code: def build_like_board_dataset(
      self,
      category: str,
      boards: List[str],
      max_count: int,
      save_path: Path,
      name: str,
  ):
      category_entries = self.get_category_entries(
          category=category, max_count=max_count
      )
      shuffle(category_entries)
      df_category = build_dataframe(entries=category_entries)
      df_category["category"] = ["category"] * len(category_entries)
      boards_entries = []
      for board in boards:
          boards_entries.extend(
              self.get_board_entries(board=board, max_count=max_count)
          )
      shuffle(boards_entries)
      df_boards = build_dataframe(entries=boards_entries)
      df_boards["category"] = ["board"] * len(df_boards)
  
      for df in [df_category, df_boards]:
          limits = [int(0.8 * len(df)), int(0.1 * len(df))]
          split = ["train"] * limits[0] + ["val"] * limits[1]
          split.extend(["test"] * (len(df) - len(split)))
          df["split"] = split
  
      df = pd.concat([df_category, df_boards])
      if not os.path.exists(save_path):
          os.makedirs(save_path)
      df.to_csv(path_or_buf=save_path + name)
  
file_path: transfer-nlp/data/feedly_data.py
imports: import os
  from pathlib import Path
  from random import shuffle
  from typing import List
  import numpy
  import pandas
  import urllib3
  from bs4 import BeautifulSoup
  from feedly.api_client.stream import StreamOptions
  from feedly.api_client.data import Entry
  from feedly.api_client.session import FeedlySession
label_desc: Use image node_id 6 for calling the FeedlyDownloader obj's underlying member method code with example usage: obj.build_like_board_dataset(category, boards, max_count, save_path, name) without return types