docstr: Reads edgelists from a Parquet file.
  
  col arguments can either be the column name or the offset of the col.
docstr_tok: ["Reads","edgelists","from","a","Parquet","file",".","col","arguments","can","either","be","the","column","name","or","the","offset","of","the","col","."]
code: def __init__(
      self,
      lhs_col: str,
      rhs_col: str,
      rel_col: Optional[str],
      weight_col: Optional[str],
  ):
      """Reads edgelists from a Parquet file.
  
      col arguments can either be the column name or the offset of the col.
      """
      self.lhs_col = lhs_col
      self.rhs_col = rhs_col
      self.rel_col = rel_col
      self.weight_col = weight_col
  
imports: import datetime
  import random
  from abc import ABC, abstractmethod
  from contextlib import ExitStack
  from pathlib import Path
  from typing import Any, Counter, Dict, Iterable, List, Optional, Tuple
  import torch
  from torchbiggraph.config import EntitySchema, RelationSchema
  from torchbiggraph.converters.dictionary import Dictionary
  from torchbiggraph.edgelist import EdgeList
  from torchbiggraph.entitylist import EntityList
  from torchbiggraph.graph_storages import AbstractEdgeAppender, AbstractEdgeStorage, AbstractEntityStorage, AbstractRelationTypeStorage, EDGE_STORAGES, ENTITY_STORAGES, RELATION_TYPE_STORAGES
  from torchbiggraph.types import UNPARTITIONED
label_desc: Use image node_id 1 to create a new ParquetEdgelistReader object from inherited base classes: EdgelistReader with example: obj = ParquetEdgelistReader(lhs_col, rhs_col, rel_col, weight_col)