README.md

USACO Dataset

This dataset contains problems from the USA Computing Olympiad (USACO) organized by seasons. Each season runs from November of the previous year → October of the current year, plus the US Open. One JSONL file per season is provided (usaco_<season>.jsonl) for efficient storage and loading.

Dataset Statistics

• Total Problems: 680
• Total Seasons: 14
• Total Sample Cases: 854
• Total Test Cases: 9,055

Data Structure

Each record contains:

• id: Unique stable identifier for the problem
• contest_name: USACO contest name (e.g., "USACO_24jan")
• difficulty_group: Problem difficulty level (bronze, silver, gold, platinum)
• problem_name: Name of the specific problem
• problem_statement: Problem description in Markdown format
• sample_data: Dictionary with inputs and outputs lists for sample test cases
• test_data: Dictionary with inputs and outputs lists for test cases
• num_sample_cases: Number of sample test cases
• num_test_cases: Number of test cases
• season: Season year (e.g., "2024")
• checker: Always null (USACO uses standard output checking)
• checker_interface: Always null (USACO uses standard output checking)

Seasons Available

Season	Problems	File
2025	48	usaco_2025.jsonl
2024	48	usaco_2024.jsonl
2023	48	usaco_2023.jsonl
2022	48	usaco_2022.jsonl
2021	48	usaco_2021.jsonl
2020	48	usaco_2020.jsonl
2019	47	usaco_2019.jsonl
2018	47	usaco_2018.jsonl
2017	47	usaco_2017.jsonl
2016	48	usaco_2016.jsonl
2015	38	usaco_2015.jsonl
2014	54	usaco_2014.jsonl
2013	55	usaco_2013.jsonl
2012	56	usaco_2012.jsonl

Difficulty Distribution

Difficulty	Problems
Bronze	192
Gold	184
Platinum	118
Silver	186

Loading Examples

from datasets import load_dataset
import json

# Load all seasons (merged dataset)
all_ds = load_dataset("vectorzhou/USACO", split="train")

# Load a specific season using data_files
s2025 = load_dataset(
    "vectorzhou/USACO",
    data_files="usaco_2025.jsonl",
    split="train",
)

# Or load directly as JSONL
with open("usaco_2025.jsonl", 'r') as f:
    problems_2025 = [json.loads(line) for line in f]

# Filter by difficulty across all seasons
bronze_problems = all_ds.filter(lambda x: x['difficulty_group'] == 'bronze')

# Filter by season (when loading all data)
season_2024 = all_ds.filter(lambda x: x['season'] == '2024')

# Access a specific problem
problem = all_ds[0]
print(f"Contest: {problem['contest_name']}")
print(f"Difficulty: {problem['difficulty_group']}")
print(f"Problem: {problem['problem_name']}")
print(f"Season: {problem['season']}")
print(f"Sample inputs: {len(problem['sample_data']['inputs'])}")
print(f"Has custom checker: {problem['checker'] is not None}")  # Always False for USACO

Data Organization

The dataset follows USACO's seasonal structure:

• November-December: Counted towards the following year's season
• January-October + US Open: Counted towards the current year's season
• Each season typically contains 3-4 contests with Bronze, Silver, Gold, and Platinum divisions

Format Benefits

• JSONL format for easy streaming and processing
• Season-based files for selective loading of specific time periods
• Consistent schema across all seasons
• Efficient storage with one record per line

Data Source

The data was crawled from the USACO platform and organized into the following structure:

• Problem statements in Markdown format
• Sample and test cases with input/output pairs
• Contest and difficulty metadata
• Season classification for temporal organization
• Comprehensive coverage of available problems

License

Please respect the original terms of use of the USACO platform when using this dataset.