| 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 = "../original_json_data" |
| |
| |
| json_files = find_json_files(directory) |
| |
| |
| df, skipped_files = load_json_to_dataframe(json_files) |
| |
| |
| 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() |
|
|