I am super new to python so new to OOP and class (I am originally MATLAB user as an engineer...) so please teach me as much as possible. Anyways I am trying to do the following.

1. Create a class called Stock - something like below

   class Stock :
         def __init__(self,estimate,earning)
             self.estimate = estimate       # estimation of quarterly earnings
             self.earning = earning         # actual quarterly earnings
   
   JPM(JP Morgan stock name) = Stock(11.7,10.9)
   

2. However, the estimate and earning values are reported every quarter and I want to create a numerical vector for each. The idea is like below, but of course it does not work.

   JPM.estimate(1) = 11.9   # the second quarter earnings value at index 1 of the estimate
   JPM.estimate(2) = 12.1   # the third quarter earnings value at index 2 of the estimate
   JPM.estimate(3) = XX.XX  # and so on.
   

   Using .estimate(#) is just to show what I want to do. Using .append() or other methods you would like to teach me is fine.

The reason I am trying to do it this way is because I need 3 vectors for one stock(and I have about 1000 stocks so at the end I would have 3000 vectors to take care of). So I am planning on creating an instance of a stock and having 3 vectors as instance attributes. (Hopefully I got the terminology right.)

1. earnings vector
2. estimate vector
3. the date those earnings were reported.

Am I using the class function wrong(as it was never intended to be used this way?) or what can I do to achieve such concatenation for instance attributes as the data are received from web scraping?

CodePudding user response：

It is not at all clear what you are trying to do with the Stock Class, but if all you want to do is create a list of stock price and earnings organized by date, you could do the following :

from collections import namedtuple, defaultdict

# Create a easily referenced tuple for defining staock data
StockData = namedtuple('StockData', ['date', 'earn', 'est']) 

class Stock:
    def __init__(self, data: StockData) -> None:
        self._quotes = defaultdict()
        self._quotes[data.date] = (data.earn, data.est)

    def add(self, data: StockData) -> None:
        self._quotes[data.date] = (data.earn, data.est)
        
    def value(self, date: str) -> tuple:
        # return tuple of (Earnings, Estimate) for date if it exists, else KeyError
        return self._quotes[date]

    def __repr__(self):
        return str(self._quotes)  

To load the stock class with data, you can do something along the lines of:

stk = Stock(StockData('1/20/2021', 123.5, 124.0))
stk.add(StockData('6/23/2021', 132.7, 119.4))

print(stk) yields:

defaultdict(None, {'1/20/2021': (123.5, 124.0), '6/23/2021': (132.7, 119.4)})

and, stk.value('1/20/2021')​ yields (123.5, 124.0)