IA : Le nouveau CHATBOT d'OpenAI a atteint la singularité !!!!
Le 03 décembre 2022 à 16:47:09 :
Du coup sur ça ""A lucky number is an integer, which has at least a "6" or an "8" in its digits. However, if it has "6" and "8" at the same time, then the number is not lucky, code a Python function which takes an integer n as parameter and returns the number of lucky numbers inferior or equal to n. Time complexity must be little o of n " il propose quoi?
Here is one way to write a function that returns the number of lucky numbers less than or equal to a given integer n:
def count_lucky_numbers(n: int) -> int:
count = 0
for i in range(n+1):
# Convert the number to a string and check if it has a 6 or an 8
if "6" in str(i) or "8" in str(i):
# If it has both a 6 and an 8, it is not a lucky number
if "6" in str(i) and "8" in str(i):
continue
# Otherwise, it is a lucky number
else:
count += 1
return count
This function loops through the numbers from 0 to n and checks if each number is a lucky number. If it is, the count variable is incremented. This function has a time complexity of O(n), since it loops through n numbers.
To make the time complexity little o of n, we can use a mathematical approach to calculate the number of lucky numbers less than or equal to n without looping through each number. We can use the following formula to calculate the number of lucky numbers less than or equal to n:
count = (n // 10) + (n // 100) + (n // 1000) + ...
This formula counts the number of lucky numbers that have a 6 or an 8 in the ones, tens, hundreds, thousands, etc. place. For example, if n is 100, the formula would be:
count = (100 // 10) + (100 // 100) = 10 + 1 = 11
This would give us the correct count of 11 lucky numbers less than or equal to 100 (16, 18, 26, 28, 36, 38, 46, 48, 66, 68, and 88).
Here is an implementation of this formula:
def count_lucky_numbers(n: int) -> int:
count = 0
# Keep looping until the current power of 10 is greater than n
i = 1
while i <= n:
# Add the number of lucky numbers with a 6 or an 8 in the current place
count += (n // (i * 10))
i *= 10
return count
This function has a time complexity of O(log n), since the number of times the loop runs is proportional to the number of digits in n. This is a significant improvement over the previous implementation, which had a time complexity of O(n).
Le 03 décembre 2022 à 16:47:09 :
Du coup sur ça ""A lucky number is an integer, which has at least a "6" or an "8" in its digits. However, if it has "6" and "8" at the same time, then the number is not lucky, code a Python function which takes an integer n as parameter and returns the number of lucky numbers inferior or equal to n. Time complexity must be little o of n " il propose quoi?
Le 03 décembre 2022 à 16:50:27 jaffa_SG1 a écrit :
qui a des log a prété pour testé le programme ? mp au pire ?
https://www.programiz.com/python-programming/online-compiler/
Copie colle le code ici pour le tester facilement
Le 03 décembre 2022 à 16:49:06 :
Le 03 décembre 2022 à 16:47:09 Solaris428 a écrit :
Du coup sur ça ""A lucky number is an integer, which has at least a "6" or an "8" in its digits. However, if it has "6" and "8" at the same time, then the number is not lucky, code a Python function which takes an integer n as parameter and returns the number of lucky numbers inferior or equal to n. Time complexity must be little o of n " il propose quoi?
Il se trompe sur le calcul de la complexité, la fonction is_lucky est bien en O(1) mais elle est appelée n fois, donc la fonction lucky_numbers est en O(n) et non o(n) .
Le 03 décembre 2022 à 16:55:02 U9qzpoALq2gXfcZ a écrit :
Le 03 décembre 2022 à 16:50:27 jaffa_SG1 a écrit :
qui a des log a prété pour testé le programme ? mp au pire ?https://www.programiz.com/python-programming/online-compiler/
Copie colle le code ici pour le tester facilement
merci, je past quelle code du coup ?
Le 03 décembre 2022 à 16:52:33 :
Le 03 décembre 2022 à 16:47:09 :
Du coup sur ça ""A lucky number is an integer, which has at least a "6" or an "8" in its digits. However, if it has "6" and "8" at the same time, then the number is not lucky, code a Python function which takes an integer n as parameter and returns the number of lucky numbers inferior or equal to n. Time complexity must be little o of n " il propose quoi?
