"""Deep test of pygount determinism - check EXACT output."""
import subprocess
import json
import hashlib
from pathlib import Path
import tempfile
import time

# Create a test file with known content
test_content = '''"""Test module."""

def function_one():
    """Function one."""
    x = 1
    y = 2
    return x + y

class MyClass:
    """A class."""
    
    def method(self):
        """Method."""
        # Comment line
        pass

if __name__ == "__main__":
    print("Hello")
'''

temp_file = Path(tempfile.mktemp(suffix=".py"))
temp_file.write_text(test_content, encoding='utf-8')

print(f"Test file: {temp_file}")
print(f"Content hash: {hashlib.md5(test_content.encode()).hexdigest()}")
print()

# Run pygount 10 times and collect EXACT JSON output
results = []
for i in range(10):
    proc = subprocess.run(['pygount', '--format', 'json', str(temp_file)], 
                         capture_output=True, text=True, check=True)
    
    # Parse JSON
    data = json.loads(proc.stdout)
    
    # Extract the file entry
    if isinstance(data, list):
        item = data[0]
    else:
        item = data['files'][0]
    
    results.append({
        'run': i + 1,
        'raw_json': proc.stdout,
        'lineCount': item.get('lineCount'),
        'sourceCount': item.get('sourceCount'),
        'codeCount': item.get('codeCount'),
        'documentationCount': item.get('documentationCount'),
        'emptyCount': item.get('emptyCount'),
        'stringCount': item.get('stringCount'),
        'language': item.get('language'),
    })
    
    print(f"Run {i+1}: code={item.get('codeCount')}, doc={item.get('documentationCount')}, "
          f"empty={item.get('emptyCount')}, source={item.get('sourceCount')}")

# Check if ALL runs produced IDENTICAL results
print()
print("=" * 70)
print("CHECKING FOR DIFFERENCES")
print("=" * 70)

first = results[0]
all_identical = True

for i, result in enumerate(results[1:], 2):
    if result['lineCount'] != first['lineCount'] or \
       result['sourceCount'] != first['sourceCount'] or \
       result['codeCount'] != first['codeCount'] or \
       result['documentationCount'] != first['documentationCount'] or \
       result['emptyCount'] != first['emptyCount']:
        
        print(f"\n❌ DIFFERENCE FOUND in run {i}:")
        print(f"  Run 1: lineCount={first['lineCount']}, sourceCount={first['sourceCount']}, "
              f"codeCount={first['codeCount']}, doc={first['documentationCount']}, empty={first['emptyCount']}")
        print(f"  Run {i}: lineCount={result['lineCount']}, sourceCount={result['sourceCount']}, "
              f"codeCount={result['codeCount']}, doc={result['documentationCount']}, empty={result['emptyCount']}")
        all_identical = False

# Check if raw JSON is byte-for-byte identical
json_hashes = [hashlib.md5(r['raw_json'].encode()).hexdigest() for r in results]
unique_hashes = set(json_hashes)

print()
if len(unique_hashes) == 1:
    print("✅ All JSON outputs are BYTE-FOR-BYTE IDENTICAL")
    print(f"   JSON hash: {json_hashes[0]}")
else:
    print(f"❌ Found {len(unique_hashes)} DIFFERENT JSON outputs:")
    for h in unique_hashes:
        count = json_hashes.count(h)
        print(f"   Hash {h[:8]}... appeared {count} times")
    
    # Show first difference in detail
    print("\n   First two different outputs:")
    for i, result in enumerate(results):
        if json_hashes[i] != json_hashes[0]:
            print(f"\n   Run 1 JSON:\n{results[0]['raw_json']}")
            print(f"\n   Run {i+1} JSON:\n{result['raw_json']}")
            break

print()
if all_identical:
    print("🎉 CONCLUSION: pygount IS deterministic (all numeric values identical)")
else:
    print("⚠️  CONCLUSION: pygount is NOT deterministic (values differ between runs)")
    print("    → This tool cannot be used for reliable baseline comparison")
    print("    → Recommend switching to a deterministic counting library")

# Cleanup
temp_file.unlink()