def getHistoricEMA(ticker: str,
sampleSize: int = 25,
returnPrice: bool = False,
closeData: list = []):
'''
returns a list of a exponential moving avarage (equal weighted)
* The list used should be shifted forward @param sampleSize times, since EMA is not calculated for those
* if @param returnPrice is true, this will return a tuple containing the SMA and the current price (mostly used for comparison)
'''
if len(closeData) != 0:
stockData = closeData
else:
stockData = IM.getCandle(ticker, timeframe="Y",
quality="high").get("c")
mult = 2 / (sampleSize + 1)
ema = []
for i in range(sampleSize - 1, len(stockData)):
if len(ema) == 0:
# Calculate inital SMA value
ema.append(sum(stockData[i - sampleSize + 1:i]) / sampleSize)
else:
# Calculate todays EMA, based on yesterdays EMA
ema.append(((stockData[i] - ema[len(ema) - 1]) * mult) +
ema[len(ema) - 1])
if returnPrice:
return ema, stockData[-1]
return ema
def getCurrentSMA(ticker: str,
sampleSize: int = 25,
returnPrice: bool = False,
closeData: list = []):
'''
returns the current simple avarage with @param sampleSize days
* if @param returnPrice is true, this will return a tuple containing the SMA and the current price (mostly used for comparison)
'''
if len(closeData) != 0:
stockData = closeData
else:
stockData = IM.getCandle(ticker, timeframe="Y",
quality="high").get("c")
stockData = stockData[-sampleSize - 1:]
sma = 0
for i in range(0, len(stockData) - sampleSize):
sma = (sum(stockData[i:i + sampleSize]) / sampleSize)
if returnPrice:
return round(sma, 2), stockData[-1]
else:
return round(sma, 2)
def __init__(self, bot, project_system):
# _info is the main point of access for anything specific to a project (e.g. urls, triggers, keywords).
self._info = InfoManager.ProjectSystemInfoManager(project_system)
# Use _bot to interact with the user (e.g. ask a question, clarify between options, acknowledge keywords).
self._bot = bot
# Maps an intent to a function.
self._STRATAGIES = {
'Get Help': self._get_help,
'undefined': self._undefined
}
def getCurrentTrend(ticker: str, weeksBack: int = 1, closeData: list = []):
'''
returns the current trend for @param weeksBack in precentage
'''
if len(closeData) != 0:
stockData = closeData
else:
stockData = IM.getCandle(ticker, timeframe="Y",
quality="high").get("c")
priceDiff = stockData[-1] - stockData[-weeksBack * 7]
diffPrecentage = (priceDiff / stockData[-weeksBack * 7]) * 100
return round(diffPrecentage, 3)
def getHistoricSMA(ticker: str, sampleSize: int = 25, closeData: list = []):
'''
returns a list of a simple moving avarage (equal weighted)
* The list used should be shifted forward @param sampleSize times, since SMA is not calculated for those
'''
if len(closeData) != 0:
stockData = closeData
else:
stockData = IM.getCandle(ticker, timeframe="Y",
quality="high").get("c")
sma = []
for i in range(0, len(stockData) - sampleSize):
sma.append(sum(stockData[i:i + sampleSize]) / sampleSize)
return sma
def test():
ticker = 'AAPL'
normalStockY = IM.getCandle(ticker, timeframe="Y", quality="high").get("c")
normalStockX = [x for x in range(len(normalStockY))]
sampleSize = 30
smaY = getHistoricSMA(ticker, sampleSize)
smaX = [x + sampleSize for x in range(len(smaY))]
emaY = getHistoricEMA(ticker, sampleSize)
emaX = [x + sampleSize for x in range(len(emaY))]
plt.plot(normalStockX, normalStockY)
plt.plot(smaX, smaY)
plt.plot(emaX, emaY)
print(getCurrentEMA("AAPL", sampleSize), emaY[-1])
plt.show()
def getWikiArticle(ticker: str) -> str:
'''
returns a wikipedia article about the stock ticker. If it cant find a article, it gives an article about the stock market
'''
name = IM.getName(ticker)
defaultArticle = "https://en.m.wikipedia.org/wiki/Stock_market"
if name == ticker:
return defaultArticle
else:
quary = name
url = 'https://en.wikipedia.org/w/api.php?action=opensearch&search="{}"&limit=1&format=json'.format(
quary)
try:
wikilink = requests.get(url).json()[-1][0].replace("en.", "en.m.")
except Exception:
return defaultArticle
return wikilink
info = info.readlines()
infobox = []
for i in info:
temp = i.replace('\n', '')
temp = temp.replace('\t', '')
temp = temp.split('_')
heading = int(temp[1])
heading = heading % 90
temp[1] = heading
temp = tuple(temp)
infobox.append(temp)
# DB.savein_tuple("Beijing",temp)
DB.update_list(CITYname, infobox)
#连接数据库
test = InfoManager("test_"+city_name+".db")
#支持给出目录绝对地址，之后在目录下链接数据库（无则创建）
#支持在当前目录下连接数据库（无则创建）
#支持给出数据库绝对地址，无则失败
#在数据库内创建表单
test.creNewTable(city_name)
#在表单city_name中从source文件中载入数据
#create(city_name,source,test)
#删除数据库中的表单city_name（表单内的数据消失，不可恢复）
#test.dropTable(city_name)
#在表单city_name中在经纬度范围内搜索数据，返回值为list，包含的元素为元组，包含满足条件点的所有信息
#r = test.selectByRange(city_name,(23.1,23.3),(113.70,113.79))