#!/usr/bin/env python
# Copyright (c) Alibaba, Inc. and its affiliates.

import argparse
import datetime
import math
import multiprocessing
import os
import subprocess
import sys
import tempfile
import time
import unittest
from fnmatch import fnmatch
from multiprocessing.managers import BaseManager
from pathlib import Path
from turtle import shape
from unittest import TestResult, TextTestResult

import pandas
# NOTICE: Tensorflow 1.15 seems not so compatible with pytorch.
#         A segmentation fault may be raise by pytorch cpp library
#         if 'import tensorflow' in front of 'import torch'.
#         Puting a 'import torch' here can bypass this incompatibility.
import torch
import yaml

from modelscope.utils.logger import get_logger
from modelscope.utils.model_tag import ModelTag, commit_model_ut_result
from modelscope.utils.test_utils import (get_case_model_info, set_test_level,
                                         test_level)

logger = get_logger()


def test_cases_result_to_df(result_list):
    table_header = [
        'Name', 'Result', 'Info', 'Start time', 'Stop time',
        'Time cost(seconds)'
    ]
    df = pandas.DataFrame(
        result_list, columns=table_header).sort_values(
            by=['Start time'], ascending=True)
    return df


def statistics_test_result(df):
    total_cases = df.shape[0]
    # yapf: disable
    success_cases = df.loc[df['Result'] == 'Success'].shape[0]
    error_cases = df.loc[df['Result'] == 'Error'].shape[0]
    failures_cases = df.loc[df['Result'] == 'Failures'].shape[0]
    expected_failure_cases = df.loc[df['Result'] == 'ExpectedFailures'].shape[0]
    unexpected_success_cases = df.loc[df['Result'] == 'UnexpectedSuccesses'].shape[0]
    skipped_cases = df.loc[df['Result'] == 'Skipped'].shape[0]
    # yapf: enable

    if failures_cases > 0 or \
       error_cases > 0 or \
       unexpected_success_cases > 0:
        final_result = 'FAILED'
    else:
        final_result = 'SUCCESS'
    result_msg = '%s (Runs=%s,success=%s,failures=%s,errors=%s,\
    skipped=%s,expected failures=%s,unexpected successes=%s)' % (
        final_result, total_cases, success_cases, failures_cases, error_cases,
        skipped_cases, expected_failure_cases, unexpected_success_cases)

    model_cases = get_case_model_info()
    for model_name, case_info in model_cases.items():
        cases = df.loc[df['Name'].str.contains('|'.join(list(case_info)))]
        results = cases['Result']
        result = None
        if any(results == 'Error') or any(results == 'Failures') or any(
                results == 'UnexpectedSuccesses'):
            result = ModelTag.MODEL_FAIL
        elif any(results == 'Success'):
            result = ModelTag.MODEL_PASS
        elif all(results == 'Skipped'):
            result = ModelTag.MODEL_SKIP
        else:
            print(f'invalid results for {model_name} \n{result}')

        if result is not None:
            commit_model_ut_result(model_name, result)
    print('Testing result summary.')
    print(result_msg)
    if final_result == 'FAILED':
        sys.exit(1)


def gather_test_suites_in_files(test_dir, case_file_list, list_tests):
    test_suite = unittest.TestSuite()
    for case in case_file_list:
        test_case = unittest.defaultTestLoader.discover(
            start_dir=test_dir, pattern=case)
        test_suite.addTest(test_case)
        if hasattr(test_case, '__iter__'):
            for subcase in test_case:
                if list_tests:
                    print(subcase)
        else:
            if list_tests:
                print(test_case)
    return test_suite


def gather_test_suites_files(test_dir, pattern):
    case_file_list = []
    for dirpath, dirnames, filenames in os.walk(test_dir):
        for file in filenames:
            if fnmatch(file, pattern):
                case_file_list.append(file)

    return case_file_list


def collect_test_results(case_results):
    result_list = [
    ]  # each item is Case, Result, Start time, Stop time, Time cost
    for case_result in case_results.successes:
        result_list.append(
            (case_result.test_full_name, 'Success', '', case_result.start_time,
             case_result.stop_time, case_result.time_cost))
    for case_result in case_results.errors:
        result_list.append(
            (case_result[0].test_full_name, 'Error', case_result[1],
             case_result[0].start_time, case_result[0].stop_time,
             case_result[0].time_cost))
    for case_result in case_results.skipped:
        result_list.append(
            (case_result[0].test_full_name, 'Skipped', case_result[1],
             case_result[0].start_time, case_result[0].stop_time,
             case_result[0].time_cost))
    for case_result in case_results.expectedFailures:
        result_list.append(
            (case_result[0].test_full_name, 'ExpectedFailures', case_result[1],
             case_result[0].start_time, case_result[0].stop_time,
             case_result[0].time_cost))
    for case_result in case_results.failures:
        result_list.append(
            (case_result[0].test_full_name, 'Failures', case_result[1],
             case_result[0].start_time, case_result[0].stop_time,
             case_result[0].time_cost))
    for case_result in case_results.unexpectedSuccesses:
        result_list.append((case_result.test_full_name, 'UnexpectedSuccesses',
                            '', case_result.start_time, case_result.stop_time,
                            case_result.time_cost))
    return result_list


