3EGwsfHh4CAAF68eMHmzZvJy8tDo9GwbNkyHj58SFNTE99++y3nz5/nq6++6tTf29vbaX6unJsgCIIgCENj9OjRVFVVdXmtpqaGiooKcnNz2bt3L/n5+f3KMFCpVHh5ebFhwwZGjRqFRqNh3LhxPH36tM/3+PXXX+W4w9vbm+XLl1NYWNhjHz8/P7777jsuXrzIsWPHCAoKYsyYMU5xSWpqKnl5eURHR7Nt2zaXlLWsra2lrKyM169fExcXx5o1aygoKCA5OZnk5GQKCgpYs2YNcXFxvH79mvLycmprawc9bpvGxkaUSmW314cPH05jY6PLxmszoKWErdHB+sxi0tcHAciB/3S1F37eri4x1BroWq1WOa2murqa5ORkdu/ejVarJSUlRf5yKioq5Dy09iZMmCC/qoLWVa3D4ZB3pbeXk5PD0qVL5Sf2wcHBhISEAK1/iFWrVmE0Gruca8dxAJ4/f97lnAYqISGB33//nbCwMHJzcykpKWHjxo1IksSdO3eYPHkyzc3NREZGduo7fvx4ysrKnOY2ceJEl81NEARBEATXCwoK6nZzp6enJwBJSUkcOXJEDpT7Sq1WY7Va5VRpaM3l75gt0JPm5manTIeGhoZeKyQCaDQajh49ysGDB5k5cyYWiwV/f3+nNm17JQMCArrM5uivw4cP8/jxY7RaLQaDgfT0dHJzcwkPDyc8PJzc3FzS09MxGAxotVqKi4tJTU0d9Lht3rx5g1qt7va6h4cHdrudpiZXlsBXDCzo91IOw/ivGcRlFcufOVok/v3jkyGp0a9QKJg3b56cVpOfn8+mTZuYPXs2y5cvJzQ0FJPJBMC1a9eIiOhcAlSr1XLz5k0qKyvlqjyRkZGd3iBUV1djMpmIior69Ls5HE7/CEuWLOHx48ddrrhnzpxJXV2dvK/g7t27eHt7uzSw9vPzY+fOndy/fx+1Wk12djY//fQT586d4/bt20iSRFJSUpevh5YtW4bRaKShoYH6+np5gSMIgiAIwl/XypUrqaqq4sSJE/LT7pqaGsxmM0qlklmzZnHp0iW5fduDUnd3dzl4VCgUSJLkFNNA68PVKVOmyHFWVVUVFRUVcup0X8yZM4fs7GwkSaKpqYlbt24xf/78HvvY7XbevXsHtD79PnXqFJGRkXh4eFBVVcWzZ8+A1spFRUVFfPjwwSXxVFt1Q4VCQWBgICNHjkSn01FXV0ddXR06nY6RI0cSGBgox4kPHjwY9Ljtx9doND22mTp1KsXFxT226QtFu5/9PpzL+zN38uJDSPv5D34uswx6Mn21bt06tm7dyqxZs9i4caPTtdWrVwOtX2JpaSk7duzo1H/s2LEkJiai1+tpbm4mJCSEDRs2dGp38eJFoqOjnQ5FmDBhglPKkJubGzqdjszMTFJSUpz6KxQKDh06RFpaGhkZGajVapeW7Gzv0qVL2O129Hq9/JkkSVy/fp0VK1Z02SciIoL379+zZcsWhg8fTlRUFLNnzx6S+QmCIAiC4BpKpZIzZ85w7tw5tm3bRnNzM56ensTExLBo0SISExM5efIk8fHxeHp6smDBAr755humTp1KY2Mjqamp7NmzB61WS0JCAkeOHHE652fPnj2kpaWxfv16VCoVKSkpcpWgXbt2YbPZePv2rbypdvfu3U6LAp1Ox8mTJ4mNjcXT05PIyMhe4wuLxcKBAwewWq2oVCoWL17MqlWrgNZFy4ULF3jx4gUOhwN/f3/2798/4LKh7XV84FtbW4vFYpE3FVssFmpra4fsgNPCwkIUCkWPVYE+fPhAYWFhr4uD3n06k7dfh3OpPnPnyvYQ0gr+4MYT8yAn8UlfD+d69OgRer2etWvXsmLFCvm1UVNTE3l5edy4cYPDhw8PeMOFJEmsXLkSlUrVp00U79+/5/Lly0NwalrvSktLMRgMnQ7famhoIDU1lczMTBdvBBEEQRAEQfj7y8rKwmg08vnnn3PgwAF8fX158OABc+fOBeC3334jNDQUi8WCXq+nvLyc2NhYdDqdS8Z/9uyZvM80Pz8ff39/Jk2aRE5ODtu3b5fbBQYG4uPjM6ixpo34J4qPh3P1K+j/h0rJ9AAvbj+tHtQEOupr0A+tgXZWVhaPHj0iICCAlpYWampqWLBgATExMfKqdKC6eu3VHYVC8V8LrIuKinBzcyM4OLjTtStXrvDll192uV9BEARBEATh/90vv/zC2bNneffuHUFBQcyZM4cxY8YgSRJms5nCwkJKSkoYO3Ys8fHxhIWFDck8Xr16hV6vx263Ex8f3+/TjnszbUTEx6Bf0b+gf6j0J+hv43A4sFqtuLu791jCShAEQRAEQRA6amlp4eHDh5hMJkpLS7FYWtPWfX19mTZtGl988QUajeZvnTkxfUQEfHzS3++c/r+KYcOG4evr23tDQRAEQRAEQejAzc2NuXPnymk9/5sUclb/fwCdy6r2QNCSywAAAABJRU5ErkJggg==" } }, "cell_type": "markdown", "metadata": {}, "source": [ "# Aliasing e riferimenti\n", "\n", "Per il resto di questo notebook faremo molti assegnamenti di variabili. Si consiglia di eseguire il notebook una istruzione alla volta, e di guardare il contenuto delle variabili mano a mano che le istruzioni vengono eseguite nel tab `JUPYTER` del pannello in basso (si può premete `Ctrl-J` per far comparire il pannello in basso se al momento non è visibile).\n", "\n", "![image.png](attachment:image.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Assegno ad `i` il valore 5." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "i = 5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Assegno a `j` lo stesso valore di `i` (cioè 5).\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "j = i" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Incremento `i` di 2. `i` diventa 7, ma `j` giustamente rimane 5." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "i = i + 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Creo una lista `l` contenente le stringhe \"a\", \"b\" e \"c\"." ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": [ "l = [ \"a\", \"b\", \"c\" ]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Copio `l` in `m`, quindi `m` diventa `[\"a\", \"b\", \"c\"]`." ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [], "source": [ "m = l" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "E adesso succede una cosa strana: cambio il valore del primo elemento di `l`, e la modifica si ripercuote in `m`." ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [], "source": [ "l[0] = \"ciao\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Se invece cambio tutto `l` con un assegnamento, la modifica resta confinata alla variabile `l`, ed `m` resta invariata." ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": [ "l = [1, 2, 3]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Adesso le due liste sono separate. Nessuna modifica ad `l` può influenzare `m`. Se cambio il primo valore di `l`, `m` rimane fissa." ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [], "source": [ "l [0] = 333" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Facciamo ancora un altro esempio. Reinizializzo `l` e lo copio in `m`." ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [], "source": [ "l = [ \"ciao\", \"sono\", \"io\"]\n", "m = l" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Se aggiorno il valore di `l` con il metodo `append`, il nuovo elemento viene aggiunto anche ad `m`." ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [], "source": [ "l.append(\"xyz\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ma se aggiungo un elemento usando l'operazione di concatenazione e assegnando il risultato ad `l`, allora la modifica non si ripercuote su `m`." ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [], "source": [ "l = l + [\"abc\"]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Come è possibile spiegare questo comportamento ?