I am trying to make a transposition cipher encryption function for a class project.
from string import ascii_lowercase
def swap(s: str, index0: int, index1: int):
smaller = index0 if index0 < index1 else index1
bigger = index0 if index0 >= index1 else index1
if bigger >= len(s) or smaller < 0:
return None
ret = s[:smaller] + s[bigger] + s[smaller+1:] # swap first
ret = ret[:bigger] + s[smaller] + s[bigger+1:] # swap second
return ret
def swap_encrypt(s: str, key:str):
ret = s
for key_chr in key:
index = ascii_lowercase.index(key_chr)
swap_this = index % len(ret)
with_this = (swap_this + 1) % len(ret)
ret = swap(ret, swap_this, with_this)
return ret
s = ''
key = ''
def main2():
s = input('Enter your message: ')
s = cleanup(s)
key = input('Enter your keyword: ')
key = cleanup(key)
ret= swap_encrypt((s), (key))
print(cleanup(ret))
main2()
I am getting the error 'substring not found', is there something I am doing wrong?
If my input is =(‘SLOTH POWER’) for s, (‘TOP’) for the key, my output should be: ‘RLOTPOHWES’
Is there also another to limit the functions to ord(), len(), and range()? If so, could I be shown how as well?
error:
Traceback (most recent call last):
File "c:\Users\darks\OneDrive\Documents\7\ciphers.py", line 139, in <module>
main2()
File "c:\Users\darks\OneDrive\Documents\7\ciphers.py", line 136, in main2
ret= swap_encrypt((s), (key))
File "c:\Users\darks\OneDrive\Documents\7\ciphers.py", line 123, in swap_encrypt
index = ascii_lowercase.index(key_chr)
ValueError: substring not found
It can't find the character in the ascii_lowercase, because your input is uppercase. Try "sloth power" instead of "SLOTH POWER", or use s.lower().
Related
I am stuck in here (picture below) and need to pass this in order for it to read my text. Also I have text.txt file. The program itself won't run with python 2. With python 2 it gives me an error in here: print(last_suggestion, end=' ', flush=True).
train_data = 'text.txt'
first_possible_words = {}
second_possible_words = {}
transitions = {}
def expandDict(dictionary, key, value):
if key not in dictionary:
dictionary[key] = []
dictionary[key].append(value)
def get_next_probability(given_list): #returns dictionary
probability_dict = {}
given_list_length = len(given_list)
for item in given_list:
probability_dict[item] = probability_dict.get(item, 0) + 1
for key, value in probability_dict.items():
probability_dict[key] = value / given_list_length
return probability_dict
def trainMarkovModel():
for line in open(train_data):
tokens = line.rstrip().lower().split()
tokens_length = len(tokens)
for i in range(tokens_length):
token = tokens[i]
if i == 0:
first_possible_words[token] = first_possible_words.get(token, 0) + 1
else:
prev_token = tokens[i - 1]
if i == tokens_length - 1:
expandDict(transitions, (prev_token, token), 'END')
if i == 1:
expandDict(second_possible_words, prev_token, token)
else:
prev_prev_token = tokens[i - 2]
expandDict(transitions, (prev_prev_token, prev_token), token)
first_possible_words_total = sum(first_possible_words.values())
for key, value in first_possible_words.items():
first_possible_words[key] = value / first_possible_words_total
for prev_word, next_word_list in second_possible_words.items():
second_possible_words[prev_word] = get_next_probability(next_word_list)
for word_pair, next_word_list in transitions.items():
transitions[word_pair] = get_next_probability(next_word_list)
def next_word(tpl):
#print(transitions)
if(type(tpl) == str): #it is first word of string.. return from second word
d = second_possible_words.get(tpl)
if (d is not None):
return list(d.keys())
if(type(tpl) == tuple): #incoming words are combination of two words.. find next word now based on transitions
d = transitions.get(tpl)
if(d == None):
return []
return list(d.keys())
return None #wrong input.. return nothing
trainMarkovModel() #generate first, second words list and transitions
########## demo code below ################
print("Usage: start typing.. program will suggest words. Press tab to chose the first suggestion or keep typing\n")
import msvcrt #use of mscvrt to get character from user on real time without pressing enter
c=''
sent=''
last_suggestion=[]
while(c != b'\r'): #stop when user preses enter
if(c != b'\t'): #if previous character was tab, then after autocompletion dont wait for user inpput.. just show suggestions
