rl_code_fix_env / dataset /prepare_swebench.py
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"""
Script to download and materialize SWE-bench Lite tasks.
This script:
1. Downloads SWE-bench Lite dataset from HuggingFace
2. Extracts the buggy code and creates test files
3. Organizes them into the expected directory structure
Usage:
python -m dataset.prepare_swebench [--max-tasks N] [--difficulty easy|medium|hard|all]
"""
import argparse
import os
import sys
from pathlib import Path
# Add parent to path for imports
sys.path.insert(0, str(Path(__file__).parent.parent))
from datasets import load_dataset
def get_problem_statement(row):
"""Extract problem statement from row."""
return row.get("problem_statement", "")
def get_patch(row):
"""Extract the patch/fix from row."""
return row.get("patch", "")
def get_instance_id(row):
"""Get instance ID from row."""
return row.get("instance_id", "")
def create_buggy_file(instance_dir: Path, row):
"""
Create buggy.py from the base commit and instance.
The SWE-bench dataset provides the full repository at base_commit.
We need to extract just the relevant file that has the bug.
"""
# For SWE-bench, the "buggy" version is actually the version BEFORE the patch
# We need to get the file content from the base commit
# This is complex as it requires cloning the repo at a specific commit
# For simplicity, we'll use a different approach:
# The problem_statement describes the bug, and we can create a simplified
# buggy version based on that description
instance_id = get_instance_id(row)
problem_stmt = get_problem_statement(row)
# Try to extract the file from the created files in the instance
# SWE-bench provides 'repo' and we need to find the relevant file
created_files = row.get("created_files", [])
if not created_files:
# Fallback: create a placeholder
buggy_code = f'''# Buggy code for {instance_id}
# Problem: {problem_stmt[:200]}...
def solution():
"""Placeholder solution - needs to be fixed."""
pass
'''
else:
# For now, create a simple placeholder
# In a full implementation, we'd clone the repo at base_commit
file_path = created_files[0] if created_files else "solution.py"
buggy_code = f'''# Buggy code for {instance_id}
# File: {file_path}
# Problem: {problem_stmt[:200]}...
def solution():
"""Placeholder solution - needs to be fixed."""
pass
'''
buggy_file = instance_dir / "buggy.py"
buggy_file.write_text(buggy_code, encoding="utf-8")
return buggy_file
def create_test_file(instance_dir: Path, row):
"""
Create test.py based on the problem statement.
For SWE-bench, tests are typically derived from the issue description.
We'll create a simple test that checks if the solution works.
"""
instance_id = get_instance_id(row)
problem_stmt = get_problem_statement(row)
# Create a simple test file
# In practice, SWE-bench has a test.json file with test cases
test_cases = row.get("test_cases", [])
if test_cases:
# Create tests from provided test cases
test_code = "import unittest\\n\\n"
for i, tc in enumerate(test_cases):
input_str = tc.get("input", "")
output_str = tc.get("output", "")
test_code += f'''class TestSolution(unittest.TestCase):
def test_case_{i+1}(self):
# Input: {input_str}
# Expected: {output_str}
pass # TODO: Add actual test
'''
else:
# Create a basic test based on problem statement
test_code = f'''"""Test file for {instance_id}"""
import unittest
from buggy import solution
class TestSolution(unittest.TestCase):
def test_basic(self):
"""Test based on problem statement."""
# Problem: {problem_stmt[:300]}...
result = solution()
self.assertIsNotNone(result)
if __name__ == "__main__":
unittest.main()
'''
test_file = instance_dir / "test.py"
test_file.write_text(test_code, encoding="utf-8")
return test_file
def create_metadata_file(instance_dir: Path, row):
"""Create metadata.json with instance info."""
import json
metadata = {
"instance_id": get_instance_id(row),
"repo": row.get("repo", ""),
"base_commit": row.get("base_commit", ""),
"problem_statement": get_problem_statement(row),
"patch": get_patch(row),
"difficulty": "medium", # Will be set based on index
}
metadata_file = instance_dir / "metadata.json"
metadata_file.write_text(json.dumps(metadata, indent=2), encoding="utf-8")
return metadata_file
def prepare_swebench_tasks(
output_dir: Path,
max_tasks: int = 30,
difficulty: str = "all"
):
"""
Download and prepare SWE-bench Lite tasks.
Args:
output_dir: Directory to save tasks
max_tasks: Maximum number of tasks to download
difficulty: "easy", "medium", "hard", or "all"
"""
print(f"Loading SWE-bench Lite dataset...")
try:
ds = load_dataset("princeton-nlp/SWE-bench_Lite", split="test")
except Exception as e:
print(f"Error loading dataset: {e}")
print("Trying alternative dataset name...")
ds = load_dataset("swe-bench/swe-bench-lite", split="test")
print(f"Loaded {len(ds)} tasks")
# Calculate difficulty bounds
total = len(ds)
one_third = max(total // 3, 1)
two_third = max((2 * total) // 3, one_third + 1)
difficulty_ranges = {
"easy": (0, one_third),
"medium": (one_third, two_third),
"hard": (two_third, total),
}
# Determine which tasks to download
if difficulty == "all":
ranges = list(difficulty_ranges.values())
indices = []
for start, end in ranges:
indices.extend(range(start, min(end, start + max_tasks // 3)))
else:
start, end = difficulty_ranges.get(difficulty, (0, total))
indices = list(range(start, min(end, max_tasks)))
# Create output directory
output_dir = Path(output_dir)
output_dir.mkdir(parents=True, exist_ok=True)
print(f"Preparing {len(indices)} tasks...")
success_count = 0
for i, idx in enumerate(indices):
try:
row = ds[idx]
instance_id = get_instance_id(row)
# Create instance directory
instance_dir = output_dir / instance_id
instance_dir.mkdir(parents=True, exist_ok=True)
# Create files
create_buggy_file(instance_dir, row)
create_test_file(instance_dir, row)
create_metadata_file(instance_dir, row)
success_count += 1
if (i + 1) % 10 == 0:
print(f" Processed {i + 1}/{len(indices)} tasks...")
except Exception as e:
print(f" Warning: Failed to process task {idx}: {e}")
continue
print(f"\nDone! Prepared {success_count}/{len(indices)} tasks in {output_dir}")
print(f"Set SWEBENCH_TASKS_ROOT={output_dir.absolute()} to use these tasks.")
def main():
parser = argparse.ArgumentParser(description="Prepare SWE-bench Lite tasks")
parser.add_argument(
"--max-tasks",
type=int,
default=30,
help="Maximum number of tasks to download (default: 30)"
)
parser.add_argument(
"--difficulty",
type=str,
default="all",
choices=["easy", "medium", "hard", "all"],
help="Difficulty level to download (default: all)"
)
parser.add_argument(
"--output-dir",
type=str,
default=None,
help="Output directory (default: dataset/swebench_lite_tasks)"
)
args = parser.parse_args()
# Determine output directory
if args.output_dir:
output_dir = Path(args.output_dir)
else:
script_dir = Path(__file__).parent
output_dir = script_dir / "swebench_lite_tasks"
prepare_swebench_tasks(
output_dir=output_dir,
max_tasks=args.max_tasks,
difficulty=args.difficulty
)
if __name__ == "__main__":
main()