Andreas/mtg_python_deckbuilder
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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.

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Added logic for 'Kindred Support' tagging in tagger
This commit is contained in:
mwisnowski 2024-12-26 09:38:21 -08:00
parent c81a5fb64e
commit f9ae7fa41e
3 changed files with 111 additions and 111 deletions
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29
main.py
View file

@ -1,10 +1,6 @@
from __future__ import annotations
#import os
import inquirer.prompt # type: ignore
#import pandas as pd # type: ignore
#import requests # type: ignore
#import scrython # type: ignore
import sys
from pathlib import Path
@ -24,20 +20,28 @@ while True:
choices=['Setup', 'Build a Deck', 'Get Card Info', 'Quit'],
carousel=True)
]
try:
answer = inquirer.prompt(question)
if answer is None:
print("Operation cancelled. Returning to menu...")
choice = 'Menu'
continue
choice = answer['menu']
except (KeyError, TypeError):
print("Invalid input. Please try again.")
choice = 'Menu'
# Run through initial setup
while choice == 'Setup':
setup.setup()
choice = 'Menu'
break
# Make a new deck
while choice == 'Build a Deck':
print('Deck building not yet implemented')
choice = 'Menu'
break
# Get a cards info
while choice == 'Get Card Info':
@ -47,15 +51,20 @@ while True:
message='Would you like to look up another card?'
)
]
try:
answer = inquirer.prompt(question)
if answer is None:
print("Operation cancelled. Returning to menu...")
choice = 'Menu'
continue
new_card = answer['continue']
if new_card:
choice == 'Get Card Info'
else:
choice = 'Get Card Info' # Fixed == to = for assignment
except (KeyError, TypeError):
print("Invalid input. Returning to menu...")
choice = 'Menu'
break
# Quit
while choice == 'Quit':
sys.exit()
break

57
setup.py
View file

@ -37,12 +37,15 @@ def filter_by_color(df, column_name, value, new_csv_name):
filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'heart']
filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'acorn']
for card in banned_cards:
filtered_df = filtered_df[~filtered_df['name'].str.contains(card)]
card_types = ['Plane —', 'Conspiracy', 'Vanguard', 'Scheme', 'Phenomenon', 'Stickers', 'Attraction', 'Hero', 'Contraption']
for card_type in card_types:
filtered_df = filtered_df[~filtered_df['type'].str.contains(card_type)]
filtered_df['faceName'] = filtered_df['faceName'].fillna(filtered_df['name'])
filtered_df.drop_duplicates(subset='faceName', keep='first', inplace=True)
columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'text', 'power', 'toughness', 'keywords']
columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'layout', 'text', 'power', 'toughness', 'keywords']
filtered_df = filtered_df[columns_to_keep]
filtered_df.sort_values(by='name', key=lambda col: col.str.lower(), inplace=True)
@ -93,12 +96,15 @@ def set_lands():
filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'heart']
filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'acorn']
card_types = ['Plane —', 'Conspiracy', 'Vanguard', 'Scheme', 'Phenomenon', 'Stickers', 'Attraction', 'Hero']
for card in banned_cards:
filtered_df = filtered_df[~filtered_df['name'].str.contains(card)]
card_types = ['Plane —', 'Conspiracy', 'Vanguard', 'Scheme', 'Phenomenon', 'Stickers', 'Attraction', 'Hero', 'Contraption']
for card_type in card_types:
filtered_df = filtered_df[~filtered_df['type'].str.contains(card_type)]
