Leetcode #1169: Invalid Transactions
In this guide, we solve Leetcode #1169 Invalid Transactions in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
A transaction is possibly invalid if: the amount exceeds $1000, or; if it occurs within (and including) 60 minutes of another transaction with the same name in a different city. You are given an array of strings transaction where transactions[i] consists of comma-separated values representing the name, time (in minutes), amount, and city of the transaction.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Array, Hash Table, String, Sorting
Intuition
Fast membership checks and value lookups are the heart of this problem, which makes a hash map the natural choice.
By storing what we have already seen (or counts/indexes), we can answer the question in one pass without backtracking.
Approach
Scan the input once, using the map to detect when the condition is satisfied and to update state as you go.
This keeps the solution linear while remaining easy to explain in an interview setting.
Steps:
- Initialize a hash map for seen items or counts.
- Iterate through the input, querying/updating the map.
- Return the first valid result or the final computed value.
Example
Input: transactions = ["alice,20,800,mtv","alice,50,100,beijing"]
Output: ["alice,20,800,mtv","alice,50,100,beijing"]
Explanation: The first transaction is invalid because the second transaction occurs within a difference of 60 minutes, have the same name and is in a different city. Similarly the second one is invalid too.
Python Solution
class Solution:
def invalidTransactions(self, transactions: List[str]) -> List[str]:
d = defaultdict(list)
idx = set()
for i, x in enumerate(transactions):
name, time, amount, city = x.split(",")
time, amount = int(time), int(amount)
d[name].append((time, city, i))
if amount > 1000:
idx.add(i)
for t, c, j in d[name]:
if c != city and abs(time - t) <= 60:
idx.add(i)
idx.add(j)
return [transactions[i] for i in idx]
Complexity
The time complexity is , and the space complexity is . The space complexity is .
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.