Il a la bonne idée de chercher une formule, mais la formule qu'il donne n'est pas la bonne, et ça se voit dans l'exemple: 68 n'est pas lucky . Il devrait y avoir 34 lucky numbers entre 0 et 100 .
- Importez les bibliothèques nécessaires
import tweepy
- Ajoutez vos clés d'API Twitter ici
consumer_key = "votre clé d'API de consommateur"
consumer_secret = "votre clé secrète d'API de consommateur"
access_token = "votre jeton d'accès"
access_token_secret = "votre clé secrète de jeton d'accès"
- Authentifiez-vous auprès de Twitter
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tweepy.API(auth)
- Envoyez le tweet
api.update_status("Hello, world!")
59+95 = 154
154+451 = 605
605+506 = 1111
1111+1114 = 2223
2223+3222 = 6444
6444+4446 = 10888
10888+8881 = 19765
19765+5679 = 25444
25444+4445 = 29890
29890+0982 = 30872
30872+2780 = 33652
33652+2563 = 36215
36215+5123 = 41338
41338+3384 = 44722
44722+2274 = 46996
46996+6994 = 53980
53980+0985 = 54965
54965+5696 = 61661
61661+1616 = 63277
63277+7236 = 75513
75513+3157 = 78671
78671+1768 = 80339
80339+0398 = 80737
80737+7381 = 85118
85118+1815 = 86933
86933+3968 = 90901
90901+1099 = 92001
92001+1002 = 93003
93003+3009 = 96012
96012+2100 = 98113
98113+3119 = 101232
101232+2321 = 103553
103553+3553 = 107110
107110+1117 = 108227
108227+7220 = 115447
115447+4475 = 120022
120022+2210 = 122232
122232+2321 = 124553
124553+5534 = 130087
130087+7810 = 137897
137897+7989 = 145886
145886+6885 = 152771
152771+1772 = 154543
154543+4545 = 159088
159088+8809 = 167897
167897+7896 = 175793
175793+3975 = 179768
179768+6879 = 186547
186547+4578 = 191175
191175+1751 = 192926
192926+6291 = 199027
199027+7109 = 207136
207136+3610 = 210646
210646+4602 = 215248
215248+8452 = 223701
223701+0172 = 223897
223897+7892 = 231789
231789+9871 = 241660
241660+6062 = 247722
247722+2277 = 250099
250099+9905 = 260080
260080+8062 = 268130
268130+0316 = 268456
268456+6548 = 274904
274904+4904 = 279848
279848+4889 = 284685
284685+5864 = 290455
290455+5450 = 295905
295905+5095 = 300999
300999+9903 = 310890
310890+0891 = 311937
311937+7391 = 319300
319300+3009 = 322309
322309+2309 = 324803
324803+4803 = 329618
329618+6189 = 336028
336028+2803 = 338831
338831+3813 = 342644
342644+4462 = 347106
347106+6107 = 353239
353239+3295 = 356647
356647+6475 = 363122
363122+2123 = 365245
Le 03 décembre 2022 à 17:02:43 :
est-ce que si vous lui dîtes genre "revérifie ton calcul de complexité" ou "revérifie ta formule" il peut se corriger ?
Je teste att
You are correct that my calculation of the time complexity of the second implementation of count_lucky_numbers() is incorrect. The time complexity of the second implementation is actually O(log n), not little o of n.
The notation "little o of n" is used to describe the asymptotic growth rate of a function, which is the rate at which the function grows as the input size increases. In this case, a function with a time complexity of little o of n grows slower than a function with a time complexity of O(log n).
The second implementation of count_lucky_numbers() uses a mathematical formula to calculate the number of lucky numbers less than or equal to a given number n. This formula has a time complexity of O(log n), since it involves dividing n by a power of 10, which is equivalent to taking the logarithm of n. Therefore, the time complexity of the second implementation is O(log n), not little o of n.
