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https://github.com/mwisnowski/mtg_python_deckbuilder.git
synced 2025-09-22 04:50:46 +02:00
Adjusted some logic in setup to filter out any banned cards, as well as add the layout column to allow for easily seeing 'Normal', 'MDFC', or 'Transform cards.
Added logic for 'Kindred Support' tagging in tagger
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mwisnowski
parent
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commit
f9ae7fa41e
3 changed files with 111 additions and 111 deletions
73
setup.py
73
setup.py
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@ -37,12 +37,15 @@ def filter_by_color(df, column_name, value, new_csv_name):
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filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'heart']
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filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'acorn']
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for card in banned_cards:
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filtered_df = filtered_df[~filtered_df['name'].str.contains(card)]
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card_types = ['Plane —', 'Conspiracy', 'Vanguard', 'Scheme', 'Phenomenon', 'Stickers', 'Attraction', 'Hero', 'Contraption']
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for card_type in card_types:
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filtered_df = filtered_df[~filtered_df['type'].str.contains(card_type)]
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filtered_df['faceName'] = filtered_df['faceName'].fillna(filtered_df['name'])
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filtered_df.drop_duplicates(subset='faceName', keep='first', inplace=True)
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columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'text', 'power', 'toughness', 'keywords']
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columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'layout', 'text', 'power', 'toughness', 'keywords']
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filtered_df = filtered_df[columns_to_keep]
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filtered_df.sort_values(by='name', key=lambda col: col.str.lower(), inplace=True)
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@ -91,14 +94,17 @@ def set_lands():
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filtered_df = filtered_df[filtered_df['availability'].str.contains('paper')]
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filtered_df = filtered_df.loc[filtered_df['promoTypes'] != 'playtest']
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filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'heart']
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filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'acorn']
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filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'acorn']
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card_types = ['Plane —', 'Conspiracy', 'Vanguard', 'Scheme', 'Phenomenon', 'Stickers', 'Attraction', 'Hero']
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for card in banned_cards:
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filtered_df = filtered_df[~filtered_df['name'].str.contains(card)]
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card_types = ['Plane —', 'Conspiracy', 'Vanguard', 'Scheme', 'Phenomenon', 'Stickers', 'Attraction', 'Hero', 'Contraption']
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for card_type in card_types:
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filtered_df = filtered_df[~filtered_df['type'].str.contains(card_type)]
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filtered_df['faceName'] = filtered_df['faceName'].fillna(filtered_df['name'])
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filtered_df.drop_duplicates(subset='faceName', keep='first', inplace=True)
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columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'layout', 'text']
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columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'layout', 'text', 'power', 'toughness', 'keywords']
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filtered_df = filtered_df[columns_to_keep]
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filtered_df.sort_values(by='edhrecRank', inplace=True)
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filtered_df.to_csv(f'{csv_directory}/land_cards.csv', index=False)
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@ -154,14 +160,17 @@ def determine_commanders():
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filtered_df = filtered_df[filtered_df['availability'].str.contains('paper')]
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filtered_df = filtered_df.loc[filtered_df['promoTypes'] != 'playtest']
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filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'heart']
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filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'acorn']
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filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'acorn']
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card_types = ['Plane —', 'Conspiracy', 'Vanguard', 'Scheme', 'Phenomena', 'Stickers', 'Attraction']
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for card in banned_cards:
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filtered_df = filtered_df[~filtered_df['name'].str.contains(card)]
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card_types = ['Plane —', 'Conspiracy', 'Vanguard', 'Scheme', 'Phenomenon', 'Stickers', 'Attraction', 'Hero', 'Contraption']
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for card_type in card_types:
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filtered_df = filtered_df[~filtered_df['type'].str.contains(card_type)]
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filtered_df['faceName'] = filtered_df['faceName'].fillna(filtered_df['name'])
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filtered_df.drop_duplicates(subset='faceName', keep='first', inplace=True)
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columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'keywords', 'text', 'power', 'toughness']
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columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'layout', 'text', 'power', 'toughness', 'keywords']
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filtered_df = filtered_df[columns_to_keep]
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filtered_df.sort_values(by='name', key=lambda col: col.str.lower(), inplace=True)
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filtered_df.to_csv(f'{csv_directory}/commander_cards.csv', index=False)
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@ -181,18 +190,18 @@ def initial_setup():
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r = requests.get(url)
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with open(f'{csv_directory}/cards.csv', 'wb') as outputfile:
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outputfile.write(r.content)
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# Load cards.csv file into pandas dataframe so it can be further broken down
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df = pd.read_csv(f'{csv_directory}/cards.csv', low_memory=False)
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# Set frames that have nothing for color identity to be 'Colorless' instead
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df['colorIdentity'] = df['colorIdentity'].fillna('Colorless')
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# Check for and create missing, individual color identity sorted CSVs
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print('Checking for color identity sorted files.\n')
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# For loop to iterate through the colors
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for i in range(len(colors), len(color_abrv)):
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for i in range(min(len(colors), len(color_abrv))):
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print(f'Checking for {colors[i]}_cards.csv.')
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try:
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with open(f'{csv_directory}/{colors[i]}_cards.csv', 'r', encoding='utf-8'):
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@ -200,13 +209,13 @@ def initial_setup():
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except FileNotFoundError:
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print(f'{colors[i]}_cards.csv not found, creating one.\n')
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filter_by_color(df, 'colorIdentity', color_abrv[i], f'{csv_directory}/{colors[i]}_cards.csv')
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# Once by-color lists have been made, Determine legendary creatures
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determine_commanders()
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# Lastly, create a file with all lands, or cards that have a land on at least one face
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set_lands()
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# Once Legendary creatures are determined, generate staple lists
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# generate_staple_lists()
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@ -282,40 +291,6 @@ def regenerate_csv_by_color(color):
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# Lastly, create a file with all lands, or cards that have a land on at least one face
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set_lands()
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def generate_staple_lists():
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for color in colors:
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staples = []
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print(f'Checking for {color} staples file.')
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try:
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with open(f'staples/{color}.txt', 'r') as file:
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staples = file.read().split('\n')
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del staples[-1]
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print(f'{color.capitalize()} staples:')
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print('\n'.join(staples), '\n')
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except FileNotFoundError:
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print(f'{color.capitalize()} staples file not found.')
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print(f'Generating {color} staples list.')
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df = pd.read_csv(f'{csv_directory}/{color}_cards.csv')
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df['edhrecRank'] = pd.to_numeric(df['edhrecRank'], downcast='integer', errors='coerce')
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df = df.dropna(subset=['edhrecRank'])
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df['edhrecRank'] = df['edhrecRank'].astype(int)
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columns_to_keep = ['name', 'edhrecRank', 'type']
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df = df[columns_to_keep]
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df.sort_values(by='edhrecRank', key=lambda col: col, inplace=True)
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i = 1
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y = 0
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while len(staples) < 20 and y < len(df):
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for index, row in df.iterrows():
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if row['edhrecRank'] == i:
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if 'Land' not in row['type'] and row['name'] not in banned_cards:
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staples.append(row['name'])
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i += 1
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y += 1
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with open(f'staples/{color}.txt', 'w') as f:
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for items in staples:
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f.write('%s\n' %items)
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def add_tags():
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pass
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@ -349,7 +324,7 @@ def setup():
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break
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break
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#regenerate_csvs_all()
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regenerate_csvs_all()
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#regenerate_csv_by_color('white')
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#determine_commanders()
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#set_lands()
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