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https://github.com/mwisnowski/mtg_python_deckbuilder.git
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Started logic for spellslinger, including storm, magecraft, and started on cantrips
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mwisnowski
parent
856ba0f572
commit
1819104253
4 changed files with 985 additions and 487 deletions
69
setup.py
69
setup.py
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@ -4,7 +4,7 @@ import pandas as pd # type: ignore
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import requests # type: ignore
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import inquirer.prompt # type: ignore
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from settings import banned_cards
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from settings import banned_cards, csv_directory
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colors = ['colorless', 'white', 'blue', 'black', 'green', 'red',
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'azorius', 'orzhov', 'selesnya', 'boros', 'dimir',
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@ -12,6 +12,7 @@ colors = ['colorless', 'white', 'blue', 'black', 'green', 'red',
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'bant', 'esper', 'grixis', 'jund', 'naya',
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'abzan', 'jeskai', 'mardu', 'sultai', 'temur',
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'dune', 'glint', 'ink', 'witch', 'yore', 'wubrg']
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color_abrv = ['Colorless', 'W', 'U', 'B', 'G', 'R',
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'U, W', 'B, W', 'G, W', 'R, W', 'B, U',
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'G, U', 'R, U', 'B, G', 'B, R', 'G, R',
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@ -51,12 +52,20 @@ def determine_legendary():
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# Filter dataframe
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while True:
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try:
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with open('csv_files/cards.csv', 'r', encoding='utf-8'):
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with open(f'{csv_directory}/cards.csv', 'r', encoding='utf-8'):
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print('cards.csv exists.')
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break
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except FileNotFoundError:
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initial_setup()
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# If the cards.csv file does not exist or can't be found, pull it from mtgjson.com
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print('cards.csv not found, downloading from mtgjson')
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url = 'https://mtgjson.com/api/v5/csv/cards.csv'
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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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df = pd.read_csv('csv_files/cards.csv', low_memory=False)
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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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legendary_options = ['Legendary Creature', 'Legendary Artifact Creature', 'Legendary Enchantment Creature']
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filtered_df = df[df['type'].str.contains('|'.join(legendary_options))]
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"""
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@ -80,14 +89,14 @@ def determine_legendary():
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columns_to_keep = ['name', 'faceName','edhrecRank','colorIdentity', 'colors', 'manaCost', 'manaValue', 'type', 'keywords', 'text', 'power', 'toughness']
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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('csv_files/legendary_cards.csv', index=False)
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filtered_df.to_csv(f'{csv_directory}/legendary_cards.csv', index=False)
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print('legendary_cards.csv file generated.')
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def initial_setup():
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print('Checking for cards.csv file.\n')
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while True:
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try:
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with open('csv_files/cards.csv', 'r', encoding='utf-8'):
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with open(f'{csv_directory}/cards.csv', 'r', encoding='utf-8'):
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print('cards.csv exists.')
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break
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except FileNotFoundError:
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@ -95,11 +104,11 @@ def initial_setup():
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print('cards.csv not found, downloading from mtgjson')
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url = 'https://mtgjson.com/api/v5/csv/cards.csv'
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r = requests.get(url)
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with open('csv_files/cards.csv', 'wb') as outputfile:
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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('csv_files/cards.csv', low_memory=False)
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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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@ -111,19 +120,19 @@ def initial_setup():
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for i in range(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_files/{colors[i]}_cards.csv', 'r', encoding='utf-8'):
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with open(f'{csv_directory}/{colors[i]}_cards.csv', 'r', encoding='utf-8'):
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print(f'{colors[i]}_cards.csv exists.\n')
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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_files/{colors[i]}_cards.csv')
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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_legendary()
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# Once Legendary creatures are determined, generate staple lists
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# generate_staple_lists()
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def regenerate_csvs():
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def regenerate_csvs_all():
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"""
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Pull the original cards.csv file and remake the {color}_cards.csv files.
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This is useful if a new set has since come out to ensure the databases are up-to-date
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@ -133,6 +142,7 @@ def regenerate_csvs():
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r = requests.get(url)
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with open('csv_files/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('csv_files/cards.csv', low_memory=False)
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@ -150,6 +160,35 @@ def regenerate_csvs():
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# Once files are regenerated, create a new legendary list
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determine_legendary()
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def regenerate_csv_by_color(color):
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"""
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Pull the original cards.csv file and remake the {color}_cards.csv files
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"""
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# Determine the color_abv to use
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color_abrv_index = colors.index(color)
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color_abv = color_abrv[color_abrv_index]
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print('Downloading cards.csv from mtgjson')
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url = 'https://mtgjson.com/api/v5/csv/cards.csv'
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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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# Color identity sorted cards
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print(f'Regenerating {color}_cards.csv file.\n')
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# Regenerate the file
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print(f'Regenerating {color}_cards.csv.')
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filter_by_color(df, 'colorIdentity', color_abv, f'{csv_directory}/{color}_cards.csv')
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print(f'A new {color}_cards.csv file has been made.\n')
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# Once files are regenerated, create a new legendary list
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determine_legendary()
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def generate_staple_lists():
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for color in colors:
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@ -165,7 +204,7 @@ def generate_staple_lists():
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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_files/{color}_cards.csv')
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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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@ -211,7 +250,7 @@ def setup():
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# Regenerate CSV files
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while choice == 'Regenerate CSV Files':
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regenerate_csvs()
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regenerate_csvs_all()
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break
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# Go back
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while choice == 'Back':
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@ -219,4 +258,4 @@ def setup():
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break
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#setup()
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#regenerate_csvs()
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#regenerate_csv_by_color('colorless')
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