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Quando diciamo che le variabili contengono degli oggetti, stiamo semplificando troppo. In realtà le variabili non contengono direttamente un oggetto, ma un `riferimento` a quell'oggetto, che possiamo pensare come una freccia dal nome della variabile all'oggetto che essa contiene. Tecnicamente, un riferimento è l'indirizzo della locazione di memoria dove risiede l'oggetto (ovviamente l'oggetto può occupare più locazioni se necessario).\n", "\n", "Lo spazio di memoria dove risiedono le variabili è solitamente chiamato *interpreter stack* o solo *stack* (in italiano, pila), mentre lo spazio di memoria adove risiedono gli oggetti è spesso chiamato *heap* (anche se questo termine non è standard in Python)." ] }, { "attachments": { "image.png": { "image/png": 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uYM+ePaoOhaKodoQm4GYihODHH3/E3r17wefzMWbMGMydOxfdunVTdWhy5eXluHDhAu7du4dHjx4hNTUVXbt2xYQJExAcHFzvVo1Uy/zwww/g8/lYvXq1qkOhKKodoQm4iWQyGVatWoVDhw7B0dERS5cuxYgRI1QdVpOIRCKcPXsWN2/exJUrVyCVSjF69GgMHz4cQ4cOBZtNx+K1RlhYGGxsbBAaGqrqUCiKakfob94mOHDgAGxtbREdHY3Lly8jMjKy3SRfANDQ0MCUKVPw008/ISsrC7du3QKPx8OmTZtgYmKC//znP9i2bRuio6NVHWq79Pr1a5iZmak6DIqi2hk6CKsBAoEAw4cPR1FREc6ePQtfX19Vh6QQjo6O+OabbwC8fY98/PhxPH78GNu3b0dJSQkCAwPRtWtXfPTRR3SD+SbIzs6mXyeKopqNPgHX4/Lly3BycsLgwYMRHx//ziTff9PS0kJISAh27dqFtLQ0JCUlYfz48UhISICPjw+cnJwwbtw4nD59GiKRSNXhtkkCgQDW1taqDoOiqHaGvgOuw1dffYWDBw/i5MmT6Nevn6rDUan09HScP38eP//8M/Ly8uDo6IghQ4bg008/pdOd/o+bmxtiYmKgoaGh6lAoimpHaAL+l8mTJyM+Ph4RERGwsrJSdThtSnV1NW7duoXNmzcjNjYWlpaWCAwMxIoVK8Dj8VQdnsq4u7sjLi5O1WFQFNXO0AT8fwghGDFiBIRCIS5cuABdXV1Vh9TmRUVFYc2aNbh//z569uyJ999/Hx9//HGHG1Xdo0cPxMbGqjqMRs2cORPh4eHNmoaWlJSEb775BjweD1paWtDW1gaXy4WRkRE0NDQgkUigpaUFXV1dFBUVgcvlIjc3FzKZDJWVlSgvLwchBKWlpdDQ0AAhBEVFRbC2tkZubi4cHR2RlJQEX19fpKWlwdvbGyUlJejatSu0tLRga2sLY2Njpcyrpyhlo9/VeDvFaNiwYVBXV8fVq1c7XAJpKV9fX1y6dAkSiQTHjx/Hzp07ER4ejiVLlmDevHkwMjJSdYhK8c+yokwjhCAzMxOxsbFIT0/Hq1ev8Pr1a7x58walpaUQCAQQiUSQyWQghEBdXR0cDgdmZmaYPXs2HBwc4OnpiR9++AEff/xxg23l5OTg4MGDSEhIgL6+PoyNjVFdXQ0+n4+CggJIpVJUVlaioKAAGhoa4HK5KCgogL29PSorK6GlpQU9PT2wWCzo6OjAwMAAOjo6YLFYMDAwgKGhIcRiMdTU1AAAxcXFSEpKglAoRExMDHg8HhITE8Fms5GXlwdtbW1wOBx0794dYrEYgwYNgqamJry8vODu7k5HoVPtUod/AiaEYOTIkWCxWLhw4QJdMaqVEhISsHjxYjx58gSBgYHYu3fvO79Mo6urKxITExVaZ25uLi5evIhbt24hKSkJ+fn5YLPZMDAwgLm5OWxsbGBnZwcrKytYWFjAyMgIhoaGMDY2BiEEUqkUhYWFiI6OxqVLlxAdHS1/ChWJRAgMDMTvv/9eo82YmBh8/PHHiIuLAyEE+vr6cHBwwLFjx9ClSxeF3l9zicVipKSkgM/n4+bNmxAKhXj8+DEyMzMhFApRVFQELS0tdO7cWf60zuFwoKmpCTU1NUgkEhQXFyMzMxNVVVUYMmQIDh8+rNJ7oqgOn4CnTJmC/Px8XL9+nSZfBcrMzMSGDRtw+vRpzJkzB+Hh4Q2ugd1eEULg5uaG+Pj4VtVTWVmJc+fO4fz583j06BG0tLTg4eEBf39/9O/fHz169Gh1N6yDgwNevXqFvLw8eHp6Ql1dHenp6fIenx9//BErVqxAXl5euxxQ9vLlS2RkZCAnJwfZ2dkoKChAVVUVysvLIZPJUFJSgqqqKlhaWuLcuXOoqqpSdchUR0c6sHnz5hFvb28ikUhUHco7q6CggAwdOpSYm5uTzz//nIhEIlWHpFAVFRXEzc2tRddKpVJy+PBhMmjQIGJlZUVGjBhBDh48SEpLSxUcJSFDhw4lZmZm8q//oUOHCIfDITExMfIyx44dI3p6egpvuy3i8XgkLS1N1WFQHVyHfdm5cuVK/P333/j777/l76EoxTMzM8Ply5fx559/IiMjA5aWltizZ4/S3psyraysrNl7Ad+9exfjx4+Hvb09Tp8+jYULFyIzMxN//PEHPvzwQ4V32WdlZeHq1avg8XhwdXWFrq4uPvvsM3z55Zfw9PSUlxMIBB1msJOxsTGioqJUHQbVwXXIBPzLL7/g8OHDuHr1arvsamuPPD098euvvyIyMhK7d+9G165dcejQIVWH1WpCoRB6enqNlhOJRFi1ahWcnZ2xYMECDB48GAkJCbh06RJGjx7N6IdAY2NjDBw4EG5ubpgzZw6ePHmCkpISrFy5ska5Bw8eQFtbm7E4/u3JkyfQ19eHpqYmLCwscPXqVaW17eXlheLiYqW1R1F16XAJOC8vD59//jlOnz4NCwsLVYfT4bi7u+P58+dYuXIltm7dCmdnZzx69EjVYbVYVVVVgx/iiouLMXv2bHTp0gUZGRm4du0aYmJiEBoa2uwn55bS09PD1atXce7cOXzxxRdwcXEBAGzevBk+Pj64dOkSgLc/G/r6+kqJCQCmT5+ODz/8ENXV1Zg/f758xTVl0NDQQHJyslLaoqj6dKgETAhBUFAQVq9eDT8/P1WH06FNnToVsbGxWLt2LYYOHYpZs2bh5cuXqg6r2crLyyEWi2sdFwgEmDNnDnr06AELCwskJibi559/ho2NjQqirNvnn38OHx8fTJgwAVwuF7Nnz0Z1dbXS2l+2bBmeP38O4O3qc4cOHUJISIhSYrCwsGiX32/Uu6VDJeAvv/wSXC6XbhvXhkyaNAnZ2dkQi8Xw9vbG8uXLQdrRwPzy8nJoamrWOLZlyxZ069YN+vr6SEpKwrp165T2tNscZ86cgampKSoqKtC/f39Mnz5dqV/7WbNm4ebNm/J/T5gwAVZWVliyZAnjbXfp0gVaWlqMt0NRDekYIy4AJCcn46effmr1dBFK8bS0tHDs2DHExsZi1qxZcHJywokTJ+Dt7a3q0BpVWloqXzUtLS0NkydPhr6+Pu7evQtbW1sVR/f/iUQi+Vaajx49QmpqKl6/fg2pVIqvv/4a06ZNk3dFq5K3t7dS3gVXV1fT5UMpleswT8ChoaFYtGgRTExMVB0KVY8ePXrgyZMnmDlzJoYNG4Zx48ahrKxM1WE1SCQSwdTUFAcPHkT//v0xd+5c3Lhxo00k34cPH2LmzJmwt7eHrq4uJk6ciFOnTkEqlSIoKAhjxowBm81GREQEpk2bhgULFqhkFPSNGzewadMmzJkzB7/99hsmTpzIeJudOnWCRCJhvB2KapCKp0EpRUREBHF1dSUymUzVoVBNlJ2dTUJCQoi+vj45ffq0qsOp1759+4i9vT3x9/cnfD5f1eGQN2/ekEWLFhELCwuip6dH+vbtS7Zs2UJycnJqlfXw8CAcDodwOByycuVKkp6eTrp166b0mO3s7AgAwuFwyOTJk5XS5u3bt4mzs7NS2qKo+nSIBOzh4UHOnTun6jCoFoiOjiZmZmbkvffeI7GxsaoOp4aUlBRiYmJC+vbtq+pQSF5eHpk4cSLR0tIiPXv2JAcOHCBSqbTBa+zs7IihoSF59OgRIYSQyMhI4uXlpYxwa5FKpWTr1q3E2NiY2Nvbk+zsbEbbi4qKIiYmJoy2QVGNeee7oI8cOQIWi4Vx48apOhSqBXr37o2cnBw4ODhgwIABCA8PV3VIAIDDhw9j8ODBGDp0KIYOHaqyOKRSKb744gs4ODigoKAAjx49wpMnTxASEtLopiIZGRkoKSlBr169AAD5+fkq2wWMzWbjs88+Q0FBATp16iSfKsUULpeLyspKRtugqMa88wl41apV2LJli6rDoFpBXV0de/fuxdWrV3Hq1Cl4eHggLS1NZfEsX74c33//PW7fvg0jIyOV7cTz6tUrdOnSBSdOnMDNmzcRGRkJNze3FtdXWFhYa0S3shFC4OrqCpFIxGg7PB6PvgOmVE4lo6Bfv36NwsJCuLm5QSKRIDExUT6dw9jYGObm5gr5RXDixAloaWlh0KBBCoiaUjUvLy8kJSVh/vz58Pb2xrx587Bu3TqlbqIxc+ZM5OTk4N69e9DT04NEIoGpqanS2v/Hb7/9hunTp2PGjBnYtWuXQr4GfD4fUqlUAdE1jBACe3t7CAQCcLlcmJmZQSQSoaioCPn5+dDW1sYPP/zAaAxcLhcSiQQymYxuP0qpjNIS8MWLF3H48GHo6uqCx+MhMzMTd+/eRXFxMdhsNvT09EAIgUwmg1AohLq6OkxNTWFpaQlra2sEBARgzJgxsLe3b3KbK1euxLZt2xi8K0rZ1NTUsHfvXsyYMQMLFizAuXPncO3aNVhbWzParlQqxcSJE6GhoYErV67If2kXFhYq/Rf4mTNnMGvWLOzYsQMhISEKq7e0tBS5ubkKq68+LBYLjx49wn//+1+kpKTA0NAQhoaGcHV1xfDhw9GzZ0/GY+BwOGCz2eDz+TA2Nma8PYqqE9MvmZOTk4mXlxcJCQkhhYWFJDk5mRgbG5POnTuTtWvXkrKysjqvy8/PJ5GRkWTr1q3kgw8+IM7OzkRPT4/o6+uT4OBgcuPGjQbbvX//PnF0dGTilqg2QiKRkA0bNhAdHR2yf/9+xtoRiUQkODiYzJgxo9a5wMBAcvPmTcba/rfk5GSio6NDtm/frvC67969SwwMDBReb1ulpaVFHj9+rOowqA6M8QTs4+ND7t+/TwghpKSkhBgZGZGFCxe2uL779++TqVOnEkNDQ+Ls7FzvFBVvb2+ybdu2FrdDtR+JiYnEysqKBAYGkszMTIXWLZFISFBQEAkJCanz/HvvvUeePn2q0DbrU11dTSwtLcmiRYsYa+OTTz7pMDMG1NXVyXfffafqMKgOjNG+s8TERPB4PPm6y5MmTUJISEiruoX9/Pxw9OhRFBUV4f3338ecOXMQFBRUY0RjdXU