import csv
from datetime import datetime

import pydantic
import json
import os
import yaml

README_META = os.getenv('README_META', '{}')
DESCRIPTION = os.getenv('DESCRIPTION', '')
MODE = os.getenv('MODE', '')

def parse_yaml_from_readme_to_dict(readme_path: str):
    with open(readme_path, 'r') as f:
        lines = f.read()
    yaml_str = ''.join(lines)
    parts = yaml_str.split("---")
    try:
        obj = yaml.load(parts[1], Loader=yaml.FullLoader)
    except Exception as e:
        print(e, yaml_str)
        obj = {}
    return obj

def get_target_csv_file_from_outputs():
    output_dir = './outputs/demo'
    dirname = os.listdir(output_dir)[0]
    output_dir = os.path.join(output_dir, dirname, 'summary')
    files = os.listdir(output_dir)
    csv_file = ''
    for file in files:
        if file.endswith('.csv'):
            csv_file = file
            break
    return os.path.join(output_dir, csv_file)

def parse_results_to_json(csv_path: str, output_dir: str):
    if not os.path.exists(csv_path):
        raise Exception(f'csv_path: {csv_path} not exists')
    if not os.path.exists(output_dir):
        os.mkdir(output_dir)

    with open(csv_path, 'r') as file:
        # 创建一个 CSV reader 对象
        reader = csv.reader(file)
        # 读取 CSV 文件的数据
        data = list(reader)
        print(data)

    class Dataset(pydantic.BaseModel):
        csv_index: int
        name: str  # 数据集名
        version: str
        measure_name: str  # 指标名
        type_: str


    datasets = []
    for i in range(1, len(data)):
        name = data[i][0].strip()
        if '---' in name:
            print(f'skip non-row line: {name}')
            continue
        print(f'dataset: {data[i][0]}, version: {data[i][1]}, measure_name: {data[i][2]},type_: {data[i][3]}')
        dataset = Dataset(csv_index=i, name=name, version=data[i][1], measure_name=data[i][2],
                        type_=data[i][3], value=-1)
        datasets.append(dataset)


    class Model(pydantic.BaseModel):
        csv_index: int
        id: str
        description: str
        updatedAt: str
        mode: str
        results: dict
        metadata: dict


    models = []
    for i in range(4, len(data[0])):
        print(f'model name: {data[0][i]}')
        model = Model(csv_index=i, id=data[0][i], description=str(DESCRIPTION), updatedAt=str(datetime.now().strftime("%Y-%m-%d %H:%M:%S")), mode=str(MODE), results={}, metadata=json.loads(README_META))
        models.append(model)


    dict_models = []
    for model in models:
        res = {}
        for dataset in datasets:
            value_str = data[dataset.csv_index][model.csv_index].strip()
            if value_str != '-':
                try:
                    value = float(value_str)
                except Exception:
                    continue
                res[dataset.name] = value
        print(res)
        model.results = res
        dict_models.append(model.dict())


    for dict_model in dict_models:
        if dict_model.get("id") == '':
            continue
        del dict_model['csv_index']
        # replace / and @ to -
        # output_dir = './outputs/'
        target_filename = dict_model.get("id").replace('/', '-').replace('@', '-')
        m_path = os.path.join(output_dir, target_filename + '.json')
        with open(m_path, 'w') as f:
            f.write(json.dumps(dict_model, indent=4, ensure_ascii=False))

if __name__ == '__main__':
    csv_file = get_target_csv_file_from_outputs()
    parse_results_to_json(csv_file, './leaderboards')