Quick Test CLI provides full support for Python 3 with direct execution of your competitive programming solutions.
File Extension
Python files must use the .py extension:
main.py
correct.py
gen.py
Execution
Python files are executed directly without compilation:
Quick Test CLI uses Python 3 by default. Python 2 is not supported.
Example Code
Here’s a typical Python solution for competitive programming:
# Maximum Subarray Problem - slow version
n = int(input())
values = list(map(int, input().split()))
best = 0
for i in range(n):
sum = 0
for j in range(i, n):
sum += values[j]
best = max(best, sum)
print(best)
Usage with Quick Test
Compare Mode (cmp)
Compare your solution against a brute-force correct solution:
quicktest cmp --target-file=main.py --correct-file=correct.py --gen-file=gen.py
Stress Testing Mode
Test your solution’s performance:
quicktest stress --target-file=main.py --gen-file=gen.py --tout 2000 --tc 1000
Checker Mode
For problems with multiple valid answers:
quicktest check --target-file=main.py --checker-file=checker.py --gen-file=gen.py
Requirements
You must have Python 3 installed on your system to run Python files.
Python is generally slower than compiled languages like C++ or Java. Be aware of timeout limits when using Python for competitive programming.
Tips for Faster Python Code
- Use fast I/O for large inputs:
import sys
input = sys.stdin.readline
-
Avoid unnecessary operations in tight loops
-
Use built-in functions which are implemented in C and are faster
-
Consider PyPy as an alternative Python interpreter for better performance
Common Patterns
# Single integer
n = int(input())
# Multiple integers on one line
a, b, c = map(int, input().split())
# List of integers
values = list(map(int, input().split()))
# Multiple lines
data = []
for _ in range(n):
data.append(int(input()))
Random Number Generation
Useful for test case generators:
import random
# Random integer in range
n = random.randint(1, 100)
# Random list
values = [random.randint(1, 1000) for _ in range(n)]
Standard Library
Python’s extensive standard library can be very helpful in competitive programming. Common useful modules include:
collections - Specialized container datatypesitertools - Iterator building blocksheapq - Heap queue algorithmbisect - Array bisection algorithmmath - Mathematical functions
- Linux: Full support
- Windows: Full support
- macOS: Full support