Develop Reference

Find Longest Alphabetically Ordered Substring - Efficiently

The goal of some a piece of code I wrote is to find the longest alphabetically ordered substring within a string.
"""
Find longest alphabetically ordered substring in string s.
"""
s = 'zabcabcd' # Test string.
alphabetical_str, temp_str = s[0], s[0]
for i in range(len(s) - 1): # Loop through string.
if s[i] <= s[i + 1]: # Check if next character is alphabetically next.
temp_str += s[i + 1] # Add character to temporary string.
if len(temp_str) > len(alphabetical_str): # Check is temporary string is the longest string.
alphabetical_str = temp_str # Assign longest string.
else:
temp_str = s[i + 1] # Assign last checked character to temporary string.
print(alphabetical_str)
I get an output of abcd.
But the instructor says there is PEP 8 compliant way of writing this code that is 7-8 lines of code and there is a more computational efficient way of writing this code that is ~16 lines. Also that there is a way of writing this code in only 1 line 75 character!
Can anyone provide some insight on what the code would look like if it was 7-8 lines or what the most work appropriate way of writing this code would be? Also any PEP 8 compliance critique would be appreciated.

Linear time:
s = 'zabcabcd'
longest = current = []
for c in s:
if [c] < current[-1:]:
current = []
current += c
longest = max(longest, current, key=len)
print(''.join(longest))
Your PEP 8 issues I see:
"Limit all lines to a maximum of 79 characters." (link) - You have two lines longer than that.
"do not rely on CPython’s efficient implementation of in-place string concatenation for statements in the form a += b" [...] the ''.join() form should be used instead" (link). You do that repeated string concatenation.
Also, yours crashes if the input string is empty.
1 line 72 characters:
s='zabcabcd';print(max([t:='']+[t:=t*(c>=t[-1:])+c for c in s],key=len))
Optimized linear time (I might add benchmarks tomorrow):
def Kelly_fast(s):
maxstart = maxlength = start = length = 0
prev = ''
for c in s:
if c >= prev:
length += 1
else:
if length > maxlength:
maxstart = start
maxlength = length
start += length
length = 1
prev = c
if length > maxlength:
maxstart = start
maxlength = length
return s[maxstart : maxstart+maxlength]

Depending on how you choose to count, this is only 6-7 lines and PEP 8 compliant:
def longest_alphabetical_substring(s):
sub = '', 0
for i in range(len(s)):
j = i + len(sub) + 1
while list(s[i:j]) == sorted(s[i:j]) and j <= len(s):
sub, j = s[i:j], j+1
return sub
print(longest_alphabetical_substring('zabcabcd'))
Your own code was PEP 8 compliant as far as I can tell, although it would make sense to capture code like this in a function, for easy reuse and logical grouping for improved readability.
The solution I provided here is not very efficient, as it keeps extracting copies of the best result so far. A slightly longer solution that avoids this:
def longest_alphabetical_substring(s):
n = m = 0
for i in range(len(s)):
for j in range(i+1, len(s)+1):
if j == len(s) or s[j] < s[j-1]:
if j-i > m-n:
n, m = i, j
break
return s[n:m]
print(longest_alphabetical_substring('zabcabcd'))
There may be more efficient ways of doing this; for example you could detect that there's no need to keep looking because there is not enough room left in the string to find longer strings, and exit the outer loop sooner.
User #kellybundy is correct, a truly efficient solution would be linear in time. Something like:
def las_efficient(s):
t = s[0]
return max([(t := c) if c < t[-1] else (t := t + c) for c in s[1:]], key=len)
print(las_efficient('zabcabcd'))
No points for readability here, but PEP 8 otherwise, and very brief.
And for an even more efficient solution:
def las_very_efficient(s):
m, lm, t, ls = '', 0, s[0], len(s)
for n, c in enumerate(s[1:]):
if c < t[-1]:
t = c
else:
t += c
if len(t) > lm:
m, lm = t, len(t)
if n + lm > ls:
break
return m

You can keep appending characters from the input string to a candidate list, but clear the list when the current character is lexicographically smaller than the last character in the list, and set the candidate list as the output list if it's longer than the current output list. Join the list into a string for the final output:
s = 'zabcabcdabc'
candidate = longest = []
for c in s:
if candidate and c < candidate[-1]:
candidate = []
candidate.append(c)
if len(candidate) > len(longest):
longest = candidate
print(''.join(longest))
This outputs:
abcd

