📖 Scenario: Imagine you are building a search suggestion feature for a website. When users type words, you want to find the longest common beginning part (prefix) of all their search queries to suggest completions.
🎯 Goal: Build a program that finds the longest common prefix string among a list of words.
📋 What You'll Learn
Create a list of words with exact values
Add a variable to hold the prefix result
Use a loop to compare characters of words
Print the longest common prefix found
💡 Why This Matters
🌍 Real World
Finding common prefixes helps in search suggestions, autocomplete features, and DNA sequence analysis.
💼 Career
Understanding string manipulation and loops is essential for software development, especially in text processing and user interface features.
Progress0 / 4 steps
1
Create the list of words
Create a list called words with these exact strings: "flower", "flow", "flight".
DSA Python
Hint
Use square brackets [] to create a list and separate words with commas.
2
Create a variable for the prefix
Create a variable called prefix and set it to the first word in the words list.
DSA Python
Hint
Use words[0] to get the first word from the list.
3
Find the longest common prefix
Use a for loop with variable word to iterate over words[1:]. Inside the loop, use a while loop to shorten prefix until it matches the start of word using word.startswith(prefix).
DSA Python
Hint
Use word.startswith(prefix) to check if word begins with prefix. Shorten prefix by removing the last character until it matches.
4
Print the longest common prefix
Print the variable prefix to show the longest common prefix found.
DSA Python
Hint
Use print(prefix) to display the result.
Practice
(1/5)
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
Step 1: Understand the problem definition
The Longest Common Prefix means the longest substring at the start of all strings that is the same.
Step 2: Compare options with the definition
Only The longest starting substring common to all strings matches this definition exactly.
Final Answer:
The longest starting substring common to all strings -> Option B
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
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.
Step 2: Match initialization with data type
lcp = '' initializes lcp as an empty string, which is correct.
Final Answer:
lcp = '' -> Option C
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
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.
Step 2: Check next string 'flight'
'flight' does not start with 'flow', remove last char to 'flo', no match; then 'fl', which matches.
Final Answer:
fl -> Option A
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
Step 1: Analyze loop and prefix shrinking
The code shrinks prefix until s starts with prefix, but does not check if prefix becomes empty.
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.
Final Answer:
Missing check for empty prefix causing infinite loop -> Option D
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
Step 1: Understand vertical scanning
Vertical scanning means checking each character position across all strings one by one.
Step 2: Identify stopping condition
Stop when a mismatch or end of any string is found at that position.
Final Answer:
Compare characters column by column across all strings until a mismatch is found -> Option A
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
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