class VendingMachine:
def __init__(self):
self.stock = Stock({'coke': 5, 'diet coke': 5, 'tea': 5})
self.money_manager = MoneyManager(5)#わかりにくい
#stock探すのと、おつりに入れる
def __check_stock(self, kindOfDrink, coin):
if self.stock.check_stock(kindOfDrink):
#raise ValueError("stockがありません!")
return True
return False
def __check_charge_stock(self, coin):
if self.money_manager.check_charge(coin):
return True
return False
def __buy_drink(self, kindOfDrink, coin):
drink = self.stock.take_from_stock(kindOfDrink)
self.money_manager.take_from_stock_charge(coin)#ここ
return drink
def buy(self, coin, kindOfDrink):#処理ごとにメソッドわける
"""購入する
Arguments:
coin {Coin} -- 投入金額. 100円と500円のみ受け付ける.
kindOfDrink {Enum} -- ジュースの種類.
コーラ({@code Juice.COKE}),ダイエットコーラ({@code Juice.DIET_COKE},お茶({@code Juice.TEA})が指定できる.
Returns:
Drink-- 指定したジュース. 在庫不足や釣り銭不足で買えなかった場合は {@code null} が返される.
"""
#飲み物の在庫確認
if not self.__check_stock(kindOfDrink, coin):
return coin
#釣り銭の在庫確認
if not self.__check_charge_stock(coin):
return coin
#釣り銭の計算と、stockの操作
drink = self.__buy_drink(kindOfDrink, coin)
return drink
def refund(self):
"""お釣りを取り出す
Returns:
int-- お釣りの金額
"""
money = self.money_manager.get_charge()
return money
def build_treemap(stocks):
"""
Takes a list of Stocks and returns a binary tree, constructed greedily,
where each internal node represents the market cap of its two children,
and each leaf is a Stock.
Leaves contain the original Stock objects.
Internal nodes store "Super" stocks that represent the sum of the
market caps of all Stocks in their subtree.
Args:
stocks (list of Stock): a list of Stock objects
Yields:
Tree: the root node of the binary tree
"""
trees = [Tree(stock) for stock in stocks]
trees.sort(reverse=True, key=lambda t: t.value.cap)
while len(trees) > 1:
tree1 = trees.pop()
tree2 = trees.pop()
t1value = tree1.value
t2value = tree2.value
superstock = Stock(t1value.symbol + " " + t2value.symbol,
t1value.cap + t2value.cap,
t1value.change + t2value.change)
trees.append(Tree(superstock, tree1, tree2))
trees.sort(reverse=True, key=lambda t: t.value.cap)
return trees[0]
def setUp(self):
'''
Setting data for unit tests
'''
self.common_stock = Stock('ABCD', EnumStockTypes.COMMON, 100, 8, None, 100)
self.preferred_stock = Stock('EFGH', EnumStockTypes.PREF, 100, 8, 0.02, 100)
self.common_stock_division_by_zero = Stock('ABCD', EnumStockTypes.COMMON, 0, 8, None, 100)
self.preferred_stock_division_by_zero = Stock('EFGH', EnumStockTypes.PREF, 100, 8, 0.02, 0)
self.calculator = Calculator()
self.common_trade = Trade(self.common_stock, datetime.strptime("09/09/18 16:30:31", "%d/%m/%y %H:%M:%S") , 200, EnumBuySellIndicator.BUY.value , 150)
self.preferred_trade = Trade(self.preferred_stock, datetime.strptime("09/09/18 16:30:32", "%d/%m/%y %H:%M:%S"), 300, EnumBuySellIndicator.SELL.value, 200)
self.list_of_trades.append(Trade(self.common_stock, datetime.strptime("09/09/18 16:30:29", "%d/%m/%y %H:%M:%S") , 200, EnumBuySellIndicator.BUY, 150))
self.list_of_trades.append(Trade(self.common_stock, datetime.strptime("09/09/18 16:30:30", "%d/%m/%y %H:%M:%S") , 200, EnumBuySellIndicator.BUY, 150))
self.list_of_trades.append(Trade(self.common_stock, datetime.strptime("09/09/18 16:30:31", "%d/%m/%y %H:%M:%S") , 200, EnumBuySellIndicator.BUY, 150))
self.list_of_trades.append(Trade(self.preferred_stock, datetime.strptime("09/09/18 16:45:30", "%d/%m/%y %H:%M:%S"), 300, EnumBuySellIndicator.SELL, 200))
self.list_of_trades.append(Trade(self.preferred_stock, datetime.strptime("09/09/18 16:45:30", "%d/%m/%y %H:%M:%S"), 300, EnumBuySellIndicator.SELL, 200))
self.list_of_trades.append(Trade(self.preferred_stock, datetime.strptime("09/09/18 16:45:30", "%d/%m/%y %H:%M:%S"), 300, EnumBuySellIndicator.SELL, 200))
def fetch_stock_data(self, stocks, run_no, data_depth, observed_days):
no_go_stocks = ['OBTEST0' + str(i) for i in range(10)]
# try:
html_text = urllib.request.urlopen(
"http://www.netfonds.no/quotes/kurs.php", None, 5).read()
stock_market = re.findall(
re.compile(b'<td name="ju.last.(.+?).OSE">(.+?)</td>'), html_text)
if stocks != 'all':
stock_market = [
stock for stock in stock_market
if stock[0].decode("UTF-8") in stocks
]
if run_no == 0:
for (stock, price) in stock_market:
if stock.decode("UTF-8") not in no_go_stocks:
self.stocks.append(Stock(stock.decode("UTF-8")))
else:
pass
print("Fetching data...")
