import argparse import json import pathlib import os parser = argparse.ArgumentParser( description="Format the output of the data card tool as .md for the hub." ) parser.add_argument("--input_path", "-i", type=pathlib.Path, required=False) parser.add_argument("--output_path", "-o", type=pathlib.Path, required=False) args = parser.parse_args() def read_json_file(json_path: pathlib.Path): """Load a json file and return it as object.""" with open(json_path, "r") as f: data = json.load(f) return data def save_file(json_path: pathlib.Path, json_obj: str): """Takes a string and saves it as .md file.""" with open(json_path, "w") as f: f.write(json.dumps(json_obj, indent=2)) def construct_json(dataset_name: str, data_card_data: dict, text_by_key: dict): """Constructs the json file This function iterates through text_by_key and extracts all answers from the data_card_data object. It uses the levels of hierarchy as indicator for the heading indentation and does not change the order in which anything appears. Args: data_card_data: Output from the data card tool text_by_key: configuration defined in key_to_question.json Returns: data_card_md_string: json content """ try: website_link = data_card_data["overview"]["where"]["website"] except KeyError: website_link = "" try: paper_link = data_card_data["overview"]["where"]["paper-url"] except KeyError: paper_link = "" try: authors = data_card_data["overview"]["credit"]["creators"] except KeyError: authors = "" try: summary = data_card_data["overview"]["what"]["dataset"] except KeyError: summary = "Placeholder" # Add summary blurb with loading script and link to GEM loader summary +=f"\n\nYou can load the dataset via:\n```\nimport datasets\ndata = datasets.load_dataset('GEM/{dataset_name}')\n```\nThe data loader can be found [here](https://huggingface.co/datasets/GEM/{dataset_name})." new_json = { "name": dataset_name, "summary": summary, "sections": [ ], } if website_link: new_json["website"] = website_link if paper_link: new_json["paper"] = paper_link if authors: new_json["authors"] = authors total_questions = 0 total_words = 0 for main_key, main_content in text_by_key.items(): l2_data = { "title": main_content["section-title"], "level": 2, "subsections": [] } if main_key not in data_card_data: continue for second_key, second_content in main_content.items(): if second_key == "section-title": continue # Skip summary data since it is already in the header. if main_key == "overview" and second_key == "what": continue l3_data = { "title": second_content["section-title"], "level": 3, "fields": [] } for final_key, final_content in second_content.items(): if final_key == "section-title": continue try: total_questions += 1 answer = data_card_data[main_key][second_key].get(final_key, "N/A") except: # print(main_key, second_key, final_key) # print("==="*50) # print(data_card_data) continue # Skip empty answers. if isinstance(answer, str): if answer.lower() == "n/a": continue if not answer: continue if isinstance(answer, list): answer = ", ".join([f"`{a}`" for a in answer]) json_answer = { "title": final_content["title"], "level": 4, "content": answer, "flags": final_content["flags"], "info": final_content["info"], "scope": final_content["scope"], } total_words += len(answer.split()) l3_data["fields"].append(json_answer) l2_data["subsections"].append(l3_data) new_json["sections"].append(l2_data) print(f"Total questions {total_questions}") print(f"total words: {total_words}") return new_json, total_words if __name__ == "__main__": text_by_key = read_json_file( os.path.join(os.path.dirname(__file__), "key_to_question.json") ) total_words_across_everything = 0 for dataset in os.listdir("../../../GEMv2"): data_card_path = f"../../../GEMv2/{dataset}/{dataset}.json" if os.path.exists(data_card_path): print(f"Now processing {dataset}.") new_path = f"datacards/{dataset}.json" data_card_data = read_json_file(data_card_path) data_card_json, total_cur_words = construct_json(dataset, data_card_data, text_by_key) total_words_across_everything += total_cur_words save_file(new_path, data_card_json) else: print(f"{dataset} has no data card!") print(total_words_across_everything) # data_card_json = construct_json(data_card_data, text_by_key) # save_file(args.output_path, data_card_json)