filtered_df['faceName'] = filtered_df['faceName'].fillna(filtered_df['name'])
filtered_df.drop_duplicates(subset='faceName', keep='first', inplace=True)
columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'layout', 'text']
columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'layout', 'text', 'power', 'toughness', 'keywords']
filtered_df = filtered_df[columns_to_keep]
filtered_df.sort_values(by='edhrecRank', inplace=True)
filtered_df.to_csv(f'{csv_directory}/land_cards.csv', index=False)
@ -156,12 +162,15 @@ def determine_commanders():
filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'heart']
filtered_df = filtered_df.loc[filtered_df['securityStamp'] != 'acorn']
card_types = ['Plane —', 'Conspiracy', 'Vanguard', 'Scheme', 'Phenomena', 'Stickers', 'Attraction']
for card in banned_cards:
filtered_df = filtered_df[~filtered_df['name'].str.contains(card)]
card_types = ['Plane —', 'Conspiracy', 'Vanguard', 'Scheme', 'Phenomenon', 'Stickers', 'Attraction', 'Hero', 'Contraption']
for card_type in card_types:
filtered_df = filtered_df[~filtered_df['type'].str.contains(card_type)]
filtered_df['faceName'] = filtered_df['faceName'].fillna(filtered_df['name'])
filtered_df.drop_duplicates(subset='faceName', keep='first', inplace=True)
columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'keywords', 'text', 'power', 'toughness']
columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'layout', 'text', 'power', 'toughness', 'keywords']
filtered_df = filtered_df[columns_to_keep]
filtered_df.sort_values(by='name', key=lambda col: col.str.lower(), inplace=True)
filtered_df.to_csv(f'{csv_directory}/commander_cards.csv', index=False)
@ -192,7 +201,7 @@ def initial_setup():
print('Checking for color identity sorted files.\n')
# For loop to iterate through the colors
for i in range(len(colors), len(color_abrv)):
for i in range(min(len(colors), len(color_abrv))):
print(f'Checking for {colors[i]}_cards.csv.')
try:
with open(f'{csv_directory}/{colors[i]}_cards.csv', 'r', encoding='utf-8'):
@ -282,40 +291,6 @@ def regenerate_csv_by_color(color):
# Lastly, create a file with all lands, or cards that have a land on at least one face
set_lands()
def generate_staple_lists():
for color in colors:
staples = []
print(f'Checking for {color} staples file.')
try:
with open(f'staples/{color}.txt', 'r') as file:
staples = file.read().split('\n')
del staples[-1]
print(f'{color.capitalize()} staples:')
print('\n'.join(staples), '\n')
except FileNotFoundError:
print(f'{color.capitalize()} staples file not found.')
print(f'Generating {color} staples list.')
df = pd.read_csv(f'{csv_directory}/{color}_cards.csv')
df['edhrecRank'] = pd.to_numeric(df['edhrecRank'], downcast='integer', errors='coerce')
df = df.dropna(subset=['edhrecRank'])
df['edhrecRank'] = df['edhrecRank'].astype(int)
columns_to_keep = ['name', 'edhrecRank', 'type']
df = df[columns_to_keep]
df.sort_values(by='edhrecRank', key=lambda col: col, inplace=True)
i = 1
y = 0
while len(staples) < 20 and y < len(df):
for index, row in df.iterrows():
if row['edhrecRank'] == i:
if 'Land' not in row['type'] and row['name'] not in banned_cards:
staples.append(row['name'])
i += 1
y += 1
with open(f'staples/{color}.txt', 'w') as f:
for items in staples:
f.write('%s\n' %items)
def add_tags():
pass
@ -349,7 +324,7 @@ def setup():
break
break
#regenerate_csvs_all()
regenerate_csvs_all()
#regenerate_csv_by_color('white')
#determine_commanders()
#set_lands()