c=msvcrt.getch()
else:
c = b' '
if(c != b'\t'): #dont print tab etc
print(str(c.decode('utf-8')), end=' ', flush=True)
sent = sent + str(c.decode('utf-8')) #create word on space
if(c == b' '):
tkns = sent.split()
if(len(tkns) < 2): #only first space encountered yet
last_suggestion = next_word(tkns[0].lower())
print(last_suggestion, end=' ', flush=True)
else: #send a tuple
last_suggestion = next_word((tkns[-2].lower(), tkns[-1].lower()))
print(last_suggestion, end=' ', flush=True)
if (c == b'\t' and len(last_suggestion) > 0): #print last suggestion on tab
print(last_suggestion[0], end=' ', flush=True)
sent = sent + " " + last_suggestion[0]
I am using Mac and running this in Visual Code and this is the error I get:
baylarbayramov#Baylars-MacBook-Pro markov-predict-next-word-master % python3 -u "markov_nextwordpred.py"
Usage: start typing.. program will suggest words. Press tab to chose the first suggestion or keep typing
Traceback (most recent call last):
File "markov_nextwordpred.py", line 69, in <module>
import msvcrt
ModuleNotFoundError: No module named 'msvcrt'
I have the following section of code which is using openpyxl to search through the top row of a spreadsheet and find the first element that does not contain a value. It returns the following error when I run it. Is there a better way to do this? Or how do I get rid of the error?
val = "something"
j = 1
titleIndex = None
while val != None:
val = lecture['%s1' % chr(ord('#') + j)].internal_value
print val
print j
j += 1
else:
titleIndex = '%s1' % chr(ord('#') + j - 1)
File "C:\Users\ecustodio\Documents\Python Scripts\ExcelIterate.py",
line 14, in set_title
val = lecture['%s1' % chr(ord('A') + j)].internal_value File "C:\Users\ecustodio\AppData\Local\Continuum\anaconda2\lib\site-packages\openpyxl\worksheet\worksheet.py",
line 345, in getitem
min_col, min_row, max_col, max_row = range_boundaries(key) File "C:\Users\ecustodio\AppData\Local\Continuum\anaconda2\lib\site-packages\openpyxl\utils\cell.py",
line 135, in range_boundaries
raise ValueError("{0} is not a valid coordinate or range") ValueError: {0} is not a valid coordinate or range
As far as I can see, the line
val = lecture['%s1' % chr(ord('A') + j)].internal_value
provided in the error message differs from the one in the code:
val = lecture['%s1' % chr(ord('#') + j)].internal_value
Please, check the value of '%s1' % chr(ord('#') + j) or whatever before requesting the item from lecture. And be sure that your lecture is really an existing worksheet.
I am trying to reverse the use of the translate function. I pass a dictionary into str.maketrans, which translates the original string correctly, as per the dictionary.
cipher_dictionary = {'a': 'h5c', 'b': 'km3', 'c': '5fv'}
def cipher(text):
trans = str.maketrans(cipher_dictionary)
return text.translate(trans)
Above is the sample dictionary, together with the function that I use to translate strings. Translating abc gives me h5ckm35fv, which is desired.
Now, to reverse it, I am trying to use the following function.
def decipher(text):
reverse = {value: key for key, value in cipher_dictionary.items()}
trans = str.maketrans(reverse)
return text.translate(trans)
Using it raises an error.
Traceback (most recent call last):
File "C:\Users\lukas\Desktop\cipher.py", line 21, in <module>
deciphered = decipher(ciphered)
File "C:\Users\lukas\Desktop\cipher.py", line 13, in decipher
trans = str.maketrans(reverse)
ValueError: string keys in translate table must be of length 1
I am aware that this is because the values in cipher_dictionary aren't equal length to a, b and c. How can I go about rewriting the decipher function, to make h5ckm35fv translate back into abc?
cipher_dictionary = {'a': 'h5c', 'b': 'km3', 'c': '5fv'}
def cipher(text):
trans = str.maketrans(cipher_dictionary)
return text.translate(trans)
def decipher(text):
reverse = {value: key for key, value in cipher_dictionary.items()}
trans = str.maketrans(reverse)
return text.translate(trans)
if __name__ == '__main__':
text_to_cipher = 'abc'
ciphered = cipher(text_to_cipher)
print(ciphered)
deciphered = decipher(ciphered)
print(deciphered)
Running any of the functions provided in answers works perfectly, except for when there is white space in the input.
