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Ertugrul
Ertugrul

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🐚 Tackling LeetCode Bash Problems – A Practical Guide

#bash #leetcode #programming

Recently, I completed the LeetCode Bash problem set, and in this post I’ll share how I approached these challenges, what I learned, and why these problems are surprisingly useful even for non-scripting heavy developers.

🚀 Why Bash Problems?

At first glance, Bash problems may look trivial compared to data structures and algorithms in Python or C++. But they focus on something equally important: practical data manipulation using Unix tools. Almost every engineer encounters situations where text processing or quick data cleanup is needed.

The problems helped me understand:

  • How to use pipes (|) to chain commands
  • How regex + grep can filter structured text
  • How to reshape data with awk
  • When to use sed for substitutions
  • And how utilities like sort, uniq, cut, and tr solve everyday text challenges

🛠 My Approach

When I saw a problem, I tried to answer three questions:

  1. What is the core task? (e.g., extract a line, validate a format, count words)
  2. Which Unix tool is most suited? (e.g., grep for patterns, awk for columns)
  3. Can it be done in a one-liner? (LeetCode problems encourage concise pipelines)

By asking these, I avoided overcomplicating and learned to think in terms of data streams.

📖 Example Problems & Explanations

1️⃣ Valid Phone Numbers

Problem: Print all valid phone numbers from a file.

grep -E '^([0-9]{3}-[0-9]{3}-[0-9]{4}|\([0-9]{3}\) [0-9]{3}-[0-9]{4})$' file.txt
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🔎 Explanation:

  • grep -E enables extended regex.
  • ^...$ anchors the full line.
  • Two formats are allowed: 123-456-7890 or (123) 456-7890.
  • Regex alternation | captures both.

This problem trains regex precision.

2️⃣ Word Frequency

Problem: Count frequency of each word in a file and sort by frequency.

cat words.txt | tr -s ' ' '\n' | sort | uniq -c | sort -nr
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🔎 Explanation:

  • tr -s ' ' '\n' replaces spaces with newlines (words per line).
  • sort groups identical words together.
  • uniq -c counts occurrences.
  • sort -nr sorts numerically and in reverse (highest first).

This problem shows the power of pipelines.

3️⃣ Transpose File

Problem: Transpose rows and columns.

awk '{
  for (i=1; i<=NF; i++) {
    if (NR==1) { out[i]=$i }
    else { out[i]=out[i]" "$i }
  }
} END {
  for (i=1; i<=NF; i++) print out[i]
}' file.txt
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🔎 Explanation:

  • NF = number of fields in current line.
  • NR = current row number.
  • For each column, we build a string.
  • After processing all lines, print the collected columns.

This problem illustrates why awk is the Swiss army knife of text processing.

4️⃣ Tenth Line

Problem: Print the 10th line of a file.

sed -n '10p' file.txt
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🔎 Explanation:

  • -n suppresses automatic printing.
  • '10p' explicitly prints line 10.

A simple but elegant use of sed.

🎯 Key Takeaways

  • Think in streams: Bash treats text as flowing streams, not fixed data structures.
  • Pick the right tool: awk for fields, grep for regex, sed for edits.
  • Chain commands: Combining simple commands often beats writing complex scripts.

📌 Final Thoughts

Even though these are small exercises, they gave me confidence in handling real-world text processing tasks. From cleaning logs to quick file inspections, these tools save enormous time.

👉 I’ve uploaded all my solutions to GitHub. Check them out and feel free to suggest improvements!
👉 Also my Linkedin Linkedin

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