fund-indicators/README.md

# fund-indicators

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fund-indicators is a cross-platform Python application that allows users to easily find relationships between various attributes of mutual funds and previous performance. This project is based on research from [*Performance Indicators of Mutual Funds*](https://nextcloud.andrewkdinh.com/s/xNgGQ4nPNkSqJti).

[![asciicast demo](https://asciinema.org/a/jLmZapnMFGCRiiSUITY21erLW.svg)](https://asciinema.org/a/jLmZapnMFGCRiiSUITY21erLW?autoplay=1&preload=1)

## Key Features

- 100% automated
- Uses multiple API's in the case another fails
- Caches http requests for future runs
- Scrapes data from Yahoo Finance
- Color-coded for easy viewing
- Optional graphs to easily visualize linear regression results
- A new joke every time
- Cross-platform (tested on Windows and Linux)
- Simple to use

## Quickstart

Give it a try at [repl.run](https://fund-indicators.andrewkdinh.repl.run) or [repl.it](https://repl.it/@andrewkdinh/fund-indicators).

If you would like to clone to your own machine:

```shell
git clone https://github.com/andrewkdinh/fund-indicators.git && cd fund-indicators
pip install -r requirements.txt
python main.py
```

- Common mutual funds are listed in `stocks.txt`
- Configure and rename `config.example.json` to `config.json` if you would like to skip beginning questions (only for advanced users)

## Planned Features

- Graphical user interface (GUI)
- Multithreading/asynchronous requests

## Contributing

Want to help? Great! Check out the [CONTRIBUTING.md](https://github.com/andrewkdinh/fund-indicators/blob/master/CONTRIBUTING.md) file!

## Credits

This project utilizes a wide variety of open-source projects:

- [NumPy](https://github.com/numpy/numpy), [Termcolor](https://github.com/hfeeki/termcolor), [Beautiful Soup](https://launchpad.net/beautifulsoup), [yahoofinancials](https://github.com/JECSand/yahoofinancials), [requests-cache](https://github.com/reclosedev/requests-cache), [halo](https://github.com/manrajgrover/halo), [matplotlib](https://github.com/matplotlib/matplotlib), [asciinema](https://github.com/asciinema/asciinema), [Core Infrastructure Initiative Best Practices Badge](https://github.com/coreinfrastructure/best-practices-badge)

And thank you to those that have helped me with the idea and product:

- Amber Bruce, [Alex Stoykov](http://stoykov.us/), Doug Achterman, [Stack Overflow](https://stackoverflow.com)

Licensed under [GPL-3.0](https://raw.githubusercontent.com/andrewkdinh/fund-indicators/master/LICENSE) | Copyright (C) 2019  Andrew Dinh