def run_command_with_popen(cmd):
    with subprocess.Popen(
            cmd,
            stdout=subprocess.PIPE,
            stderr=subprocess.STDOUT,
            bufsize=1,
            encoding='utf8') as sub_process:
        for line in iter(sub_process.stdout.readline, ''):
            sys.stdout.write(line)


def async_run_command_with_popen(cmd, device_id):
    logger.info('Worker id: %s args: %s' % (device_id, cmd))
    env = os.environ.copy()
    env['CUDA_VISIBLE_DEVICES'] = '%s' % device_id
    sub_process = subprocess.Popen(
        cmd,
        stdout=subprocess.PIPE,
        stderr=subprocess.STDOUT,
        bufsize=1,
        universal_newlines=True,
        env=env,
        encoding='utf8')
    return sub_process


def save_test_result(df, args):
    if args.result_dir is not None:
        file_name = str(int(datetime.datetime.now().timestamp() * 1000))
        os.umask(0)
        Path(args.result_dir).mkdir(mode=0o777, parents=True, exist_ok=True)
        Path(os.path.join(args.result_dir, file_name)).touch(
            mode=0o666, exist_ok=True)
        df.to_pickle(os.path.join(args.result_dir, file_name))


def run_command(cmd):
    logger.info('Running command: %s' % ' '.join(cmd))
    response = subprocess.run(
        cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
    try:
        response.check_returncode()
        logger.info(response.stdout.decode('utf8'))
    except subprocess.CalledProcessError as error:
        logger.error(
            'stdout: %s, stderr: %s' %
            (response.stdout.decode('utf8'), error.stderr.decode('utf8')))


def install_packages(pkgs):
    cmd = [sys.executable, '-m', 'pip', 'install']
    for pkg in pkgs:
        cmd.append(pkg)

    run_command(cmd)


def install_requirements(requirements):
    for req in requirements:
        cmd = [
            sys.executable, '-m', 'pip', 'install', '-r',
            'requirements/%s' % req, '-f',
            'https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html'
        ]
        run_command(cmd)


def wait_for_free_worker(workers):
    while True:
        for idx, worker in enumerate(workers):
            if worker is None:
                logger.info('return free worker: %s' % (idx))
                return idx
            if worker.poll() is None:  # running, get output
                for line in iter(worker.stdout.readline, ''):
                    if line != '':
                        sys.stdout.write(line)
                    else:
                        break
            else:  # worker process completed.
                logger.info('Process end: %s' % (idx))
                workers[idx] = None
                return idx
        time.sleep(0.001)


def wait_for_workers(workers):
    while True:
        for idx, worker in enumerate(workers):
            if worker is None:
                continue
            # check worker is completed.
            if worker.poll() is None:
                for line in iter(worker.stdout.readline, ''):
                    if line != '':
                        sys.stdout.write(line)
                    else:
                        break
            else:
                logger.info('Process idx: %s end!' % (idx))
                workers[idx] = None

        is_all_completed = True
        for idx, worker in enumerate(workers):
            if worker is not None:
                is_all_completed = False
                break

        if is_all_completed:
            logger.info('All sub porcess is completed!')
            break
        time.sleep(0.001)


def parallel_run_case_in_env(env_name, env, test_suite_env_map, isolated_cases,
                             result_dir, parallel):
    logger.info('Running case in env: %s' % env_name)
    # install requirements and deps # run_config['envs'][env]
    if 'requirements' in env:
        install_requirements(env['requirements'])
    if 'dependencies' in env:
        install_packages(env['dependencies'])
    # case worker processes
    worker_processes = [None] * parallel
    for test_suite_file in isolated_cases:  # run case in subprocess
        if test_suite_file in test_suite_env_map and test_suite_env_map[
                test_suite_file] == env_name:
            cmd = [
                'python',
                'tests/run.py',
                '--pattern',
                test_suite_file,
                '--result_dir',
                result_dir,
            ]
            worker_idx = wait_for_free_worker(worker_processes)
            worker_process = async_run_command_with_popen(cmd, worker_idx)
            os.set_blocking(worker_process.stdout.fileno(), False)
            worker_processes[worker_idx] = worker_process
        else:
            pass  # case not in run list.

