def create_history_object(**kwargs):
stock = make_tuple(kwargs)
stock.open_, stock.high, stock.low, stock.close = [
float(x) for x in [stock.open_, stock.high, stock.low, stock.close]
]
all_stock_dates = set(
db.query(History.date).filter_by(symbol=stock.symbol).all())
# Lets check if we already have that day's data
have_data = True if (stock.dt, ) in all_stock_dates else False
if have_data:
print 'Already have the data for this date! Updating!'
# continue
h = db.query(History).filter_by(date=stock.dt).first()
h.__dict__ = History(kwargs).__dict__.copy()
return h
# init new object and add it to the db session
h = History(symbol=stock.symbol,
date=stock.dt,
open=stock.open_,
high=stock.high,
low=stock.low,
close=stock.close,
volume=stock.volume.replace('\n', ''))
return h
def save_data(symbol):
try:
for data in list_of_datas[symbol]:
last_update_date = db.query(History.date).filter_by(symbol=symbol).order_by(History.date.desc()).first()
last_update_date = last_update_date[0].date() if last_update_date else datetime.datetime.today().date()
today_date = datetime.datetime.today().date()
if last_update_date >= today_date:
for row in xrange(7, len(data)):
if data[row].count(',') != 5:
continue
offset, close, high, low, open_, volume = data[row].split(',')
if offset[0] == 'a':
day = float(offset[1:])
offset = 0
else:
offset = float(offset)
open_, high, low, close = [float(x) for x in [open_, high, low, close]]
dt = datetime.datetime.fromtimestamp(day + (86400 * offset))
h = History(symbol=symbol,
date=dt,
open=open_,
high=high,
low=low,
close=close,
volume=volume.replace("\n", ""))
db.add(h)
print "Saved " + symbol
db.commit()
else:
print "already got the data for this date!"
except:
print "Failed to save the data to " + symbol
def create_history_object(**kwargs):
stock = make_tuple(kwargs)
stock.open_, stock.high, stock.low, stock.close = [float(x) for x in
[stock.open_, stock.high, stock.low, stock.close]]
all_stock_dates = set(db.query(History.date).filter_by(symbol=stock.symbol).all())
# Lets check if we already have that day's data
have_data = True if (stock.dt,) in all_stock_dates else False
if have_data:
print 'Already have the data for this date! Updating!'
# continue
h = db.query(History).filter_by(date=stock.dt).first()
h.__dict__ = History(kwargs).__dict__.copy()
return h
# init new object and add it to the db session
h = History(symbol=stock.symbol,
date=stock.dt,
open=stock.open_,
high=stock.high,
low=stock.low,
close=stock.close,
volume=stock.volume.replace('\n', ''))
return h
def find_resistance_line(symbol, show_resets=False, include_history=False, start_date=datetime.date(2086, 8, 26)):
"""
@symbol: Symbol of specific stock
@show_resets: While iterating the stock data we gives point every time the close price is close to the
resistance line. When the close price goes over the line we reset the points. This option
will determine if we want to print or not the resets.
@include_history: When reset occurs should we continue or stop iterate this stock. This good if we want
to find resistance line older then the last break. Most of the time we will turn this
off because the most important is the last resistance line.
@start_date: Date that the loop start from.
"""
try:
stocks = db.query(History).filter(History.symbol == symbol, History.date < start_date).order_by(History.date.desc()).all()
if not stocks:
return
except:
print 'error'
return
today_price = stocks[0].close
points = 0
for day_number in xrange(5, 100):
# Make sure we wont go more then the stock data have(for new stocks)
if day_number > len(stocks)-1:
return
# Check if we passed the resistance line
if stocks[day_number].close > today_price * 1.025:
if show_resets:
print 'point reset for {} - {}: {}, {}, {}'.format(stocks[day_number].symbol, stocks[day_number].date.strftime("%d/%m/%y"), stocks[day_number+5].close, stocks[day_number].close, stocks[day_number-5].close)
points = 0
if include_history:
continue
else:
return
# check if current close is +- % of the given close(today)
if today_price * 0.985 < stocks[day_number].close < today_price * 1.125:
#check if we have a parabola max
if stocks[day_number+5].close * 1.025 < stocks[day_number].close > stocks[day_number-5].close * 1.025:
# print 'point - {}: {}, {}, {}'.format(stocks[i].date, stocks[i+5].close, stocks[i].close, stocks[i-5].close)
# Add point, points given as long as the price didn't broke throe our line
points += 1
if points == 4:
print 'Found: {}'.format(stocks[day_number].symbol)
def find_behavior(symbol, weeks):
"""
iterate over closep and look for technical behaviors
"""
days_period = 7 # The days differences between the 3 points.
