procesar_uchile.py

import pandas as pd

print("cargar data")
# Login using e.g. `huggingface-cli login` to access this dataset
df = pd.read_csv("hf://datasets/erickfmm/Tesis_UChile/train.csv", encoding="utf-8")
print("data cargada")

final_data = {}
total = len(df)
for idx, row in df.iterrows():
	#print(idx, row)
	final_data[row["origen"]] = {"_id": row["origen"]} if row["origen"] not in final_data else final_data[row["origen"]]
	
	valor = row["value"] if not pd.isna(row["value"]) or row["value"] is not None else None
	if valor is None:
		continue
	lang = row["lang"] if not pd.isna(row["lang"]) else None
	valor = {"value": valor}
	if lang is not None:
		valor["lang"] = lang

	if pd.isna(row["DC"]) and row["nombre"] == "filelink":
		row["DC"] = "extra.file.link"

	if row["DC"] not in final_data[row["origen"]]:
		final_data[row["origen"]][row["DC"]] = valor
	else:
		if type(final_data[row["origen"]][row["DC"]]) is list:
			final_data[row["origen"]][row["DC"]].append(valor)
		else:
			final_data[row["origen"]][row["DC"]] = [final_data[row["origen"]][row["DC"]], valor]
	if idx % 10000 == 0:
		print("procesados ", idx)
		print(idx/float(total)*100.0, "%")

#import pprint
#pprint.pprint(final_data, indent=2)

import json
#print(json.dumps(final_data, indent=2))
print("save pretty")
json.dump([final_data[idx] for idx in final_data.keys()], open("tesis_uchile_pretty.json", "w", encoding="utf-8"), indent=2, ensure_ascii=False)
print("save min")
json.dump([final_data[idx] for idx in final_data.keys()], open("tesis_uchile_min.json", "w", encoding="utf-8"), ensure_ascii=False)

print("save jsonl")
with open("tesis.uchile.jsonl", "w", encoding="utf-8") as fh:
	for idx in final_data.keys():
		json.dump(final_data[idx], fh, ensure_ascii=False)
		fh.write("\n")
	fh.flush()