lakshmi

Lakshmi

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Screenshot of lak in action (Screenshot of the lak command in action)

Background

This project is inspired by Bogleheads forum. Bogleheads focus on a simple but powerful philosophy that allows investors to achieve above-average returns after costs. This tool is built around the same principles to help an average investor manage their investing portfolio.

Lakshmi (meaning “She who leads to one’s goal”) is one of the principal goddesses in Hinduism. She is the goddess of wealth, fortune, power, health, love, beauty, joy and prosperity.

Introduction

This project consists of a library module (lakshmi) and a command-line tool (lak) that exposes some of the functionality of the library. The library provides useful abstractions and tools to manage your investing portfolio.

Bogleheads wiki is a great resource for introduction to basic investing concepts like asset-allocation, asset-location, etc.

The following features are currently available:

Installation

This project can be installed via pip. To install the library and the lak command line tool, run:

pip install lakshmi

Command-line interface

For detailed help on the CLI, please see lak user guide. For tips and tricks, please refer to Lakshmi Recipes.

The simplest way to use this project is via the lak command. To access the up to date help, run:

$ lak --help
Usage: lak [OPTIONS] COMMAND [ARGS]...

  lak is a simple command line tool inspired by Bogleheads philosophy.
  Detailed user guide is available at:
  https://sarvjeets.github.io/lakshmi/docs/lak.html

Options:
  --version          Show the version and exit.
  -r, --refresh      Re-fetch all data instead of using previously cached
                     data. For large portfolios, this would be extremely slow.
  -c, --config PATH  The configuration file.  [env var: LAK_CONFIG; default:
                     ~/.lakrc]
  --debug            If set, prints stack track when an exception is raised.
  --help             Show this message and exit.

Commands:
  add      Add new entities to the portfolio.
  analyze  Analyze the portfolio.
  delete   Delete different entities from the portfolio.
  edit     Edit parts of the portfolio.
  info     Print detailed information about parts of the portfolio.
  init     Initializes a new portfolio by adding asset classes.
  list     Command to list various parts of the portfolio.
  whatif   Run hypothetical what if scenarios by modifying the total...

The following section gives a quick summary of how to create a new portfolio. For detailed help, please read creating a portfolio section of the lak user guide.

A new portfolio can be created by either:

  1. Copying an existing portfolio file to ~/portfolio.yaml and editing it, OR
  2. Using the lak commands to create a new portfolio.

The following command will open up an editor to input the desired asset allocation:

$ lak init

Accounts (His/Her 401(k), Roth IRAs, Taxable, etc.) can be added via the lak add account command:

$ lak add account
# Use the above command multiple times to add more accounts.

Assets can be added to an account via the lak add asset command. Different kinds of assets can be added to a portfolio. For a complete list, pull up the help for the command:

$ lak add asset --help
Usage: lak add asset [OPTIONS]

  Add a new asset to the portfolio.

Options:
  -p, --asset-type [ManualAsset|TickerAsset|VanguardFund|IBonds|EEBonds]
                                  Add this type of asset.  [required]
  -t, --account substr            Add asset to this account (a substring that
                                  matches the account name).  [required]
  --help                          Show this message and exit.

TickerAsset represents an asset with a ticker symbol. The value of these assets is updated automatically. To add a TickerAsset:

lak add asset -p TickerAsset -t account_str

where account_str is a sub-string that uniquely matches an account added previously.

That’s it. To view all the assets, asset allocation and asset location, run:

lak list assets total aa al

Library

The lakshmi library can also be used directly. The modules and classes are well documented and there are numerous examples for using each method or class in the tests accompanying this package. The example portfolio can be constructed and the asset allocation, etc. can be printed by the following piece of python code:

from lakshmi import Account, AssetClass, Portfolio
from lakshmi.assets import TaxLot, TickerAsset
from lakshmi.table import Table


def main():
    asset_class = (
        AssetClass('All')
        .add_subclass(0.6, AssetClass('Equity')
                      .add_subclass(0.6, AssetClass('US'))
                      .add_subclass(0.4, AssetClass('Intl')))
        .add_subclass(0.4, AssetClass('Bonds')))
    portfolio = Portfolio(asset_class)

    (portfolio
     .add_account(Account('Schwab Taxable', 'Taxable')
                  .add_asset(TickerAsset('VTI', 1, {'US': 1.0})
                             .set_lots([TaxLot('2021/07/31', 1, 226)]))
                  .add_asset(TickerAsset('VXUS', 1, {'Intl': 1.0})
                             .set_lots([TaxLot('2021/07/31', 1, 64.94)])))
     .add_account(Account('Roth IRA', 'Tax-Exempt')
                  .add_asset(TickerAsset('VXUS', 1, {'Intl': 1.0})))
     .add_account(Account('Vanguard 401(k)', 'Tax-Deferred')
                  .add_asset(TickerAsset('VBMFX', 20, {'Bonds': 1.0}))))

    # Save the portfolio
    # portfolio.Save('portfolio.yaml')
    print('\n' + portfolio.asset_allocation_compact().string() + '\n')
    print(Table(2, coltypes=['str', 'dollars'])
          .add_row(['Total Assets', portfolio.total_value()]).string())
    print('\n' + portfolio.asset_allocation(['US', 'Intl', 'Bonds']).string())
    print('\n' + portfolio.assets().string() + '\n')
    print(portfolio.asset_location().string())


if __name__ == "__main__":
    main()

Development

Here are the steps to download the source code and start developing on Lakshmi:

# Fork and clone this repo.
$ git clone https://github.com/yourusername/lakshmi.git
$ cd lakshmi

# All development is done on the 'develop' branch
$ git checkout develop

# Setting up a virtual environment is strongly recommended. Install virtualenv
# by one of the following:
# pip install virtualenv --user  # If you have pip installed
# sudo apt-get install python-virtualenv # Ubuntu
# sudo pacman -S python-virtualenv  # Arch linux
$ virtualenv venv
# Activate the virtual environment
$ source venv/bin/activate

# Install all the dependencies
$ pip install -r requirements.txt

# Run unittests
$ python -m unittest

# Install pre-commit hooks to run it automatically on commits
$ pre-commit install
# Run pre-commit manually
$ pre-commit run --all-files

# Create your own bug or feature branch and start developing. Remember to
# run tests (and add them when necessary) and pre-commit hooks on changes.

License

Distributed under the MIT License. See LICENSE for more information.

Acknowledgements

I am indebted to the following folks whose wisdom has helped me tremendously in my investing journey: John Bogle, Taylor Larimore, Nisiprius, Livesoft, Mel Lindauer and LadyGeek.

This project would not have been possible without my wife Niharika, who helped me come up with the initial idea and encouraged me to start working on this project.

The not-so-fine print

The author is not a financial adviser and you agree to treat this tool for informational purposes only. The author does not promise or guarantee that the information provided by this tool is correct, current, or complete, and it may contain technical inaccuracies or errors. The author is not liable for any losses that you might incur by acting on the information provided by this tool. Accordingly, you should confirm the accuracy and completeness of all content, and seek professional advice taking into account your own personal situation, before making any decision based on information from this tool.

In a nutshell:

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