- made a class

git-svn-id: http://moon:8086/svn/projects/Stock@305 fda53097-d464-4ada-af97-ba876c37ca34

pandas_eval.py

@@ -20,6 +20,40 @@ import os
 # https://ntguardian.wordpress.com/2016/09/19/introduction-stock-market-data-python-1
 
 key = '0UO7Z2MVZ2YSQSVE'
+thresh_macd = 0.5
+show_range_days = 20
+
+titles = [
+	'AAPL',
+	'XLNX',
+	'QCOM',
+	'DPW.DE',
+	'CSCO',
+	'AIR',
+	'BA',
+	'NVDA',
+	'MSFT',
+	'DIS',
+	'NFLX',
+	'OHB.DE',
+	'ERCA.DE',
+	'VAR1.DE',
+	'HD',
+	'AMZN',
+	'GOOGL',
+	'ZIL2.DE',
+	'SIS.DE',
+	'GFT.DE',
+	'AMD.DE',
+	'PANW',
+	'RIB.DE',
+	'WAF.DE',
+	'EVT.DE',
+	'VOW.DE',
+	'AMS.SW',
+	'I',
+	'OQ3.F']
+
 
 def ema(data, key, alpha=0.5, ic=None):
 	result = []
@@ -95,106 +129,101 @@ def bollinger(data, window_days, f=2):
 	result['mid'] = mid
 	return result
 
-data = {}
-titles = []
-titles.append('AAPL')
-titles.append('XLNX')
-titles.append('QCOM')
-titles.append('DPW.DE')
-titles.append('CSCO')
-titles.append('AIR')
-titles.append('NVDA')
 
-show_title = 'XLNX'
+class Symbol(object):
-show_range_days = 20
+	def __init__(self, name):
+		self.name = name
+		self.ax = None
+		self.fig = None
+		self.k_euro = 1/1.11
 
-pd.DatetimeIndex
+	def fetch(self):
-def fetch(title):
+		filename = self.name.replace('.','_') + '.h5'
-	filename = title + '.h5'
+		fetch = False
-	fetch = False
+		today = dt.date.today()
-	today = dt.date.today()
 
-	try:
+		try:
-		hdf = pd.HDFStore(filename, 'r')
+			hdf = pd.HDFStore(filename, 'r')
-		hdf.close()
+		except:
-	except:
-		fetch = True
-
-	try:
-		lastmodified = dt.datetime.fromtimestamp(os.stat(filename).st_mtime).date()
-		if lastmodified != today:
 			fetch = True
-	except:
-		fetch = True
 
-	if fetch:
+		try:
-		print ("Fetching \"{}\"".format(title))
+			lastmodified = dt.datetime.fromtimestamp(os.stat(filename).st_mtime).date()
-		# Get stock price via data reader
+			if lastmodified != today:
-		start = dt.datetime(2019,1,1)
+				fetch = True
-		end = dt.date.today()
+		except:
-		data = web.DataReader(title, "av-daily", start, end, api_key=key)
+			fetch = True
-		hdf = pd.HDFStore(title + '.h5')
-		hdf[title] = data
-	else:
-		hdf = pd.HDFStore(filename, 'r')
-		data = hdf[title]
-	hdf.close()
 
-def plot(ax, fig, data):
+		if fetch:
-	dates = data.index
+			print ("Fetching \"{}\"".format(self.name))
-	data.plot()
+			# Get stock price via data reader
-	def hover(event):
+			start = dt.datetime(2019,1,1)
-		if event.inaxes == ax:
+			end = dt.date.today()
-			x_idx = int(event.xdata)
+			data = web.DataReader(self.name, "av-daily", start, end, api_key=key)
-			ax.format_xdata = lambda x: dates[x_idx]
+			hdf = pd.HDFStore(filename)
-			ax.format_ydata = lambda y: '{:.2f}'.format(data[x_idx])
+			hdf[self.name] = data
 
-	fig.canvas.mpl_connect("motion_notify_event", hover)
+		self.data_full = hdf[self.name]*self.k_euro
+		hdf.close()
 
-def show(title):
+	def __plot(self, data):
+		dates = data.index
+		data.plot()
+		def hover(event):
+			if event.inaxes == self.ax:
+				x_idx = int(event.xdata)
+				self.ax.format_xdata = lambda x: dates[x_idx]
+				self.ax.format_ydata = lambda y: '€{:.2f}'.format(data[x_idx])
 
-	k_euro = 1/1.11
+		self.fig.canvas.mpl_connect("motion_notify_event", hover)
 
-	filename = title + '.h5'
+	def analyze(self):
+		self.data_full['ema'] = ema(self.data_full, key='close', alpha=0.75)
+		self.data_full['macd'] = macd(self.data_full, key='close')
+		self.data_full['sma'] = sma(self.data_full, key='close', window_days=30)
+		self.boll_full = bollinger(self.data_full, window_days=30)
 
-	hdf = pd.HDFStore(filename, 'r')
+		_macd = self.data_full['macd'][len(self.data_full)-1]
-	data_full = hdf[title]*k_euro
+		return {'macd' : _macd}
 
-	data_full['ema'] = ema(data_full, key='close', alpha=0.75)
-	data_full['macd'] = macd(data_full, key='close')
-	data_full['sma'] = sma(data_full, key='close', window_days=30)
-	boll_full = bollinger(data_full, window_days=30)
-	hdf.close()
 
-	data = data_full[len(data_full)-1 - show_range_days:]
+	def show(self, figNum=1):
-	boll = boll_full[len(boll_full)-1 - show_range_days:]
+		data = self.data_full[len(self.data_full)-1 - show_range_days:]
+		boll = self.boll_full[len(self.boll_full)-1 - show_range_days:]
 
-	fig = plt.figure(1)
+		self.fig = plt.figure(figNum)
-	ax = plt.subplot(311)
+		self.ax = plt.subplot(311)
-	plot(ax, fig, data['close'])
+		self.__plot(data['close'])
-	plot(ax, fig, data['ema'])
+		self.__plot(data['ema'])
-	plot(ax, fig, data['sma'])
+		self.__plot(data['sma'])
-	plt.title(title)
+		plt.title(self.name)
-	plt.legend()
+		plt.legend()
-	plt.grid()
+		plt.grid()
 
-	plt.subplot(312)
+		plt.subplot(312)
-	boll['upper'].plot()
+		boll['upper'].plot()
-	boll['mid'].plot()
+		boll['mid'].plot()
-	boll['lower'].plot()
+		boll['lower'].plot()
-	plt.legend()
+		plt.legend()
-	plt.grid()
+		plt.grid()
 
-	plt.subplot(313)
+		plt.subplot(313)
-	data['macd'].plot()
+		data['macd'].plot()
-	plt.legend()
+		plt.legend()
-	plt.grid()
+		plt.grid()
-
-	plt.show()
 
 
 
+
+figNum = 1
 for title in titles:
-	fetch(title)
+	sym = Symbol(title)
+	sym.fetch()
+	result = sym.analyze()
+	if result['macd'] > thresh_macd:
+		sym.show(figNum)
+		figNum += 1
+
+
+plt.show()
 
-show(show_title)