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293
mtg_card_fetcher copy.py
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293
mtg_card_fetcher copy.py
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import json
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import csv
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import sys
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from pathlib import Path
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from datetime import datetime
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import openpyxl
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from openpyxl import Workbook
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def flatten_card_data(card):
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"""
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Flatten a single card's data structure into a dictionary suitable for CSV.
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Handles nested fields and converts lists to comma-separated strings.
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"""
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flat_card = {}
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# Basic fields
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simple_fields = [
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'id', 'oracle_id', 'name', 'lang', 'released_at', 'uri', 'scryfall_uri',
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'layout', 'highres_image', 'image_status', 'mana_cost', 'cmc', 'type_line',
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'oracle_text', 'power', 'toughness', 'loyalty', 'life_modifier', 'hand_modifier',
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'reserved', 'foil', 'nonfoil', 'oversized', 'promo', 'reprint', 'variation',
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'set_id', 'set', 'set_name', 'set_type', 'set_uri', 'set_search_uri',
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'scryfall_set_uri', 'rulings_uri', 'prints_search_uri', 'collector_number',
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'digital', 'rarity', 'card_back_id', 'artist', 'border_color', 'frame',
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'full_art', 'textless', 'booster', 'story_spotlight', 'edhrec_rank',
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'penny_rank', 'flavor_text', 'watermark', 'printed_name', 'printed_type_line',
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'printed_text', 'security_stamp', 'preview_text', 'content_warning',
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'flavor_name', 'game_changer'
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]
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# Copy simple fields
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for field in simple_fields:
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if field in card:
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flat_card[field] = card[field]
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# Handle array fields - convert to comma-separated strings
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array_fields = [
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'multiverse_ids', 'colors', 'color_identity', 'keywords', 'produced_mana',
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'games', 'finishes', 'artist_ids', 'all_parts', 'card_faces', 'related_cards'
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]
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for field in array_fields:
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if field in card:
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if isinstance(card[field], list):
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# Convert list items to strings and join
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flat_card[field] = ', '.join(str(item) for item in card[field])
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else:
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flat_card[field] = card[field]
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# Handle MTGO and Arena IDs
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if 'mtgo_id' in card:
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flat_card['mtgo_id'] = card['mtgo_id']
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if 'arena_id' in card:
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flat_card['arena_id'] = card['arena_id']
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if 'tcgplayer_id' in card:
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flat_card['tcgplayer_id'] = card['tcgplayer_id']
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if 'cardmarket_id' in card:
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flat_card['cardmarket_id'] = card['cardmarket_id']
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# Handle image_uris (nested dict)
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if 'image_uris' in card and isinstance(card['image_uris'], dict):
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for key, value in card['image_uris'].items():
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flat_card[f'image_uri_{key}'] = value
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# Handle legalities (nested dict)
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if 'legalities' in card and isinstance(card['legalities'], dict):
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for format_name, status in card['legalities'].items():
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flat_card[f'legal_{format_name}'] = status
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# Handle prices (nested dict)
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if 'prices' in card and isinstance(card['prices'], dict):
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for currency, price in card['prices'].items():
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flat_card[f'price_{currency}'] = price
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# Handle related_uris (nested dict)
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if 'related_uris' in card and isinstance(card['related_uris'], dict):
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for uri_type, uri in card['related_uris'].items():
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flat_card[f'uri_{uri_type}'] = uri
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# Handle purchase_uris (nested dict)
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if 'purchase_uris' in card and isinstance(card['purchase_uris'], dict):
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for store, uri in card['purchase_uris'].items():
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flat_card[f'purchase_{store}'] = uri
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# Handle preview information
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if 'preview' in card and isinstance(card['preview'], dict):
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if 'source' in card['preview']:
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flat_card['preview_source'] = card['preview']['source']
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if 'source_uri' in card['preview']:
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flat_card['preview_source_uri'] = card['preview']['source_uri']
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if 'previewed_at' in card['preview']:
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flat_card['preview_date'] = card['preview']['previewed_at']
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return flat_card
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def detect_json_format(input_file):
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"""
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Detect if the file is NDJSON or JSON array format
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"""
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with open(input_file, 'r', encoding='utf-8') as f:
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# Read first few characters
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first_chars = f.read(100).strip()
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if first_chars.startswith('['):
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return 'array'
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elif first_chars.startswith('{'):
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return 'ndjson'
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else:
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# Try to read first line and detect
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f.seek(0)
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first_line = f.readline().strip()
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if first_line.startswith('[') or first_line == '[':
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return 'array'
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else:
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return 'ndjson'
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def process_scryfall_array(input_file, output_file):
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"""
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Process a Scryfall JSON array file using streaming JSON parser to handle large files.
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"""
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print(f"Processing {input_file} (JSON array format)...")
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print("Loading and parsing JSON data (this may take a minute for large files)...")
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import ijson # We'll need ijson for streaming large JSON arrays
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# First, let's try with regular json
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try:
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with open(input_file, 'r', encoding='utf-8') as f:
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data = json.load(f)
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print(f"Loaded {len(data):,} cards")
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# Analyze structure
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print("Analyzing card structure...")
