Why?

I occasionally need historical stock price information that can easily be parsed for charting and analysis.

How does it work?

historical_finance_data.py will retrieve historical stock information and save it to a .csv file. Information comes from Yahoo Finance, and requests are limited to the information in their database.

Dependencies

• Python (currently running on Python 2.7)
• Virtualenv is recommended. I recommend reading The Hitchhikers Guide to Python section on Virtual Environments if you are not familiar with Python virtual environments.

Getting Started

$ git clone https://github.com/stvnjacobs/historical_finance_data.git
$ cd historical_finance_data

Install the necessary dependencies using pip. (Again, Virtualenv is recommended to isolate dependencies)

$ virtualenv env
$ source env/bin/activate
$ pip install -r requirements.txt

Running The Program

The program is run from the command line, and you must provide it with a valid ticker symbol.

note: These commands are run from the folder which contains historical_finance_data.py. The ability to run it from anywhere, or infomration on how to do so, will soon be added.

$ python historical_finance_data.py VTI

If you do not set an interval, you will be prompted to enter one. The script currently pulls daily data by default. You also have the option of weekly, monthly, yearly, or only dividend data.

note: These can all be set from the start as an attribute with the -i or --interval flag when you first input the command.

• d or daily for daily data.
• w or weekly for weekly data.
• m or monthly for monthly data.
• v or dividends will return all dividend payouts.

The newly created .csv file will be placed in a data directory. If you were to get information for VTI, the Vanguard Total Stock Market ETF, the resulting file tree of the directory will look something like this:

historical_finance_data
├── data
│   └── VTI.csv
├── historical_finance_data.py
└── readme.md

Here is what the first 10 lines of the VTI.csv we just created (on April 29th, 2014) looks like.

$ head -10 data/VTI.csv

Date,Open,High,Low,Close,Volume,Adj Close
2014-04-28,96.90,97.22,95.65,96.69,2046000,96.69
2014-04-25,97.19,97.25,96.34,96.55,1927700,96.55
2014-04-24,97.84,97.90,96.96,97.50,1471400,97.50
2014-04-23,97.62,97.68,97.30,97.37,1798400,97.37
2014-04-22,97.26,97.91,97.19,97.62,2442400,97.62
2014-04-21,96.78,97.12,96.57,97.12,3043000,97.12
2014-04-17,96.42,96.97,96.26,96.73,2241100,96.73
2014-04-16,96.21,96.55,95.75,96.54,4498500,96.54
2014-04-15,95.13,95.60,94.03,95.54,3339400,95.54

Taking it further

• Add more command line arguments for refining output:
  • Intervals & Dividends
  • Date ranges and deltas
• Setuptools integration (Instructions)
• Option to create chart