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feat: complete include/exclude observability, fix validation bugs, and organize tests
- Add structured logging for include/exclude operations with comprehensive event tracking - Fix duplicate counting bug in validation API by eliminating double validation passes - Simplify color identity validation UX by consolidating into single 'illegal' status - Organize project structure by moving all test files to centralized code/tests/ directory - Update documentation reflecting feature completion and production readiness - Add validation test scripts and performance benchmarks confirming targets met - Finalize include/exclude feature as production-ready with EDH format compliance
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matt
parent
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commit
3e4395d6e9
32 changed files with 470 additions and 89 deletions
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@ -2786,85 +2786,26 @@ async def validate_include_exclude_cards(
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elif len(exclude_unique) > MAX_EXCLUDES * 0.8: # 80% capacity warning
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result["excludes"]["warnings"].append(f"Approaching limit: {len(exclude_unique)}/{MAX_EXCLUDES}")
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# Do fuzzy matching regardless of commander (for basic card validation)
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if fuzzy_matching and (include_unique or exclude_unique):
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print(f"DEBUG: Attempting fuzzy matching with {len(include_unique)} includes, {len(exclude_unique)} excludes")
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try:
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# Get card names directly from CSV without requiring commander setup
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import pandas as pd
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cards_df = pd.read_csv('csv_files/cards.csv')
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print(f"DEBUG: CSV columns: {list(cards_df.columns)}")
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# Try to find the name column
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name_column = None
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for col in ['Name', 'name', 'card_name', 'CardName']:
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if col in cards_df.columns:
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name_column = col
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break
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if name_column is None:
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raise ValueError(f"Could not find name column. Available columns: {list(cards_df.columns)}")
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available_cards = set(cards_df[name_column].tolist())
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print(f"DEBUG: Loaded {len(available_cards)} available cards")
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# Validate includes with fuzzy matching
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for card_name in include_unique:
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print(f"DEBUG: Testing include card: {card_name}")
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match_result = fuzzy_match_card_name(card_name, available_cards)
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print(f"DEBUG: Match result - name: {match_result.matched_name}, auto_accepted: {match_result.auto_accepted}, confidence: {match_result.confidence}")
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if match_result.matched_name and match_result.auto_accepted:
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# Exact or high-confidence match
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result["includes"]["fuzzy_matches"][card_name] = match_result.matched_name
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result["includes"]["legal"].append(match_result.matched_name)
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elif not match_result.auto_accepted and match_result.suggestions:
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# Needs confirmation - has suggestions but low confidence
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print(f"DEBUG: Adding confirmation for {card_name}")
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result["confirmation_needed"].append({
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"input": card_name,
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"suggestions": match_result.suggestions,
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"confidence": match_result.confidence,
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"type": "include"
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})
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else:
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# No match found at all, add to illegal
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result["includes"]["illegal"].append(card_name)
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# Validate excludes with fuzzy matching
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for card_name in exclude_unique:
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match_result = fuzzy_match_card_name(card_name, available_cards)
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if match_result.matched_name:
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if match_result.auto_accepted:
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result["excludes"]["fuzzy_matches"][card_name] = match_result.matched_name
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result["excludes"]["legal"].append(match_result.matched_name)
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else:
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# Needs confirmation
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result["confirmation_needed"].append({
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"input": card_name,
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"suggestions": match_result.suggestions,
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"confidence": match_result.confidence,
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"type": "exclude"
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})
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else:
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# No match found, add to illegal
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result["excludes"]["illegal"].append(card_name)
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except Exception as fuzzy_error:
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print(f"DEBUG: Fuzzy matching error: {str(fuzzy_error)}")
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import traceback
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traceback.print_exc()
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result["overall_warnings"].append(f"Fuzzy matching unavailable: {str(fuzzy_error)}")
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# If we have a commander, do advanced validation (color identity, etc.)
