FQuant Document

Appearance

Util - 示例 ​

阅读路径 ​

🟢🔵 新手+开发者：README → quick-start → examples → concepts

案例1：数据处理流水线 ​

python
from FQBase.Util.converters import parse_number, percentage_change
from FQBase.Util.transformer import dict_to_df, pandas_to_json

data = {
    'symbol': ['AAPL', 'GOOGL', 'MSFT'],
    'price': ['150.25', '2800.50', '300.75'],
    'volume': ['1000000', '500000', '750000']
}

df = dict_to_df(data)
df['price'] = df['price'].apply(lambda x: parse_number(x, 0.0))
df['volume'] = df['volume'].apply(lambda x: parse_number(x, 0.0))

json_result = pandas_to_json(df)
print(f"Processed {len(json_result)} records")

案例2：批量文件哈希计算 ​

python
from FQBase.Util.file import file_md5, file_sha256
from FQBase.Util.parallel import ParallelProcess
import os

def hash_file(filepath):
    return {
        'file': filepath,
        'md5': file_md5(filepath),
        'sha256': file_sha256(filepath)
    }

files = [os.path.join('/data', f) for f in os.listdir('/data') if os.path.isfile(os.path.join('/data', f))]

runner = ParallelProcess(max_workers=4)
results = runner.map(hash_file, files)

相关文档 ​