def get_netprofit_with_period(structured_data, from_date, to_date):
full_data = structured_data
filtered = filter_remove_greater_than(structured_data, "날짜",
to_date.strftime("%Y-%m-%d"))
filtered = filter_remove_less_than(filtered, "날짜",
from_date.strftime("%Y-%m-%d"))
filtered = filter_remove_greater_than(filtered, "수량", 0)
earned_profit = 0
for idx in range(len(filtered.data)):
count = int(filtered.get_value_with_label(idx, "수량"))
price = int(filtered.get_value_with_label(idx, "가격"))
cur_date = filtered.get_value_with_label(idx, "날짜")
name = filtered.get_value_with_label(idx, "종목")
stock_infos = get_stock_infos_with_date(
full_data,
datetime.datetime.strptime(cur_date, "%Y-%m-%d") -
datetime.timedelta(days=1))
bep_price = stock_infos[name]["bep_price"]
earned_profit += (price - bep_price) * -count
value_profit = get_valueprofit_with_period(structured_data, to_date) \
- get_valueprofit_with_period(structured_data, from_date)
print("value_profit=[{}]".format(value_profit))
print("earned_profit=[{}]".format(earned_profit))
return value_profit + earned_profit
def get_total_earn(structured_data, target_date):
structured_data = filter_remove_greater_than(structured_data, "날짜",
target_date)
structured_data = convert_to_int(structured_data, "총가격")
structured_data = filter_remove_greater_than(structured_data, "총가격", 0)
structured_data = filter_remove_equals(structured_data, "총가격", "")
balance = 0
for idx, each_row in enumerate(structured_data.data):
# print(structured_data.get_value_with_label(idx, "종목"))
# print(structured_data.get_value_with_label(idx, "총가격"))
# print()
balance += int(structured_data.get_value_with_label(idx, "총가격"))
print()
return -balance
def get_stock_infos_with_date(structured_data, curr_date):
if isinstance(curr_date, datetime.datetime) or isinstance(
curr_date, datetime.date):
curr_date = curr_date.strftime("%Y-%m-%d")
structured_data = filter_remove_greater_than(structured_data, "날짜",
curr_date)
stock_infos = {}
for idx in range(len(structured_data.data)):
name = structured_data.get_value_with_label(idx, "종목")
count = int(structured_data.get_value_with_label(idx, "수량"))
price = int(structured_data.get_value_with_label(idx, "가격"))
if not name in stock_infos:
stock_infos[name] = {
"count": 0,
"avg_price": 0,
}
prev_count, prev_avg_price = stock_infos[name]["count"], stock_infos[
name]["avg_price"]
stock_infos[name]["count"] = prev_count + count
if count > 0:
stock_infos[name]["avg_price"] = (prev_avg_price * prev_count +
price * count) / (prev_count +
count)
stock_infos[name][
"bep_price"] = stock_infos[name]["avg_price"] * 1.0025
if stock_infos[name]["count"] == 0:
del stock_infos[name]
return stock_infos
def get_balance_with_date(structured_data, curr_date):
structured_data = filter_remove_greater_than(
structured_data, "날짜", curr_date.strftime("%Y-%m-%d"))
balance = 0
for idx in range(len(structured_data.data)):
count = int(structured_data.get_value_with_label(idx, "수량"))
price = int(structured_data.get_value_with_label(idx, "가격"))
balance += count * price
return balance
def get_evaluation_stock_sum(structured_data, target_date_as_string):
structured_data = filter_remove_greater_than(structured_data, "날짜",
target_date_as_string)
# structured_data = filter_remove_equals(structured_data, "현재평가금", "")
# print_data(structured_data)
structured_data = sort_by(structured_data, "날짜")
structured_data = sort_by(structured_data, "종목")
current_evaluation = {}
current_quantity = {}
for idx, each in enumerate(structured_data.data):
# print(structured_data.get_value_with_label(idx, "날짜"))
# print(structured_data.get_value_with_label(idx, "종목"))
# print(structured_data.get_value_with_label(idx, "현재평가금"))
# print()
name = structured_data.get_value_with_label(idx, "종목")
current_price = structured_data.get_value_with_label(idx, "현재평가금")
# print("current_price", current_price)
if current_price:
current_evaluation[name] = int(current_price)
if name not in current_quantity:
current_quantity[name] = 0
price = safe_int(structured_data.get_value_with_label(idx, "가격"))
quantity = safe_int(structured_data.get_value_with_label(idx, "수량"))
direction = safe_division(price, abs(price))
# print("direction")
# print(direction)
current_quantity[name] += direction * quantity
# print("name", name)
# print("current_quantity[name]", current_quantity[name])
evaluation_sum = 0
for idx, val in current_evaluation.items():
evaluation_sum += current_quantity[idx] * val
return evaluation_sum
def print_information(structure_data,
target_date,
investment_type,
investment_name=None):
structure_data = filter_remove_not_equals(structure_data, "종류",
investment_type)
if investment_name is not None:
structure_data = filter_remove_not_equals(structure_data, "종목",
investment_name)
structure_data = filter_remove_greater_than(structure_data, "날짜",
target_date)
structure_data = filter_remove_not_equals(structure_data, "환금가능금액", "")
# print("데이터개수", len(structure_data.data))
average_balance = get_average_balance(structure_data, target_date)
start_date_as_string = get_start_date(structure_data)
days = date_minus(target_date, start_date_as_string)
current_profit = get_p2p_profit(structure_data, target_date)
annual_interest_rate = get_annual_interest_rate(current_profit,
average_balance, days)
print_profits(average_balance, current_profit, start_date_as_string,
target_date, days, annual_interest_rate)