def get(self):
lastRunDateObj = ScheduledInvestRunDate.all().get();
if (lastRunDateObj == None):
lastRunDate = date.today() - timedelta(days=20);
lastRunDateObj = ScheduledInvestRunDate(lastRunDate=lastRunDate, key_name="last_run_date");
lastRunDateObj.put();
lastRunDate = lastRunDateObj.lastRunDate;
startDate = lastRunDate + timedelta(days=1);
endDate = date.today() - timedelta(days=3);
currDate = startDate;
scheduleQuery = ScheduledInvestment.all();
for scheduledInvest in scheduleQuery:
while (True):
if currDate.day == scheduledInvest.dayOfMonth:
sharePrice = self.get_share_price(currDate, scheduledInvest.ticker);
invest = Investment(ticker=scheduledInvest.ticker,
amount=scheduledInvest.amount,
date=currDate,
sharePrice=sharePrice,
shares=self.num_shares(scheduledInvest.amount, sharePrice));
invest.put();
currDate = currDate + timedelta(days=1);
if currDate > endDate:
break;
lastRunDateObj.lastRunDate = endDate;
lastRunDateObj.put();
self.response.out.write("scheduled");
def getInvestments(self, investmentId, startDate, endDate, active):
investmentList = []
# if no period is informed, find the second max date in such a way to allow evaluate the evolution
# TODO: figure out a better way to do this
# TODO: after inserting an operation with bigger date than the end date of balance, the same is not returned in the result: this must be fixed somehow
if startDate is None and endDate is None:
for investment in self.investment:
if active == True and investment.balance[0].amount == 0:
continue
if len(investment.balance) > 1 and (
startDate is None
or investment.balance[1].date < startDate):
startDate = investment.balance[1].date
if endDate is None or investment.balance[0].date > endDate:
endDate = investment.balance[0].date
print(f'[debug] get investment: {startDate} - {endDate}')
# trasverse the investments list to fetch those that satisfy all search criteria
for investment in self.investment:
if active == True and investment.balance[0].amount == 0:
continue
if investmentId is not None and investmentId != str(investment.id):
continue
balance = []
for balanceItem in investment.balance:
if startDate <= balanceItem.date and endDate >= balanceItem.date:
balance.append(balanceItem)
operation = []
for operationItem in investment.operation:
if startDate <= operationItem.date and endDate >= operationItem.date:
operation.append(operationItem)
revenue = []
for revenueItem in investment.revenue:
if startDate <= revenueItem.date and endDate >= revenueItem.date:
revenue.append(revenueItem)
if len(balance) > 0:
investmentAux = Investment()
investmentAux.id = investment.id
investmentAux.name = investment.name
investmentAux.type = investment.type
investmentAux.bank = investment.bank
investmentAux.operation = operation
investmentAux.balance = balance
investmentAux.revenue = revenue
investmentList.append(investmentAux.to_json())
return investmentList
def test_results_file(self):
try:
os.remove('results.txt')
except IOError:
pass
positions = [1, 10, 100, 1000]
no_trials = 1000
Investment.calculate_for_positions(positions, no_trials)
self.assertTrue(os.path.isfile('results.txt'))
def visit_investment(self, investment: Investment):
print('visit investment')
if investment.getBalance() >= 500:
return investment
else:
return None
pass
def add_investment(self, id, cur_value, marketItem, amount=None):
"""
Create an investment object or add value to an existing one
:param id: The ID of the post to invest in
:param cur_value: The current value of the post
:param marketItem: The post object
:param amount: The amount to invest in the post
:return: The success of the action (boolean)
"""
from investment import Investment
if amount is None:
amount = self.default_invest
