Leetcode #1767: Find the Subtasks That Did Not Execute
In this guide, we solve Leetcode #1767 Find the Subtasks That Did Not Execute 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: Tasks +----------------+---------+ | Column Name | Type | +----------------+---------+ | task_id | int | | subtasks_count | int | +----------------+---------+ task_id is the column with unique values for this table. Each row in this table indicates that task_id was divided into subtasks_count subtasks labeled from 1 to subtasks_count.
Quick Facts
- Difficulty: Hard
- 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 |
+----------------+---------+
| task_id | int |
| subtasks_count | int |
+----------------+---------+
task_id is the column with unique values for this table.
Each row in this table indicates that task_id was divided into subtasks_count subtasks labeled from 1 to subtasks_count.
It is guaranteed that 2 <= subtasks_count <= 20.
Python Solution
import duckdb
import pandas as pd
def solution(tasks: pd.DataFrame, executed: pd.DataFrame) -> pd.DataFrame:
con = duckdb.connect()
con.register("Tasks", tasks)
con.register("Executed", executed)
return con.execute("""WITH RECURSIVE
T(task_id, subtask_id) AS (
SELECT
task_id,
subtasks_count
FROM Tasks
UNION ALL
SELECT
task_id,
subtask_id - 1
FROM t
WHERE subtask_id > 1
)
SELECT
T.*
FROM
T
LEFT JOIN Executed USING (task_id, subtask_id)
WHERE Executed.subtask_id IS NULL;""").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.