error_stocks = []
for stock in self.stocks:
if data_depth == 'day':
stock.fetch_intraday_data(run_no)
elif data_depth == 'historic':
error = stock.fetch_historic_data(run_no, observed_days)
if error != None:
error_stocks.append(stock)
self.stocks = [
stock for stock in self.stocks if not stock in error_stocks
]
print("Finished fetching data")
def scrapper():
stock_list = []
driver = webdriver.Chrome(executable_path='/usr/local/bin/chromedriver', )
driver.get("https://finance.yahoo.com/gainers")
result = driver.page_source #load entire page
assert "Stock" in driver.title
tbody = driver.find_element_by_tag_name("tbody")
for row in tbody.find_elements_by_tag_name("tr"):
cells = row.find_elements_by_tag_name("td")
symbol = cells[0].text
name = cells[1].text
price = cells[2].text
change = cells[3].text
percent_change = cells[4].text
stock_list.append(Stock(symbol, name, price, change, percent_change))
top_names = []
top_symbols = []
top_price = []
top_change = []
top_percent_change = []
for top_stock in stock_list[:5]:
top_names.append(top_stock.name)
top_symbols.append(top_stock.symbol)
top_price.append(top_stock.price)
top_change.append(top_stock.change)
top_percent_change.append(top_stock.percent_change)
data_top_5 = {
'Name': top_names,
'Symbol':top_symbols,
'Price':top_price,
'Change':top_change,
'Change (%)':top_percent_change
}
df = pd.DataFrame(data_top_5, columns=['Name', 'Symbol', 'Price', 'Change', 'Change (%)'])
print(df)
driver.close()
def __init__(self, stocks: dict()):
"""Inits Market instance and constructs stock dictionary
"""
self.stocks = {ticker : Stock(ticker) for ticker in stocks}
from timeseries import TimeSeries
import csv
from stocks import StockRecord, Stock
myAPIkey = 'Your API KEY'
ts = TimeSeries(key=myAPIkey, output_format='csv', indexing_type='integer')
data, metadata = ts.get_intraday(symbol='ASX',
interval='60min',
outputsize='full')
IND = StockRecord(symbol='IND')
counter = 0
for row in data:
if counter != 0:
newStockEntry = Stock(counter, row[1], row[4], row[2], row[3], row[5])
IND.addStock(newStockEntry)
counter += 1
print(IND)
IND.showRecords()
print(IND)
def test_create_stock(self, symbol_, last_dividend_, par_value_):
with self.assertRaises(TypeError):
Stock(symbol_, last_dividend_, par_value_)
import argparse
from stocks import Stock
from userinput import CSVInput, UserInput
parser = argparse.ArgumentParser(conflict_handler='resolve')
parser.add_argument('csv_file', nargs='?', default=None, help="CSV file path")
args = parser.parse_args()
csv_file = args.csv_file
if __name__ == "__main__":
all_stock_data = CSVInput().read(csv_file)
user_input = UserInput(list(all_stock_data.keys()))()
stock_records = all_stock_data[user_input['name']]
stock = Stock(stock_records, user_input['start_date'],
user_input['end_date'])
stock.print_all_data()
def __init__(self):
self.stock = Stock({'coke': 5, 'diet coke': 5, 'tea': 5})
self.money_manager = MoneyManager(5)#わかりにくい
def setup(self):
self.stock = Stock('FB')
def process_recos_html(reco_elements):
'''
Input is of type bs4.element.ResultSet.