Text to cipher: some white space
Ciphered text: px3h54oa4b83 ky6u1v0t6yq3b83 px3sy9h5c5fvb83
Traceback (most recent call last):
File "C:\Users\Lukasz\Desktop\Python\Cipher\cip.py", line 45, in <module>
deciphered = decipher(ciphered)
File "C:\Users\Lukasz\Desktop\Python\Cipher\cip.py", line 36, in decipher
decoded_text = ''.join(reverse[text[i:i+3]] for i in range(0, len(text), 3))
File "C:\Users\Lukasz\Desktop\Python\Cipher\cip.py", line 36, in <genexpr>
decoded_text = ''.join(reverse[text[i:i+3]] for i in range(0, len(text), 3))
KeyError: ' ky'
def decipher(sentence):
reverse = {value: key for key, value in cipher_dictionary.items()}
decoded_text = ' '.join(''.join(reverse[word[i:i+3]] for i in range(0, len(word), 3)) for word in sentence.split(' '))
return decoded_text
Assuming that every letter is being encoded into a set of 3 letters.
Assuming that the values in the dictionary for a prefix free code, then you can keep trying prefixes of the unprocessed ciphertext until you find a match in the reverse dictionary:
def decipher(text, d):
r = {v: k for k,v in d.items()} # Reversed dictionary
plaintext = ''
index = 0
length = 1
while index + length <= len(text):
try:
plaintext += r[text[index:index+length]]
index = index + length
length = 1
except:
length += 1
return plaintext
If the values of the dictionary do not form a prefix free code, then the algorithm involves backtracking, and will return one possible plaintext if the cipher is non bijective:
def decipher2(text, d):
r = {v: k for k,v in d.items()} # Reversed dictionary
length = 1
while length <= len(text):
try:
val = r[text[:length]]
if length == len(text):
return val
else:
return val + decipher2(text[length:], d)
except:
length += 1
raise ValueError('Malformed input.')
If you know that all cipher values are of length 3 (i.e. that all values in cipher_dictionary are three characters long), then:
def decrypt(ciphertext, cipher_dict):
decipher_dict = {v:k for k,v in cipher_dict.items()}
answer = []
for cipher in (ciphertext[i:i+3] for i in range(0,len(ciphertext), 3)):
answer.append(decipher_dict[cipher])
return ''.join(answer)
On the other hand, if you don't know that all values are of length 3 (or if they are not of constant size), then try this:
def decrypt(ciphertext, cipher_dict):
decipher_dict = {v:k for k,v in cipher_dict.items()}
answer = []
start = 0
for end in range(len(ciphertext)):
if ciphertext[start:end] not in decipher_dict: continue
answer.append(decipher_dict[ciphertext[start:end]])
start = end
return ''.join(answer)
The problem with this is that it is a greedy algorithm and incurs all the shortcomings of its naïvité
UPDATE:
If you want to do this with sentences (words separated by whitespace):
encryptedSentence = '...'
answer = []
for word in sentence.split():
answer.append(decrypt(word, cipher_dict))
return ' '.join(answer)
I trying to use a Python script to decrypt a message. I have the cipher text (noted as FLAG in code) and most of the Python code used for encryption. I need to find the original plaintext message. Below I am trying to build a decode function into my Python code but failing (novice to Python). Can any genius help?
