get api data

import sys #import libraries
from xml.etree import ElementTree as ET #parsing xml
import glob #for testing with local files
from urllib.request import urlopen #when trying to parse xml from url
import pandas as pd#for csv
import time
import os
#safepath='./extract/isbnlist/'
filelist=glob.glob('./extract/Reihe A/Reihe*_extract.csv',recursive=True) #there is currently only one file, but later on, there will be multiple files
print(filelist)
for file in filelist:
    print('currently looking at file: ' + file)
    #read csv, make a list of all isbns
    data=pd.read_csv(file, sep="\t",  encoding='utf8')
    isbnlist=[]
    for row in data['ISBN']:
        isbnlist.append(row)
        #print ('currently looking at row: ' + row)

        for isbn in isbnlist:
            with urlopen('https://sru.k10plus.de/opac-de-627!rec=1?version=1.1&operation=searchRetrieve&query=pica.isb%3D' + isbn + '+and+pica.bib%3D20735&maximumRecords=10&recordSchema=marcxml') as file:
                doc = ET.parse(file)
                root = doc.getroot()
                namespaces = {
        "zs": "http://www.loc.gov/zing/srw/",
        "": "http://www.loc.gov/MARC21/slim",
        }
        datafield_nodes_path = "./zs:records/zs:record/zs:recordData/record/datafield"  # XPath
        datafield_attribute_filters = [ #which fields to extract
        {
            "tag": "100", #author
            "ind1": "1",
            "ind2": " ",
        }]
        aut = []
        for datafield_node in root.iterfind(datafield_nodes_path, namespaces=namespaces):
            if datafield_attribute_filters:
                skip_node = True
                for attr_dict in datafield_attribute_filters:
                    for k, v in attr_dict.items():
                        if datafield_node.get(k) != v:
                            break
                    else:
                        skip_node = False
                        break
                if skip_node:
                    continue
            for subfield_node in datafield_node.iterfind("./subfield[@code='a']", namespaces=namespaces):
                aut.append(subfield_node.text) #this gets the author name
        datafield_attribute_filters = [
        {
        "tag": "245", #title
        "ind1": "1",
        "ind2": "0",
        }]
        title = []
        for datafield_node in root.iterfind(datafield_nodes_path, namespaces=namespaces):
            if datafield_attribute_filters:
                skip_node = True
                for attr_dict in datafield_attribute_filters:
                    for k, v in attr_dict.items():
                        if datafield_node.get(k) != v:
                            break
                    else:
                        skip_node = False
                        break
                if skip_node:
                    continue
            for subfield_node in datafield_node.iterfind("./subfield[@code='a']", namespaces=namespaces):
                title.append(subfield_node.text) #this gets the title
        subtitle = []
        for datafield_node in root.iterfind(datafield_nodes_path, namespaces=namespaces):
            if datafield_attribute_filters:
                skip_node = True
                for attr_dict in datafield_attribute_filters:
                    for k, v in attr_dict.items():
                        if datafield_node.get(k) != v:
                            break
                    else:
                        skip_node = False
                        break
                if skip_node:
                    continue
            for subfield_node in datafield_node.iterfind("./subfield[@code='b']", namespaces=namespaces):
                subtitle.append(subfield_node.text)
        datafield_attribute_filters = [
        {
        "tag": "024",
        "ind1": "3",
        "ind2": " ",
        }]
        isbnextract = [] #this gets the isbn, currently errors out if there are multiple isbns
        for datafield_node in root.iterfind(datafield_nodes_path, namespaces=namespaces):
            if datafield_attribute_filters:
                skip_node = True
                for attr_dict in datafield_attribute_filters:
                    for k, v in attr_dict.items():
                        if datafield_node.get(k) != v:
                            break
                    else:
                        skip_node = False
                        break
                if skip_node:
                    continue
            for subfield_node in datafield_node.iterfind("./subfield[@code='a']", namespaces=namespaces):
                isbnextract.append(subfield_node.text)

    df=pd.DataFrame({'author': aut, 'title': title, 'subtitle': subtitle, 'isbn': isbn})
    #save as csv
    df.to_csv("api2.csv")