def getRevenueEstimate(company, fileName=pathConfig.cache+'revenueEstimate.csv'):
parName1 = ''.join([company, '-low'])
parName2 = ''.join([company, '-growth'])
if Path(fileName).is_file() and isColumnExist([parName1, parName2], fileName):
return getDF([parName1, parName2], fileName)
else:
url = ''.join(['https://query1.finance.yahoo.com/v10/finance/quoteSummary/',
company, '?modules=earningsTrend'])
urlName = 'Yahoo Finance QuoteSummary API'
content = fetchUrlWithLog(url, requestRetrySession, urlName)
forcast1Quarter = None
forcast1Year = None
try:
trendDict = json.loads(
content)["quoteSummary"]["result"][0]["earningsTrend"]["trend"]
forcast1Year = trendDict[2]["revenueEstimate"]
forcast2Year = trendDict[3]["revenueEstimate"]
except Exception as x:
print('JSON Parse failed when getting estimate revenue :(',
x.__class__.__name__)
return pd.DataFrame()
else:
forcast1YearDF = pd.DataFrame(
forcast1Year).loc['raw'].rename('1 Year')
forcast2YearDF = pd.DataFrame(
forcast2Year).loc['raw'].rename('2 Year')
DF = pd.concat([forcast1YearDF, forcast2YearDF], axis=1)
NewDF = DF.loc[['low', 'growth']].rename(
{'low': parName1, 'growth': parName2}, axis='index')
return saveDFtoFile(NewDF, [parName1, parName2], fileName)
def getMyStock(company, fileName=pathConfig.cache+'myStock.csv'):
sheetName = "Stock"
sheetTabName = 'MyStock'
def getName(bidArr):
result = []
i = 1
for ele in bidArr:
result.append(ele+'-'+str(i))
i = i + 1
return result
def getMyStockSheet(sheetTabName, data):
bidArr = [ele for ele in data[4] if re.match("Bid/BidDate-*", ele)]
columnList = []
columnList.extend(['Company', 'Own Shares'])
columnList.extend(getName(bidArr))
df = pd.DataFrame(data[6:, 1:], columns=columnList)
return df.set_index('Company')
if Path(fileName).is_file() and isColumnExist(company, fileName):
return getDF(company, fileName)
else:
data = getDataFromGoogleSheet(sheetName, sheetTabName)
df = getMyStockSheet(sheetTabName, np.array(data))
return saveDFtoFile(df, company, fileName)
def getTreasuriesYield(fileName=pathConfig.cache+'treasuriesYield.csv'):
parName = ''.join(['treasuriesYield'])
if Path(fileName).is_file() and isColumnExist(parName, fileName):
# if file exist read from file
return getDF(parName, fileName)
else:
# if file not exist call api and save in file
df = quandl.get("ML/AAAEY").sort_index(ascending=False)
treasuriesYieldDF = df.iloc[:2].T.loc[['BAMLC0A1CAAAEY']].rename(
{'BAMLC0A1CAAAEY': parName}, axis='index')
return saveDFtoFile(treasuriesYieldDF, parName, fileName)
def getCompanyAndIndustryInfo(company, fileName=pathConfig.cache+'company.csv'):
sheetName = "Stock"
sheetTabName = 'Company'
def getCompanySheet(sheetTabName, data):
df = pd.DataFrame(data[1:], columns=data[0])
return df.set_index('Name')
if Path(fileName).is_file() and isColumnExist(company, fileName):
return getDF(company, fileName)
else:
data = getDataFromGoogleSheet(sheetName, sheetTabName)
df = getCompanySheet(data)
return saveDFtoFile(df, company, fileName)
def getStockPrice(company, fileName=pathConfig.cache+'stockPrice.csv'):
parName1 = ''.join([company, '-amount'])
parName2 = ''.join([company, '-date'])
if Path(fileName).is_file() and isColumnExist([parName1, parName2], fileName):
# if file exist read from file
return getDF([parName1, parName2], fileName)
else:
# if file not exist call api and save in file
url = ''.join(['https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=',
company, '&apikey=', alphaVantageAPIKey, '&datatype=csv'])
urlName = 'Alphavantage'
content = fetchUrlWithLog(url, requestRetrySession, urlName)
df = pd.read_csv(io.StringIO(content.decode('utf-8')))
time.sleep(20)
# DF = pd.DataFrame(dividendDict).rename(
# {'amount': parName1, 'date': parName2}, axis='index')
# priceDF = df.T.loc[['timestamp', 'close']].rename(
# {'timestamp': 'timestamp', 'close': company}, axis='index')
priceDF = df.T.loc[['timestamp', 'close']].rename(
{'close': parName1, 'timestamp': parName2}, axis='index')
return saveDFtoFile(priceDF, company, fileName)
def getMyDividendRecord(myStockDF, company, fileName=pathConfig.cache+'myDividendRecord.csv'):
parName1 = ''.join([company, '-amount'])
parName2 = ''.join([company, '-date'])
firstBidTime = getBidDate(myStockDF)
firstBidUnixTimestamp = getUnixTimeStamp(firstBidTime)
if Path(fileName).is_file() and isColumnExist([parName1, parName2], fileName):
return getDF([parName1, parName2], fileName)
else:
url = ''.join(['https://query1.finance.yahoo.com/v8/finance/chart/',
company, '?period1=', firstBidUnixTimestamp, '&period2=9999999999&interval=1d&includePrePost=false&events=div%2Csplit'])
urlName = 'Yahoo Finance Chart API'
content = fetchUrlWithLog(url, requestRetrySession, urlName)
try:
dividendDict = json.loads(
content)["chart"]["result"][0]["events"]["dividends"]
except Exception as x:
print('JSON Parse failed when getting dividend :(',
x.__class__.__name__)
return pd.DataFrame()
else:
DF = pd.DataFrame(dividendDict).rename(
{'amount': parName1, 'date': parName2}, axis='index')
return saveDFtoFile(DF, [parName1, parName2], fileName)