1srKy8Omnn7b6Hqi2z8XFBRkZGTA3N4e3tzeOHTumkHoJIRg7dizs7Oxw4MCBOsuwWCylbWDw4YcfwtjYmNH3owEBAQgJCYGOjg709PTQqVMneHt7Y/z48ViyZAl27dqFqKgoCIVCxmJQFkdHR7ocJaVSLEKYW/x1/fr1kMlk+PLLLwEAf/31F4YMGaLQNnJychAYGIjq6mrEx8dDS0sLW7duxYULF2qsM0t1DOfPn8fs2bMxZswY7Nu3r1Xb/E2fPh1sNhs///xzvWV69+6NM2fONGtsQkvcvXsX7733HpKTk2FlZcVoW/8QiURITExEUlISUlNTkZKSgrS0NKSlpUEgEIAQAgsLC+jq6sLExAQeHh4QCoVwcXGBtrY2dHR0YGlpCbFYDBMTE7BYLHC5XJSVlUFfXx/l5eXQ09ODUCgEh8ORt6mtrS0/98+fFRUV0NbWhkwmg1gshra2tryef/4UCAQwMDCQ/1laWgpDQ0Pk5ubKy2tqasLAwABisRgaGhpgs9kwMDCAkZERTcaU0jGagKdPn46JEydi5MiRTDUBAJBIJHB1dYWJiQkePHgAPz8/rFixAqNGjWK0XaptevPmDQYNGgSZTIbTp0+ja9euza4jPDwcUVFRuHr1aoMjjHv06IGrV6/C3Ny8NSE3ysXFBcHBwYyPDm4OgUCAly9f4sWLF4iLi4OmpiaePHkCmUyG0tJSFBcXQ09PD69evYKRkRFyc3NhZWWFzMxMGBoaoqysDDo6OqiqqqqRgPX09MDn82FiYoLCwkKYmZmBz+dDR0cHUqkUEokEOjo6KC0thbGxsbxMUVERjI2Nwefz5YnY0NAQfD4fPB4PJSUl0NLSAiEEQqEQGhoakMlkqKiokCf18vJyFX9VqY6E0VHQOjo6sLOza7BMcXExjIyMWtWOuro67ty5AwcHBxw/fhwVFRU0+XZgxsbGePr0KebPn49+/fph6dKlCAsLa/L1J06cwB9//IE7d+40Or1HJpMx/uS0b98+CASCNjef3cDAAO7u7nB3d8ekSZNUHU6L5eXl4caNGy36oEZRrcHoO+CXL182OKHezs4ONjY2MDIyavUnT0tLS0ybNg1hYWHo2BaZKwAAIABJREFU3r17q+qi2j8Wi4Xdu3fjl19+wYEDB+Dv7w+BQNDodQkJCVi5ciWOHj0KQ0PDJrXD5FaDMpkMa9euxRdffNGq7nSqfpaWlpg6dSq8vLxUHQrVwTA+gbGuzcoB4Ouvv0ZlZSXKy8thb28Pf39/zJ07F1paWjA1NUV+fj6At92JP//8M6Kiohpta9OmTcjLy8OKFSsUeg9U+xUcHIyYmBh07doV1tbWuHHjRr1lxWIxpk6dilWrVqFHjx5Nqv9/u0+ZcPToUQDAwoULGWuDoigVYXKI9bRp08iDBw/qPGdjY0OOHTtGCHk7vUJHR4doamqS58+fEz8/P2Jra0seP35MtLS0iIGBAdHS0iI8Hq/RnXEsLS3J6NGjFX4vVPt38eJFYmRkRCZNmlTnzkUhISFk/vz5zarTwcFBUeHVqVu3bmTt2rWMtkFRlGow+gTMYrHqXPBcLBZDIBBgypQpAAANDQ0MGjQIYrEY7u7uuHPnDoqKijBu3Di4ubmhtLQUVVVVCA0NxdSpU/Hdd9/V22ZQUBBevHjB2D1R7dfw4cORlZWFqqoqODs715iu9PPPPyM+Ph47duxoVp0ymUzRYcqlpaUhKysLy5cvZ6wNiqJUh9EEXF1djeLi4lrHf/jhB9jY2NQ4Nm7cOJD/G5Ctrq6OiRMnIjc3t8YI6m+++QZLly5tsIt50qRJKCoqUtAdUO8aPT09/P777/jpp5+waNEijBgxArGxsVizZg2OHz/e7DWVtbW1GYr07Wuavn37QkNDg7E2KIpSHUYTsKamJkpLS2sd379/P+bNm1fjWEZGRo1/r1u3DhKJBJaWljWOr127FjKZrN6txP7zn/+goqJCnswpqi6jR49GZmYmqqur0atXLwwZMqRFc3nrG+OgCLdv36aLyVDUO4zRBGxoaIjCwsJax11cXPDJJ5/UKvvPvqQA5Ik3Li6uRjmZTIb58+fXO/JUV1cXbDYbr1+/bm341DtOT08Pfn5+8Pb2xrlz5zB8+PA6e2zqU1lZydhGDDk5OXjz5g2CgoIYqZ+iKNVjNAEbGxvXubvKhQsXah1bsmQJoqOjaxxzc3Ortdk5h8Np9D2dpqZms36RUh1TTEwMzpw5g9u3b8t35enSpQuOHz/epOtzcnLA5XIZie369etwcnJidIQ1RVGqxWgCdnBwqNW13BzPnz/HsGHDmn2dTCajv7ioBgmFQkycOBEXL16Euro6DAwMcPz4cZw+fRoLFy7EyJEj633N8Q8+n9/oQjMtdeXKFXTr1o2RuimKahsYTcDe3t5IS0tjsolaRCIRqqurGd8flmrfJk6ciLlz56JLly41jgcGBiIrKwtCoRCOjo4NzhtOTk5mrAv6yZMndGEIinrHMZqAXV1dUVJSAolEwmQzNaxbtw5cLpeOHKXqdfz4cZSWlmLJkiV1ntfV1cXVq1cRHh6OcePGYfny5XUO6ktLS4OpqSkjMfL5fHh7ezNSN0VRbQPj84BtbW1x+PBhJpuRe/bsGTZu3CjffYmi/q20tBTffvstdu7c2eiUowULFuDhw4e4cOEC+vTpg7y8vBrny8vLawwcVKTKyspaT+cURb1bGF+K8rPPPsPGjRuZbganTp2Cr68vgoKC6LJ9VL2WLFmCIUOGNHm9cGdnZ7x48QK2trbw8vLCX3/9JT+Xm5sLY2NjRuIUCoXg8XiM1E1RVNvAeAKeNGkSCCFYunQpI/Wnp6cjICAAc+bMwYYNG+ocYU1RwNuRxdHR0Q2upFYXNTU1nDhxAsuWLcOkSZOwevVqAEBKSgpjg7CkUindn5ai3nGMbkf4j4iICPj7+0Mmk2HLli3NXm2oLpcuXcL69esRExODiRMn4vr164yuSkS1b9XV1ViwYAEiIiJa/P33+eefw9vbG1OmTMHjx49RWlrKWDcxm81mbIAXRVFtg1J+wp2dnZGamor79+/Dzs4OR48ebfYaujKZDLdu3cL48eNhYmKC2bNnw8/PD3l5eTh8+DBNvlSDNm7ciOHDh7dotav/1a9fP8TExKCkpASZmZlITU1VUIQ1yWQySKVSRuqmKKptYBElr9l4+/ZtLFiwADk5OejSpQt69eoFDw8PWFlZgcvlQltbG0VFRXjz5g0yMjKQkJCAuLg4pKSkQE9PDwMGDMCyZcsYG/xCvXuSkpIwYsQIJCQkQF1dMZ0+hBDweDywWCx8++23mDt3rkLq/YempiZKSkroB0uKeocpPQH/o7S0FKdPn0ZkZCRSU1NRWlqK6upqiMViaGlpQUdHBxYWFujSpQu8vb0xbNgwmJubqyJUqh0jhMDd3R1HjhxR6Ie27OxsDBkyBGvWrMG8efMwYsQIHDx4UCGvV4C3U6EyMjJgZmamkPooimp7VJaAKUoZtmzZgvT0dOzatUuh9d6/fx9bt27F6dOnkZGRgZEjR0JLSwuXLl1SyAdFfX19PH78GM7OzgqIlqKotoiO8qDeWW/evMHOnTuxdu1ahdedlZUFPT09AIC9vT2ePXsGOzs7eHp64vr1662u39jYmG4oQlHvOJqAqXfWpEmT8MUXX8DIyEjhdT958qTGk66amhrOnj2LBQsWYNy4ca2e+25gYAA+n9/aMCmKasNoAqbeSefOnYNEIsHHH3/MSP2FhYV1bpYQHh6O33//Hd9//z3GjBmDioqKFtVPCEFCQkJrw6Qoqg1TyjxgSjFkMhni4+MRGxuLmzdvgsVi4eHDh2CxWGCz2RAKheBwOKioqIBMJkPnzp1RWFgITU1NGBgYgMPhoE+fPuByuQgICICXlxc0NTVVfVsKJ5VKsW7dOmzdupWxNsrLy+t9PztgwACkp6cjMDAQ7u7uOHv2bLMHgHXu3BlFRUWKCJWiqDaKJuA2LC0tDbdu3cJvv/0GgUCAgoICdOvWDVZWVvDx8YGvry86deoEExOTRuuqrKxEfHw8MjIy8OzZM3z99deoqqpCXl4eHBwc4OHhAW9vbwwdOhQGBgZKuDvmfPPNN7C1tUX//v0ZayMjIwMWFhb1ntfV1cX9+/exfPlyDBw4EN9++y1CQ0ObXL+9vT1EIpEiQqUoqo2io6DbkNTUVBw8eBAZGRmIiYmBo6MjnJ2dMXz4cPTt25expQnj4uIQFxeHc+fOoaCgAIWFhXB1dcWkSZMwePDgdjUVJicnBwEBAYiLi4O+vj5j7Tg6OiIlJaVJq1XdunULEyZMQEBAAI4ePdqkuObPn4+srCxcvHhREeFSFNUG0QSsQoWFhbh58yb27duHkpIS6OrqIjg4GCNGjGjyZgFMkEgkiIiIwLNnz3DixAloaGhgxIgRGDduXJvfo/ajjz6Cp6cn5s+fz2g7jo6OzdrrurKyEkFBQcjMzMSvv/4KHx+fBsuvXbsWly9fxr1791obKkVRbRRNwEr28uVL/Pnnn9i1axc4HA4GDhyIsWPHIiAgQNWh1SsvLw+RkZH44YcfIBAIMG7cOMyaNQtOTk6qDq2GR48eYfr06YiPj1fYghh1kUql8PDwQFxcXLOv/eabb7BhwwaEhYXhq6++qrfcqVOnsHfvXty8ebM1oVIU1YbRBKwEpaWliIiIwJYtWwAAEydOxLRp09CpUycVR9Z8fD4fFy5cwJYtW6Crq4sFCxZg8uTJUFNTU2lcUqkULi4u+P333+Hm5sZoW/n5+QgKCkJsbGyLrk9JScGAAQNgbW2N69evQ1dXt1aZEydO4Ouvv0ZycnJrw6Uoqo2i05AYFBMTg5EjR8LPzw+JiYk4duwYHj16hOXLl7fL5AsAPB4PM2fORGxsLHbu3IknT57AxcUFS5cuRVlZmcri2rRpE0aNGsV48gXeDsBqzftlJycnZGRkwMTERL6Ix78ZGRmhqqqqNWFSFNXG0QSsYBKJBDt27ICnpyc2btyIkJAQJCQkYPXq1XBxcVF1eArVq1cvbNmyBc+fPwebzYafnx9mz56NgoICpcaRmZmJXbt24ZtvvlFKewUFBa3uftfQ0MDFixexePFi9O3bF4cPH65x3szMDDo6Oq1qg6Koto0mYAURCoUIDw+Hl5cXnj59iuvXr+PkyZMYO3asqkNjnLa2Nr777js8e/YMAwcOREBAAEJCQlBSUsJ424QQjBo1CkeOHFFawiouLlbYxiBffPEF9u7di4ULF2LlypXy4yKRCG/evFFIGxRFtU00AbeSSCTCqlWr4OnpCXNzc9y9excHDhyAsbGxqkNTOnV1dUybNg0pKSlwcHBAQEAAPv30U5SXlzPW5q5du+Dt7Y2BAwcy1sa/vXjxAhoaGgqrb+rUqbh16xb27NmDCRMmgBACTU1NhW2dSFFU20QTcAsRQrBjxw706tULxcXFePbsGRYuXMjo3NP2gs1m48svv0RMTAy6du0Kd3d3fPXVVwpfWCI9PR3fffcdtm/frtB6G5OXlwc7OzuF1tmzZ0+kpKTg2bNn8PLygkQioXsBU9Q7jibgFvjrr7/g5eWF9PR03LhxA9u3b38nl3RsLU1NTYSGhiIhIQF5eXnw8PDA7t27FVK3TCbD2LFjceLEiTpHETNJLBYzMtiLy+UiLi4OPB4Pw4YNo5sxUNQ7jibgZigtLcXw4cOxbt06/Pbbb9i6dStMTU1VHVabp62tjf379+PSpUu4f/8+evbs2axFLOqyadMmeHl5oU+fPgqKsuny8vLA4/EYqVtTUxM3btxAQEAAysrKcOvWLUbaoShK9WgCbqLjx48jICAA06dPx+3btxXeBdkRODg44JdffsHevXsRHByMDRs2QCKRNLuee/fuYe/evfjxxx8ZiLJx+fn5jP//h4aGgsvlIjg4mJH9jCmKUj2agBtRXV2N0aNH48iRI3jw4AEmT56s6pDaPV9fX7x48QKxsbHo378/Hj582ORrKyoqsHDhQly4cEGhA6Ga459BUkyqqKiApaUlLl68iO+//x5BQUGQSqWMtklRlHK16QScm5uLJUuWwMvLC5aWljAwMIChoSE6deqE9957Dzt37mR0qktBQQH8/PwwfPhw/Pnnn3SAlQJxOBycOHECS5YswZQpU7B58+YmXTd37lz4+vqqbK1sQohSpjuJxWJwuVwMGjQI6enpSE1NhY2NTau77imKajvaRAK+d+8efvjhB/m///zzT7i6usLR0RGRkZEYPHgwdu7ciWvXruHChQsIDw8Hl8vF5s2bYW5uju7du2Pbtm2QyWQKiyk+Ph79+/fHjz/+yNim7hQwbtw4PHr0COfOncOoUaManPu6c+dO5ObmYufOnUqMsKbCwkKFfp/VJz09XT5qnMfjIS0tDV5eXujevTt+/fVXxtunKEoJiApJJBLy1Vdfkf/+97+ksrKSpKWlkR49ehADAwPyxRdfkMrKykbryMrKIvPnzydcLpfo6emR1atXtzqu+Ph44u7uTh4+fNjquqimW7RoEXF2diZnzpypda6wsJC4urqSpKQkFUT2/12/fp0MHDiQ8XZ27NhBZs2aVev4nj17iKamJpk/fz7jMVAUxSyVJeDKykoyc+ZMcvPmTUIIIQsXLiRaWlpk9uzZRCgUNngtn88nixYtIikpKTWOf/fdd0RLS4t4eHgQsVjcoriysrKIh4eHPC5Kua5du0bc3NzIzJkziUQiIYQQIpPJiIeHBzl58qSKoyPk9OnTZPHixYy3M23aNDJs2LA6z0VHRxMTExPSo0cPUlFRwXgsFEUxQyVd0JWVlZg3bx42bNiAAQMGoFevXjh+/DgiIyOxf//+Bge4VFdXw93dHb/99hu6detWY3GHZcuWITMzEy9fvkTv3r2bHZdIJMLo0aMRHh6OAQMGtOTWqFYaPHgwoqOjIRQK0b17d6SlpWH9+vXo27cvJk2apOrw8OLFC6W8A+bxePVOserduzfS09Oho6ODzp0748aNG4zHQ1GU4ik9ARNCEBoairCwMFhaWkImk2H48OHIzc2Fr69vo9d/8MEHeO+995CVlQVTU1P88ccfNc6bm5sjNjYWiYmJzZ6+ERwcjLlz5+L9999v1nWUYmlra+PkyZNYsmQJ+vXrhy1btjR5kBbTnj9/DkdHR8bbiYuLQ2lpab3n9fX1cf/+fXz22WcYPnw4Pv30U8ZjoihKsZSegNevX48RI0aga9eubwNgs7FmzRpwOJxGr83OzsazZ8+wY8cOAICnpyeePHlSq5yVlRW+//57rF+/vsnrEIeGhsLKygrz5s1rxt1QTJo8eTI4HA7c3Nzwn//8B8XFxaoOCVVVVS3qXWkuiUSCbt26NVru66+/RmRkJE6dOgVnZ2dkZmYyHhtFUYqh1AT84MEDFBUVYcKECS26/vPPP8ewYcOgp6cHALC0tEROTk6dZUNDQ2FhYYGZM2c2Wu+5c+cQExODQ4cOtSguihmLFy/G7NmzcefOHcyZMwdubm6IiIhQaUy5ubmwtrZmvJ2ysrImr7Lm6+uL7Oxs2NrawtXVVaWjxCmKagZlvWwWCoVk6NChLR4cVVFRQWxtbYlAIJAfCw0NJTNnzqz3muvXrxMNDQ3y5s2bessUFRURJycnkp+f36K4KGbs3r2b+Pj41DiWkZFB3NzcyPjx41X2/2Vvb6+UdszMzEhUVFSzrzt48CDR1tYm/v7+jQ5mpChKtZT2BLxmzRpMmzatxVusnTt3DjY2NjUWwxCJRA0+jQwaNAgODg4NDt4ZPXo0vvvuO4Xt70q13q1bt7Br1y5cuXKlxnE7Ozs8f/4cvXv3Rs+ePbFnzx6lxiWRSMBmK+dHRl1dHba2ts2+7sMPP0RaWhpycnJgZmZW5ysaiqLaBqX8NikvL8e9e/cwderUFtdx6dIlLFu2rMax169fN7om77FjxxAZGYmkpKRa57Zt2wZzc3OMGTOmxXFRilVZWYmFCxdi48aNMDQ0rHWexWIhLCwMjx8/xqFDh9CnTx+lbViQm5vboqTYEsXFxXXef1NYWloiKysLgYGB8PX1xeLFixUcHUVRiqCUBLxt27ZWr6F89erVWlODHj9+DHd39wav8/LygoeHByZOnFjjeGVlJXbt2oWjR4+2Ki5KsYYNG4Zp06Zh+PDhDZaztLTEw4cPMXv2bISGhiI4OLjBVbQU4fnz500aLNhaEokELBYLWlpararn3Llz+Omnn7B7925YWFjg77//VlCEFEUpglIS8LVr1zBjxowWX5+RkVGr+/nNmzcQCATw8fFp9Prz588jISEB0dHR8mOffPIJZsyYQTc9b0PWrFkDW1vbWj0dDQkJCcGzZ8/g4+MDNzc3hIeHo7q6mpH44uPjlTIFqbi4WGHfl7NmzUJxcTFsbGzQv39/mJuby7v2P/rooxa/EqIoqvUYT8ACgQAcDqdVv1Bu3rxZa//VY8eOYfDgwWCxWI1eb2Vlhe7du2PhwoXyY0+ePEF4eHiLY6IU6/Hjxzh27FiLRvCqq6tj9erVeP78OSorK2Fvb4/du3crfM3myspKeHh4KLTOumRnZyv0SVtXVxcPHz5EamoqeDwehg4diu3bt+PgwYOQSqWoqKhQWFsURTUd4wn4/v37jXYTNyY9PR3e3t41jp04cQLDhg1rch3Lly9HbGwsACAiIgLBwcFNSt4U8/h8PsaNG4eLFy+2ascpU1NTbN26FVFRUThx4gR69OiBLVu2gBCikDgTExOhq6urkLoaIpVKGXnXbG9vj8TERHTq1AmfffaZ/APK48ePFd4WRVGNYzwBR0VFtXrruMLCwhpPwPHx8UhJSUFISEiT6xg/fjxEIhGEQiFcXFzo028bQQjB2LFj8cMPP8DJyUkhdVpbW+POnTs4fPgwIiMjYWNjg9OnT7f6ifjVq1ewsbFRSIwNSUpKAp/PZ6z+qVOn1vhQsmvXLsbaoiiqfown4OTk5Fa/N3v58mWNd1UzZ85EWFhYs6aEqKurQ11dHYmJiXB0dGzxCFNKsTZu3AhTU1OMHTtW4XX37t0bf/zxB/744w8cP34cjo6O2LRpEyQSSYvqU1dXV0oCrqqqatIqWC3x3nvvYdOmTTV6f86cOVPnspfZ2dkICgpCv379MGXKFHz77bc4f/48UlNTa6zBTlFUyzA+AkMgEMDMzKxVddjY2MjfIZ88eRJv3rzBokWLml2PhoYGcnNz4enp2ap4KMW4fPkyjh07hpiYGEbb8fT0xPnz5/Hy5UvMmTMHe/fuxYwZMxAeHt6sQUglJSUwMDBgMNK3cnNzGRkctX//fty4cQMsFqtWb0B8fDz8/f1rHBOJRNi8eTO4XC5SUlKQmJiIa9euYd++feDz+SCEQCKRyD/QiMViGBoaoqKiAlKpFCwWC2pqapBKpTAyMkJRURHEYjHMzMxQWloKV1dX5Ofno0uXLhCJRLCysoKBgQH09fVhZmYGbW1tmJubQ09PD4aGhtDX1weXy1X414WiVIXxBCyVSlv9Do7FYiEhIQGVlZVYuXIl1q9fr5TpIBRzYmNjsXjxYty+fVtpI3FtbGxw5coVxMXFYefOnbCxsUF4eDg++ugjaGhoNHp9aWmpUnpOUlNTGUn0ycnJkMlktcY+BAYG1kq+AODg4CD/u42NDQYPHqywWMrKylBVVYXc3FxUVlYiOzsbfD4fpaWlSE9Ply8mwuFwkJOTA0IIBAIBqqurIRaLIZFIYGhoiJKSEpiYmKC8vBy2trYoKCiAq6srcnNz4eTkhMrKSnkCLysrQ7du3ZCXlwcPDw8UFRXBxsYGGhoa0NLSgqmpKVgsFkxNTaGmpgYej0dHiVOMYvy7S0dHByUlJa2qo0+fPti4cSPCwsJgZ2fX4jnFhBA67agNEAgEmDdvHjZt2tTq3pGWcHd3x969e7Fy5UrMnj0b27dvxwcffICVK1c2+FqDzWYrZSUsDQ0NRjZ8OHDgANTU1ODl5QWJRAI3Nzds3LgRnTp1qrN8QkICSktL4efnp/BY9PX15U+6rSWRSMDn88FisZCfnw8NDQ1kZmbC0NAQOTk5YLPZ8mSvq6srT/hJSUnIyMhAYWEhSktLoaOjg8TERFhYWCA9PR08Hk++ohifz4eGhgZYLBaEQiHMzc1RUlICe3t75ObmwsbGBtXV1dDW1oaJiQny8/PRs2dPpKamwtvbG1lZWfD09ASfz4ejoyM4HA5MTU1hamoKfX19mJiY0GTfATH+P96pUydkZ2e3qo4pU6bgk08+wcmTJ5GVldXiemQyGX33q2KEEEyZMgVBQUEYOXKkSmPp1KkTLl++jISEBHz11VewsbHBjh07MGbMmDpHyLd2YYymioqKatLWnM117NgxDBgwoMn3IZFIcPToUUYSsCKpq6vLN64wMTEBADg7OzPaZlVVFcrLy6Guro7i4mKwWCwIBAJUVVVBTU0NL1++BJfLRefOnWFubo7i4mJUV1cjLS0Nr1+/Rnp6OgghKCkpQXFxMSQSCcrKyqCjo4PKyko4ODigrKwMnp6eKCoqgq+vL16/fg0fHx+Ul5fDzc0NbDYb1tbW8m57pu+3rKwMHA4HxcXFEAqF0NDQgEAgQFlZGdTV1SGVSiESiUAIAYvFgrq6uvxDq6WlJezs7OiHjH9hEUXN0ajHjh07UFRUhNWrV7e4jqdPnyIgIACWlpZITk6Gmppai+rR0NBAUVGRUt7jUXWbPXs21NXV8eOPP6o6lFpevHiBTz/9FPn5+Zg/fz7mz59f47ytrW2rPgA2lZOTE37//XfGBmI1lUgkwpQpU3D27FmVxtHRiEQi8Pl8vHr1CmKxGPHx8dDW1sajR49gYmKCqKgoWFhYyP+dnJwMHR0d+SsSPp8PHo8HgUAAU1NTFBcXg8fjyf8sKSmBvr4+ysrKoKuri9LSUshkMmhqaspXYROJRDAyMkJxcTEMDAwgkUggk8lgbW2NgoIC6OrqwsTEBMXFxWCz2dDX14dUKoVYLIZYLAaLxYJYLEZlZSVSU1NBCMGyZcuwceNGVX952xTGE/DTp08RHh6OS5cutej6wsJC+Pj4YN26ddi8eTO0tLRw8+bNZj+NJCYmwsPDg7FVkqjGff3110hMTMTJkyfb9Bzs58+f45NPPkF+fj42btwon8Lm6uqK9PR0xts3MDBATk4O4081jSGEoF+/fu12Ccvq6mpwOBylbaDRFgkEAkilUgBvB8lxOBz5n5qamtDR0WE8hq5duyIhIYHxdtojxr8zPT09kZqa2qJrKyoq0K9fP0yfPh1Tp05FdHQ09PX1YW1tjY0bN9ZawSc1NRUBAQH45ZdfatW1du3aJu+vSinetWvXcP36dezfv79NJ18A6N69O/7++28cOHAA+/btg4uLC3bu3AlLS0vG2y4sLAQhROXJF3g7gPLVq1eqDqPF9uzZ0yZ7WpTJwMAAPB4PPB4PZmZmNf5URvIF0OIey45AKR8Nu3XrhnPnzjXrmqKiInTv3h2jRo3C2rVrAbx913PlyhXs27cPR44cgampKaysrODs7Axzc3P4+vrCx8cH06dPr1VfREQEPvzwQ4XcD9U8cXFxCA0NxYULF9pEYmmq/v3746+//sL58+dx9OhRPH78GNu2bWN0DmxmZmarV45TFHV1dYUv56lMXbt2xZ07d1QdRoenrETfLilj0+GHDx8Sb2/vJpd/+fIlMTY2JmFhYQ2WKysrI9evXycnT54kz58/r7fcwYMHiZaWFpFIJE2OgVKMrKws4uDgQLKyslQdSqtcv36d9O7dm8yZM4eYm5uTKVOmNPg911KrV68m/v7+Cq+3pSwtLVUdQovl5+eT0aNHqzqMDs/X11fVIbRZSnkC9vb2BpfLxcmTJ5tUXk1NDb///js2bNjQYDk9PT0MGjQIkyZNqvepoaKiAgsXLsR///tf2hWiZOnp6Rg7diwuXLiglBWkmCSTyeDl5YWffvoJ6enpsLW1xccffwwHBwd8+umnePHihULaycjIYGRVsJZq668LGmJubl7nPuCUctGRz/VT2uiE48eP46uvvmrSnq2dOnVCnz59Wt0mRp1WAAAgAElEQVTmP7807e3tsWrVqlbXRzVdWVkZZsyYgaVLl8LNzU3V4bRafHw8qqqqALztUlu/fj3u3buHu3fvQiaTITQ0FJ07d8a4cePwyy+/IC8vr0XtPH36FHZ2dgqJOSIiApqamli+fHmLu83b+05JHW3lrO+//77NvbenCbh+SkvAJiYm+OijjxAUFKSw3WkaUlpaChcXF4jFYjx69Ijx9qj/TygUYtCgQfj000/xwQcfqDochcjLy4OVlVWt45aWlti1axdu3bqFpKQkBAYGIioqCt7e3rCzs0NwcDA+//xz3L9/H8XFxQ22QQhBamoqhgwZopCYhw0bBpFIhO+//x5mZmYICgrCs2fPmny9VCqVL3LRXgkEglYvBNSenD17ts2tElhWVqbqENospY7PX758OTp37owxY8Yw2s6GDRvQuXNn2NjYICUlpUnLDFKKIRaL0b9/f4SFhWHSpEmqDkehunbt2uB5PT09hIaGYufOncjOzsbjx4+xZMkS8Pl8fPvtt+jevTs6deqE4OBgTJgwATt27MD58+eRnJyM6upqpKamwsLCQmHz1AsKCgC8TaSlpaWIjIxEv3794Ofnh8LCwkavV1NTw7Bhw1q9kI4q9ejRQ/516Aj+WWubah+U3jdw4cIFDBo0CB9//DH27dunsHplMhm2b9+O7777DpWVldiyZQvmzp2rsPqpxkkkEowfPx4hISEYP368qsNRqKdPn6JHjx7NusbY2BiBgYEIDAyUHxMIBEhNTcWff/6J5ORkXLt2DS9evACLxUJeXh5EIhF69uyJiooKmJiYwNjYGKWlpdDX14eRkRGqqqoglUqhr68PAwMD+VrrmpqaIISgqqoKeXl54PP5qKysrBHPP4skxMXFwdHREVlZWTAyMmrwHnx9fZGamtrqLUVVRSwWIzY2Fi4uLqoORSkEAkGbm/fc1p7I2xKVdM5fu3YNwcHBGDVqFM6ePduqJ9S0tDR88cUXuHLlCiwsLLBmzRrMmTNHgdFSTSGTyTB79mw4ODi8kx98ysvLFbK8oYGBAby8vODl5VXr3OTJk/Hee+9h3LhxKCgoQEFBATgcDrKysiCTycBms1FUVCRf7rCyslK+x/U/GxWUl5dDKBRCS0sLDg4OePr0aa12KioqoKGhgatXrzbaS2FiYtKkcRttlb29fbueStVcbW2VP/J/y1JSdVNJAmaz2fjrr7+wYsUKdO3aFfPnz8dnn33W5E9uT548wf79+3H58mUUFxdj0KBB+Pvvv9vM/MmORiaTYezYsXB2dsamTZtUHQ4jxGIx4yO5I/9fe/cd1uTZ/QH8m4DsEUCGgEyhgMVFCzhw4KLWui+pVlGrratVah3V+tbxqtXWiaOXHY4WtVq1KlJxUXEUEKotyh5h7xFCWElIfn/4a676KkjIeCCcz3+SPPdzQq9yct/PfZ9z5w5Wr14tK5zg4eEBABgyZEiHxwwPD3/pz4VCIWbMmPHK662trbtsJSzgWUJqz3K7JuDxeJ3uyxKPx5NV4iIvYnR72o4dOzB//nxs3boVjo6O8PLygp+fH5ycnGBsbAxtbW1UVlYiPz8faWlpSE5ORlFREQwNDfHmm29i9+7dmDZtGn3DYpBYLMaYMWMwderUDvVo7iqKiopgYWGhsvGzsrIgFotV0gWJxWLJNj5qaWlBX18f33zzTbuO5VlaWsp2f3dFIpFI6buCi4qKYGpqCiMjI6WOq6iamppX7lNQt7KysufaWpLnMb4/3N3dHeHh4RAKhYiIiEB0dDQePXoEgUAAiUQCPT09WFhYwNXVFfPnz8fo0aPV1pWGtK2hoQETJ05EcHAwli5dynQ4KqXqmsJxcXEvXZZWhn+SL4vFgr+/P65cufLKZ7//sLCwQFFRkdz3rKqqUukXlvZycXEBl8tVylg1NTVwdnaGoaEhgGez69OnT2PgwIFKGV9RBQUFr6x1X1paiuTkZNjb26vluXhpaSm1gG0D4wn4Hzo6Opg+fbrGbd7RVKWlpQgJCcGECRM0PvmKRCKVn2X8/vvvERgYqNQx/730N378eFy7dk3u1SJTU1OIRCK57x0cHIxbt27JfZ2y8Xg8pKWlKWUsMzMzREVFydozXrlyBUFBQYiOjpb7rLtEIkFFRQVMTEyUlqAaGxvbbLf60Ucf4ezZs3BxcUFzczPKy8sREhKCnTt3KuX+L5Oamtrpnkt3Jp0mAZOuo6CgAO+88w7Wrl2L2bNnMx2OyuXn56u8ilphYaHSf5dsNhvm5uYKPRc0NjZGZWWl3NeJxeIO31OZnJyclNpC8t+9kSdNmoSKigosW7YMMTEx7R5j37592LFjB3r06CFrOHPq1CmFe5U3Nze32XDm888/x/79+2VfJvl8PoYPHw5tbW1s27ZNoXu3hsfjqWxlRxN0rv3qpNNLSkrC+PHjcerUqW6RfIFnS4+qPIaTm5uLiooK9OnTR6njslgshTflaGtrd2j239rGm6KiIqxYsQLe3t74+OOPVb5Duby8HCkpKSob393dHXw+v93v//7773HgwAHcu3cPxcXFKC4uBvBso52iBYpyc3NRWlra6uu9evV67r+liYkJfvzxR1y5ckWh+7aFy+W2+3FHd0QJmLTb2bNnMXv2bNy6dUsjyku2F5fL7dAybHtFRERg4sSJKhtfUbW1tXJf09rv69KlSzhz5gw++OADPH36FN7e3irt0W1ra4vevXurbPzQ0FB89NFH7X5/WFgYLly4INvhbmhoiKtXr0IikSjcrN7S0hJ2dnZyXbN27VqMHTv2hZ//9NNPmDRpEpydnWFlZYVp06YhOztb7piSk5M73cawzoQSMGmXzZs348SJE4iJiYGtrS3T4ahVbm6uSr/FR0ZGdupCEcr87Lm5ubCwsMC7776L33//Hb1798bChQuVNv7/qqioUFlt5NmzZ8PJyUmu+O3t7eHj4/PCz/39/REfH69QPBUVFcjNzW3zPdevX8eiRYswadIk2NvbQ1tbG3v27JG9LpVKMWbMGKxduxa+vr74+eefERERAQMDAwwaNAg3btyQK6aamhraBd0GegZMXmndunXgcrn49ddfu+UOdDabrdIl6IcPH+LYsWMqG19RHXkG3Npmr9raWqxdu1Y2Qz5x4gT69++vUHxt0dfXV/jZ6v+SSCR46623IBKJcPv27Xa9/86dOwgMDGy1+l9CQgKCgoIUisvW1vaVR6Nu3ryJkydPIjAwEImJibCxsXnu9eDgYNTV1SEzM/O5sfz8/PD9999jzpw5KC0tbfeJAFWfHujq6DdDWtXY2IgFCxagrKwM586d65bJF3jWCUlVS9BpaWno2bNnp15V6Mgu3db+6DY2NkJfX1+2VMpms1V6jl8ikSh1fJFIhIEDB0IoFOL27dvtGtvf3x/79u0DgBcaerS0tODdd99FeXk5tm7dqlBsLS0tqKioaPM9u3fvRlZWFiorKxEYGPhcc46CggL8/vvviIiIwIQJE/D48ePnrl20aBH09PRw/PjxdsVTU1MDXV1d+T9IN0IJmLxUWVkZAgMD4eXlhRMnTjAdDqP4fP4LMwVlOXTokNLaD6pKU1OT3NdIJBLZBqN/s7OzQ1RUlOzfISEhGDdunELxtaWiouKVXajk4ePjAxaLhejo6HYl37y8PKSkpODixYsvvBYfHw8PDw8kJiYiLi4OBgYGCsVmYWHRrs5Djo6O+PPPP7Fq1SqMHTsWJ0+eBADcvn0bAQEB2LNnD7hc7kvPN4vFYmRkZLQrnocPH3bqL5adASVg8oK4uDgEBgbi8OHDWLNmDdPhME5fX19lSTIxMRGrV69WydjK0pFews7Ozjhy5MgLP1+xYgUuX76Md955B2+++SZKSkpUuvyuq6v70jaSHbFmzRoUFRUhISFBlnwrKytx+fJlPHny5KXXZGZmgs1my3Y4i8VinD17VtakY+rUqcjMzFTKc1IbGxu5yj4uWrQIV69elW0iMzU1xYIFC3Dt2jUEBAQ8997y8nKMGDECfD4fn376abvGT0xMVEr9dE1Gz4CJjFQqxc6dO3HlyhXcvXu3U1Qy6gyys7NVclxGIBAgJSVFoVrP6tCRM72HDh3C7t27X/i5ra0tEhIScODAAYwZMwYff/yxSp8RKrOMZmVlJcRiMaZOnSrrOvTmm29i/vz5rZ4KGD16NFxcXGBubg5dXV00NjbC1dUVEydOxJUrVxSe9f6blZUV8vPz23xPVVUVJBIJLC0tIZVKcezYMdnvf+rUqQCePXLZtGkTli1bBlNTUyQkJCAuLg4+Pj7Iyclpd7vD/Px8hZ9razpKwAQAUF1djUmTJmH8+PH4448/qL72v4hEIpV8GTl8+DA8PT07XU3hl/mnG1N7mZubY8eOHS99zc3NDYcOHVJWaG36p0uUMhw/fhxLlixBfn4+PD0929X8hcVi4a+//oJAIEBRURFcXV1VVlXN0tKyXasV48ePR2lpKQQCAXr27InY2NjnXl+3bh2MjIxw+vRp2e7nQ4cOyY5OtReXy5X7mu6GEjDBnTt3sHjxYhw7dgxDhw5lOpxOR1dXVyXHkOLj47Fs2TKlj6tsUqkUAoGgS5YUFIlEqK+vV9p4fn5+8PPzk/s6IyMjlR81Y7FYMDExQUFBQatnny0sLPDo0aNXtglcvnw5li9frlA8BQUFtAT9CvQMuBuTSCQICQnB/v37ER8fT8m3FcXFxQr1rH6ZxsZGXL9+HZMnT1bquKpQX1/foSIMnYGuri4aGhqYDkNt7OzscO7cuVe+Tx0rXGKxWOUlXLs6SsDdVElJiezb/KVLl8DhcJgOqdOSSCRKn/0dPHgQQ4YM6RK/dwcHh1cWeOislixZgv/85z9Mh6E2wcHB2L9/f4eqlylTY2OjyhuYaAL6DXVDR48exQ8//ICDBw8+V1yevBybzVb6DPi3337DnDlzlDqmKkilUly6dAnGxsZMh9IhlpaWbTYo0DSrVq3Ca6+9xvjMMysrq9vWDZAHJeBupKmpCXPnzoWhoSEiIyO71R8mRSh7CTM7OxuPHj3qFO36XiUrKwsjRowAm82WLSna2dlh6NChmDNnzkvLKhJmvf3220yHgKqqKoWbS3QHlIC7icjISGzevBlLly7F+++/z3Q4XYqyj8ls27YNK1eu7BJLdG5ubs8V1GhpacHdu3cRHh6OoKAgSCQSnD59GkOHDkV6ejoyMzORmpqK/Px8VFdXQygUQkdHB2KxGPX19TAyMoKJiQnq6+thZ2cnO7vq4eEBAwMDWFtbw8nJCT179uwSvx/ycnp6et3q2XtHsaT0NUWjNTQ0YP78+WCxWNi+fbvSW95pOqlUCjc3N2RlZSllvLq6Ojg4OCA+Pr7L7hAVCoUYNGgQWlpaUF5ejpqaGtjY2MDFxQW2trawsrKCra0tbGxsYGlpCQ6HA7FYLJtBSyQSFBUVoa6uDhKJBGlpaQCenbPlcrkwNjZGRkaGrIwhi8XCa6+9hrq6OgwcOBC1tbVwd3eHoaEhjIyMYGdnB11dXTg6OkJfX1925pYwp7m5GX369FFZIwxNwdhXzOrqagQHB6O0tBRGRkYYO3YssrKyUFFRARaLBQsLCzg6OsLJyQkeHh5wc3OTu9VWd3fq1Cl89dVXWLduXbfp3atstbW1Si3CsXLlSgwdOrTLJl8A0NHRwa1bt5CVlYUBAwbgzz//hEAgUNnSZ1VVFXg8HtLT08FisZCcnIzm5mYUFBSgsLAQenp6SEtLg6WlJdLS0mBsbIyysjIYGxujtrYWdnZ2aG5uhoeHByQSiexs6j9t8vr27Qs9PT307t27S5zJ7gp0dXUhFAplKyDk5RiZAZ8/fx4LFiyAhYUF6uvrZd+gnZycYGVlBRaLherqapSVlaG6uhr19fWyijYcDgdWVlZwcnLC9OnTsWDBAuq28T9ycnIwZ84cDBs2DOvXr4eZmRnTIXVZycnJmDFjBlJTUxUeq7a2Fp6enoiOjqYCBWrE4/FQXl6OiooK5OTkoL6+Hjk5OZBKpcjIyICWlhYyMjKgra2NkpIScDgcCAQCvPbaa+Dz+fD390d1dTV8fX0hFovh7OwMMzMzGBgYwMrKCoaGhtDV1e0SO9rVaciQIXjvvfcUPk+sydSegGNjYzF27FhIJBJoaWlhyZIl2Lx5MwwNDV95bX5+Pp48eYLY2Fj8/vvvSExMBIvFwrp167BlyxY1RN+5VVdXY9u2bYiLi8OxY8foj7wSPHjwAF9++SWuXr2q8FiffPIJHj16hJiYGCVERlSpublZtiTe1NSEhIQEmJiYICkpCWw2G6WlpeDxeGCz2eByuTA3N0dxcTH09fXR1NQkS+KNjY0wNjaGQCCAkZER6urqoK+vD6lUiubmZtjZ2aGiogLW1taorq6Gvr4+tLW1UVNTAz09PfD5fBgaGkIgEIDD4aCpqQkikQi2trYoKyuDi4sLysrK4OzsDKFQCCMjI3A4HNTV1cHLywuFhYXw8/NDZWUl+vXrB4lEAmdnZ1hYWKBnz57t7nQlkUggkUjafC5fUVHx3MbODRs2IDc3F6dPn1b4v4emUusStEAgwOTJk/Hdd9/B3d1d7h2UDg4OcHBwkC11icViLF26FNu2bUNMTAzu3Lmjgqg7P7FYjD179uDHH3/E9u3bsXfvXqZD0hgFBQVKWWHJy8vD8ePHkZKSooSoiKrp6urCzs5O9thrzJgxDEf0PIFAgIaGBmhpackSf3FxMVpaWtDc3IzCwkKYmppCIpGgsbERKSkpqKiowNOnT6GtrY2CggLU19dDKBSipaUFPXv2lCXn+vp69O7dGyKRCMbGxtDS0kJhYSGKi4tRWloKHR0dCAQCCIVCiMVisFgssNls2Nra4rfffkOfPn3AZrORmpoKR0dHpn9VnZpaZ8CjRo2Cubk5Lly4oNRxo6OjERQUhOHDh3eJox3KFBYWhvPnz+ONN97AV199RTtHlWzLli1IS0vDmTNnFBpn+fLlEIvFOHr0qJIiI0Q5hEIhqqqqUFBQgMbGRuTm5kIqlaKqqgpNTU1gs9moqamRFWRxd3eHrq4uLCwsYGNjg+LiYpSVleHGjRvIzMxEWVmZrP723bt321Uzu7tSWwKOjo7GzJkzVVLWD3hWV3fYsGF499138dNPPyl9/M4mJiYGn332GQYMGIDt27erpFYxeVaYnsPhYP369R0eIykpCcOHD0dRUVG7HrUQQroHtU2XFi9ejA0bNqhsR5yfnx/OnDmD4OBg2NraYteuXSq5D9MyMjKwaNEiuLm54dtvv4W3tzfTIWm0srIyhXsBL1q0CEeOHKHkSwh5jloScExMDHg8HlatWvXK9zY3N+OXX35BTEwMcnNzUV1djcbGRgwZMgTff/99m9fOmDEDW7ZswaZNm2BsbIyNGzcq6yMwLi8vDx9//DEkEgmOHDlCyzpqkpKSIuuT2hGnT59GTU0NZs2apcSoCCGaQC1L0CNHjoS3tzcOHjzY5vtqampgZ2eHlpYWcDgc2YH60tJSlJeXIzc3Fw4ODq+839KlS3H06FEcPXoUH3zwgbI+BiOysrKwe/du/PXXXzh8+DCV/lOzAQMG4Ny5cx06t1tVVQVXV1c8ePCg1YbthJDuSy0J2MTEBFwuV+6m5v9U0AGA1atXY/Pmze2+9s0338Tjx49RXFwMKysrue7bGURHR+OHH35AdnY2Dhw40KEepERxffr0wePHjzvUjGDx4sXQ0dF55RdPQkj3pPIEzOfzYW9vDz6fL/e1hw4dwqpVq1BRUQFTU1O5rzc1NYWXlxdiY2PlvpYJLS0tOH/+PMLCwmBtbY3Q0FAMHz6c6bC6NUtLS1RUVMh93e3btzFz5kwUFRVRVxhCyEupPAHX1dXB3t6+w/0pbWxs0K9fP9y4cUPuaydPnoybN292+qLgCQkJuHTpEq5evYoZM2Zg+vTp8PLyYjqsbk8qlcLa2hrl5eVyXdfQ0AAvLy8cP34co0aNUlF0hJCuTuWbsP5Zuquuru7QUZkjR45g5syZKC8vl3speeLEifjtt9/kvqc6JCcnY+/evcjOzoaenh7Wr1+Pbdu2gcViMR0a+X88Hk/uxyYA8OWXX8LJyYmSLyGkTWrZBe3h4YGNGzfiyJEjcl87bdo0GBoaYvr06bh3755c1xoYGIDFYuGbb76Br68voxuYampqEBUVhTNnzqCkpASOjo5477338Pbbb1Ox8k6qrKxM7i9EcXFxCAsLA5fLVVFUhBBNoZYEfOTIEYwePRq7du3q0GYWJyenDv1BS0xMBJvNxty5c/HWW2/ByckJmzZtUktLvkePHiEpKQlnz55Fc3MzmpqaMHv2bKxfvx6DBw9W+f2J4vLz8+VqaycWi/HRRx8hLCyMCqMQQl5JLQnYx8cHAQEBGDdu3Cs3REVGRmLv3r0Qi8Wyo0dCoRDh4eFy3/fixYuwt7eHkZER7t27h+joaHz++ecQiUQQi8Xw8vKCr68vhg0bptBO6bS0NGRmZuL8+fMoLS1FWVkZ3NzcMGTIEOzcuRP9+vWjpeUuqKGhQa4WmLt27YJIJMK8efNUGBUhRFOorRLWr7/+CmdnZ6xcuRIHDhxo9X15eXl48uQJevToAWtra6xYsQIbN26Ue+bc0NCAwsJC/Prrr7KfBQYGIjAwEMCzgh/x8fG4e/cujh8/jtraWrDZbFhbW8v6ENvb24PD4cDMzAyNjY0oKSlBSUkJqqurERcXh7q6OtTU1MDc3Bzjxo3DlClTMHbsWOopqiGEQmG7q1clJibi66+/VkrbQkJI96DWZgxFRUV4/fXXERoaik2bNqn0XosWLcK5c+fkOv7U0tKC9PR0PH78GFlZWbKWY8bGxmCxWJBKpXB1dYWDgwNcXFwwcOBAen6rwcLCwnDz5k1ERES0+T6RSITBgwcjJCQEK1asUFN0hJCuTq2tc+zs7PDHH39g8ODB4PP52LNnj8rudebMGbnL/2lpacHLy4uOABEAz1ZJ2vMF67///S9aWloo+RJC5KL23nWenp548uQJfH19kZSUhMjISKXPInfu3AmhUIhDhw4pdVzSvejr67/y0cetW7cQFhaG7OxsNUVFCNEUinca74DevXsjOzsbAoEADg4OiImJUdrYJSUl+OKLLzB58mSqQEQUwmaz29w8V1paipCQEJw7d65D54UJId0bIwkYeHZGNzY2FmvXrsU777yDIUOGICkpSaExY2Nj4erqCktLS5w/f15JkZLuqrGxEfX19S99TSqVYtGiRRg7dizGjRun5sgIIZqAsQT8j1WrViE/Px/29vbw9/eHs7MzPv/8c9TU1LR7jL///ht+fn4ICAjAoEGDUFhYqMKISXfSWgLeunUr0tPTcfz4cTVHRAjRFGp/BvwyHA4H586dg1AoxM6dO3Hq1Cns3r0bBgYGcHZ2xuuvvw5nZ2fY2NhAIpEgKysLXC4XmZmZsnPC7u7uuH//Pvz9/Zn+OERD9OjRA9raL/4vcvr0aYSFhSEjIwNsNuPfYQkhXZRajyHJQywW48aNG7h16xYyMzNRVVUFPp+Puro61NfXo1evXujbty8mTZqEmTNnvvQPJSGK+O6773D79m38/PPPsp/FxcVh8uTJiIiIgK+vL4PREUK6uk6btbS1tTFhwgRMmDCB6VBIN8Vms9HS0iL7d1VVFebNm4fQ0FBKvoQQhdH6GSGtaGxshEAgAPBsRWbixIkYMGAA1q9fz3BkhBBNQAmYkFaIxWJIJBIAwPjx42FkZPTccjQhhCii0y5BE8I0qVQKMzMzzJw5Ey0tLYiMjKSmGoQQpaEETEgrxGIxMjIyIBKJcPv2bSrsQghRKkrAhLTi+vXryMjIQH5+PvX3JYQoHT0DJuQl1qxZg9jYWMyfP5+SLyFEJWgGTMi/SCQSvPPOOygrK8OwYcPg5ubGdEiEEA1FM2BC/l9TUxOGDRsGNpuN6OhoSKVSuLi4MB0WIURDUQImBEB2djaGDx8OGxsbXL58GSYmJqitrYWlpSXToRFCNBQlYNLtpaWlITAwEP7+/rh48aKsvnNlZSU9/yWEqAw9Aybd2rVr1xAcHIzTp09j4sSJz70mEAhga2vLUGSEEE1HCZh0S1KpFJ9++ilOnTqF+Ph4eHp6vvCelpYWGBkZMRAdIaQ7oARMuh0ej4dRo0bBxsYG6enp4HA4L7ynpaUFPXr0YCA6Qkh3Qc+ASbcSEREBDw8PTJgwAZGRkS9NvsCz57+6urpqjo4Q0p3QDJh0C83NzQgODkZKSgoOHz6M6dOnt/n+goICmgETQlSKZsBE412+fBleXl7Q0dHBw4cPX5l8AaCoqAgmJiZqiI4Q0l3RDJhorPr6esyaNQupqanYsGEDFi5c2O5r+Xw+evbsqcLoCCHdHc2AiUb64Ycf0L9/f2hrayMpKUmu5AsADQ0NtAOaEKJSNAMmGoXL5WLdunX4888/cfDgQUyYMKFD49TX11P7QUKIStEMmGgEqVSKffv2YejQoTA2NkZ6enqHky/wrAgH7YImhKgSzYBJl3fnzh189tlnqKurwx9//AEnJyeFx6yqqpKVpCSEEFWgBEy6rJSUFOzYsQNRUVH48ccfFZrx/q/m5maaARNCVIq+4pMuJz8/HytXrsTgwYMxaNAglJSUKDX5AoC+vj4sLCyUOiYhhPwbJWDSZZSUlGDdunXw9vaGoaEhiouLsWrVKpUUzJBIJLQJixCiUl1iCTojIwN5eXnIzMxEWloa+Hw+gGd/JNlsNhwdHTF06FCMGDGClg01UG1tLfbt24e9e/di4cKFyMvLa7WEpLJUVlbC2NhYpfcghHRvnS4Bl5eX48yZM7h37x6SkpIgkUhgYmICDw8PcDgccDgcuLu7o1evXmhqakJxcTG4XC527NiBhQsXwsHBAR9++CHmzZvH9EchCqqtrcWBAwewe/duLFiwADk5OWorjtHY2AgdHR213Fz5tiIAAAp7SURBVIsQ0j11mgScmpqK999/H7W1tQgICMCCBQswYsQIuYshREVFYdeuXdi1axeOHDmCkSNHqiZgojIVFRU4cOAADh48iA8++ACZmZmwtrZWawza2tpUipIQolKMJ+DS0lJMnDgRRUVFcHZ2RlRUFBwcHDo8XlBQEIKCgvDrr78iJCQEK1aswOrVq5UYMVGVlJQUhIWF4cyZMwgNDUV2djZj5SCbm5thaGjIyL0JId0Do5uwYmNj4evrizlz5qCkpAR//PGHQsn336ZOnYq///4bJ06cwKZNm5QyJlG+pqYmnDx5EgEBARg1ahQGDhyIkpISbNmyhdFazAKBgJ4BE0JUirEZ8OPHj/Huu+/i3Llz8Pf3V8k9zMzMkJCQgP79+6NXr15YsmSJSu5D5BcbG4ujR4/i+vXrsLe3x9dff40RI0aAxWIxHRoAoK6ujpagCSEqxUgCLiwsxMyZM3Hp0iUMHDhQpffS19fHpUuXMHr0aEyZMgU2NjYqvR9pXXl5OQ4ePIizZ8+iR48eGDlyJJ4+fdopz9vW1dXBwMCA6TAIIRpM7UvQfD4fb731Fo4fPy5X8q2oqOjwPb28vPDRRx8hJCSkw2OQjiksLERYWBj8/f3h6emJ2tpahIWFITk5GYcPH+6UyRd49gzY1NSU6TAIIRqMJZVKpeq84ZQpUzBixAh88skncl1nbm4OPp+PDRs2YOvWrXLfVyKRwNHREQ8ePFDac2bycsXFxfj2228RGRmJgoIC+Pj4YO3atQgICOgy9ZX79OmDa9euwc3NjelQCCEaSq1L0Pv27QObzZY7+QLPiuPHxsZCW7tjIbPZbCxevBhr167Fzz//3KExSOsePHiAixcvIioqClVVVZg+fTrWrFmDGTNmdJmk+28SiYSWoAkhKqW2GTCPx8Mbb7yB2NhYWFpaquOWL6ivr4eXlxdyc3M7zWafrqq2thZRUVG4dOkSbt26BTs7OwwaNAihoaHo168f0+EpzN7eHomJibRngBCiMmqbAYeGhmLBggWMJV8AMDQ0hJ2dHa5fv46goCDG4uiqUlNTER4ejsjISNm57WXLlmH79u1wcXFhOjylEovFKqkxTQgh/1DLDLipqQne3t5ITU3t8BKysoSFheHOnTu4ePEio3F0BfX19bh06RLOnj2Lx48fAwBmzZoFX19fTJ06FVpaWgxHqDqWlpbIysqijViEEJVRSzbct28fRo8erVDyDQgIAJ/Px99//61QLHPnzsX+/fsVGkNTSaVSJCQk4NSpU3j06BH++usvjBs3Dv3798d3332n9nKQTGKxWBCJREyHQQjRYGpJwGfOnMEvv/zS4ev/+usvxMXFwdzcXOFYzMzMAABxcXFYuXIlLl68CDs7O4XH7aqys7Nx8uRJJCcn48aNG+jbty8cHBzw1VdfwdfXV6NnuW3p0aMHeDweo9W4CCGaTeXbU0UiEfh8Pl577bUOXd/U1IS3334bs2bNQmNjo1JicnV1RUFBAcaMGQNPT094e3sjMjJSKWN3ZhKJBMnJyVi9ejVCQkLA4XAwadIkPHjwAPPmzQOXy0VcXBzOnTuHwYMHd9vkCzzbL1BUVMR0GIQQDabyBPz06VOFZhEjR46Ev78/Tpw4gebmZiQmJiock5OTExITE7F9+3bU1NQgODgYn3zyCezt7REaGoqamhqF78E0Pp+P27dvY+/evZg6dSr8/f3B4XAwf/58PH36FNOmTUNqaiqSk5Nx+/ZtTJo0iWZ7/2JqaoqcnBymwyCEaDCVL0HX1NR0eCPL7Nmz0djYiAsXLgAAPD09MWXKFHz44Yf44osvOhyTWCwGj8cDAGhpaWHjxo3YuHEjsrKysHXrVnh7e2PQoEFYtmxZp90tLRaLkZubiydPnqCoqAixsbGQSqW4f/8+hEIhhEIh3N3dYWdnhyFDhsDf3x/+/v60s7edrK2tkZ2dzXQYhBANpvJd0CkpKfjwww9x//59ua67efMm5s6dCy6XC319fQBASUkJBgwYACcnJ8THx3c4Jn9/fyxevBgLFix46etisRhhYWEIDw9HYWEhPDw84OPjg379+mHgwIHw8vJSebP2srIypKeno7KyEg8ePACbzUZ0dDT09fXx5MkTaGlpwcDAAM7OzrCzs4O1tTWGDRsmO4+rp6en0vg03ZIlS8Dj8ahoCyFEZVSegFtaWuDm5ib3ct6yZcuwcOFC+Pj4KDUeHo8HV1dXlJSUtCuJVlVVITIyEnFxccjIyEBOTg5qa2shlUphbm4OHR0dGBsbo0+fPhCLxdDV1YWLiwsqKythaWkJfX19lJSUwNXVFSkpKbLqSsXFxTA3N8ejR49ga2uLpKQk6OrqIj8/H1KpFEZGRjAzM4OLiwsMDAwwePBgGBgYYOjQoejVq5dSNqSR1u3fvx+nTp1CQkIC06EQQjSUWs4BDxgwACdPnkT//v1VfatXCggIgKOjI8LDwxUap6WlBWVlZeByucjJyYFUKkVhYSGqqqpgYmKCvLw8GBgYQCwWo6qqCv369UNOTg4sLCzAYrHAZrPh5uaG+vp69O3bF2KxGJ6enjA1NQWHw1HSpyUddefOHcydOxcFBQVMh0II0VBqScCHDh3C9evXERERoepbtWnnzp0IDw9HUlJSl6xPTNSHx+PB3t4eAoGA6VAIIRpKLVlo+fLlSEtLw4MHD9Rxu5e6cOECvv32W0RHR1PyJa/E4XAgkUjQ3NzMdCiEEA2llkzEYrHw888/4/3330dpaak6bvmcXbt2YcOGDUhISICVlZXa70+6JgMDA2RlZTEdBiFEQ6ltKujj44M1a9Zg2LBhSE1NVcs9S0pKMH78eERERCA+Pr7TNn8nnZOpqanCpU8JIaQ1al2LXbRoEfbv34/Jkydjw4YNEAqFKrlPXl4eFi9ejCFDhmD8+PG4f/8+bWwicrOwsMCTJ0+YDoMQoqHU/jB04sSJSEpKAo/Hg5eXF9577z08fPhQ4XGfPn2Kzz//HG+88Qbeeust2NjYICkpCatWrVJC1KQ7srS0RH5+PtNhEEI0FCO9AfX09HDkyBEIhUJ89913WLlyJcrLy2FjYwMfHx/0798fTk5O6NmzJ7S1taGlpQUWi4WGhgYUFBSAy+WitLQUBQUFSE1NRVVVFczMzBAUFITw8HB4eHgw8bGIhrG2tkZeXh7TYRBCNJRajiG1h1QqxcOHDxETE4Ps7GxUVVWBx+PJSkaamprKCmdYWlqiX79+cHd3R9++feHq6spk6ERDrVq1CpGRkUhPT2c6FEKIBmJkBvwyLBYLfn5+8PPzYzoUQgAAVlZWKC8vZzoMQoiGogOxhLRi2LBhdA6YEKIynWYJmpDORiQSQV9fHyKRCCwWi+lwCCEahmbAhLSiR48e6NGjBzVkIISoBCVgQtpgamqKy5cvMx0GIUQDUQImpA1WVlaIi4tjOgxCiAaiBExIG3R0dFBYWMh0GIQQDUQJmJA28Hg8GBoaMh0GIUQD0S5oQtpQV1cHkUgEc3NzpkMhhGgYSsCEEEIIA2gJmhBCCGEAJWBCCCGEAZSACSGEEAZQAiaEEEIYQAmYEEIIYcD/AW05SA2VjOccAAAAAElFTkSuQmCC" } }, "cell_type": "markdown", "metadata": {}, "source": [ "Supponiamo di dare la seguente serie di istruzioni:\n", "```python\n", "i = 3\n", "j = i\n", "l = [10, 20, 30]\n", "m = l\n", "```\n", "Quello che accade è:\n", " * viene creato un oggetto contentente il l'oggetto `3`, e la variabile `i` viene fatta puntare a questo oggetto.\n", " * il riferimento presente in `i` viene copiato in `j`, il risultato è che `j` punta allo stesso oggetto di `i`.\n", " * viene creata una oggetto contenente la lista `[10, 20, 30]` e la variabile `l` viene fatta puntare ad essa.\n", " * il puntatore presente in `l` viene copiato in `m`, il risultato è che `m` punta allo stesso oggetto di `l`.\n", "\n", "Questa è la rappresentazione grafica della situazione.\n", "\n", "![image.png](attachment:image.png)\n", "\n", "Il fatto che `l` ed `m` si riferiscono allo stesso oggetto si afferma dicendo che `l` ed `m` sono *alias*. In teoria anche `i` e `j` sono alias, ma di solito questo termine non si usa per i tipi interi e gli altri tipi immutabili (vedremo poi cosa vuol dire in dettaglio il termine *immutabile*)." ] }, { "attachments": { "image.png": { "image/png": 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" } }, "cell_type": "markdown", "metadata": {}, "source": [ "Eseguiamo ora l'istruzione:\n", "```python\n", "l[1] = 99\n", "```\n", "Il risultato è che nell'oggetto puntato da `l`, l'elemento in posizione 1 viene rimpiazzato da 99.\n", "\n", "![image.png](attachment:image.png)\n", "\n", "Ma così facendo abbiamo cambiato anche il valore di `m`!!" ] }, { "attachments": { "image.png": { "image/png": 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" } }, "cell_type": "markdown", "metadata": {}, "source": [ "Nel momento in cui assegnamo ad `l` una nuova lista, con\n", "```python\n", "l = [\"Ciao\", \"ab\"]\n", "```\n", "si spezza il legame che la lega ad `m`, e le due variabili si riferiscono a oggetti distinti.