Longest Common Prefix from list elements in Python

I have a list as below:
strs = ["flowers", "flow", "flight"]
Now, I want to find the longest prefix of the elements from the list. If there is no match then it should return "". I am trying to use the 'Divide and Conquer' rule for solving the problem. Below is my code:
strs = ["flowers", "flow", "flight"]
firstHalf = ""
secondHalf = ""
def longestCommonPrefix(strs) -> str:
minValue = min(len(i) for i in strs)
length = len(strs)
middle_index = length // 2
firstHalf = strs[:middle_index]
secondHalf = strs[middle_index:]
minSecondHalfValue = min(len(i) for i in secondHalf)
matchingString=[] #Creating a stack to append the matching characters
for i in range(minSecondHalfValue):
secondHalf[0][i] == secondHalf[1][i]
return secondHalf
print(longestCommonPrefix(strs))
I was able to find the mid and divide the list into two parts. Now I am trying to use the second half and get the longest prefix but am unable to do so. I have had created a stack where I would be adding the continuous matching characters and then I would use it to compare with the firstHalf but how can I compare the get the continuous matching characters from start?
Expected output:
"fl"
Just a suggestion would also help. I can give it a try.

No matter what, you need to look at each character from each string in turn (until you find a set of corresponding characters that doesn't match), so there's no benefit to splitting the list up. Just iterate through and break when the common prefix stops being common:
def common_prefix(strs) -> str:
prefix = ""
for chars in zip(*strs):
if len(set(chars)) > 1:
break
prefix += chars[0]
return prefix
print(common_prefix(["flowers", "flow", "flight"])) # fl

Even if this problem has already found its solution, I would like to post my approach (I considered the problem interesting, so started playing around with it).
So, your divide-and-conquer solution would involve a very big task split in many smaller subtasks, whose solutions get processed by other small tasks and so, until you get to the final solution. The typical example is a sum of numbers (let's take 1 to 8), which can be done sequentially (1 + 2 = 3, then 3 + 3 = 6, then 6 + 4 = 10... until the end) or splitting the problem (1 + 2 = 3, 3 + 4 = 7, 5 + 6 = 11, 7 + 8 = 15, then 3 + 7 = 10 and 11 + 15 = 26...). The second approach has the clear advantage that it can be parallelized - increasing the time performance dramatically in the right set up - reason why this goes generally hand in hand with topics like multithreading.
So my approach:
import math
def run(lst):
if len(lst) > 1:
lst_split = [lst[2 * (i-1) : min(len(lst) + 1, 2 * i)] for i in range(1, math.ceil(len(lst)/2.0) + 1)]
lst = [Processor().process(*x) for x in lst_split]
if any([len(x) == 0 for x in lst]):
return ''
return run(lst)
else:
return lst[0]
class Processor:
def process(self, w1, w2 = None):
if w2 != None:
zipped = list(zip(w1, w2))
for i, (x, y) in enumerate(zipped):
if x != y:
return w1[:i]
if i + 1 == len(zipped):
return w1[:i+1]
else:
return w1
return ''
lst = ["flowers", "flow", "flight", "flask", "flock"]
print(run(lst))
OUTPUT
fl
If you look at the run method, the passed lst gets split in couples, which then get processed (this is where you could start multiple threads, but let's not focus on that). The resulting list gets reprocessed until the end.
An interesting aspect of this problem is: if, after a pass, you get one empty match (two words with no common start), you can stop the reduction, given that you know the solution already! Hence the introduction of
if any([len(x) == 0 for x in lst]):
return ''
I don't think the functools.reduce offers the possibility of stopping the iteration in case a specific condition is met.
Out of curiosity: another solution could take advantage of regex:
import re
pattern = re.compile("(\w+)\w* \\1\w*")
def find(x, y):
v = pattern.findall(f'{x} {y}')
return v[0] if len(v) else ''
reduce(find, lst)
OUTPUT
'fl'