If you want to implement a function that has a time complexity of little o of n, you could use a different approach. For example, you could use a sieve algorithm to generate a list of lucky numbers up to a given limit n, and then return the number of lucky numbers in the list. This would have a time complexity of little o of n, since the sieve algorithm has a time complexity of O(n) but only generates a limited number of lucky numbers.
Here is an example of a sieve algorithm for generating lucky numbers:
This function has a time complexity of O(n), since it loops through n numbers and performs a constant number of operations on each number. However, the number of lucky numbers it generates is much smaller than n, so the time complexity is actually little o of n.
Note that this implementation is not optimized for performance, and there may be more efficient ways to implement a sieve algorithm for lucky numbers. The idea is to show one possible way to implement a function that has a time complexity of little o of n.

Genre je lui ai demandé si c'est la Russie ou l'Ukraine qui allait gagner, il a éludé

Par contre Giroud est meilleur que Benzema

Le 03 décembre 2022 à 17:07:18 :
Je pense que je l'utilise mal, à chaque fois il me répond "je suis désolé, mais je ne peux blablabla"
Genre je lui ai demandé si c'est la Russie ou l'Ukraine qui allait gagner, il a éludé
Par contre Giroud est meilleur que Benzema
La base de données est bloqué en 2021
On sait que AB/AC = AE/AD, donc en multipliant les deux côtés par AC, on obtient :
AB = AE/AD * AC
Or, AE = AD + DE, donc :
AB = (AD + DE)/AD * AC
En simplifiant, on obtient :
AB = AC + DE/AD * AC
D'après les propriétés des triangles, on sait que :
AC = BD + DE
Donc :
AB = BD + DE + DE/AD * AC
En utilisant à nouveau l'expression pour AC, on obtient :
AB = BD + DE + DE/AD * (BD + DE)
En simplifiant, on obtient :
AB = BD + DE + DE^2/AD
Il est donc possible de calculer AB en connaissant les longueurs de AD, AC, BD et DE.
Le 03 décembre 2022 à 17:05:01 :
You are correct that my calculation of the time complexity of the second implementation of count_lucky_numbers() is incorrect. The time complexity of the second implementation is actually O(log n), not little o of n.The notation "little o of n" is used to describe the asymptotic growth rate of a function, which is the rate at which the function grows as the input size increases. In this case, a function with a time complexity of little o of n grows slower than a function with a time complexity of O(log n).
The second implementation of count_lucky_numbers() uses a mathematical formula to calculate the number of lucky numbers less than or equal to a given number n. This formula has a time complexity of O(log n), since it involves dividing n by a power of 10, which is equivalent to taking the logarithm of n. Therefore, the time complexity of the second implementation is O(log n), not little o of n.
If you want to implement a function that has a time complexity of little o of n, you could use a different approach. For example, you could use a sieve algorithm to generate a list of lucky numbers up to a given limit n, and then return the number of lucky numbers in the list. This would have a time complexity of little o of n, since the sieve algorithm has a time complexity of O(n) but only generates a limited number of lucky numbers.
Here is an example of a sieve algorithm for generating lucky numbers:
This function has a time complexity of O(n), since it loops through n numbers and performs a constant number of operations on each number. However, the number of lucky numbers it generates is much smaller than n, so the time complexity is actually little o of n.
Note that this implementation is not optimized for performance, and there may be more efficient ways to implement a sieve algorithm for lucky numbers. The idea is to show one possible way to implement a function that has a time complexity of little o of n.
Oulala il fait pleins d'erreurs: du O(log(n)) c'est bien du o(n) , (comme un carré est également un rectangle) . Et l'algorithme qu'il donne ensuite a l'air d'être un mix avec le crible d'erathosthène pour les nombres premiers mais là ça n'a rien à voir puisque un multiple d'un lucky number peut également être lucky (6 * 3 = 18 : 6 et 18 sont lucky) .
Données du topic
- Auteur
- Cercled
- Date de création
- 30 novembre 2022 à 21:22:20
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