# Check if the user has enough to invest
if self.balance <= 0:
return None
elif self.balance < amount:
amount = self.balance
self.balance -= amount
investmnt = Investment(amount, int(id), cur_value + amount, marketItem)
self.investments.append(investmnt)
marketItem.value += amount
# return True if an investment was successfully added
return True
def load(self):
with open(self.dataFileName, 'r') as fileHandler:
fileData = json.load(fileHandler)
for investmentAttributes in fileData['investments']:
self.investment.append(
Investment.unserialize(investmentAttributes))
def save(self):
investmentList = []
for investment in self.investment:
investmentList.append(Investment.serialize(investment))
with open(self.dataFileName, 'w') as fileHandler:
json.dump({'investments': investmentList}, fileHandler)
def test_plots_files(self):
try:
os.remove('histogram_0001_pos.pdf')
os.remove('histogram_0010_pos.pdf')
os.remove('histogram_0100_pos.pdf')
os.remove('histogram_1000_pos.pdf')
except IOError:
pass
positions = [1, 10, 100, 1000]
no_trials = 1000
Investment.calculate_for_positions(positions, no_trials)
self.assertTrue(os.path.isfile('histogram_0001_pos.pdf'))
self.assertTrue(os.path.isfile('histogram_0010_pos.pdf'))
self.assertTrue(os.path.isfile('histogram_0100_pos.pdf'))
self.assertTrue(os.path.isfile('histogram_1000_pos.pdf'))
def makeInvestment(self, date, amount, account, interest, userId,
productId):
if amount <= 0:
raise ValueError("Investment value must be greater than zero!")
investment = Investment(date, amount, account, interest, userId,
productId)
self.products.append(investment)
self.invest(account, amount)
return investment
def solve(positions, num_trials):
"""
For a given position list and number of trials, run the experiments
and draw the plots.
"""
for position in positions:
# create a new class
investment = Investment(position)
daily_ret = []
for trial in range(num_trials):
# do a invest each time
investment.invest()
# calculate the corresponding daily_ret, using double
daily_ret.append(investment.ret * 1.0 / 1000.0 - 1.0)
print("The mean of position", position, "is", mean(daily_ret))
print("The standard deviation of position", position, "is",
stdev(daily_ret))
plt.hist(daily_ret, 100, range=[-1, 1])
plt.show()
def run_process():
"""."""
try:
Organization.run()
Fund.run()
Person.run()
FundingRound.run()
HasAcquired.run()
Funding.run()
HasFund.run()
Investment.run()
HasAffiliation.run()
HasStudiedat.run()
except Exception as e:
logger = Logger()
logger.logg(debug_msg='Error while running cron job.',
info_msg='Function = run_process()',
warning_msg='Error in executing scheduled job',
error_msg='Module = ' + log_file,
critical_msg=str(e))
def getSummData(self, ticker):
invs = Investment.all().filter("ticker", ticker);
data = SummaryData();
data.ticker = ticker;
for inv in invs:
data.amount = data.amount + inv.amount;
data.shares = data.shares + inv.shares;
latestPriceQ = stockPrice.all().filter("ticker", ticker).order("-date");
latestPrice = latestPriceQ.get().price;
data.currPrice = latestPrice;
data.value = data.currPrice * data.shares;
if data.amount > 0:
data.percentage = data.value / Decimal(data.amount) - Decimal("1.0");
return data;
def find_worth(submissions, my_investments, score=0, age=10):
limit = 0
print(YELLOW)
print("\tSearching for:\t" + "at least " + str(score) + " upvotes")
print("\t\t\t" + "and less than " + str(age) + " hours")
investments = []
for submission in submissions:
sub_age = (datetime.now() - datetime.fromtimestamp(
submission.created_utc)).total_seconds() / (60 * 60)
if submission.subreddit == "MemeEconomy":
if sub_age <= age and submission.score >= score:
no_double = 1
for investment in my_investments:
