Why Longest Common Prefix in DSA Python?

The Big Idea

What if you could instantly find the shared start of many words without checking each letter one by one?

The Scenario

Imagine you have a list of words from your friends, and you want to find the part at the start of each word that is the same. Doing this by looking at each word one by one and comparing letters can be very tiring and confusing.

The Problem

Checking each letter of every word manually takes a lot of time and mistakes can happen easily, especially if the list is long or words are very different. It's slow and frustrating to keep track of where the words stop matching.

The Solution

The Longest Common Prefix method quickly finds the shared beginning part of all words by smartly comparing letters step by step, saving time and avoiding confusion. It makes the process simple and fast.

Before vs After

✗ Before

words = ['flower', 'flow', 'flight']
prefix = ''
for i in range(min(len(w) for w in words)):
    char = words[0][i]
    for word in words:
        if word[i] != char:
            break
    else:
        prefix += char
print(prefix)

✓ After

def longest_common_prefix(words):
    if not words:
        return ''
    prefix = words[0]
    for word in words[1:]:
        while not word.startswith(prefix):
            prefix = prefix[:-1]
            if not prefix:
                return ''
    return prefix

print(longest_common_prefix(['flower', 'flow', 'flight']))

What It Enables

This lets you quickly find the shared start of many words, helping in tasks like searching, grouping, or auto-completing text.

Real Life Example

When you type in a search box, the system suggests words that start the same way you typed. Longest Common Prefix helps find those suggestions fast.

Key Takeaways

Manually comparing words letter by letter is slow and error-prone.

Longest Common Prefix finds the shared start efficiently.

This method speeds up tasks like search suggestions and grouping words.

Practice

1. What does the Longest Common Prefix (LCP) problem ask you to find given a list of strings?

easy

A. The total number of strings in the list

B. The longest starting substring common to all strings

C. The longest substring common to any two strings

D. The longest ending substring common to all strings

Solution

1. Step 1: Understand the problem definition

   The Longest Common Prefix means the longest substring at the start of all strings that is the same.

2. Step 2: Compare options with the definition

   Only The longest starting substring common to all strings matches this definition exactly.

3. Final Answer:

   The longest starting substring common to all strings -> Option B

4. Quick Check:

   Longest Common Prefix = longest starting substring [OK]

Hint: Focus on the start of strings, not anywhere else [OK]

Common Mistakes:

• Confusing prefix with suffix
• Thinking about any substring instead of prefix
• Counting total strings instead of prefix length

2. Which of the following Python code snippets correctly initializes a variable to store the longest common prefix as an empty string?

easy

A. lcp = None

B. lcp = []

C. lcp = ''

D. lcp = 0

Solution

1. Step 1: Identify the correct data type for prefix storage

   The longest common prefix is a string, so it should be initialized as an empty string.

2. Step 2: Match initialization with data type

   lcp = '' initializes lcp as an empty string, which is correct.

3. Final Answer:

   lcp = '' -> Option C

4. Quick Check:

   Prefix is a string, so empty string initialization [OK]

Hint: Use empty string '' to start prefix, not list or number [OK]

Common Mistakes:

• Using list [] instead of string
• Using None which is not a string
• Using 0 which is a number, not string

3. What will be the output of the following Python code?

def longest_common_prefix(strs):
    if not strs:
        return ''
    prefix = strs[0]
    for s in strs[1:]:
        while not s.startswith(prefix):
            prefix = prefix[:-1]
            if not prefix:
                return ''
    return prefix

print(longest_common_prefix(['flower', 'flow', 'flight']))

medium

A. fl

B. flow

C. f

D. flower

Solution

1. Step 1: Initialize prefix and iterate over strings

   Prefix starts as 'flower'. Check 'flow': 'flow' does not start with 'flower', so remove last char to 'flowe', then 'flow', which matches.

2. Step 2: Check next string 'flight'

   'flight' does not start with 'flow', remove last char to 'flo', no match; then 'fl', which matches.

3. Final Answer:

   fl -> Option A

4. Quick Check:

   Common start of all strings = 'fl' [OK]

Hint: Shrink prefix until all strings start with it [OK]

Common Mistakes:

• Returning first string without checking others
• Not shrinking prefix correctly
• Confusing substring anywhere with prefix

4. The following code is intended to find the longest common prefix but has a bug. What is the bug?

def longest_common_prefix(strs):
    prefix = strs[0]
    for s in strs:
        while not s.startswith(prefix):
            prefix = prefix[:-1]
    return prefix

print(longest_common_prefix(['dog', 'racecar', 'car']))

medium

A. No return statement inside the loop

B. Loop starts from first string causing incorrect prefix update

C. Using s.startswith(prefix) instead of prefix.startswith(s)

D. Missing check for empty prefix causing infinite loop

Solution

1. Step 1: Analyze loop and prefix shrinking

   The code shrinks prefix until s starts with prefix, but does not check if prefix becomes empty.

2. Step 2: Identify infinite loop risk

   If no common prefix exists, prefix will shrink to empty string, then prefix[:-1] stays empty, causing infinite loop.

3. Final Answer:

   Missing check for empty prefix causing infinite loop -> Option D

4. Quick Check:

   Empty prefix check needed to stop loop [OK]

Hint: Always check if prefix is empty to avoid infinite loops [OK]

Common Mistakes:

• Not checking prefix empty condition
• Looping over all strings including first
• Confusing startswith arguments

5. Given a list of strings, how would you efficiently find the longest common prefix using a vertical scanning approach? Which of the following best describes the method?

hard

A. Compare characters column by column across all strings until a mismatch is found

B. Sort the strings and compare only the first and last strings completely

C. Use a hash map to count character frequencies at each position

D. Concatenate all strings and find the longest substring

Solution

1. Step 1: Understand vertical scanning

   Vertical scanning means checking each character position across all strings one by one.

2. Step 2: Identify stopping condition

   Stop when a mismatch or end of any string is found at that position.

3. Final Answer:

   Compare characters column by column across all strings until a mismatch is found -> Option A

4. Quick Check:

   Vertical scanning = column-wise character comparison [OK]

Hint: Check characters by columns, stop at first mismatch [OK]

Common Mistakes:

• Confusing vertical scanning with sorting
• Using hash maps unnecessarily
• Concatenating strings instead of comparing