import argparse
import os
import re
from collections import defaultdict

import pandas as pd
from tqdm import tqdm

from mutpy import commandline
import sys
from io import StringIO
import contextlib
import subprocess

from typing import List, Dict, DefaultDict

ROOT_DIR = os.path.dirname(__file__)
IN_SOURCE_DIR = os.path.join(ROOT_DIR, "benchmark")
IN_TEST_DIR = os.path.join(ROOT_DIR, "tests")
OUT_DIR = os.path.join(ROOT_DIR, "tests")
MUT_PY_PATH = os.path.join(ROOT_DIR, 'env37', 'bin', 'mut.py')
REPS: int = 10


class OutputCapture():
    result: str


@contextlib.contextmanager
def capture_stdout():
    old = sys.stdout
    capturer = StringIO()
    sys.stdout = capturer

    data = OutputCapture()
    yield data

    sys.stdout = old
    data.result = capturer.getvalue()


def run_mutpy(test_path: str, source_path: str) -> float:
    output = subprocess.check_output(
        [sys.executable, MUT_PY_PATH, '-t', source_path, '-u', test_path]).decode('utf-8')
    score = re.search('Mutation score \\[.*]: (\\d+\\.\\d+)%', output).group(1)
    return float(score)


def main():
    parser = argparse.ArgumentParser(prog='mutmuttest.py',
                                     description='Runs MutPy over generated test suite.')
    parser.add_argument('file', type=str, help="Source file to test",
                        nargs="*")

    files = parser.parse_args().file
    if len(files) == 0:
        files = [os.path.splitext(f) for f in os.listdir(IN_SOURCE_DIR)]
        to_test = [file[0] for file in files if file[1] == ".py"]
    else:
        to_test = [os.path.splitext(os.path.basename(file))[0] for file in files]

    scores: List[Dict[str, any]] = []

    to_test = [e for t in to_test for e in ([t] * REPS)]

    for filename in tqdm(to_test, desc="Running mut.py over test suite"):
        source_path = os.path.join(IN_SOURCE_DIR, f"{filename}.py")
        test_path = os.path.join(IN_TEST_DIR, f"test_{filename}.py")
        scores.append({
            'file': filename,
            'score': run_mutpy(test_path, source_path)
        })

    df = pd.DataFrame.from_records(scores)
    df.to_csv(os.path.join(OUT_DIR, 'mutation_results.csv'))


if __name__ == "__main__":
    main()