Each element represents one stock in reco table
which needs to be converted to Stock object and
stored in DB
:param reco_elements:
:return:
'''
# record new recos encountered
new_recos = []
for row in reco_elements:
cells = list(row.find_all('td'))
# Sample row
# 0: <td>
# <a href="/stocks/296/ashiana-housing-ltd#premium-coverage">
# Ashiana Housing </a>
# <small class="text-capitalize drkgrey"></small> </td>
# 1: <td data-order="20171027" width="8%">
# 27-Oct-17 </td>
# 2: <td class="text-right">166.70</td>
# 3: <td class="text-right">147.25</td>
# 4: <td class="text-right" width="">-11.7</td>
# 5: <td class="text-right" width="">3.5</td>
# 6: <td class="text-right">1,520</td>
# 7: <td class="text-right ">39.77</td>
# 8: <td class="text-right ">1.99</td>
# 9: <td class="text-right">24/30</td>
# 10: <td class="text-center text-right"><a class="text-uppercase view-coverage" href="/coverage?company_code=296">view</a></td>
# 11: <td class="text-center text-right">
# <a class="text-uppercase add-watchlist" href="#"> added </a>
# </td>
if len(cells) < 2:
# not a valid row
break
reco_date = cells[1].text.strip()
# Extract name and stock_id from 1st cell
reco_name = cells[0].text.strip()
if '\n' in reco_name:
stock_name, stock_type = reco_name.split('\n')
stock_name = stock_name.strip()
stock_type = stock_type.strip()
else:
stock_name = reco_name
stock_type = 'NA'
# extract href
href = cells[0].find_all('a')[0]['href']
vr_code = href.rsplit('/')[2]
stock_symbol = get_symbol(vr_code)
# Timely or All-weather -- this can be missing.
#stock_type = row.find()
print(f' {stock_name},{stock_type}, {stock_symbol}')
# cells[2] -- market cap not required right now
reco_date_price = cells[3].text.strip()
print(f" 2: {cells[2].text}")
print(f" 3: {cells[3].text}")
#(self, name, type, symbol, reco_date, reco_date_price, stock_id)
# create a stock object check if it exists in db if not add.
if not check_stock_in_db(stock_symbol):
stock = Stock(stock_name, stock_type, stock_symbol, reco_date,
reco_date_price, vr_code)
new_recos.append(stock)
# add_recos to the csv file
add_recos(new_recos)
print(f"Saved {len(new_recos)}")
#TODO Send alert for new recos added using list new_recos
return
def week_8():
'''
create accounts database, within accounts.db there will be 3 tables:
investor, stock, bond
'''
#database name
current_date = date.today()
db_name = "accounts.db"
table_name = "investor"
db_table_headers = """
investor_id text,
name text,
address text,
phone_number text
"""
#create_table investor table if it does not exist
db.create_table(db_name, table_name, db_table_headers)
#create instance of Investor Object uuid generates unique ID in hex format as string
investor = Investor(uuid.uuid1().hex, "Bob Smith",
"2199 S University Blvd, Denver, CO 80208",
"303-871-2000")
#content to add to database record
content = (investor.investor_id, investor.name, investor.address,
investor.phone_number)
#create record in investor table
db.add_one(db_name, table_name, content)
#date object with today's date
print()
#[0][0]access first list and first tuple itme in db query
print("Investor Name: " +
db.get_selected_data(db_name, table_name, "name")[0][0])
print("Investor Address: " +
db.get_selected_data(db_name, table_name, "address")[0][0])
print("Investor Phone: " +
db.get_selected_data(db_name, table_name, "phone_number")[0][0])
'''
====================================================================
STOCK SECTION
====================================================================
'''
#declare variables
sub_header = []
stocks = [] #stores stock object(s)
stock_file = "Lesson6_Data_Stocks.csv"
#opening stock file
try:
read_file = open(stock_file, "r")
except FileNotFoundError:
print("Could not open the file, program terminated! I'll be back!")