Sort of "divide and conquer" :
solve for 2 strings
solve for the other strings
def common_prefix2_(s1: str, s2: str)-> str:
if not s1 or not s2: return ""
for i, z in enumerate(zip(s1,s2)):
if z[0] != z[1]:
break
else:
i += 1
return s1[:i]
from functools import reduce
def common_prefix(l:list):
return reduce(common_prefix2_, l[1:], l[0]) if len(l) else ''
Tests
for l in [["flowers", "flow", "flight"],
["flowers", "flow", ""],
["flowers", "flow"],
["flowers", "xxx"],
["flowers" ],
[]]:
print(f"{l if l else '[]'}: '{common_prefix(l)}'")
# output
['flowers', 'flow', 'flight']: 'fl'
['flowers', 'flow', '']: ''
['flowers', 'flow']: 'flow'
['flowers', 'xxx']: ''
['flowers']: 'flowers'
[]: ''

How to find the longest repeating sequence using python

I went through an interview, where they asked me to print the longest repeated character sequence.
I got stuck is there any way to get it?
But my code prints only the count of characters present in a string is there any approach to get the expected output
import pandas as pd
import collections
a = 'abcxyzaaaabbbbbbb'
lst = collections.Counter(a)
df = pd.Series(lst)
df
Expected output :
bbbbbbb
How to add logic to in above code?

A regex solution:
max(re.split(r'((.)\2*)', a), key=len)
Or without library help (but less efficient):
s = ''
max((s := s * (c in s) + c for c in a), key=len)
Both compute the string 'bbbbbbb'.

Without any modules, you could use a comprehension to go backward through possible sizes and get the first character multiplication that is present in the string:
next(c*s for s in range(len(a),0,-1) for c in a if c*s in a)
That's quite bad in terms of efficiency though
another approach would be to detect the positions of letter changes and take the longest subrange from those
chg = [i for i,(x,y) in enumerate(zip(a,a[1:]),1) if x!=y]
s,e = max(zip([0]+chg,chg+[len(a)]),key=lambda se:se[1]-se[0])
longest = a[s:e]
Of course a basic for-loop solution will also work:
si,sc = 0,"" # current streak (start, character)
ls,le = 0,0 # longest streak (start, end)
for i,c in enumerate(a+" "): # extra space to force out last char.
if i-si > le-ls: ls,le = si,i # new longest
if sc != c: si,sc = i,c # new streak
longest = a[ls:le]
print(longest) # bbbbbbb

A more long winded solution, picked wholesale from:
maximum-consecutive-repeating-character-string
def maxRepeating(str):
len_s = len(str)
count = 0
# Find the maximum repeating
# character starting from str[i]
res = str[0]
for i in range(len_s):
cur_count = 1
for j in range(i + 1, len_s):
if (str[i] != str[j]):
break
cur_count += 1
# Update result if required
if cur_count > count :
count = cur_count
res = str[i]
return res, count
# Driver code
if __name__ == "__main__":
str = "abcxyzaaaabbbbbbb"
print(maxRepeating(str))
Solution:
('b', 7)

Finding if string is concatenation of others

I am working on a problem where one must determine if a string is a concatenation of other string (these strings can be repeated in the concatenated strings). I am using backtracking to be as efficient as possible. If the string is a concatenation, it will print the strings it is a concatenation of. If not, it will print NOT POSSIBLE. Here is my python code:
# note: strList has to have been sorted
def findFirstSubstr(strList, substr, start = 0):
index = start
if (index >= len(strList)):
return -1
while (strList[index][:len(substr)] != substr):
index += 1
if (index >= len(strList)):
return -1
return index
def findPossibilities(stringConcat, stringList):
stringList.sort()
i = 0
index = 0
substr = ''
resultDeque = []
indexStack = []
while (i < len(stringConcat)):
substr += stringConcat[i]
index = findFirstSubstr(stringList, substr, index)
if (index < 0):
if (len(resultDeque) == 0):
return 'NOT POSSIBLE'
else:
i -= len(resultDeque.pop())
index = indexStack.pop() + 1
substr = ''
continue
elif (stringList[index] == substr):
resultDeque.append(stringList[index])
indexStack.append(index)
index = 0
substr = ''
i += 1
return ' '.join(resultDeque)
I keep failing the last half of the test cases and can't figure out why. Could someone prompt me in the right direction for any cases that this would fail? Thanks!

