mirror of
https://github.com/mwisnowski/mtg_python_deckbuilder.git
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Began work on refactoring deck_builder
Fixed logging for the other files such that they actually log to the file instead of just creating it
This commit is contained in:
mwisnowski
parent
503068b20c
commit
e0dd09adee
8 changed files with 1228 additions and 807 deletions
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@ -1,7 +1,24 @@
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"""MTG Python Deckbuilder setup utilities.
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This module provides utility functions for setting up and managing the MTG Python Deckbuilder
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application. It handles tasks such as downloading card data, filtering cards by various criteria,
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and processing legendary creatures for commander format.
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Key Features:
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- Card data download from MTGJSON
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- DataFrame filtering and processing
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- Color identity filtering
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- Commander validation
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- CSV file management
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The module integrates with settings.py for configuration and exceptions.py for error handling.
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"""
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from __future__ import annotations
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# Standard library imports
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import logging
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import os
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import requests
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from pathlib import Path
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from typing import List, Optional, Union, TypedDict
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@ -27,21 +44,19 @@ from exceptions import (
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CommanderValidationError
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)
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"""MTG Python Deckbuilder setup utilities.
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# Create logs directory if it doesn't exist
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if not os.path.exists('logs'):
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os.makedirs('logs')
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This module provides utility functions for setting up and managing the MTG Python Deckbuilder
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application. It handles tasks such as downloading card data, filtering cards by various criteria,
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and processing legendary creatures for commander format.
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Key Features:
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- Card data download from MTGJSON
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- DataFrame filtering and processing
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- Color identity filtering
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- Commander validation
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- CSV file management
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The module integrates with settings.py for configuration and exceptions.py for error handling.
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"""
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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logging.StreamHandler(),
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logging.FileHandler('logs/setup_utils.log', mode='a', encoding='utf-8')
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]
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)
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logger = logging.getLogger(__name__)
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# Type definitions
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class FilterRule(TypedDict):
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@ -83,7 +98,7 @@ def download_cards_csv(url: str, output_path: Union[str, Path]) -> None:
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pbar.update(size)
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except requests.RequestException as e:
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logging.error(f'Failed to download cards data from {url}')
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logger.error(f'Failed to download cards data from {url}')
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raise MTGJSONDownloadError(
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"Failed to download cards data",
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url,
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@ -128,14 +143,14 @@ def filter_dataframe(df: pd.DataFrame, banned_cards: List[str]) -> pd.DataFrame:
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>>> filtered_df = filter_dataframe(cards_df, ['Channel', 'Black Lotus'])
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"""
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try:
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logging.info('Starting standard DataFrame filtering')
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logger.info('Starting standard DataFrame filtering')
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# Fill null values according to configuration
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for col, fill_value in FILL_NA_COLUMNS.items():
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if col == 'faceName':
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fill_value = df['name']
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df[col] = df[col].fillna(fill_value)
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logging.debug(f'Filled NA values in {col} with {fill_value}')
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logger.debug(f'Filled NA values in {col} with {fill_value}')
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# Apply basic filters from configuration
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filtered_df = df.copy()
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@ -148,22 +163,22 @@ def filter_dataframe(df: pd.DataFrame, banned_cards: List[str]) -> pd.DataFrame:
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elif rule_type == 'require':
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for value in values:
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filtered_df = filtered_df[filtered_df[field].str.contains(value, na=False)]
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logging.debug(f'Applied {rule_type} filter for {field}: {values}')
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logger.debug(f'Applied {rule_type} filter for {field}: {values}')
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# Remove illegal sets
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for set_code in NON_LEGAL_SETS:
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filtered_df = filtered_df[~filtered_df['printings'].str.contains(set_code, na=False)]
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logging.debug('Removed illegal sets')
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logger.debug('Removed illegal sets')
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# Remove banned cards
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for card in banned_cards:
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filtered_df = filtered_df[~filtered_df['name'].str.contains(card, na=False)]
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logging.debug('Removed banned cards')
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logger.debug('Removed banned cards')
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# Remove special card types
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for card_type in CARD_TYPES_TO_EXCLUDE:
