def coco_mixer(acc, curr):
return _.flat_map(
acc, lambda xo: {
"id":
curr['id'],
"image_id":
xo['image_id'],
"coco_class":
xo['category_id'],
"x":
xo['bbox'][0],
"y":
xo['bbox'][1],
"bbox_width":
xo['bbox'][2],
"bbox_height":
xo['bbox'][3],
"img_width":
curr['width'],
"img_height":
curr['height'],
"output":
curr['file_name'] + ".txt",
"darkchocolate": [
int(xo['category_id']), xo['bbox'][0] / curr['width'], xo[
'bbox'][1] / curr['height'], xo['bbox'][2] / curr['width'],
xo['bbox'][3] / curr['height']
]
})
def get_available_cells(field: MatrixInt, dimensions: Coord) -> List[Coord]:
checked = find_checked_cells(field)
all_cells = [
Coord(tup) for tup in product(range(dimensions.i), range(dimensions.j))
]
nearby = py_.flat_map(checked,
lambda cell: find_adjacent_cells(cell, all_cells))
return list(set(all_cells) - set(nearby) - set(checked))
def _serarch_by_selects(selects, body_json):
if not selects:
return True
queries = body_json.get('queries', [])
resp_selects = pydash.flat_map(
queries, lambda q: pydash.get(
q, 'Query.Commands.0.SemanticQueryDataShapeCommand.Query.Select'))
return len(set(as_list(selects)) - {s.get('Name')
for s in resp_selects}) == 0
def _search_by_entity(entity, body_json):
if not entity:
return True
queries = body_json.get('queries', [])
query_entities = pydash.flat_map(
queries, lambda q: pydash.get(
q, 'Query.Commands.0.SemanticQueryDataShapeCommand.Query.From'))
entity_names = [pydash.get(qe, 'Entity') for qe in query_entities]
return entity in entity_names
def get_move_candidates(v: MatrixInt) -> List[Coord]:
ships = find_ships(v) # Находим все куски кораблей
# Находим все пустые клетки
empty = [Coord((i, j))
for i, row in enumerate(v)
for j, cell in enumerate(row)
if cell == CellState.CELL_FOG.value]
# Для каждого куска корабля выбираем клетки, где он может продолжаться
candidates = py_.flat_map(ships, lambda ship: calculate_ship_extension(ship, empty))
return candidates or empty
def test_get_page_iobes():
with open('test/fixtures/parade_page_db.json') as f:
parade_page = json.load(f)
with open('test/fixtures/parade_page_contexts.json') as f:
filter_out_of_bounds = lambda mention: mention['offset'] < len(parade_page['content'])
parade_page_contexts = _.map_values(json.load(f),
lambda mentions: list(filter(filter_out_of_bounds, mentions)))
context_pairs = _.mapcat(_.to_pairs(parade_page_contexts),
lambda pair: [[pair[0], mention] for mention in pair[1]])
contexts = _.sort_by(context_pairs,
lambda title_mention: title_mention[1]['offset'])
mentions = _.flat_map(contexts, _.last)
mention_link_titles = list(map(_.head, contexts))
assert parade_iobes == iobes.get_page_iobes(parade_page, mentions, mention_link_titles)
def stat_product(self):
"""统计某天商品数据"""
# 查询当天消费过的商品
res = db.session.query(Order.snap_products).filter_by(
soft=True).filter(Order.order_status != OrderStatus.UNPAID.value,
Order.order_status != OrderStatus.CANCEL.value,
Order._create_time >= self.date_from,
Order._create_time <= self.date_to).all()
if res:
product_dicts = flat_map(res, lambda x: json.loads(x[0]))
products = self.define_products(product_dicts)
else:
products = []
product_ids = db.session.query(Product.id).filter_by(soft=True).all()
# 所有商品ID列表
product_ids = [item[0] for item in product_ids]
# 所有当天消费过的商品ID列表
ids_products_paid = key_by(products, 'id')
with db.auto_commit():
for product_id in product_ids:
total_price_res = Decimal('0.00')
total_count_res = 0
if product_id in ids_products_paid.keys():
total_price_res = ids_products_paid[product_id][
'total_price_str']
total_count_res = ids_products_paid[product_id]['count']
# StatProductDaily.create(
# date=self.one_date,
# product_id=product_id,
# total_price=total_price_res,
# total_count=total_count_res
# )
StatProductDaily.create(
date=self.one_date,
product_id=product_id,
total_price=Decimal(f'{randint(1, 999)}.34'),
total_count=randint(1, 999))
def test_flat_map(case, expected):
assert _.flat_map(*case) == expected