Set the Python file maximum line length to 88 characters (#2122)

* flake8 --max-line-length=88

* fixup! Format Python code with psf/black push

Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>

strings/boyer_moore_search.py

@@ -41,7 +41,9 @@ class BoyerMooreSearch:
         return -1
 
     def mismatch_in_text(self, currentPos):
-        """ finds the index of mis-matched character in text when compared with pattern from last
+        """
+        find the index of mis-matched character in text when compared with pattern
+        from last
 
         Parameters :
             currentPos (int): current index position of text

strings/is_palindrome.py

@@ -14,8 +14,8 @@ def is_palindrome(s: str) -> bool:
     >>> is_palindrome("Mr. Owl ate my metal worm?")
     True
     """
-    # Since Punctuation, capitalization, and spaces are usually ignored while checking Palindrome,
-    # we first remove them from our string.
+    # Since Punctuation, capitalization, and spaces are usually ignored while checking
+    # Palindrome,  we first remove them from our string.
     s = "".join([character for character in s.lower() if character.isalnum()])
     return s == s[::-1]
 

strings/jaro_winkler.py

@@ -3,7 +3,8 @@
 
 def jaro_winkler(str1: str, str2: str) -> float:
     """
-    Jaro–Winkler distance is a string metric measuring an edit distance between two sequences.
+    Jaro–Winkler distance is a string metric measuring an edit distance between two
+    sequences.
     Output value is between 0.0 and 1.0.
 
     >>> jaro_winkler("martha", "marhta")

strings/knuth_morris_pratt.py

@@ -5,11 +5,11 @@ def kmp(pattern, text):
 
     1) Preprocess pattern to identify any suffixes that are identical to prefixes
 
-        This tells us where to continue from if we get a mismatch between a character in our pattern
-        and the text.
+        This tells us where to continue from if we get a mismatch between a character
+        in our pattern and the text.
 
-    2) Step through the text one character at a time and compare it to a character in the pattern
-        updating our location within the pattern if necessary
+    2) Step through the text one character at a time and compare it to a character in
+        the pattern updating our location within the pattern if necessary
 
     """
 

strings/lower.py

@@ -16,8 +16,9 @@ def lower(word: str) -> str:
     'what'
     """
 
-    # converting to ascii value int value and checking to see if char is a capital letter
-    # if it is a capital letter it is getting shift by 32 which makes it a lower case letter
+    # converting to ascii value int value and checking to see if char is a capital
+    # letter if it is a capital letter it is getting shift by 32 which makes it a lower
+    # case letter
     return "".join(
         chr(ord(char) + 32) if 65 <= ord(char) <= 90 else char for char in word
     )

strings/min_cost_string_conversion.py

@@ -1,5 +1,6 @@
 """
-Algorithm for calculating the most cost-efficient sequence for converting one string into another.
+Algorithm for calculating the most cost-efficient sequence for converting one string
+into another.
 The only allowed operations are
 ---Copy character with cost cC
 ---Replace character with cost cR

strings/rabin_karp.py

@@ -8,15 +8,18 @@ def rabin_karp(pattern, text):
     """
     The Rabin-Karp Algorithm for finding a pattern within a piece of text
     with complexity O(nm), most efficient when it is used with multiple patterns
-    as it is able to check if any of a set of patterns match a section of text in o(1) given the precomputed hashes.
+    as it is able to check if any of a set of patterns match a section of text in o(1)
+    given the precomputed hashes.
 
-    This will be the simple version which only assumes one pattern is being searched for but it's not hard to modify
+    This will be the simple version which only assumes one pattern is being searched
+    for but it's not hard to modify
 
     1) Calculate pattern hash
 
-    2) Step through the text one character at a time passing a window with the same length as the pattern
-        calculating the hash of the text within the window compare it with the hash of the pattern. Only testing
-        equality if the hashes match
+    2) Step through the text one character at a time passing a window with the same
+        length as the pattern
+        calculating the hash of the text within the window compare it with the hash
+        of the pattern. Only testing equality if the hashes match
     """
     p_len = len(pattern)
     t_len = len(text)

strings/split.py

@@ -1,6 +1,7 @@
 def split(string: str, separator: str = " ") -> list:
     """
-    Will split the string up into all the values separated by the separator (defaults to spaces)
+    Will split the string up into all the values separated by the separator
+    (defaults to spaces)
 
     >>> split("apple#banana#cherry#orange",separator='#')
     ['apple', 'banana', 'cherry', 'orange']

strings/upper.py

@@ -14,7 +14,8 @@ def upper(word: str) -> str:
     """
 
     # converting to ascii value int value and checking to see if char is a lower letter
-    # if it is a capital letter it is getting shift by 32 which makes it a capital case letter
+    # if it is a capital letter it is getting shift by 32 which makes it a capital case
+    # letter
     return "".join(
         chr(ord(char) - 32) if 97 <= ord(char) <= 122 else char for char in word
     )