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filtered_df = filtered_df[~filtered_df['type'].str.contains(card_type, na=False)]
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logging.debug('Removed special card types')
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logger.debug('Removed special card types')
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# Select columns, sort, and drop duplicates
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filtered_df = filtered_df[CSV_PROCESSING_COLUMNS]
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@ -172,12 +187,12 @@ def filter_dataframe(df: pd.DataFrame, banned_cards: List[str]) -> pd.DataFrame:
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key=lambda col: col.str.lower() if not SORT_CONFIG['case_sensitive'] else col
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)
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filtered_df = filtered_df.drop_duplicates(subset='faceName', keep='first')
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logging.info('Completed standard DataFrame filtering')
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logger.info('Completed standard DataFrame filtering')
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return filtered_df
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except Exception as e:
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logging.error(f'Failed to filter DataFrame: {str(e)}')
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logger.error(f'Failed to filter DataFrame: {str(e)}')
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raise DataFrameProcessingError(
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"Failed to filter DataFrame",
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"standard_filtering",
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@ -202,7 +217,7 @@ def filter_by_color_identity(df: pd.DataFrame, color_identity: str) -> pd.DataFr
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DataFrameProcessingError: If general filtering operations fail
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"""
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try:
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logging.info(f'Filtering cards for color identity: {color_identity}')
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logger.info(f'Filtering cards for color identity: {color_identity}')
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# Validate color identity
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with tqdm(total=1, desc='Validating color identity') as pbar:
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@ -222,14 +237,14 @@ def filter_by_color_identity(df: pd.DataFrame, color_identity: str) -> pd.DataFr
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# Filter by color identity
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with tqdm(total=1, desc='Filtering by color identity') as pbar:
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filtered_df = filtered_df[filtered_df['colorIdentity'] == color_identity]
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logging.debug(f'Applied color identity filter: {color_identity}')
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logger.debug(f'Applied color identity filter: {color_identity}')
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pbar.update(1)
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# Additional color-specific processing
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with tqdm(total=1, desc='Performing color-specific processing') as pbar:
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# Placeholder for future color-specific processing
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pbar.update(1)
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logging.info(f'Completed color identity filtering for {color_identity}')
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logger.info(f'Completed color identity filtering for {color_identity}')
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return filtered_df
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except DataFrameProcessingError as e:
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@ -259,7 +274,7 @@ def process_legendary_cards(df: pd.DataFrame) -> pd.DataFrame:
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DataFrameProcessingError: If general processing fails
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"""
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try:
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logging.info('Starting commander validation process')
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logger.info('Starting commander validation process')
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filtered_df = df.copy()
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# Step 1: Check legendary status
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@ -273,7 +288,7 @@ def process_legendary_cards(df: pd.DataFrame) -> pd.DataFrame:
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"DataFrame contains no cards matching legendary criteria"
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)
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filtered_df = filtered_df[mask].copy()
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logging.debug(f'Found {len(filtered_df)} legendary cards')
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logger.debug(f'Found {len(filtered_df)} legendary cards')
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pbar.update(1)
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except Exception as e:
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raise CommanderValidationError(
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@ -288,7 +303,7 @@ def process_legendary_cards(df: pd.DataFrame) -> pd.DataFrame:
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special_cases = df['text'].str.contains('can be your commander', na=False)
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special_commanders = df[special_cases].copy()
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filtered_df = pd.concat([filtered_df, special_commanders]).drop_duplicates()
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logging.debug(f'Added {len(special_commanders)} special commander cards')
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logger.debug(f'Added {len(special_commanders)} special commander cards')
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pbar.update(1)
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except Exception as e:
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raise CommanderValidationError(
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@ -306,7 +321,7 @@ def process_legendary_cards(df: pd.DataFrame) -> pd.DataFrame:
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~filtered_df['printings'].str.contains(set_code, na=False)
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]
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removed_count = initial_count - len(filtered_df)
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logging.debug(f'Removed {removed_count} cards from illegal sets')
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logger.debug(f'Removed {removed_count} cards from illegal sets')
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pbar.update(1)
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except Exception as e:
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raise CommanderValidationError(
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@ -314,7 +329,7 @@ def process_legendary_cards(df: pd.DataFrame) -> pd.DataFrame:
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"set_legality",
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str(e)
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) from e
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logging.info(f'Commander validation complete. {len(filtered_df)} valid commanders found')
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logger.info(f'Commander validation complete. {len(filtered_df)} valid commanders found')
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return filtered_df
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except CommanderValidationError:
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