stockeasy 0.0.20220227174346

A package for a quick and dirty portfolio analysis.

stockeasy

Quick and Easy Stock Portfolio Analysis - FOR ENTERTAINMENT PURPOSES ONLY!!

Introduction

All exposed functions in this package have been designed with the intent that they can be strung together in a DAG; as such, they all follow a consistent contract.

function contract

def function_name (data: Dict, config: dict, logging: logging.Logger)
return results: dict

data contract

data = {'name': pandas dataframe}

config contract

config = {'setting': setting values}

Example Code

import stockeasy
import pandas as pd

df_stocklist = pd.DataFrame([['VTSAX', 120], ['MSFT', 100]], columns=['symbol', 'sharesOwned'])

config = {
    'symbolField': 'symbol',
    'sharesField': 'sharesOwned',
    'dataFields': ['exchange', 'symbol', 'shortName', 'sector', 'country', 'marketCap']
}

results = stockeasy.get_info({'input': df_stocklist}, config=config)

print(results.get('output').head())

logging

Standard python logging object

Notes

• I use Docker for enviroment management; as such, my build process will deviate from more classical approaches.
• I attempt to follow functional programming style

Getting Started Contributing

for windows create a env.bat file after pulling with the mount path to the current directory. In windows, you can't use relative paths with Docker Volume mounts, so...

set LOCAL_MOUNT=C:\Users\ablac\OneDrive\Documents\stockeasy\

then run

make DOCKER
cd stockeasy
doit

Available doit tasks

lint -- runs linting setup_tool -- installs local tool unit_tests -- runs unit tests