multi-process scraping, transforming unternehmensregister output

This commit is contained in:
TrisNol 2023-06-25 15:58:53 +02:00
parent c9c7b0cf7a
commit 37fb1b1da3
3 changed files with 4105 additions and 591 deletions

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import glob
import multiprocessing
import os
from pathlib import Path
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.ui import WebDriverWait
from tqdm import tqdm
def scrape(query: str, download_dir: list[str]):
download_path = os.path.join(str(Path.cwd()), *download_dir)
print(download_path)
options = webdriver.ChromeOptions()
preferences = {
"profile.default_content_settings.popups": 0,
"safebrowsing.enabled": True,
"download": {
"directory_upgrade": True,
"prompt_for_download": False,
"extensions_to_open": "",
"default_directory": download_path,
},
}
options.add_argument("--headless=new")
options.add_experimental_option("prefs", preferences)
driver = webdriver.Chrome(options=options)
driver.get("https://www.unternehmensregister.de/ureg/")
# Accept Cookies
driver.find_elements(
By.XPATH, '//button[text()="Nur technisch notwendige Cookies akzeptieren"]'
)[0].click()
# Enter search query
driver.find_elements(By.ID, "globalSearchForm:extendedResearchCompanyName")[
0
].send_keys(query)
# Trigger search
driver.find_elements(By.ID, "globalSearchForm:btnExecuteSearchOld")[0].click()
# Wait for results
wait = WebDriverWait(driver, 15)
wait.until(
lambda driver: driver.current_url != "https://www.unternehmensregister.de/ureg/"
)
num_pages = int(
driver.find_element(By.XPATH, '//*[@class="page_count"]').text.split(" ")[0]
)
processed_companies = []
for page_index in tqdm(range(num_pages)):
# Find all "Registerinformationen"
companies_tab = driver.find_elements(
By.LINK_TEXT, "Registerinformationen des Registergerichts"
)
company_names = [
elem.text
for elem in driver.find_elements(
By.XPATH, '//div[@class="company_result"]/span/b'
)
]
for index, company_link in enumerate(companies_tab):
company_name = company_names[index]
if company_name in processed_companies:
continue
# Go to intermediary page
company_link.click()
# Trigger next redirect
driver.find_element(By.LINK_TEXT, "Registerinformationen anzeigen").click()
# Trigger SI download
driver.find_element(By.LINK_TEXT, "SI").click()
# Show shopping cart
wait.until(
EC.visibility_of_element_located(
(By.LINK_TEXT, "Dokumentenkorb ansehen")
)
)
driver.find_element(By.LINK_TEXT, "Dokumentenkorb ansehen").click()
# Get document
elems = driver.find_elements(By.TAG_NAME, "input")
elems[-2].click()
wait.until(
EC.visibility_of_element_located((By.ID, "paymentFormOverview:btnNext"))
)
driver.find_element(By.ID, "paymentFormOverview:btnNext").click()
wait.until(
EC.visibility_of_element_located((By.LINK_TEXT, "Zum Dokumentenkorb"))
)
driver.find_element(By.LINK_TEXT, "Zum Dokumentenkorb").click()
num_files = get_num_files(download_path)
driver.find_element(By.CLASS_NAME, "download-wrapper").click()
try:
wait.until(
lambda x: wait_for_download_condition(download_path, num_files)
)
file_name = "".join(e for e in company_name if e.isalnum()) + ".xml"
rename_latest_file(
download_path,
file_name,
)
processed_companies.append(company_name)
except Exception:
pass
finally:
for click_counter in range(6):
driver.back()
driver.find_element(By.XPATH, '//*[@class="fas fa-angle-right"]').click()
driver.close()
def wait_for_download_condition(
path: str, num_files: int, pattern: str = "*.xml"
) -> bool:
return len(glob.glob1(path, pattern)) > num_files
def get_num_files(path: str, pattern: str = "*.xml") -> int:
return len(glob.glob1(path, pattern))
def rename_latest_file(path: str, filename: str, pattern: str = "*.xml"):
list_of_files = [os.path.join(path, file) for file in glob.glob1(path, pattern)]
latest_download = max(list_of_files, key=os.path.getctime)
os.rename(latest_download, os.path.join(path, filename))
if __name__ == "__main__":
import pandas as pd
df = pd.read_excel(
"./data/study_id42887_top-100-unternehmen-deutschland.xlsx",
sheet_name="Toplist",
skiprows=1,
)
df = df[df["Name"].notna()]
batch_size = 5
pool = multiprocessing.Pool(processes=batch_size)
params = [
(query, ["data", "Unternehmensregister", "scraping", query.strip()])
for query in df.Name
]
# Map the process_handler function to the parameter list using the Pool
pool.starmap(scrape, params)
# Close the Pool to prevent any more tasks from being submitted
pool.close()
# Wait for all the processes to complete
pool.join()

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bs4
selenium
xmltodict
tqdm
tqdm
openpyxl
pandas