cubescripts/cube_pool.py
2021-02-22 22:21:36 -05:00

62 lines
2.3 KiB
Python

# Loads disjoint pools from a cube CSV
import collections
import csv
import itertools
import random
from collections import defaultdict
from typing import Dict, List, Set
import cubecobra_csv
class CubePool:
def __init__(self):
self._categories = defaultdict(list)
def add_card(self, card_name: str, color_category: str):
assert color_category in 'wubrgchml', f'{card_name}: {color_category}'
self._categories[color_category].append(card_name)
def wide_sample(self, n: int) -> List[str]:
wide_iterator = list(itertools.chain.from_iterable(self._categories.values()))
sample = random.sample(wide_iterator, n)
return sample
def category_sample(self, color_category: str, n: int) -> List[str]:
return random.sample(self._categories[color_category], n)
def draw_from_category(self, color_category: str, n: int) -> List[str]:
drawn = self.category_sample(color_category, n)
self.remove_cards(drawn, color_category)
return drawn
def remove_cards(self, removed: List[str], color_category: str):
existing_counter = collections.Counter(self._categories[color_category])
removed_counter = collections.Counter(removed)
self._categories[color_category] = list((existing_counter - removed_counter).elements())
def load_pools(csv_path: str, pool_tags: Set[str]) -> Dict[str, CubePool]:
pools = defaultdict(CubePool)
with open(csv_path) as f:
reader = csv.reader(f)
header_line = next(reader)
cubecobra_csv.assert_header(header_line)
for line in reader:
card = cubecobra_csv.get_name(line)
tags = cubecobra_csv.get_tags(line)
# print(f'{card} {tags}')
pool_tags_for_card = pool_tags.intersection(tags)
if len(pool_tags_for_card) == 0:
print(f'{card} does not have any of the tags: {pool_tags}')
elif len(pool_tags_for_card) > 1:
print(f'{card} should only be tagged as one in {pool_tags} '
'but is tagged as {pool_tags_for_card}')
else:
(pool_tag,) = pool_tags_for_card
color_category = cubecobra_csv.get_color_category(line)
# print(f'{card} {color_category}')
pools[pool_tag].add_card(card, color_category)
return pools