import os
import pandas as pd

def get_data_dict(file_path: str, to_replace:str="##########") -> dict:
    """get data headers from a mol2 file (assumes header lines start with `to_replace`)
    :parameter
        - file_path:
          path to the file of interest
        - to_replace:
          the 'marker' that specifies the header
    :return
        - data_dict
          dict containing the header parts as keys and their values as value
    """
    data_dict = {}
    # open and read file until all header info is read
    with open(file_path, "r") as mol2_file:
        for line in mol2_file:
            # contains header info
            if line.startswith(to_replace):
                key = None
                value = None
                for i in line.split(":"):
                    i = i.strip()
                    if to_replace in i:
                        key = i.replace(to_replace, "").strip()
                    else:
                        value = i
                data_dict[key] = [value]
            # header ended
            else:
                return data_dict

all_data = pd.DataFrame()
# path to the directory containing all files
parent_path = "/PARENT/PATH"
for file in os.listdir(parent_path):
    data_df = pd.DataFrame.from_dict(get_data_dict(os.path.join(parent_path, file)))
    all_data = pd.concat([all_data, data_df])

这会将所有头文件保存在pandas DataFrame中，然后您可以根据自己的喜好对其进行操作（例如：保存为csv或执行其他操作）。对于那些来这里寻找如何解析mol2文件的解决方案的人来说，你可以用biopandas来做。