First, of all, this code is unnecessary complicated. For example, here is an equivalent but shorter solution:
def findPossibilities(stringConcat, stringList):
if not stringConcat: # if you want exact match, add `and not stringList`
return True
return any(findPossibilities(stringConcat[len(s):],
stringList[:i] + stringList[i+1:]) # assuming non-repeatable match. Otherwise, simply replace with `stringList`
for i, s in enumerate(stringList)
if stringConcat.startswith(s))
Actual answer:
Border condition: remaining part of stringConcat matches some of stringList, search is stopped:
>>> findPossibilities('aaaccbbbccc', ['aaa', 'bb', 'ccb', 'cccc'])
'aaa ccb bb'

Finding longest substring in alphabetical order

EDIT: I am aware that a question with similar task was already asked in SO but I'm interested to find out the problem in this specific piece of code. I am also aware that this problem can be solved without using recursion.
The task is to write a program which will find (and print) the longest sub-string in which the letters occur in alphabetical order. If more than 1 equally long sequences were found, then the first one should be printed. For example, the output for a string abczabcd will be abcz.
I have solved this problem with recursion which seemed to pass my manual tests. However when I run an automated tests set which generate random strings, I have noticed that in some cases, the output is incorrect. For example:
if s = 'hixwluvyhzzzdgd', the output is hix instead of luvy
if s = 'eseoojlsuai', the output is eoo instead of jlsu
if s = 'drurotsxjehlwfwgygygxz', the output is dru instead of ehlw
After some time struggling, I couldn't figure out what is so special about these strings that causes the bug.
This is my code:
pos = 0
maxLen = 0
startPos = 0
endPos = 0
def last_pos(pos):
if pos < (len(s) - 1):
if s[pos + 1] >= s[pos]:
pos += 1
if pos == len(s)-1:
return len(s)
else:
return last_pos(pos)
return pos
for i in range(len(s)):
if last_pos(i+1) != None:
diff = last_pos(i) - i
if diff - 1 > maxLen:
maxLen = diff
startPos = i
endPos = startPos + diff
print s[startPos:endPos+1]

There are many things to improve in your code but making minimum changes so as to make it work. The problem is you should have if last_pos(i) != None: in your for loop (i instead of i+1) and you should compare diff (not diff - 1) against maxLen. Please read other answers to learn how to do it better.
for i in range(len(s)):
if last_pos(i) != None:
diff = last_pos(i) - i + 1
if diff > maxLen:
maxLen = diff
startPos = i
endPos = startPos + diff - 1

Here. This does what you want. One pass, no need for recursion.
def find_longest_substring_in_alphabetical_order(s):
groups = []
cur_longest = ''
prev_char = ''
for c in s.lower():
if prev_char and c < prev_char:
groups.append(cur_longest)
cur_longest = c
else:
cur_longest += c
prev_char = c
return max(groups, key=len) if groups else s
Using it:
>>> find_longest_substring_in_alphabetical_order('hixwluvyhzzzdgd')
'luvy'
>>> find_longest_substring_in_alphabetical_order('eseoojlsuai')
'jlsu'
>>> find_longest_substring_in_alphabetical_order('drurotsxjehlwfwgygygxz')
'ehlw'
Note: It will probably break on strange characters, has only been tested with the inputs you suggested. Since this is a "homework" question, I will leave you with the solution as is, though there is still some optimization to be done, I wanted to leave it a little bit understandable.

You can use nested for loops, slicing and sorted. If the string is not all lower-case then you can convert the sub-strings to lower-case before comparing using str.lower:
def solve(strs):
maxx = ''
for i in xrange(len(strs)):
for j in xrange(i+1, len(strs)):
s = strs[i:j+1]
if ''.join(sorted(s)) == s:
maxx = max(maxx, s, key=len)
else:
break
return maxx
Output:
>>> solve('hixwluvyhzzzdgd')
'luvy'
>>> solve('eseoojlsuai')
'jlsu'
>>> solve('drurotsxjehlwfwgygygxz')
'ehlw'

Python has a powerful builtin package itertools and a wonderful function within groupby
An intuitive use of the Key function can give immense mileage.
In this particular case, you just have to keep a track of order change and group the sequence accordingly. The only exception is the boundary case which you have to handle separately
Code
def find_long_cons_sub(s):
class Key(object):
'''
The Key function returns
1: For Increasing Sequence
0: For Decreasing Sequence
'''
def __init__(self):
self.last_char = None
def __call__(self, char):
resp = True
if self.last_char:
resp = self.last_char < char
self.last_char = char
return resp
def find_substring(groups):
'''
The Boundary Case is when an increasing sequence
starts just after the Decresing Sequence. This causes
the first character to be in the previous group.
If you do not want to handle the Boundary Case
seperately, you have to mak the Key function a bit
complicated to flag the start of increasing sequence'''
yield next(groups)
try:
while True:
yield next(groups)[-1:] + next(groups)
except StopIteration:
pass
groups = (list(g) for k, g in groupby(s, key = Key()) if k)
#Just determine the maximum sequence based on length
return ''.join(max(find_substring(groups), key = len))
Result
>>> find_long_cons_sub('drurotsxjehlwfwgygygxz')
'ehlw'
>>> find_long_cons_sub('eseoojlsuai')
'jlsu'
>>> find_long_cons_sub('hixwluvyhzzzdgd')
'luvy'

Simple and easy.
Code :
s = 'hixwluvyhzzzdgd'
r,p,t = '','',''
for c in s:
if p <= c:
t += c
p = c
else:
if len(t) > len(r):
r = t
t,p = c,c
if len(t) > len(r):
r = t
print 'Longest substring in alphabetical order is: ' + r
Output :
Longest substring in alphabetical order which appeared first: luvy

Here is a single pass solution with a fast loop. It reads each character only once. Inside the loop operations are limited to
1 string comparison (1 char x 1 char)
1 integer increment
2 integer subtractions
1 integer comparison
1 to 3 integer assignments
1 string assignment
No containers are used. No function calls are made. The empty string is handled without special-case code. All character codes, including chr(0), are properly handled. If there is a tie for the longest alphabetical substring, the function returns the first winning substring it encountered. Case is ignored for purposes of alphabetization, but case is preserved in the output substring.
def longest_alphabetical_substring(string):
start, end = 0, 0 # range of current alphabetical string
START, END = 0, 0 # range of longest alphabetical string yet found
prev = chr(0) # previous character
for char in string.lower(): # scan string ignoring case
if char < prev: # is character out of alphabetical order?
start = end # if so, start a new substring
end += 1 # either way, increment substring length
if end - start > END - START: # found new longest?
START, END = start, end # if so, update longest
prev = char # remember previous character
return string[START : END] # return longest alphabetical substring
Result
>>> longest_alphabetical_substring('drurotsxjehlwfwgygygxz')
'ehlw'
>>> longest_alphabetical_substring('eseoojlsuai')
'jlsu'
>>> longest_alphabetical_substring('hixwluvyhzzzdgd')
'luvy'
>>>

a lot more looping, but it gets the job done
s = raw_input("Enter string")
fin=""
s_pos =0
while s_pos < len(s):
n=1
lng=" "
for c in s[s_pos:]:
if c >= lng[n-1]:
lng+=c
n+=1
else :
break
if len(lng) > len(fin):
fin= lng`enter code here`
s_pos+=1
print "Longest string: " + fin

def find_longest_order():
`enter code here`arr = []
`enter code here`now_long = ''
prev_char = ''
for char in s.lower():
if prev_char and char < prev_char:
arr.append(now_long)
now_long = char
else:
now_long += char
prev_char = char
if len(now_long) == len(s):
return now_long
else:
return max(arr, key=len)
def main():
print 'Longest substring in alphabetical order is: ' + find_longest_order()
main()

Simple and easy to understand:
s = "abcbcd" #The original string
l = len(s) #The length of the original string
maxlenstr = s[0] #maximum length sub-string, taking the first letter of original string as value.
curlenstr = s[0] #current length sub-string, taking the first letter of original string as value.
for i in range(1,l): #in range, the l is not counted.
if s[i] >= s[i-1]: #If current letter is greater or equal to previous letter,
curlenstr += s[i] #add the current letter to current length sub-string
else:
curlenstr = s[i] #otherwise, take the current letter as current length sub-string
if len(curlenstr) > len(maxlenstr): #if current cub-string's length is greater than max one,
maxlenstr = curlenstr; #take current one as max one.
print("Longest substring in alphabetical order is:", maxlenstr)

s = input("insert some string: ")
start = 0
end = 0
temp = ""
while end+1 <len(s):
while end+1 <len(s) and s[end+1] >= s[end]:
end += 1
if len(s[start:end+1]) > len(temp):
temp = s[start:end+1]
end +=1
start = end
print("longest ordered part is: "+temp)

