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Update stocks.py
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stocks.py
CHANGED
@@ -1,7 +1,5 @@
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#from asyncio.windows_events import NULL
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from configparser import ParsingError
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from logging import raiseExceptions
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#from sympy import comp
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import yfinance as yf
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import requests
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import pandas as pd
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@@ -53,7 +51,7 @@ class Stock_Data(object):
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'''
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This method will get the current price only if the market is open.
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'''
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current_price = None
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if self.status_getter(Ticker) == "Open":
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current_price = float(soup.find("bg-quote", class_="value").text.replace(',',''))
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return current_price
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@@ -79,9 +77,15 @@ class Stock_Data(object):
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'''
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data = yf.download(tickers = str(Ticker), period = "2y", interval = "1d")
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df = pd.DataFrame(data)
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#
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#
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return df
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@@ -111,7 +115,7 @@ class Stock_Data(object):
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if counter <= 17:
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ticker = company_ticker
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title = art.text.strip()
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if title is None
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break
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rows.append([ticker, title])
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counter = counter + 1
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from configparser import ParsingError
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from logging import raiseExceptions
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import yfinance as yf
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import requests
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import pandas as pd
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'''
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This method will get the current price only if the market is open.
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'''
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current_price = None
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if self.status_getter(Ticker) == "Open":
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current_price = float(soup.find("bg-quote", class_="value").text.replace(',',''))
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return current_price
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'''
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data = yf.download(tickers = str(Ticker), period = "2y", interval = "1d")
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df = pd.DataFrame(data)
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# Prediction in the data we evaluate the model
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# If the user wants to run the model with the data that has been evaluated and predicted for , uncomment the 2 lines below ( Rows 111-112 )
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# Setting the start = 2022-08-26 and end = 2020-08-26 Yahoo Finance will return data from 25-8-2020 to 25-8-2022 (2 years period).
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# In those data our model has been evaluated.
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#data = yf.download(tickers = str(Ticker),end="2022-08-26", start="2020-08-26")
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#df = pd.DataFrame(data)
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return df
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if counter <= 17:
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ticker = company_ticker
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title = art.text.strip()
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if title is None:
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break
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rows.append([ticker, title])
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counter = counter + 1
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