Giter Club home page Giter Club logo

rahuls5 / dash-app Goto Github PK

View Code? Open in Web Editor NEW

This project forked from gogoladzetedo/dash-app

0.0 0.0 1.0 1.68 MB

The application lets users upload the stock market transactions and calculates the daily time-series metrics on individual and summary levels. Metrics are dynamically visualized on the web dashboard. Application is written using Dash and Plotly libraries in Python.

Home Page: https://portfolio-dash.azurewebsites.net/

Python 99.53% Dockerfile 0.47%

dash-app's Introduction

Financial Stokcs Portfolio Analytics

Application lets users to upload the stock market transactions and calculates the metrics accordingly.

Web dashboard application written in Dash and plotly.

Application takes the stock trading operations as input, loads the daily historical prices for the stocks in the portfolio, calculates the metrics and shows the respective plots per stock, compares profits and investments of stocks in time, shows the metrics in the context of open or closed positions together and separately, and the proportion of the stocks in the portfolio. Upload of the transactions can be done either, by manually entering each stock market operation - sell or buy, or by uploading a .csv file that holds these transactions.

The Application is deployed on Azure web apps.

Portal is still in active development phase.

Installation using docker

If you already have docker installed on your machine, dockerfile needed for the build and run for the application is included in the repository. Build the application by running the commands from the dash-app folder: docker build -t portfolio-app-dash . docker run -dp 80:80 portfolio-app-dash And browse the application at the localhost:80 address.

Installation:

It is strongly recommended to create a python virtual environment:

  • python -m venv DashVenv

Activate virtual environment:

  • Mac/Linux: source DashVenv/bin/activate
  • Windows: DashVenv\Scripts\activate.bat

Install the libraries needed for the app:

  • pip install -r requirements.txt

How to run application:

  • python app.py Application will run on local machine port 80.

Screenshots from the dashboard:

image 1 image 2 image 3 image 4 image 5

Known Issues and development under progress:

  • Improve input data refresh functionality.
  • Change the metric tabs to one tab with all the metrics as the option within.
  • Store the state of the user input.
  • UI input validation

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.