<jupyter_start><jupyter_text>VK API is used to load the dataURL: https://vk.com/dev/methods<jupyter_code>%pip install vk_api
import json
import vk_api
def main():

  # authorization 

  vk_session = vk_api.VkApi('login', 'password')
  vk_session.auth()

  # initializing VK tools

  tools = vk_api.VkTools(vk_session)

  # initializing wall.get method 
  # wall.getComments or other methods can also be here

  wall = tools.get_all('wall.get', 100, {'domain': '---'})

  # saving the JSON object with the data

  with open('output.json', 'w') as fw:json.dump(wall, fw, ensure_ascii=False)

  return wall

if __name__ == '__main__':
    main()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12648809523809523, 'fraction_numerical': 0.004464285714285714, 'mean_word_length': 4.299212598425197, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '592856', 'license': 'Apache-2.0', 'n_tokens_mistral': 261, 'n_tokens_neox': 239, 'n_words': 62, 'path': 'Data_Loader.ipynb', 'repo_name': 'vifirsanova/Binary-Text-Classification-with-BERT', 'size': '672'}