I suppose this is problem set question for CS6.00.1x on EDX. Here is what I came up with.
s = raw_input("Enter the string: ")
longest_sub = ""
last_longest = ""
for i in range(len(s)):
if len(last_longest) > 0:
if last_longest[-1] <= s[i]:
last_longest += s[i]
else:
last_longest = s[i]
else:
last_longest = s[i]
if len(last_longest) > len(longest_sub):
longest_sub = last_longest
print(longest_sub)

I came up with this solution
def longest_sorted_string(s):
max_string = ''
for i in range(len(s)):
for j in range(i+1, len(s)+1):
string = s[i:j]
arr = list(string)
if sorted(string) == arr and len(max_string) < len(string):
max_string = string
return max_string

Assuming this is from Edx course:
till this question, we haven't taught anything about strings and their advanced operations in python
So, I would simply go through the looping and conditional statements
string ="" #taking a plain string to represent the then generated string
present ="" #the present/current longest string
for i in range(len(s)): #not len(s)-1 because that totally skips last value
j = i+1
if j>= len(s):
j=i #using s[i+1] simply throws an error of not having index
if s[i] <= s[j]: #comparing the now and next value
string += s[i] #concatinating string if above condition is satisied
elif len(string) != 0 and s[i] > s[j]: #don't want to lose the last value
string += s[i] #now since s[i] > s[j] #last one will be printed
if len(string) > len(present): #1 > 0 so from there we get to store many values
present = string #swapping to largest string
string = ""
if len(string) > len(present): #to swap from if statement
present = string
if present == s[len(s)-1]: #if no alphabet is in order then first one is to be the output
present = s[0]
print('Longest substring in alphabetical order is:' + present)

I agree with #Abhijit about the power of itertools.groupby() but I took a simpler approach to (ab)using it and avoided the boundary case problems:
from itertools import groupby
LENGTH, LETTERS = 0, 1
def longest_sorted(string):
longest_length, longest_letters = 0, []
key, previous_letter = 0, chr(0)
def keyfunc(letter):
nonlocal key, previous_letter
if letter < previous_letter:
key += 1
previous_letter = letter
return key
for _, group in groupby(string, keyfunc):
letters = list(group)
length = len(letters)
if length > longest_length:
longest_length, longest_letters = length, letters
return ''.join(longest_letters)
print(longest_sorted('hixwluvyhzzzdgd'))
print(longest_sorted('eseoojlsuai'))
print(longest_sorted('drurotsxjehlwfwgygygxz'))
print(longest_sorted('abcdefghijklmnopqrstuvwxyz'))
OUTPUT
> python3 test.py
luvy
jlsu
ehlw
abcdefghijklmnopqrstuvwxyz
>

s = 'azcbobobegghakl'
i=1
subs=s[0]
subs2=s[0]
while(i<len(s)):
j=i
while(j<len(s)):
if(s[j]>=s[j-1]):
subs+=s[j]
j+=1
else:
subs=subs.replace(subs[:len(subs)],s[i])
break
if(len(subs)>len(subs2)):
subs2=subs2.replace(subs2[:len(subs2)], subs[:len(subs)])
subs=subs.replace(subs[:len(subs)],s[i])
i+=1
print("Longest substring in alphabetical order is:",subs2)

s = 'gkuencgybsbezzilbfg'
x = s.lower()
y = ''
z = [] #creating an empty listing which will get filled
for i in range(0,len(x)):
if i == len(x)-1:
y = y + str(x[i])
z.append(y)
break
a = x[i] <= x[i+1]
if a == True:
y = y + str(x[i])
else:
y = y + str(x[i])
z.append(y) # fill the list
y = ''
# search of 1st longest string
L = len(max(z,key=len)) # key=len takes length in consideration
for i in range(0,len(z)):
a = len(z[i])
if a == L:
print 'Longest substring in alphabetical order is:' + str(z[i])
break

first_seq=s[0]
break_seq=s[0]
current = s[0]
for i in range(0,len(s)-1):
if s[i]<=s[i+1]:
first_seq = first_seq + s[i+1]
if len(first_seq) > len(current):
current = first_seq
else:
first_seq = s[i+1]
break_seq = first_seq
print("Longest substring in alphabetical order is: ", current)