if (investment.submission.permalink == submission.permalink
):
no_double = 0
if no_double:
mine_soon = Investment(submission)
print_investment(mine_soon)
investments.append(mine_soon)
print(RESET)
return investments
def setUp(self):
self.bank_id = 1
self.bank = Bank(bank_id=self.bank_id)
self.products = []
self.accounts = []
self.credits = []
self.investments = []
# Prepare products
for i in range(1, 11):
# accounts
account = BankAccount(bank_id=self.bank_id,
user_id=1,
product_id=i * 10)
self.bank.deposit(account, i * 300)
self.accounts.append(account)
# credits
credit = Credit(product_id=i * 20,
account=account,
end_date=date.today,
money=100 * i,
user_id=1,
number_of_installment=12,
bank_id=self.bank_id)
self.credits.append(credit)
# investment
investment = Investment(endDate=date.today,
amount=100 * i + 1,
interest=InvestmentInterest,
product_id=i * 30,
account=account,
user_id=1,
bank_id=self.bank_id)
self.investments.append(investment)
# prepare one collection with all products
self.products.append(account)
self.products.append(credit)
self.products.append(investment)
def calcPositionValue(self):
inv = Investment('[1, 10, 100, 1000]', 100, 17)
inv.setSeed()
inv.calcPositionValue()
self.assertEqual(inv.position_value, np.array([1000, 100, 10, 1]))
def insertNewInvestment(self, investmentData):
investmentAux = Investment.unserialize(investmentData)
self.investment.append(investmentAux)
return investmentAux.to_json()
def calcPositionValue(self):
inv = Investment('[1, 10, 100, 1000]', 100, 17)
inv.setSeed()
inv.calcPositionValue()
self.assertEqual(inv.position_value, np.array([1000, 100, 10, 1]))
def calcCumulativeReturn(self):
inv = Investment('[1, 10, 100, 1000]', 100, 17)
inv.setSeed()
inv.calcPositionValue()
inv.calcCumulativeReturn()
inv.calcDailyReturn()
inv.calcDailyReturnMean()
self.assertEqual(np.round(inv.daily_mean, 4), np.array([0.1, 0.024, 0.0212, 0.0177]))
def main():
inputPositions = input('Please give a list of shares that you would like to buy. The input can be something like [1, 10, 100, 1000]. Type in \'quit\' to quit the program.\n')
if inputPositions == 'quit':
return
# check 1st input string
checkInput(inputPositions)
# convert 1st input string to a list
inputStrSplit = inputPositions[1:-1].strip().split(',')
shares_list = []
for share in inputStrSplit:
shares_list.append(int(share))
# check 2nd input string
num_trails = input('Please give a number of trails that you would like to simulate. For example, 10000.Type in \'quit\' to quit the program.\n')
if num_trails == 'quit':
return
# run Investment class
print('Calculating...')
inv = Investment(shares_list, int(num_trails))
inv.calcPositionValue()
inv.calcCumulativeReturn()
inv.calcDailyReturn()
inv.calcDailyReturnMean()
inv.calcDailyReturnStd()
inv.saveResults()
print('Done. Results are saved.')
def calcCumulativeReturn(self):
inv = Investment('[1, 10, 100, 1000]', 100, 17)
inv.setSeed()
inv.calcPositionValue()
inv.calcCumulativeReturn()
inv.calcDailyReturn()
inv.calcDailyReturnMean()
inv.calcDailyReturnStd()
self.assertEqual(inv.daily_std, np.array([0.995 , 0.3829, 0.1005, 0.0346]))
def calcCumulativeReturn(self):
inv = Investment('[1, 10, 100, 1000]', 100, 17)
inv.setSeed()
inv.calcPositionValue()
inv.calcCumulativeReturn()
inv.calcDailyReturn()
inv.calcDailyReturnMean()
inv.calcDailyReturnStd()
self.assertEqual(inv.daily_std,
np.array([0.995, 0.3829, 0.1005, 0.0346]))
def calcCumulativeReturn(self):
inv = Investment('[1, 10, 100, 1000]', 100, 17)
inv.setSeed()
inv.calcPositionValue()
inv.calcCumulativeReturn()
inv.calcDailyReturn()
inv.calcDailyReturnMean()
self.assertEqual(np.round(inv.daily_mean, 4),
np.array([0.1, 0.024, 0.0212, 0.0177]))
