From c2341d898958cf6f8707f8bca53b848f63f1a83e Mon Sep 17 00:00:00 2001 From: scoopgracie Date: Mon, 20 Apr 2020 07:09:04 -0700 Subject: [PATCH] Clean up README No code changes yet, mostly just README reformatting --- README.md | 33 ++++++++++++++++++++++++++++----- 1 file changed, 28 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 7c83e8d..340a298 100644 --- a/README.md +++ b/README.md @@ -1,15 +1,21 @@ -`stockquotes` is a simple Python module for collecting stock quotes and historical data from Yahoo! Finance. It's perfect for developers who can't afford the (often steep) prices charged by many stock data APIs. +`stockquotes` is a simple Python module for collecting stock quotes and +historical data from Yahoo! Finance. It's perfect for developers who can't +afford the (often high) prices charged by many stock data APIs. + # Requirements * Python 3.6+ * Beautiful Soup 4 + # Installation pip3 install stockquotes + # Usage First, import the `stockquotes` module. import stockquotes -To get a stock quote, instantiate a `stockquotes.Stock` object. The only parameter is the ticker symbol to look up. +To get a stock quote, instantiate a `stockquotes.Stock` object. The only +parameter is the ticker symbol to look up. kroger = stockquotes.Stock('KR') @@ -22,13 +28,30 @@ To get the day gain in dollars, get the `Stock`'s `increaseDollars`. krogerGainDollars = kroger.increaseDollars -The same value as a percent is available in the `increasePercent` property. To indicate losses, these values are negative. +The same value as a percent is available in the `increasePercent` property. To +indicate losses, these values are negative. ## Historical data -The historical data for a stock can be accessed through the `Stock`'s `historical` property. This is an array of `dict`s, with the first item representing the most recent quote. The `dict`'s `date` property is a `datetime` object representing the date the quote is from. `open` is the opening price for that day. `high` and `low` are the high and low prices, respectively, for that day. `close` and `adjClose` are the closing price. The difference is that `adjClose` is adjusted for splits and dividends, whereas `close` is adjusted only for splits. `volume` is the stock's volume for that day. +The historical data for a stock can be accessed through the `Stock`'s +`historical` property. This is an array of `dict`s, with the first item +representing the most recent quote. The `dict`'s `date` property is a +`datetime` object representing the date the quote is from. `open` is the +opening price for that day. `high` and `low` are the high and low prices, +respectively, for that day. `close` and `adjClose` are the closing price. The +difference is that `adjClose` is adjusted for splits and dividends, whereas +`close` is adjusted only for splits. `volume` is the stock's volume for that +day. + +Typically, this should give at least a month of data. Obviously, it gives less +for recent IPOs. Also, a known but unexplained bug causes it to only give two +days of data for some stocks. + # Exceptions `stockquotes.StockDoesNotExistError` is raised when the stock does not exist. -`stockquotes.NetworkError` is raised when a connection to Yahoo! Finance cannot be established. + +`stockquotes.NetworkError` is raised when a connection to Yahoo! Finance +cannot be established. + # License Copyright (c) 2019 ScoopGracie. All rights reversed. This is free and unencumbered software released into the public domain.