exit() #exit application if file cannot be found
#create list of items separated by comma delimiters
sub_header = read_file.readline().split(',')
#remove the '\n' character at the end of the line
sub_header[-1] = sub_header[-1][:-1]
#add investor id to subheader list
sub_header.append("investor_id")
#create stocks table in database
db_name = "accounts.db"
table_name = "stocks"
#sub_header = [0] = SYMBOL, [1] = NO_SHARES, [2] = PUR_PRICE, [3] = CUR_VALUE, [4] = PUR_DATE
db_table_headers = "investor_id text, stock_id text," + sub_header[0] + " text, " \
+ sub_header[1] + " integer, " + sub_header[2] + " real, " \
+ sub_header[3] + " real, " + sub_header[4] + " text"
#create_table investor table if it does not exist
db.create_table(db_name, table_name, db_table_headers)
#read data from stock file and store in stocks[]
for line in read_file:
line_split = line.split(',')
#removed the '/n' from the last item
line_split[-1] = line_split[-1][:-1]
symbol = line_split[0]
quantity = int(line_split[1])
purchase_price = float(line_split[2])
current_price = float(line_split[3])
#converts string formated as MM/DD/YYYY to date object
purchase_date = datetime.strptime(line_split[4], '%m/%d/%Y').date()
#create object and appends to list
stock = Stock(symbol, purchase_price, current_price,quantity,purchase_date, \
investor.investor_id, uuid.uuid1().hex ) #uuid generates unique transaction number
stocks.append(stock)
#add record to database
content = (investor.investor_id, stock.id, stock.symbol,
stock.quantity, stock.purchase_price, stock.current_price,
stock.purchase_date)
#create record in investor table
db.add_one(db_name, table_name, content)
read_file.close()
#sub_header = [0] = SYMBOL, [1] = NO_SHARES, [2] = PUR_PRICE, [3] = CUR_VALUE, [4] = PUR_DATE
data = db.get_selected_data(db_name,"stocks", sub_header[0] + ", " + sub_header[1] + ", " + \
sub_header[2] + ", " + sub_header[3] + ", " + sub_header[4])
#print table stock table
print()
print("=================== Stock Positions ===================")
stock_table = PrettyTable()
stock_table.field_names = [
sub_header[0], sub_header[1], "Earnings/Loss", "Yearly Earning/Loss"
]
for row in data:
#instance of stock class
stock = Stock(row[0], row[2], row[3], row[1], row[4], None, None)
earnings = round(stock.calculate_earnings(row[3], row[2], row[1]), 2)
purchase_date = datetime.strptime(row[4], '%Y-%m-%d').date()
yearly_earnings = round(stock.calculate_yearly_earnings(row[3], row[2], \
current_date, purchase_date), 2)
stock_table.add_row([
row[0], row[1], "$ {:,.2f}".format(earnings),
str(yearly_earnings) + " %"
])
print(stock_table)
'''
=============================================================
Week 8 JSON to DB
=============================================================
'''
filename = "AllStocks.json"
dates = []
transactions = []
symbols = ["GOOG", "MSFT", "RDS-A", "AIG", "FB", "M", "F", "IBM"]
db_name = "accounts.db"
table_name = "json_data"
db_table_headers = """
Symbol text,
Date text,
Open text,
High text,
Low text,
Close real,
Volume integer
"""
#load JSON file
try:
with open(filename) as f:
stocks = json.load(f)
except FileNotFoundError:
print("Could not find file")
exit()
# #create database
db.create_table(db_name, table_name, db_table_headers)
#pass informatiom from JSON to DB
for stock in stocks:
content = (stock["Symbol"], stock["Date"], stock["Open"],
stock["High"], stock["Low"], stock["Close"],
stock["Volume"])
db.add_one(db_name, table_name, content)
for stock in stocks:
#convert date string to date object
purchase_date = datetime.strptime(stock["Date"], '%d-%b-%y').date()
transactions.append({
"Symbol": stock["Symbol"],
"Date": purchase_date,
"Close": float(stock["Close"])
})
# creates lists with all the different dates
for stock in transactions:
date = stock["Date"]
if date in dates:
pass
else:
dates.append(date)
dates = sorted(dates)
#hold total portifolio value per day
total = []
#make data symetrical so it can be graphed
data_to_graph = []
for date in dates:
for symbol in symbols:
close_price = get_close_price(symbol, date, transactions)
data_graph = add_stock(symbol, date, close_price, transactions,
data_to_graph)
total
data_to_graph = sorted(data_to_graph,
key=lambda stock: (stock['Symbol'], stock['Date']))
plt.plot(dates, get_stock_value_history("GOOG", 125, data_to_graph))
plt.plot(dates, get_stock_value_history("MSFT", 85, data_to_graph))
plt.plot(dates, get_stock_value_history("RDS-A", 400, data_to_graph))
plt.plot(dates, get_stock_value_history("AIG", 235, data_to_graph))
plt.plot(dates, get_stock_value_history("FB", 150, data_to_graph))
plt.plot(dates, get_stock_value_history("M", 425, data_to_graph))
plt.plot(dates, get_stock_value_history("F", 85, data_to_graph))
plt.plot(dates, get_stock_value_history("IBM", 80, data_to_graph))
plt.legend(symbols)
plt.title("Stock Positions")
plt.ylabel('Value in Dollars')
plt.xlabel("Date")
plt.savefig('stock_positions.png')
plt.show()
'''
====================================================================
BOND SECTION
====================================================================
'''
sub_header = []
bonds = [] #hold bond object(s)
bond_file = "Lesson6_Data_Bonds.csv"
#try opening stock file
try:
read_file = open(bond_file, "r")
except FileNotFoundError:
print("Could not open the file, program terminated! I'll be back!")
