thestockslib

A simple library to manage stocks data

Sample code

# library import
from thestockslib import TheStock

# initialization
stock = TheStock('AAPL')

# getting live price
stock.getliveprice()

# getting current Yahoo recommendation
r = stock.getyahoorecommendation()
TheStock.getyahoorecommendationstring(r)

# getting Yahoo performance outlook information (short term, medium term, long term)
stock.getyahooperformanceoutlook()

# getting historical price at July 31st, 2020
stock.gethistoricalprice('2020-07-31')

# adding some mapping to recommendations actions
stock.addactiontoperiod('buy', 7) # when a 'buy' suggestion is received, consider a sell after 7 days
stock.addactiontoperiod('strong buy', 7) # when a 'strong buy' suggestion is received, consider a sell after 7 days
stock.addactiontoperiod('long-term buy', 30) # when a 'long-term buy' suggestion is received, consider a sell after 30 days

# initializing the suggester name
suggestername = 'Cascend'

# simulating purchases by suggester name
purchases = stock.simulatepurchases(suggestername)
print(purchases)

# simulating sells
stock.simulatesells(purchases)

# compute suggester's reliability for 'buy' actions
stock.getsuggestionreliability(suggestername, 'buy')

Available Enums

ConsideredAverage

This Enum is used to pass as input the average method to adopt, when historical data are requested. Following values are possible:

• OPEN_CLOSE, to consider as daily value the average between open and close prices for a given stock
• HIGH_LOW, to consider as daily value the average between higher and lower prices for that day, for given stock

Available classes

Just a single TheStock class is available.

Following attributes are supported:

• ticker the string of the ticker considered (e.g. AAPL)
• tickerobject the yfinance Ticker object
• dateformat the date format to consider (default to %Y-%m-%d)
• consideredaverage the average computation metric to consider (default to ConsideredAverage.OPEN_CLOSE)
• historicaldata the historical market data for the current ticker, according to yfinance data format, converted to an array of records

Following methods are supported:

• __init__(self, t, df='%Y-%m-%d', ca=ConsideredAverage.OPEN_CLOSE), initializes the TheStock object

  • t (str) is the ticker/symbol
  • df (str) is the date format to consider
  • ca (ConsideredAverage) is the average to consider

• addactiontoperiod(a, p), adds a match between a recommendation action and the duration to consider for that recommendation

  • a (str) is the action title/name, as mapped with the list of recommedations
  • p (int) is the period to consider, in days

• convertdatetime(d), converts a datetime object d to a string, in the format df passed during the object initialization

  • d (datetime) the datetime object to convert

• getliveprice(round_decimals=2), returns the current live price for the current symbol

  • round_decimals (int) the decimals to consider for rounding

• gethistoricalprice(d, round_decimals=2), returns the historical price for the current symbol at time d

  • d (datetime) the date to consider
  • round_decimals (int) the decimals to consider for rounding

• simulatepurchases(s), simulates purchases of the current symbol for the suggester s

  • s (str) the suggester's name to consider

• simulatesells(p), simulates sell of given purchases p, after the expiration of the relative period for the action suggested for that purchase

  • p (list) the list of purchases objects

• getsuggestionreliabilitydata(suggester, suggestion, transactionprice=0.0), provides structured information on the reliability of a given suggester and for a given suggestion

  • suggester (str) the suggester's name
  • suggestion (str) the suggestion action
  • transactionprice (float) the price for transaction to consider

• getsuggestionreliability(suggester, suggestion, transactionprice=0.0), computes the reliability of a given suggester and for a given suggestion

  • suggester (str) the suggester's name
  • suggestion (str) the suggestion action
  • transactionprice (float) the price for transaction to consider

• generategraphs(fcast_time, alphavantage_apikey, outputname_pre=''), generates the graphs to be displayed for the current symbol

  • fcast_time (int) the forecast time to consider, in days
  • alphavantage_apikey (str) the AlphaVantage API key to use
  • outputname_pre (str) the preliminary file name to use for generated graphs

• getyahoorecommendation(), returns the current Yahoo recommendation for the current symbol

• getyahooperformanceoutlook(), returns the current Yahoo performance outlook for the current symbol (output is a list containing, in order, short term, medium term, long term results)

• getcompanynews(finnhub_apikey, fromdate=None), returns the list of today news related to the current symbol

  • finnhub_apikey (str) the FinnHub API key to use
  • fromdate (str) the starting date to consider when retrieving the news, if the retrieval of news older than today is needed

Following statical methods are supported:

• getrevolutsymbols(), returns the list of symbols supported by Revolut

• combineimages(l, vertical=False, outputfile='output.png'), combines a list of images to an output file

  • l (list) the list of file names of the input images to combine
  • vertical (bool) the combination mode (vertical or horizonal)
  • outputfile (str) the output file name to generate

• removeimages(outputname_pre=''), removes all images generated

  • outputname_pre (str) the preliminary file name to use for generated graphs

• getyahoorecommendationstring(r), retrieves the Yahoo recommendation string from the input value represented as float

  • r (float) the recommendation value represented as float

TODO

• Improve code readability

Contacts

You can find me on Twitter as @auino.