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if commander and commander.strip():
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try:
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# Create a temporary builder to get available card names
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# Create a temporary builder
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builder = DeckBuilder()
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# Set up commander FIRST (before setup_dataframes)
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df = builder.load_commander_data()
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commander_rows = df[df["name"] == commander.strip()]
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if not commander_rows.empty:
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# Apply commander selection (this sets commander_row properly)
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builder._apply_commander_selection(commander_rows.iloc[0])
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# Now setup dataframes (this will use the commander info)
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builder.setup_dataframes()
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# Get available card names for fuzzy matching
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available_cards = set(builder._full_cards_df['Name'].tolist())
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name_col = 'name' if 'name' in builder._full_cards_df.columns else 'Name'
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available_cards = set(builder._full_cards_df[name_col].tolist())
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# Validate includes with fuzzy matching
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for card_name in include_unique:
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@ -2915,10 +2856,85 @@ async def validate_include_exclude_cards(
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result["excludes"]["legal"].append(card_name)
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else:
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result["excludes"]["illegal"].append(card_name)
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# Color identity validation for includes (only if we have a valid commander with colors)
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commander_colors = getattr(builder, 'color_identity', [])
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if commander_colors:
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color_validated_includes = []
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for card_name in result["includes"]["legal"]:
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if builder._validate_card_color_identity(card_name):
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color_validated_includes.append(card_name)
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else:
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# Add color-mismatched cards to illegal instead of separate category
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result["includes"]["illegal"].append(card_name)
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# Update legal includes to only those that pass color identity
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result["includes"]["legal"] = color_validated_includes
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except Exception as validation_error:
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# Advanced validation failed, but return basic validation
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result["overall_warnings"].append(f"Advanced validation unavailable: {str(validation_error)}")
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else:
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# No commander provided, do basic fuzzy matching only
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if fuzzy_matching and (include_unique or exclude_unique):
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try:
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# Get card names directly from CSV without requiring commander setup
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import pandas as pd
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cards_df = pd.read_csv('csv_files/cards.csv')
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# Try to find the name column
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name_column = None
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for col in ['Name', 'name', 'card_name', 'CardName']:
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if col in cards_df.columns:
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name_column = col
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break
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if name_column is None:
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raise ValueError(f"Could not find name column. Available columns: {list(cards_df.columns)}")
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available_cards = set(cards_df[name_column].tolist())
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# Validate includes with fuzzy matching
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for card_name in include_unique:
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match_result = fuzzy_match_card_name(card_name, available_cards)
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if match_result.matched_name and match_result.auto_accepted:
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# Exact or high-confidence match
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result["includes"]["fuzzy_matches"][card_name] = match_result.matched_name
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result["includes"]["legal"].append(match_result.matched_name)
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elif not match_result.auto_accepted and match_result.suggestions:
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# Needs confirmation - has suggestions but low confidence
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result["confirmation_needed"].append({
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"input": card_name,
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"suggestions": match_result.suggestions,
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"confidence": match_result.confidence,
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"type": "include"
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})
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else:
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# No match found at all, add to illegal
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result["includes"]["illegal"].append(card_name)
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# Validate excludes with fuzzy matching
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for card_name in exclude_unique:
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match_result = fuzzy_match_card_name(card_name, available_cards)
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if match_result.matched_name:
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if match_result.auto_accepted:
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result["excludes"]["fuzzy_matches"][card_name] = match_result.matched_name
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result["excludes"]["legal"].append(match_result.matched_name)
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else:
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# Needs confirmation
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result["confirmation_needed"].append({
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"input": card_name,
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"suggestions": match_result.suggestions,
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"confidence": match_result.confidence,
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"type": "exclude"
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})
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else:
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# No match found, add to illegal
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result["excludes"]["illegal"].append(card_name)
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except Exception as fuzzy_error:
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result["overall_warnings"].append(f"Fuzzy matching unavailable: {str(fuzzy_error)}")
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return JSONResponse(result)
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