Hands-on data engineering practice.

Python 1: Reverse a string

Implement the function for this coding task: Reverse a string.

Python 2: Check whether a string is a palindrome

Implement the function for this coding task: Check whether a string is a palindrome.

Python 3: Find the first non-repeating character

Implement the function for this coding task: Find the first non-repeating character.

Python 4: Check whether two strings are anagrams

Implement the function for this coding task: Check whether two strings are anagrams.

Python 5: Find the most frequent character

Implement the function for this coding task: Find the most frequent character.

Python 6: Longest common prefix

Implement the function for this coding task: Longest common prefix.

Python 7: Compress a string with counts

Implement the function for this coding task: Compress a string with counts.

Python 8: Validate parentheses

Implement the function for this coding task: Validate parentheses.

Python 9: Count vowels and consonants

Implement the function for this coding task: Count vowels and consonants.

Python 10: Word frequency from a sentence

Implement the function for this coding task: Word frequency from a sentence.

Python 11: Remove duplicates while preserving order

Implement the function for this coding task: Remove duplicates while preserving order.

Python 12: Find the missing number from 1 to n

Implement the function for this coding task: Find the missing number from 1 to n.

Python 13: Two Sum

Python 14: Rotate a list by k steps

Python 15: Move all zeros to the end

Python 16: Merge two sorted lists

Python 17: Find the intersection of two lists

Python 18: Top K frequent elements

Python 19: Group records by key

Python 20: Flatten a nested list

Python 21: Count occurrences using a dictionary

Python 22: Invert a dictionary with duplicate values

Python 23: Merge a list of dictionaries by id

Python 24: Detect duplicates in a list

Python 25: Sort a dictionary by value

Python 26: Count pairs with a given sum

Python 27: Find symmetric pairs

Python 28: Build running balance from transactions

Python 29: Factorial

Python 30: Fibonacci number

Python 31: Prime number check

Python 32: Generate all primes up to n

Python 33: Binary search in a sorted array

Python 34: Longest substring without repeating characters

Python 35: Merge overlapping intervals

Python 36: Maximum subarray sum

Python 37: Read a large log file and count ERROR lines

Python 38: Parse CSV and aggregate a numeric column

Python 39: Parse nested JSON and extract selected fields

Python 40: Compare two files line by line

Python 41: Find duplicate records in a CSV by key

Python 42: Compute a rolling 7-day average

Python 43: Convert a list of tuples into a nested dictionary

Python 44: Implement a simple log parser

Python 45: Write a decorator that measures execution time

Python 46: Create a generator that yields chunks from an iterable

Python 47: Implement a simple LRU cache

Python 48: Find common elements across multiple lists

Python 49: Normalize an email list

Python 50: Find the top customer by revenue from transactions

Python 51: Normalize payment statuses for a dashboard

Normalize raw payment status strings into success, failed, pending, and unknown buckets, then return the count for every bucket.

Python 52: Extract failed job IDs from pipeline logs

Read log lines and return unique job IDs from lines containing FAILED or ERROR. Job IDs may appear as job_id=... or job=....

Python 53: Deduplicate replayed event IDs

Given event dictionaries, keep the first valid occurrence of every event_id and preserve arrival order.

Python 54: Build a required-field reject list

For each record, identify required fields whose value is None or an empty string.

Python 55: Summarize inventory movements by SKU

Aggregate quantities by sku. Inbound movements add stock; outbound movement types out, sale, and ship subtract stock.

Python 56: Parse partition dates from lake paths

Extract unique dates from paths containing dt=YYYY-MM-DD or date=YYYY-MM-DD.

Python 57: Mask customer emails before logging

Mask each valid email as first_letter***@domain. Invalid or missing emails should return None.

Python 58: Calculate pipeline success rate

Count success-like statuses and return success percentage rounded to two decimals.

Python 59: Keep latest customer update per key

Python 60: Reconcile source and warehouse snapshot keys

Python 61: Sessionize clickstream events by inactivity gap

Python 62: Detect delayed orchestration jobs

Python 63: Summarize Airflow retry attempts

Python 64: Aggregate daily net revenue from events

Python 65: Find missing daily data lake partitions

Python 66: Normalize records after schema drift

Python 67: Build a small-file compaction plan

Python 68: Return top customers including revenue ties

Python 69: Apply CDC events to current state

Python 70: Build a deterministic DAG run order

Python 71: Calculate rolling pipeline error rate

Python 72: Deduplicate exactly-once replayed events

Python 73: Prepare SCD Type 2 change rows

Python 74: Detect metric drift beyond tolerance

Python 75: Allocate safe backfill windows