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https://github.com/andrewkdinh/fund-indicators.git
synced 2024-11-21 09:24:16 -08:00
Added support for datetime
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.gitignore
vendored
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vendored
@ -4,3 +4,5 @@ __pycache__/
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quickstart.py
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creds.json
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test/
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.vscode/
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listGoogle.py
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@ -4,6 +4,8 @@ A project to determine indicators of overperforming mutual funds.
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This project is written in Python and will examine market capitalization, persistence, turnover, and expense ratios.
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### Prerequisites
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`$ pip install -r requirements.txt`
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or
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`$ pip install requests`
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Created by Andrew Dinh from Dr. TJ Owens Gilroy Early College Academy
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24
StockData.py
24
StockData.py
@ -141,9 +141,17 @@ class StockData:
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def getAV(self):
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listAV = []
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url = ''.join(('https://www.alphavantage.co/query?function=TIME_SERIES_MONTHLY&symbol=', self.name, '&apikey=', apiAV))
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#url = ''.join(('https://www.alphavantage.co/query?function=TIME_SERIES_MONTHLY&symbol=', self.name, '&apikey=', apiAV))
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# https://www.alphavantage.co/query?function=TIME_SERIES_MONTHLY&symbol=MSFT&apikey=demo
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#url = ''.join(('https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=', self.name, '&outputsize=full&apikey=', apiAV))
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# https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=MSFT&outputsize=full&apikey=demo
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url = ''.join(('https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=', self.name, '&outputsize=full&apikey=', apiAV))
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# https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=MSFT&outputsize=full&apikey=demo
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print("\nSending request to:", url)
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print("(This will take a while)")
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f = requests.get(url)
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json_data = f.text
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loaded_json = json.loads(json_data)
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@ -156,9 +164,9 @@ class StockData:
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return 'Not available'
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#print(loaded_json['Monthly Time Series'])
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monthlyTimeSeries = loaded_json['Monthly Time Series']
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dailyTimeSeries = loaded_json['Time Series (Daily)']
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#print(monthlyTimeSeries)
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listOfDates = list(monthlyTimeSeries)
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listOfDates = list(dailyTimeSeries)
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#print(listOfDates)
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firstDate = listOfDates[-1]
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@ -179,8 +187,9 @@ class StockData:
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values = []
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for i in range(0, len(listOfDates), 1):
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temp = listOfDates[i]
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loaded_json2 = monthlyTimeSeries[temp]
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value = loaded_json2['4. close']
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loaded_json2 = dailyTimeSeries[temp]
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#value = loaded_json2['4. close']
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value = loaded_json2['5. adjusted close']
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values.append(value)
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listAV.append(values)
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#print(listOfDates[0])
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@ -485,6 +494,8 @@ class StockData:
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listOfFirstLastDates = []
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self.allLists = []
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print('\nNOTE: Only IEX and Alpha Vantage support adjusted returns')
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# IEX
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print("\nIEX")
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listIEX = StockData.getIEX(self)
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@ -504,6 +515,7 @@ class StockData:
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# COMMENTED OUT FOR NOW B/C LIMITED
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'''
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print("\nTiingo")
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print("NOTE: Tiingo does not return adjusted returns!!")
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listTiingo = StockData.getTiingo(self)
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#print(listTiingo)
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if listTiingo != 'Not available':
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@ -515,7 +527,7 @@ class StockData:
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#print(listOfFirstLastDates)
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if (len(self.allLists) > 0):
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print("\n")
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print(len(self.allLists), "available sources for", self.name)
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print(len(self.allLists), "available source(s) for", self.name)
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self.absFirstLastDates = StockData.getFirstLastDate(self, listOfFirstLastDates)
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print("\nThe absolute first date with close values is:", self.absFirstLastDates[0])
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print("The absolute last date with close values is:", self.absFirstLastDates[1])
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@ -107,11 +107,12 @@ class Return:
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print("\nPlease enter a time frame in years: ", end='')
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#timeFrameYear = int(input())
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timeFrameYear = 5
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print(timeFrameYear)
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self.timeFrame.append(timeFrameYear)
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print("Please enter a time frame in months (30 days): ", end='')
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#timeFrameMonth = int(input())
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timeFrameMonth = 0
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print('')
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print(timeFrameMonth)
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self.timeFrame.append(timeFrameMonth)
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#print(self.timeFrame)
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self.firstLastDates = Return.getFirstLastDates(self, stock)
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@ -124,7 +125,8 @@ class Return:
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print('\nGetting unadjusted return')
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unadjustedReturn = Return.getUnadjustedReturn(self, stock)
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self.listOfReturn.append(unadjustedReturn)
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print(self.listOfReturn[0], '%')
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print(self.listOfReturn[0])
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print(self.listOfReturn[0]/timeFrameYear, '%')
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def main():
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stockName = 'spy'
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