94
tagger.py
View file

@ -1,5 +1,6 @@
from __future__ import annotations
import os
import pandas as pd # type: ignore
import settings
@ -8,45 +9,46 @@ from settings import artifact_tokens, csv_directory, colors, counter_types, ench
from setup import regenerate_csv_by_color
from utility import pluralize, sort_list
karnstruct = '0/0 colorless Construct'
### Setup
## Load the dataframe
def load_dataframe(color):
# Setup an output file for card processing
"""f = open(f'tag_output/{color}_tagging.txt', 'w+')
f.write(f'Begin tagging {color}_cards.csv.\n')
f.close()"""
# Iterate through the defined {color}_cards.csv file to find spells matter cards
print(f'Loading {color}_cards.csv as a pandas dataframe.\n')
# Setup dataframe
while True:
"""Load and validate the card dataframe for a given color"""
try:
with open(f'{csv_directory}/{color}_cards.csv', 'r', encoding='utf-8') as f:
print(f'{color}_cards.csv found.')
f.close()
break
except FileNotFoundError:
filepath = f'{csv_directory}/{color}_cards.csv'
# Check if file exists, regenerate if needed
if not os.path.exists(filepath):
print(f'{color}_cards.csv not found, regenerating it.')
regenerate_csv_by_color(color)
check_df = pd.read_csv(f'{csv_directory}/{color}_cards.csv')
column_checks = ['creatureTypes', 'themeTags']
if 'themeTags' not in check_df.columns or 'creatureTypes' not in check_df.columns:
for column in column_checks:
if column in check_df.columns:
print(f'"{column}" column in {color}_cards.csv.')
elif column not in check_df.columns:
print(f'"{column}" column not found in {color}_cards.csv.\n')
if column == 'creatureTypes':
kindred_tagging(check_df, color)
if column == 'themeTags':
create_theme_tags(check_df, color)
if 'themeTags' in check_df.columns and 'creatureTypes' in check_df.columns:
df = pd.read_csv(f'{csv_directory}/{color}_cards.csv', converters={'themeTags': pd.eval, 'creatureTypes': pd.eval})
# Load initial dataframe for validation
check_df = pd.read_csv(filepath)
# Validate required columns
required_columns = ['creatureTypes', 'themeTags']
missing_columns = [col for col in required_columns if col not in check_df.columns]
# Handle missing columns
if missing_columns:
print(f"Missing columns: {missing_columns}")
if 'creatureTypes' not in check_df.columns:
kindred_tagging(check_df, color)
if 'themeTags' not in check_df.columns:
create_theme_tags(check_df, color)
# Load final dataframe with proper converters
df = pd.read_csv(filepath, converters={'themeTags': pd.eval, 'creatureTypes': pd.eval})
# Process the dataframe
tag_by_color(df, color)
except FileNotFoundError as e:
print(f'Error: {e}')
except pd.errors.ParserError:
print('Error parsing the CSV file.')
except Exception as e:
print(f'An unexpected error occurred: {e}')
## Tag cards on a color-by-color basis
def tag_by_color(df, color):
@ -130,6 +132,7 @@ def kindred_tagging(df, color):
df.at[index, 'creatureTypes'] = kindred_tags
print(f'Creature types set in {color}_cards.csv.\n')
print('==========\n')
# Set outlaws
print(f'Checking for and setting Outlaw types in {color}_cards.csv')
outlaws = ['Assassin', 'Mercenary', 'Pirate', 'Rogue', 'Warlock']
@ -144,19 +147,17 @@ def kindred_tagging(df, color):
df.at[index, 'creatureTypes'] = kindred_tags
print(f'Outlaw types set in {color}_cards.csv.\n')
print('==========\n')
# Check for creature types in text (i.e. how 'Voja, Jaws of the Conclave' cares about Elves)
print(f'Checking for and setting creature types found in the text of cards in {color}_cards.csv')
for index, row in df.iterrows():
kindred_tags = row['creatureTypes']
if pd.isna(row['text']):
continue
split_text = row['text'].split()
ignore_list = ['Elite Inquisitor', 'Breaker of Armies', 'Cleopatra, Exiled Pharaoh', 'Nath\'s Buffoon']
for creature_type in settings.creature_types:
if ('Elite Inquisitor' in row['name']
or 'Breaker of Armies' in row['name']
or 'Cleopatra, Exiled Pharaoh' in row['name']
or 'Nath\'s Buffoon' in row['name']):
if row['name'] in ignore_list:
continue
if creature_type in row['name']:
continue
@ -167,8 +168,6 @@ def kindred_tagging(df, color):
if creature_type not in row['name']:
if creature_type not in kindred_tags:
kindred_tags.append(creature_type)
if creature_type in outlaws:
kindred_tags.append(creature_type)
df.at[index, 'creatureTypes'] = kindred_tags
# Tag for pluralized types (i.e. Elves, Wolves, etc...) in textbox
@ -176,10 +175,9 @@ def kindred_tagging(df, color):
if pluralize(f'{creature_type}') not in row['name']:
if creature_type not in kindred_tags:
kindred_tags.append(creature_type)
if creature_type in outlaws:
kindred_tags.append(creature_type)
df.at[index, 'creatureTypes'] = kindred_tags
print(f'Creature types from text set in {color}_cards.csv.\n')
# Overwrite file with creature type tags
columns_to_keep = ['name', 'faceName','edhrecRank', 'colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'creatureTypes', 'text', 'power', 'toughness', 'keywords']
df = df[columns_to_keep]
@ -256,6 +254,24 @@ def add_creatures_to_tags(df, color):
# Overwrite file with kindred tags added
print(f'Creature types added to theme tags in {color}_cards.csv.\n')
print('==========\n')
# Set Kindred Support
print(f'Checking for and setting Kindred Support tag in {color}_cards.csv')
all_kindred = ['changeling', 'choose a creature type', 'shares a creature type',
'shares at least one creature type', 'you control of the chosen type']
for index, row in df.iterrows():
if pd.isna(row['text']):
continue
theme_tags = row['themeTags']
#if all_kindred in row['text'].lower():
for item in all_kindred:
if item in row['text'].lower():
if 'Kindred Support' not in theme_tags:
theme_tags.extend(['Kindred Support'])
df.at[index, 'themeTags'] = theme_tags
print(f'"Kindred Support" tag set in {color}_cards.csv.\n')
## Add keywords to theme tags
def tag_for_keywords(df, color):