exit() #exit application if file cannot be found
sub_header = read_file.readline().split(',')
#remove the '\n' character at the end of the line
sub_header[-1] = sub_header[-1][:-1]
#create bonds table in database
db_name = "accounts.db"
table_name = "bonds"
#sub_header = [0] = SYMBOL, [1] = NO_SHARES, [2] = PUR_PRICE, [3] = CUR_VALUE, [4] = PUR_DATE
#[5] = COUPON, [6] = YIELD
db_table_headers = "investor_id text, bond_id text," + sub_header[0] + " text, " \
+ sub_header[1] + " integer, " + sub_header[2] + " real, " \
+ sub_header[3] + " real, " + sub_header[4] + " text," \
+ sub_header[5] + " real, " + sub_header[6] + " real"
#create_table investor table if it does not exist
db.create_table(db_name, table_name, db_table_headers)
#read data from bond file and store in bonds[]
for line in read_file:
line_split = line.split(',')
#removed the '/n' from the last item
line_split[-1] = line_split[-1][:-1]
symbol = line_split[0]
quantity = int(line_split[1])
purchase_price = float(line_split[2])
current_price = float(line_split[3])
#converts string formated as MM/DD/YYYY to date object
purchase_date = datetime.strptime(line_split[4], '%m/%d/%Y').date()
coupon = float(line_split[5])
bond_yield = float(line_split[6])
bond = Bond(symbol, purchase_price, current_price, quantity,
purchase_date, investor.investor_id,
uuid.uuid1().hex, coupon, bond_yield)
bonds.append(bond)
#add record to database
content = (investor.investor_id, bond.id, bond.symbol, bond.quantity,
bond.purchase_price, bond.current_price, bond.purchase_date,
bond.coupon, bond.bond_yield)
#create record in investor table
db.add_one(db_name, table_name, content)
read_file.close()
#sub_header = [0] = SYMBOL, [1] = NO_SHARES, [2] = PUR_PRICE, [3] = CUR_VALUE, [4] = PUR_DATE
# [5] = COUPON, [6] = YIELD
data = db.get_selected_data(db_name,"bonds", \
sub_header[0] + ", " + sub_header[1] + ", " + \
sub_header[2] + ", " + sub_header[3] + ", " + \
sub_header[4] + ", " + sub_header[5] + ", " + \
sub_header[6])
#print table bond table
print()
print("=================== Bond Positions ===================")
bond_table = PrettyTable()
bond_table.field_names = [sub_header[0], sub_header[1], "Earnings/Loss", \
"Yearly Earning/Loss", sub_header[5], sub_header[6]]
for row in data:
#instance of stock class
#[0] = SYMBOL, [1] = NO_SHARES, [2] = PUR_PRICE, [3] = CUR_VALUE, [4] = PUR_DATE
#[5] = COUPON, [6] = YIELD
bond = Bond(row[0], row[2], row[3], row[1], row[4], None, None, row[5],
row[6])
earnings = round(bond.calculate_earnings(row[3], row[2], row[1]), 2)
purchase_date = datetime.strptime(row[4], '%Y-%m-%d').date()
yearly_earnings = round(bond.calculate_yearly_earnings(row[3], row[2], \
current_date, purchase_date), 2)
#[0] = SYMBOL, [1] = NO_SHARES, [5] = COUPON, [6] = YIELD
bond_table.add_row([row[0], row[1], "$ {:,.2f}".format(earnings), \
str(yearly_earnings) + " %", row[5], row[6]])
print(bond_table)