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all_fields = set()
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for i, card in enumerate(data):
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flat_card = flatten_card_data(card)
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all_fields.update(flat_card.keys())
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if (i + 1) % 10000 == 0:
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print(f" Analyzed {i + 1:,} cards...")
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print(f"Found {len(all_fields)} unique fields")
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fieldnames = sorted(list(all_fields))
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# Write CSV
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print("Writing CSV file...")
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with open(output_file, 'w', newline='', encoding='utf-8') as csvfile:
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writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
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writer.writeheader()
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for i, card in enumerate(data):
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flat_card = flatten_card_data(card)
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writer.writerow(flat_card)
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if (i + 1) % 10000 == 0:
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print(f" Written {i + 1:,} cards...")
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print(f"\nComplete! Written {len(data):,} cards to {output_file}")
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except MemoryError:
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print("File too large for memory. Please install ijson: pip install ijson")
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print("Then run the script again.")
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sys.exit(1)
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except json.JSONDecodeError as e:
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print(f"Error parsing JSON: {e}")
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print("The file might be corrupted or not in valid JSON format.")
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sys.exit(1)
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def process_scryfall_ndjson(input_file, output_file):
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"""
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Process a Scryfall NDJSON (newline-delimited JSON) file and convert it to CSV format.
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"""
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print(f"Processing {input_file} (NDJSON format)...")
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# First pass: collect all possible fields
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print("First pass: Analyzing card structure...")
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all_fields = set()
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cards_processed = 0
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errors = 0
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with open(input_file, 'r', encoding='utf-8') as f:
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for line_num, line in enumerate(f, 1):
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line = line.strip()
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if not line:
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continue
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try:
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card = json.loads(line)
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flat_card = flatten_card_data(card)
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all_fields.update(flat_card.keys())
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cards_processed += 1
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if cards_processed % 10000 == 0:
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print(f" Analyzed {cards_processed:,} cards...")
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except json.JSONDecodeError as e:
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errors += 1
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continue
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print(f"Found {len(all_fields)} unique fields across {cards_processed:,} cards")
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if errors > 0:
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print(f" (Skipped {errors} malformed lines)")
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# Sort fields for consistent column order
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fieldnames = sorted(list(all_fields))
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# Second pass: write CSV
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print("\nSecond pass: Writing CSV...")
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cards_written = 0
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errors = 0
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with open(input_file, 'r', encoding='utf-8') as f:
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with open(output_file, 'w', newline='', encoding='utf-8') as csvfile:
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writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
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writer.writeheader()
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for line_num, line in enumerate(f, 1):
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line = line.strip()
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if not line:
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continue
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try:
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card = json.loads(line)
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flat_card = flatten_card_data(card)
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writer.writerow(flat_card)
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cards_written += 1
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if cards_written % 10000 == 0:
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print(f" Written {cards_written:,} cards...")
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except (json.JSONDecodeError, Exception) as e:
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errors += 1
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continue
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print(f"\nComplete! Written {cards_written:,} cards to {output_file}")
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if errors > 0:
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print(f"Skipped {errors} problematic lines")
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def main():
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"""
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Main function to handle command line arguments and run the conversion.
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"""
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"""
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if len(sys.argv) != 3:
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print("Usage: python3 mtg_card_fetcher.py <input_json_file> <output_csv_file>")
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print("Example: python3 mtg_card_fetcher.py mtg-default-cards-20251018212333.json cards_collection.csv")
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sys.exit(1)
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"""
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if len(sys.argv) != 2:
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print("Usage: python3 mtg_card_fetcher.py <input_json_file>")
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print("Example: python3 mtg_card_fetcher.py mtg-default-cards-20251018212333.json")
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sys.exit(1)
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timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
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input_file = sys.argv[1]
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output_file = f'mtg_cards_{timestamp}.csv' # sys.argv[2]
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# Validate input file exists
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if not Path(input_file).exists():
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print(f"Error: Input file '{input_file}' not found!")
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sys.exit(1)
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# Check file size
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file_size = Path(input_file).stat().st_size / (1024 * 1024) # Size in MB
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print(f"Input file size: {file_size:.1f} MB")
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# Detect format
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print("Detecting file format...")
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format_type = detect_json_format(input_file)
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print(f"Detected format: {format_type.upper()}")
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# Warn if output file exists
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if Path(output_file).exists():
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response = input(f"Warning: Output file '{output_file}' already exists. Overwrite? (y/n): ")
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if response.lower() != 'y':
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print("Cancelled.")
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sys.exit(0)
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try:
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if format_type == 'array':
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process_scryfall_array(input_file, output_file)
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else:
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process_scryfall_ndjson(input_file, output_file)
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except KeyboardInterrupt:
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print("\n\nProcess interrupted by user.")
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sys.exit(1)
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except Exception as e:
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print(f"Error processing file: {e}")
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import traceback
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traceback.print_exc()
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sys.exit(1)
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if __name__ == "__main__":
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main()
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