To solve the problem of finding the longest substring without repeating characters, we can use the sliding window technique. This approach allows us to efficiently traverse the string while maintaining a record of the characters we’ve seen and their positions. Below is the implementation of the find_longest_substring function, along with the specified test cases.

def find_longest_substring(s):
char_index = {}
start = 0
longest_start = 0
longest_length = 0

for i, char in enumerate(s):
if char in char_index and char_index[char] >= start:
start = char_index[char] + 1 # Move the start pointer to the right of the last occurrence

char_index[char] = i # Update the last seen index of the character

if (i – start + 1) > longest_length: # Update longest substring if needed
longest_length = i – start + 1
longest_start = start

return s[longest_start:longest_start + longest_length]

# Test Cases
assert find_longest_substring(“abcabcbb”) == “abc”
assert find_longest_substring(“bbbbb”) == “b”
assert find_longest_substring(“pwwkew”) == “wke”
assert find_longest_substring(“abcddefg”) == “abcdefg”
assert find_longest_substring(“anviaj”) == “nviaj”

print(“All test cases passed!”)

Explanation of the Code:

1. Initialization:

– char_index: A dictionary to store the last seen index of each character.
– start: The starting index of the current substring being examined.
– longest_start: The starting index of the longest substring found.
– longest_length: The length of the longest substring found.

2. Loop Through Characters:

– We iterate over each character in the string using enumerate to get both the index (i) and the character (char).
– If char has been seen before and its last seen index is within the current substring (start), we update start to be one position after the last occurrence of char.
– Update the last seen index of char in char_index.

3. Check for Longest Substring:

– Calculate the current length of the substring as i – start + 1. If this length is greater than longest_length, we update both longest_length and longest_start.

4. Return Result:

– Finally, we return the longest substring using string slicing.

This approach runs in O(n) time complexity, making it efficient even for long strings, as required by the constraints.