highlighted_dates = [] # We will append dates that chosen by change rate.
start_date = datetime.datetime.now() - datetime.timedelta(weeks=weeks)
# Get all the stocks from start_date
stocks = db.query(History).filter((History.symbol == symbol) & (History.date > start_date)).all()
for index, stock in enumerate(stocks):
# Check we don't get out of list size
if index < days_period or index > len(stocks) - days_period-1: continue
# define 3 points: +- *days_period* days from current day
close_left = stocks[index - days_period].close
close_right = stocks[index + days_period].close
close_center = stocks[index].close
# Get the percentage change between all the points
left_per = get_percentage_change(close_left, close_center)
right_per = get_percentage_change(close_right, close_center)
# print "left-val: {}, center-val: {}, right-val: {}".format(close_left, close_center, close_right)
# Find points where the change from the center is 4 or -4 percentages
if (left_per > 4 and right_per > 4) or (left_per < -4 and right_per < -4):
highlighted_dates.append(stock)
if len(highlighted_dates) > 2:
print "#########################################################"
print "FOUND IT! left:{}, center:{}, right:{}".format(close_left, close_center, close_right)
print "percentage-left: {}, percentage-right: {}".format(left_per, right_per)
print highlighted_dates
highlighted_dates = []
# Drop old date from highlghteds!
if highlighted_dates and highlighted_dates[0].date < stock.date - datetime.timedelta(weeks=10):
del highlighted_dates[0]
import time
import matplotlib.pyplot as plt
import matplotlib.ticker as mticket
import matplotlib.dates as mdates
from matplotlib.finance import candlestick
from project import db
from project.models.history import History
t0 = time.time()
import matplotlib
matplotlib.rcParams.update({'font.size': 9})
symbol = 'AMG'
stocks = db.query(History.date, History.open, History.close, History.high,
History.low, History.volume).filter_by(symbol=symbol).all()
stocks_list = [list(tup) for tup in stocks]
# stocks_list = [for x in stocks_list if stocks_list.index(x) == 1]
dates = [stock[0] for stock in stocks]
opens = [stock[1] for stock in stocks]
closes = [stock[2] for stock in stocks]
highs = [stock[3] for stock in stocks]
lows = [stock[4] for stock in stocks]
volumes = [stock[5] for stock in stocks]
x = 0
y = len(dates)
newAr = []
while x < y:
appendLine = mdates.date2num(
dates[x]), opens[x], closes[x], highs[x], lows[x], volumes[x]
newAr.append(appendLine)
def set_money(money):
new_money = db.query(User).first()
new_money.money = money
save(new_money)
import time
import matplotlib.pyplot as plt
import matplotlib.ticker as mticket
import matplotlib.dates as mdates
from matplotlib.finance import candlestick
from project import db
from project.models.history import History
t0 = time.time()
import matplotlib
matplotlib.rcParams.update({'font.size': 9})
symbol = 'AMG'
stocks = db.query(History.date, History.open, History.close, History.high, History.low, History.volume).filter_by(symbol=symbol).all()
stocks_list = [list(tup) for tup in stocks]
# stocks_list = [for x in stocks_list if stocks_list.index(x) == 1]
dates = [stock[0] for stock in stocks]
opens = [stock[1] for stock in stocks]
closes = [stock[2] for stock in stocks]
highs = [stock[3] for stock in stocks]
lows = [stock[4] for stock in stocks]
volumes = [stock[5] for stock in stocks]
x = 0
y = len(dates)
newAr = []
while x < y:
appendLine = mdates.date2num(dates[x]), opens[x], closes[x], highs[x], lows[x], volumes[x]
newAr.append(appendLine)
x += 1
def get_money():
return db.query(User).first().money
def get_all_stocks_symbols():
all_stocks = db.query(Stock.symbol).all()
return [x[0] for x in all_stocks]
def get_all_stocks():
return db.query(Stock).all()
def set_money(money):
new_money = db.query(User).first()
new_money.money = money
save(new_money)
def get_money():
return db.query(User).first().money