Good Morning

Good Morning (morningstar) is a simple Python module for downloading fundamental financial data from financials.morningstar.com. It will work as long as the structure of the responses from financials.morningstar.com do not change.

Prerequisites:

• Python 3, bs4, csv, datetime, http.client, json, numpy, pandas, pymysql, re, urllib.request.

Motivation

Good Morning is intended to be used as an extension to QSToolKit (QSTK) library. By using QSTK you can easily download historical stock market data from Yahoo Finance. You can also download fundamental financial data from Compustat. However, most individuals and institutions do not have access to Compustat. Good Morning attempts to mitigate this limitation by providing a very simple Python interface for downloading fundamental financial data from financials.morningstar.com.

Example of Downloading Key Ratios from MorningStar

import good_morning as gm
kr = gm.KeyRatiosDownloader()
kr_frames = kr.download('AAPL')

The variable kr_frames now holds an array of pandas.DataFrames containing the key ratios for the morningstar ticker AAPL.

print kr_frames[0]

Outputs:

Period                            2005      2006      2007 ...
Key Financials USD                                         ...
Revenue USD Mil               13931.00  19315.00  24006.00 ...
Gross Margin %                   29.00     29.00     34.00 ...
Operating Income USD Mil       1650.00   2453.00   4409.00 ...
Operating Margin %               11.80     12.70     18.40 ...
Net Income USD Mil             1335.00   1989.00   3496.00 ...
Earnings Per Share USD            0.22      0.32      0.56 ...
...

Example of Downloading Financial data

import good_morning as gm
kr = gm.FinancialsDownloader()
kr_fins = kr.download('AAPL')

Different from the KeyRatiosDownloader class, kr_fins now holds a dictionary containing the financials for the morningstar ticker AAPL. The financials may differ from company to company.

print (fins.keys())

Output:

dict_keys(['income_statement', 'balance_sheet', 'cash_flow', 'period_range', 'fiscal_year_end', 'currency'])

Storing Good Morning Data in a Database

We can also store this data in a relational database. If we specify the MySQL connection conn the retrieved data will be uploaded to the MySQL database:

import pymysql
conn = pymysql.connect(
    host = DB_HOST, user = DB_USER, passwd = DB_PASS, db = DB_NAME)
kr_frames = kr.download('AAPL', conn)

Every pandas.DataFrame in the array kr_frames will be uploaded to a different database table. In our case the following tables will be created:

`morningstar_key_balance_sheet_items_in_percent`
`morningstar_key_cash_flow_ratios`
`morningstar_key_efficiency_ratios`
`morningstar_key_eps_percent`
`morningstar_key_financials_usd`
`morningstar_key_liquidity_per_financial_health`
`morningstar_key_margins_percent_of_sales`
`morningstar_key_net_income_percent`
`morningstar_key_operating_income_percent`
`morningstar_key_profitability`
`morningstar_key_revenue_percent`

For example, the following MySQL query:

SELECT * FROM `morningstar_key_cash_flow_ratios`;

Outputs:

ticker      period     ...
  AAPL  2005-09-30  171.41  200.13  1.87  16.33  1.70
  AAPL  2006-09-30  -12.43  -31.30  3.40   8.09  0.79
  AAPL  2007-09-30  146.40  186.88  4.11  18.68  1.28
  AAPL  2008-09-30   75.43   87.27  3.69  25.85  1.74
...

Where the columns are:

ticker
period
operating_cash_flow_growth_percent_yoy
free_cash_flow_growth_percent_yoy
cap_ex_as_a_percent_of_sales
free_cash_flow_per_sales_percent
free_cash_flow_per_net_income

Unit Tests

We include unittest to troubleshoot your use of the library. It's a simple command line process to run the test. Navigate to the base directory of good-morning and use the standard library unittest command line interface:

python -m unittest test/

Output:

----------------------------------------------------------------------
Ran 3 tests in 0.626s

OK

If you see anything other than this, you should get an error report. Before submitting an issue, run the test and try to paste the output if the error persists.

Available Classes

There are two classes in good_morning:

• KeyRatiosDownloader - Used to download key ratios. Key ratios share the same structure across all Morningstar tickers.
• FinancialsDownloader - Used to download financials (i.e. income statement, balance sheet, cash flow). Financials may differ in structure across the Morningstar tickers.

LICENSE

Good Morning is licensed to you under MIT.X11:

Copyright (c) 2015 Peter Cerno

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.