Leetcode #1949: Strong Friendship
In this guide, we solve Leetcode #1949 Strong Friendship 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
Table: Friendship +-------------+------+ | Column Name | Type | +-------------+------+ | user1_id | int | | user2_id | int | +-------------+------+ (user1_id, user2_id) is the primary key (combination of columns with unique values) for this table. Each row of this table indicates that the users user1_id and user2_id are friends.
Quick Facts
- Difficulty: Medium
- Premium: Yes
- Tags: Database
Intuition
The task is relational in nature, which maps cleanly to DataFrame operations in Python.
By treating tables as DataFrames, joins and group-bys become concise and readable.
Approach
Load the inputs as DataFrames and apply the appropriate merge, filter, or group-by.
Select or rename the columns to match the required output.
Steps:
- Load inputs as DataFrames.
- Apply merge/groupby/filter operations.
- Select the output columns.
Example
+-------------+------+
| Column Name | Type |
+-------------+------+
| user1_id | int |
| user2_id | int |
+-------------+------+
(user1_id, user2_id) is the primary key (combination of columns with unique values) for this table.
Each row of this table indicates that the users user1_id and user2_id are friends.
Note that user1_id < user2_id.
Python Solution
import duckdb
import pandas as pd
def solution(friendship: pd.DataFrame) -> pd.DataFrame:
con = duckdb.connect()
con.register("Friendship", friendship)
return con.execute("""WITH
t AS (
SELECT
*
FROM Friendship
UNION ALL
SELECT
user2_id,
user1_id
FROM Friendship
)
SELECT
t1.user1_id,
t1.user2_id,
COUNT(1) AS common_friend
FROM
t AS t1
JOIN t AS t2 ON t1.user2_id = t2.user1_id
JOIN t AS t3 ON t1.user1_id = t3.user1_id
WHERE t3.user2_id = t2.user2_id AND t1.user1_id < t1.user2_id
GROUP BY t1.user1_id, t1.user2_id
HAVING COUNT(1) >= 3;""").df()
Complexity
The time complexity is O(n log n) (typical). The space complexity is O(n).
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.