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Infinite monkey theorem demonstration in Python
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Problem
This was the assignment:
Here’s a self check that really covers everything so far. You may have
heard of the infinite monkey theorem? The theorem states that a monkey
hitting keys at random on a typewriter keyboard for an infinite amount
of time will almost surely type a given text, such as the complete
works of William Shakespeare. Well, suppose we replace a monkey with a
Python function. How long do you think it would take for a Python
function to generate just one sentence of Shakespeare? The sentence
we’ll shoot for is: “methinks it is like a weasel”
You’re not going to want to run this one in the browser, so fire up
your favorite Python IDE. The way we’ll simulate this is to write a
function that generates a string that is 27 characters long by
choosing random letters from the 26 letters in the alphabet plus the
space. We’ll write another function that will score each generated
string by comparing the randomly generated string to the goal.
A third function will repeatedly call generate and score, then if
100% of the letters are correct we are done. If the letters are not
correct then we will generate a whole new string.To make it easier to
follow your program’s progress this third function should print out
the best string generated so far and its score every 1000 tries
Soo i have created a python program which generates the string provided, i am in learning phase, can someone please suggest any improvement or any tips or corrections.
Note: I know i have not did the exact method said in that question, but i have created the expected result.
makeRandSent: This will give me random character.
compare: This will give me final result by comparing each user character with randomly generated character and it will only change those chracter which are not match.
```
def makeRandSent(userSent):
counter = 0
randSent = [""] * (len(userSent) - 1)
randSent.clear()
while counter 0:
counter = 0
Here’s a self check that really covers everything so far. You may have
heard of the infinite monkey theorem? The theorem states that a monkey
hitting keys at random on a typewriter keyboard for an infinite amount
of time will almost surely type a given text, such as the complete
works of William Shakespeare. Well, suppose we replace a monkey with a
Python function. How long do you think it would take for a Python
function to generate just one sentence of Shakespeare? The sentence
we’ll shoot for is: “methinks it is like a weasel”
You’re not going to want to run this one in the browser, so fire up
your favorite Python IDE. The way we’ll simulate this is to write a
function that generates a string that is 27 characters long by
choosing random letters from the 26 letters in the alphabet plus the
space. We’ll write another function that will score each generated
string by comparing the randomly generated string to the goal.
A third function will repeatedly call generate and score, then if
100% of the letters are correct we are done. If the letters are not
correct then we will generate a whole new string.To make it easier to
follow your program’s progress this third function should print out
the best string generated so far and its score every 1000 tries
Soo i have created a python program which generates the string provided, i am in learning phase, can someone please suggest any improvement or any tips or corrections.
Note: I know i have not did the exact method said in that question, but i have created the expected result.
makeRandSent: This will give me random character.
compare: This will give me final result by comparing each user character with randomly generated character and it will only change those chracter which are not match.
```
def makeRandSent(userSent):
counter = 0
randSent = [""] * (len(userSent) - 1)
randSent.clear()
while counter 0:
counter = 0
Solution
In Python you don't need to declare your variables. So the
Second, Python has an official style-guide, PEP8, which programmers are encouraged to adhere to. It recommends using
Python also has a built-in module called
The requirements also mention a
Alternatively, you could use the Levenshtein distance as score:
Which you can then use like this:
When testing these two score functions, the Levenshtein seems to be about twice as fast:
The actual main function can be a lot simpler, I use
I think your code has a bug, in that it seems to set a position as
As alluded to in the problem statement, this takes quite a long time to run. Mine has been running about 10 minutes now and has gone through about 32 million iterations and has a maximum score of 11/27. But considering that there are \$27^{27} = 443426488243037769948249630619149892803\$ permutations for a 27 character long string with 27 possible characters at each position, this could take quite a bit longer...
randSent = [""] * (len(userSent) - 1); randSent.clear() part is completely unnecessary.Second, Python has an official style-guide, PEP8, which programmers are encouraged to adhere to. It recommends using
lower_case_with_underscores as variable and function names.Python also has a built-in module called
string, which has all lowercase characters. With it, generating a random sentence becomes a lot easier. I renamed this function generate, to adhere more closely to the requirements. It uses random.choice, which just chooses a random element from a sequence and _ as a placeholder for the unused loop variable.import random
import string
ALLOWED_CHARS = string.ascii_lowercase + " "
def generate(n):
return "".join(random.choice(ALLOWED_CHARS) for _ in range(n))The requirements also mention a
score function, which you have kind of implemented in your main function. I would implement it using sum and iterating over both sentences simultaneously:def score(user_sentence, sentence):
return sum(user_char == char for user_char, char in zip(user_sentence, sentence))Alternatively, you could use the Levenshtein distance as score:
$ pip install python-LevenshteinWhich you can then use like this:
import Levenshtein
def score(user_sentence, sentence):
return len(user_sentence) - Levenshtein.distance(user_sentence, sentence)When testing these two score functions, the Levenshtein seems to be about twice as fast:
In [8]: s1 = generate(27)
In [9]: s2 = generate(27)
In [10]: %timeit score(s1, s2)
100000 loops, best of 3: 3.47 µs per loop
In [11]: %timeit score_levenshtein(s1, s2)
1000000 loops, best of 3: 1.75 µs per loopThe actual main function can be a lot simpler, I use
itertools.count to have a loop that runs infinitely long and keeps track of how many iterations it has gone through.I think your code has a bug, in that it seems to set a position as
True if you ever found a string that has the correct character in that position. The requirements are quite clear that you should generate new sentence each time and discard the old characters (even if some were correct). I also implemented the output every 1000 iterations. I call the code with a if __name__ == "__main__": guard to allow importing parts of this script from another script.import itertools
def compare(user_sentence):
n = len(user_sentence)
max_score = 0
best_fit = " " * n
sentence = generate(n)
for i in itertools.count():
if sentence == user_sentence:
# We are done
print i
break
# Calculate score of current sentence and update best score if necessary
current_score = score(user_sentence, sentence)
if current_score > max_score:
max_score = current_score
best_fit = sentence
# Output every 1000 iterations
if i % 1000 == 0:
print i, best_fit, max_score
# Get a new random sentence
sentence = generate(n)
if __name__ == "__main__":
compare("methinks it is like a weasel")As alluded to in the problem statement, this takes quite a long time to run. Mine has been running about 10 minutes now and has gone through about 32 million iterations and has a maximum score of 11/27. But considering that there are \$27^{27} = 443426488243037769948249630619149892803\$ permutations for a 27 character long string with 27 possible characters at each position, this could take quite a bit longer...
Code Snippets
import random
import string
ALLOWED_CHARS = string.ascii_lowercase + " "
def generate(n):
return "".join(random.choice(ALLOWED_CHARS) for _ in range(n))def score(user_sentence, sentence):
return sum(user_char == char for user_char, char in zip(user_sentence, sentence))$ pip install python-Levenshteinimport Levenshtein
def score(user_sentence, sentence):
return len(user_sentence) - Levenshtein.distance(user_sentence, sentence)In [8]: s1 = generate(27)
In [9]: s2 = generate(27)
In [10]: %timeit score(s1, s2)
100000 loops, best of 3: 3.47 µs per loop
In [11]: %timeit score_levenshtein(s1, s2)
1000000 loops, best of 3: 1.75 µs per loopContext
StackExchange Code Review Q#160748, answer score: 4
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