    # run remain cases in a process.
    remain_suite_files = []
    for k, v in test_suite_env_map.items():
        if k not in isolated_cases and v == env_name:
            remain_suite_files.append(k)
    if len(remain_suite_files) == 0:
        return
    # roughly split case in parallel
    part_count = math.ceil(len(remain_suite_files) / parallel)
    suites_chunks = [
        remain_suite_files[x:x + part_count]
        for x in range(0, len(remain_suite_files), part_count)
    ]
    for suites_chunk in suites_chunks:
        worker_idx = wait_for_free_worker(worker_processes)
        cmd = [
            'python', 'tests/run.py', '--result_dir', result_dir, '--suites'
        ]
        for suite in suites_chunk:
            cmd.append(suite)
        worker_process = async_run_command_with_popen(cmd, worker_idx)
        os.set_blocking(worker_process.stdout.fileno(), False)
        worker_processes[worker_idx] = worker_process

    wait_for_workers(worker_processes)


def run_case_in_env(env_name, env, test_suite_env_map, isolated_cases,
                    result_dir):
    # install requirements and deps # run_config['envs'][env]
    if 'requirements' in env:
        install_requirements(env['requirements'])
    if 'dependencies' in env:
        install_packages(env['dependencies'])

    for test_suite_file in isolated_cases:  # run case in subprocess
        if test_suite_file in test_suite_env_map and test_suite_env_map[
                test_suite_file] == env_name:
            cmd = [
                'python',
                'tests/run.py',
                '--pattern',
                test_suite_file,
                '--result_dir',
                result_dir,
            ]
            run_command_with_popen(cmd)
        else:
            pass  # case not in run list.

    # run remain cases in a process.
    remain_suite_files = []
    for k, v in test_suite_env_map.items():
        if k not in isolated_cases and v == env_name:
            remain_suite_files.append(k)
    if len(remain_suite_files) == 0:
        return
    cmd = ['python', 'tests/run.py', '--result_dir', result_dir, '--suites']
    for suite in remain_suite_files:
        cmd.append(suite)
    run_command_with_popen(cmd)


def run_in_subprocess(args):
    # only case args.isolated_cases run in subporcess, all other run in a subprocess
    test_suite_files = gather_test_suites_files(
        os.path.abspath(args.test_dir), args.pattern)
    run_config = None
    isolated_cases = []
    test_suite_env_map = {}
    # put all the case in default env.
    for test_suite_file in test_suite_files:
        test_suite_env_map[test_suite_file] = 'default'

    if args.run_config is not None and Path(args.run_config).exists():
        with open(args.run_config, encoding='utf-8') as f:
            run_config = yaml.load(f, Loader=yaml.FullLoader)
        if 'isolated' in run_config:
            isolated_cases = run_config['isolated']

        if 'envs' in run_config:
            for env in run_config['envs']:
                if env != 'default':
                    for test_suite in run_config['envs'][env]['tests']:
                        if test_suite in test_suite_env_map:
                            test_suite_env_map[test_suite] = env

    if args.subprocess:  # run all case in subprocess
        isolated_cases = test_suite_files

    with tempfile.TemporaryDirectory() as temp_result_dir:
        for env in set(test_suite_env_map.values()):
            parallel_run_case_in_env(env, run_config['envs'][env],
                                     test_suite_env_map, isolated_cases,
                                     temp_result_dir, args.parallel)

        result_dfs = []
        result_path = Path(temp_result_dir)
        for result in result_path.iterdir():
            if Path.is_file(result):
                df = pandas.read_pickle(result)
                result_dfs.append(df)
        result_pd = pandas.concat(
            result_dfs)  # merge result of every test suite.
        print_table_result(result_pd)
        print_abnormal_case_info(result_pd)
        statistics_test_result(result_pd)


def get_object_full_name(obj):
    klass = obj.__class__
    module = klass.__module__
    if module == 'builtins':
        return klass.__qualname__
    return module + '.' + klass.__qualname__


class TimeCostTextTestResult(TextTestResult):
    """Record test case time used!"""