Here's the code so far:
import string
import random
from base64 import b64encode, b64decode
FLAG = '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'
enc_ciphers = ['rot13', 'b64e', 'caesar']
dec_ciphers = ['rot13', 'b64d', 'caesard']
def rot13(s):
_rot13 = string.maketrans(
"zyxwvutsrqponZYXWVUTSRQPONmlkjihgfedcbaMLKJIHGFEDCBA",
"mlkjihgfedcbaMLKJIHGFEDCBAzyxwvutsrqponZYXWVUTSRQPON")
return string.translate(s, _rot13)
def b64e(s):
return b64encode(s)
def b64d(s):
return b64decode(s)
def caesar(plaintext, shift=4):
alphabet = string.ascii_lowercase
shifted_alphabet = alphabet[shift:] + alphabet[:shift]
table = string.maketrans(alphabet, shifted_alphabet)
return plaintext.translate(table)
def caesard(plaintext, shift=-4):
alphabet = string.ascii_lowercase
shifted_alphabet = alphabet[shift:] + alphabet[:shift]
table = string.maketrans(alphabet, shifted_alphabet)
return plaintext.translate(table)
def encode(pt, cnt=50):
tmp = '2{}'.format(b64encode(pt)) #2.format(b64encode(pt))
for cnt in xrange(cnt):
c = random.choice(enc_ciphers) # choose some enc_cipher
i = enc_ciphers.index(c) + 1 # position in the array + 1
_tmp = globals()[c](tmp)
tmp = '{}{}'.format(i, _tmp)
return tmp
def decode(tmp, cnt=50):
for cnt in xrange(cnt):
i = int(tmp[:1])-1
_tmp = tmp[1:]
c = dec_ciphers[i]
tmp = globals()[c](_tmp)
try:
s = b64decode(tmp[1:])
if s.find("flag") != -1:
return s
except:
pass
return b64decode(tmp[1:])
if __name__ == '__main__':
cnt=70
print "Cnt: %d" % cnt
print decode(FLAG, cnt)
Here is the error message:
/usr/bin/python -u "/media/pc/A8560F93560F6204/Python investigation/transfer_csaw2015 fully MODDED2.py"
Cnt: 70
Traceback (most recent call last):
File "/media/pc/A8560F93560F6204/Python investigation/transfer_csaw2015 fully MODDED2.py", line 64, in <module>
print decode(FLAG, cnt)
File "/media/pc/A8560F93560F6204/Python investigation/transfer_csaw2015 fully MODDED2.py", line 47, in decode
i = int(tmp[:1])-1
ValueError: invalid literal for int() with base 10: 'W'
I am trying to make a script where a '-' is put in between all odd digits in a given number (ie 991453 would be 9-9-145-3), but for some reason python wont allow me to insert a str into a list of integers. The error I keep on getting is 'TypeError: not all arguments converted during string formatting'
My code:
def DashInsert(text):
list_int = map(int, list(text))
for i in xrange(len(list_int)-1):
if (list_int[i] % 2 == 1) and (list_int[i+1] % 2 == 1):
print i
list_int.insert(i+1,'-')
return list_int
Here is my actual input and error:
999472
0
Traceback (most recent call last):
File "DashInsert.py", line 17, in
print DashInsert(string)
File "DashInsert.py", line 11, in DashInsert
if (list_int[i] % 2 == 1) and (list_int[i+1] % 2 == 1):
TypeError: not all arguments converted during string formatting
Your error is because you are modifying the list that you are iterating over. When you insert - into the list, that becomes the target of % and you get a TypeError.
In Python, % is an operator for string formatting and '-' is a string; that is why you get a less than clear error:
>>> '-' % 2
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: not all arguments converted during string formatting
For strings you use % this way:
>>> 'x %s y %s %i' % ('and', 'is', 13)
'x and y is 13'
The fix to your code is to append to a separate list:
def DashInsert(s):
list_int = map(int, s)
rtr=[]
for i, e in enumerate(list_int[0:-1]):
rtr.append(str(e))
if e % 2 == 1 and list_int[i+1] % 2 == 1:
rtr.append('-')
rtr.append(str(list_int[-1]))
return rtr
You could do this through regex.
>>> import re
>>> s = 991453
>>> re.sub(r'(?<=[13579])(?=[13579])', r'-', str(s))
'9-9-145-3'
I suspect this is horrible code but it works-
number = 991453
number_list = []
for i, item in enumerate(str(number)):
try:
if int(item) % 2 != 0 and int(str(number)[i + 1]) % 2 != 0:
number_list.append(item + '-')
else:
number_list.append(item)
except:
number_list.append(item)
print(''.join(number_list))
Edit: Actually, there's no need to make a list so we can do this-
number = 991453
dash_number = ''
for i, item in enumerate(str(number)):
try:
if int(item) % 2 != 0 and int(str(number)[i + 1]) % 2 != 0:
dash_number += item + '-'
else:
dash_number += item
except:
dash_number += item
print(dash_number)
Edit: Here's how to do it without the try/except.
number = 991453
dash_number = ''
for i, item in enumerate(str(number)[:-1]):
if int(item) % 2 != 0 and int(str(number)[i + 1]) % 2 != 0:
dash_number += item + '-'
else:
dash_number += item
dash_number += str(number)[-1]
print(dash_number)