Datasets:
| import json | |
| # Load the JSON data from your file | |
| with open('discord_logs.json', 'r') as json_file: | |
| data = json.load(json_file) | |
| # Define the minimum values for filtering | |
| minimum_average_token_length = 125 # Set your desired minimum average token length | |
| minimum_median_token_length = 125 # Set your desired minimum median token length | |
| minimum_conversations_length = 6 # Set your desired minimum length of the 'conversations' array | |
| # Filter the items that meet the minimum criteria | |
| filtered_items = [ | |
| item for item in data | |
| if item.get('average_token_length', 0) >= minimum_average_token_length | |
| and item.get('median_token_length', 0) >= minimum_median_token_length | |
| and len(item.get('conversations', [])) >= minimum_conversations_length | |
| ] | |
| # Save the filtered items to a new JSON file | |
| with open(f'{minimum_median_token_length}_tokens_{minimum_conversations_length}_messages.json', 'w') as filtered_json_file: | |
| json.dump(filtered_items, filtered_json_file, indent=4) | |
| # Optionally, you can print the filtered items | |
| for i, item in enumerate(filtered_items): | |
| print(f"Filtered Item {i + 1} - Average Token Length: {item.get('average_token_length')}, Conversations Length: {len(item.get('conversations', []))}") |