    def __init__(self, stream, descriptions, verbosity):
        self.successes = []
        return super(TimeCostTextTestResult,
                     self).__init__(stream, descriptions, verbosity)

    def startTest(self, test):
        test.start_time = datetime.datetime.now()
        test.test_full_name = get_object_full_name(
            test) + '.' + test._testMethodName
        self.stream.writeln('Test case:  %s start at: %s' %
                            (test.test_full_name, test.start_time))

        return super(TimeCostTextTestResult, self).startTest(test)

    def stopTest(self, test):
        TextTestResult.stopTest(self, test)
        test.stop_time = datetime.datetime.now()
        test.time_cost = (test.stop_time - test.start_time).total_seconds()
        self.stream.writeln(
            'Test case: %s stop at: %s, cost time: %s(seconds)' %
            (test.test_full_name, test.stop_time, test.time_cost))
        if torch.cuda.is_available(
        ) and test.time_cost > 5.0:  # print nvidia-smi
            cmd = ['nvidia-smi']
            run_command_with_popen(cmd)
        super(TimeCostTextTestResult, self).stopTest(test)

    def addSuccess(self, test):
        self.successes.append(test)
        super(TextTestResult, self).addSuccess(test)


class TimeCostTextTestRunner(unittest.runner.TextTestRunner):
    resultclass = TimeCostTextTestResult

    def run(self, test):
        return super(TimeCostTextTestRunner, self).run(test)

    def _makeResult(self):
        result = super(TimeCostTextTestRunner, self)._makeResult()
        return result


def gather_test_cases(test_dir, pattern, list_tests):
    case_list = []
    for dirpath, dirnames, filenames in os.walk(test_dir):
        for file in filenames:
            if fnmatch(file, pattern):
                case_list.append(file)

    test_suite = unittest.TestSuite()

    for case in case_list:
        test_case = unittest.defaultTestLoader.discover(
            start_dir=test_dir, pattern=case)
        test_suite.addTest(test_case)
        if hasattr(test_case, '__iter__'):
            for subcase in test_case:
                if list_tests:
                    print(subcase)
        else:
            if list_tests:
                print(test_case)
    return test_suite


def print_abnormal_case_info(df):
    df = df.loc[(df['Result'] == 'Error') | (df['Result'] == 'Failures')]
    for _, row in df.iterrows():
        print('Case %s run result: %s, msg:\n%s' %
              (row['Name'], row['Result'], row['Info']))


def print_table_result(df):
    df = df.loc[df['Result'] != 'Skipped']
    df = df.drop('Info', axis=1)
    formatters = {
        'Name': '{{:<{}s}}'.format(df['Name'].str.len().max()).format,
        'Result': '{{:<{}s}}'.format(df['Result'].str.len().max()).format,
    }
    with pandas.option_context('display.max_rows', None, 'display.max_columns',
                               None, 'display.width', None):
        print(df.to_string(justify='left', formatters=formatters, index=False))


def main(args):
    runner = TimeCostTextTestRunner()
    if args.suites is not None and len(args.suites) > 0:
        logger.info('Running: %s' % ' '.join(args.suites))
        test_suite = gather_test_suites_in_files(args.test_dir, args.suites,
                                                 args.list_tests)
    else:
        test_suite = gather_test_cases(
            os.path.abspath(args.test_dir), args.pattern, args.list_tests)
    if not args.list_tests:
        result = runner.run(test_suite)
        logger.info('Running case completed, pid: %s, suites: %s' %
                    (os.getpid(), args.suites))
        result = collect_test_results(result)
        df = test_cases_result_to_df(result)
        if args.result_dir is not None:
            save_test_result(df, args)
        else:
            print_table_result(df)
            print_abnormal_case_info(df)
            statistics_test_result(df)


if __name__ == '__main__':
    parser = argparse.ArgumentParser('test runner')
    parser.add_argument(
        '--list_tests', action='store_true', help='list all tests')
    parser.add_argument(
        '--pattern', default='test_*.py', help='test file pattern')
    parser.add_argument(
        '--test_dir', default='tests', help='directory to be tested')
    parser.add_argument(
        '--level', default=0, type=int, help='2 -- all, 1 -- p1, 0 -- p0')
    parser.add_argument(
        '--disable_profile', action='store_true', help='disable profiling')
    parser.add_argument(
        '--run_config',
        default=None,
        help='specified case run config file(yaml file)')
    parser.add_argument(
        '--subprocess',
        action='store_true',
        help='run all test suite in subprocess')
    parser.add_argument(
        '--result_dir',
        default=None,
        help='Save result to directory, internal use only')
    parser.add_argument(
        '--parallel',
        default=1,
        type=int,
        help='Set case parallels, default single process, set with gpu number.'
    )
    parser.add_argument(
        '--suites',
        nargs='*',
        help='Run specified test suites(test suite files list split by space)')
    args = parser.parse_args()
    set_test_level(args.level)
    os.environ['REGRESSION_BASELINE'] = '1'
    logger.info(f'TEST LEVEL: {test_level()}')
    if not args.disable_profile:
        from utils import profiler
        logger.info('enable profile ...')
        profiler.enable()
    if args.run_config is not None or args.subprocess:
        run_in_subprocess(args)
    else:
        main(args)