\n", "\n", "![image.png](attachment:image.png)" ] }, { "attachments": { "image-2.png": { "image/png": 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" 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" 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" } }, "cell_type": "markdown", "metadata": {}, "source": [ "Stessa cosa accade con il metodo `append`. Il metodo modifica l'oggetto di tipo lista a cui è applicato. Supponiamo sia:\n", "```python\n", "l = [\"Ciao\", \"sono\"]\n", "m = l\n", "```\n", "Ovvero, si ha questa situazione:\n", "\n", "![image.png](attachment:image.png)\n", "\n", "Dopo l'istruzione\n", "```python\n", "l.append(10)\n", "```\n", "otteniamo\n", "\n", "![image-2.png](attachment:image-2.png)\n", "\n", "e anche la variabile `m` è stata modificata.\n", "\n", "Invece l'istruzione\n", "```python\n", "l = l + [20]\n", "```\n", "fa una cosa completamente diversa: \n", " * crea un oggetto nello heap contenente la lista `[20]`, oggetto che non è puntato da alcuna variabile;\n", " * concatena l'oggetto puntato da `l` con il nuovo oggetto `[20]`, creando una **nuova** lista, senza modificare la lista originaria;\n", " * camba la variabile `l` in modo che punti alla nuova lista concatenata.\n", "La situazione è dunque:\n", "\n", "![image-3.png](attachment:image-3.png)" ] }, { "attachments": { "image.png": { "image/png": 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" } }, "cell_type": "markdown", "metadata": {}, "source": [ "Notare che la stessa situazione si verifica anche per qualunque altro tipo di dato. Ad esempio, \n", "```python\n", "s = \"Ciao\"\n", "r = s\n", "k = \"Ciao\"\n", "```\n", "dà origine alla seguente organizzazione in memoria:\n", "\n", "![image.png](attachment:image.png)\n", "\n", "Notare che `s` ed `r` sono alias, mentre `k` punta ad un altro oggetto in memoria, sebbene con lo stesso contenuto del primo. Il motivo però per cui non ci siamo prima interessati della cosa e non ci siamo mai accorti di questo comportamento, è che non esiste nessun modo di alterare un oggetto di tipo stringa una volta che è stato creato. Ad esempio, non è possibile modificare un carattere con una istruzione del tipo `s[0]=\"T\"`. Inoltre, tutti i metodi che operano sulle stringhe non modificano mai la stringa di partenza, ma ne creano una nuova (si pensi, ad esempio, al metodo `upper()` per convertire in maiuscolo).\n", "\n", "Poiché non è possibile modificare un oggetto di tipo stringa già presente in memoria, si dice che le stringhe in Python sono un tipo di dato *immutabile*. Lo stesso vale per interi, numeri in virgola mobile, booleani e tutti gli altri tipi che abbiamo già visto tranne il tipo lista e i tipi *GraphicsWindow*, *GraphicsCanvas* e *GraphicsImage* della libreria *ezgraphics*." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Per maggior precisione" ] }, { "attachments": { "image-2.png": { "image/png": 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" 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" 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" } }, "cell_type": "markdown", "metadata": {}, "source": [ "In realtà, anche quella che vi ho presentato sopra è una versione semplificata della realtà. Secondo quanto detto sopra, infatti, sembrerebbe che una lista sia una sequenza di oggetti. Ma in realtà, le liste non contengono una sequenza di oggetti, ma una sequenza di riferimenti. Ad esempio, la istruzioni\n", "\n", "```python\n", "l = [\"Ciao\", 10, 20]\n", "```\n", "\n", "non causano in realtà questa organizzazione della memoria:\n", "\n", "![image.png](attachment:image.png)\n", "\n", "ma quest'altra\n", "\n", "![image-2.png](attachment:image-2.png)\n", "\n", "Se a qesto punto diamo il comando \n", "```python\n", "v = l[1]\n", "```\n", "\n", "si ottiene \n", "\n", "![image-3.png](attachment:image-3.png)\n", "\n", "Tuttavia, finché si opera con tipi immutabili, non è un grosso problema pensare che una variabile o una lista contengano direttamente oggetti invece che riferimenti." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## La funzione `id`\n", "\n", "In Python ci sono vari modi per determinare se due oggetti sono in realtà lo stesso. Uno di questi è la funzione `id(x)` che restituisce l'*identità* di `x`: è un intero che è garatito essere costante er un oggetto `x`. Se due oggetti sono in realtà lo stesso, il valore restiuito da `id` è uguale. Per CPython (l'implementazione standard di Python) `id` è proprio l'indirizzo in memoria dove risiede l'oggetto." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "l = [1,2,3]" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "139782533728576" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "id(l)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "m = l" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Si vede che l'id di `m` e lo stesso di `l` perché le due variabili puntano in realtà alla stessa lista." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "139782533728576" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "id(m)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "n = [1,2,3]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Sebbene `n` contenga gli stessi valori di `l` ed `n`, l'istruzione di assegnamento qua sopra crea una lista completamente nuova, quindi il suo `id` è diverso." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "139782533728448" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "id(n)" ] } ], "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": "3.12.0" } }, "nbformat": 4, "nbformat_minor": 2 }