import os import json import pandas as pd import re def find_json_files(directory): json_files = [] for root, dirs, files in os.walk(directory): for file in files: if file.endswith(".json"): json_files.append(os.path.join(root, file)) return json_files def clean_and_convert_data(json_data): if "text" in json_data: json_data["text"] = re.sub(r'[^\x00-\x7F]+', ' ', json_data["text"]) int_fields = ["minkilled", "mincaptured", "minleaderskilled", "minfacilitatorskilled", "minleaderscaptured", "minfacilitatorscaptured"] bool_fields = ["killq", "captureq", "killcaptureraid", "airstrike", "noshotsfired", "dataprocessed", "flagged", "glossarymeta", "leaderq"] for field in int_fields: if field in json_data: json_data[field] = int(json_data[field]) for field in bool_fields: if field in json_data: json_data[field] = json_data[field].lower() == "true" return json_data def load_json_to_dataframe(json_files): data = [] skipped_files = [] for file in json_files: try: with open(file, "r") as f: json_data = json.load(f) json_data = clean_and_convert_data(json_data) data.append(json_data) except json.JSONDecodeError as e: print(f"Skipping file {file} due to JSON decoding error: {str(e)}") skipped_files.append(file) return pd.DataFrame(data), skipped_files def main(): # Directory containing the JSON files directory = "../original_json_data" # Find all JSON files recursively within the directory json_files = find_json_files(directory) # Load the contents of JSON files into a pandas DataFrame df, skipped_files = load_json_to_dataframe(json_files) # Export the DataFrame as a Parquet file output_file = "../exported_press_releases_2024.parquet" df.to_parquet(output_file) print(f"Successfully exported {len(json_files) - len(skipped_files)} JSON files to {output_file}") if skipped_files: print(f"Skipped {len(skipped_files)} files due to JSON decoding errors.") print("Skipped files:") for file in skipped_files: print(file) if __name__ == "__main__": main()