CS50 pset9: Using flask API to create a web application to exchange stocks' shares.

Overview

C$50 Finance

In this guide we want to implement a website via which users can “register”, “login” “buy” and “sell” stocks, like below:

Picture of dashboard

Background

If you’re not quite sure what it means to buy and sell stocks (i.e., shares of a company), head here for a tutorial.

We’re about to implement C$50 Finance, a web app via which you can manage portfolios of stocks. Not only will this tool allow us to check real stocks’ actual prices and portfolios’ values, it will also let you buy and sell stocks by querying IEX for stocks’ prices.

Indeed, IEX lets you download stock quotes via their API (application programming interface) using URLs like https://cloud.iexapis.com/stable/stock/nflx/quote?token=API_KEY.

Before getting started on this project, we’ll need to register for an API key in order to be able to query IEX’s data. To do so, follow these steps:

  • Visit iexcloud.io/cloud-login#/register/.
  • Select the “Individual” account type, then enter your email address and a password, and click “Create account”.
  • Once registered, scroll down to “Get started for free” and click “Select Start” to choose the free plan.
  • Once you’ve confirmed your account via a confirmation email, visit (https://iexcloud.io/console/tokens).
  • Copy the key that appears under the Token column (it should begin with pk_).
  • In a terminal window execute:
export API_KEY=value

where value is that (pasted) value, without any space immediately before or after the =. You also may wish to paste that value in a text document somewhere, in case you need it again later.

Install requirements

This guide wrote for Windows Terminal and if you have another OS you may change it.

Before we start, you should clone this GitHub repo and then install the dependencies.

git clone https://github.com/magnooj/CS50-finance.git
cd CS50-fincance
pip install -r requirements.txt

Through the files

Now, we are ready to run and test our project. By running ls you can see these files:

Flask API

The first step in building APIs is to think about the data we want to handle, how we want to handle it and what output we want with our APIs. In our example, we want users can register, log in, log out and buy, sell and qout stocks; Finally, see the history of their transactions.

The main HTML file in our app is layout.html. We created a template that other HTML files cand extend that.

In this example, we create Flask eight routs so that we can serve HTTP traffic on that route.

  • / or index : Is the homepage of our app. If user loged in, it display the user’s current cash balance along with a grand total (i.e., stocks’ total value plus cash). But, if user didn.t log in, it displays the login page.
  • register : It has a form that user can register by filling it.
  • buy : In this route, users can input a stock’s symbol and buy some shares.
  • sell : In this page, users can SELECT from theis stocks’ symbol and sell their shares.
  • qoute : Users can lookup the price each share in a stock’s symbol.
  • history : It displays an HTML table summarizing all of a user’s transactions ever, listing row by row each and every buy and every sell.
  • login and logout : These routes start and terminate user’s session.

Of course there is some files like apology.html that displays the error to the user. You can check other files.

Now, We cheked our files and sqw how our app is working. To run the app, when you are in CS50-finance directory, enter this command in the terminal:

flask run

I hope you enjoyed how to stocks' exchange web application using flask. if you have any comments please do not hesitate to send me an e-mail.

Regards,

Ali Ganjizadeh

In this tutorial, raster models of soil depth and soil water holding capacity for the United States will be sampled at random geographic coordinates within the state of Colorado.

Raster_Sampling_Demo (Resulting graph of this demo) Background Sampling values of a raster at specific geographic coordinates can be done with a numbe

2 Dec 13, 2022
A real data analysis and modeling project - restaurant inspections

A real data analysis and modeling project - restaurant inspections Jafar Pourbemany 9/27/2021 This project represents data analysis and modeling of re

Jafar Pourbemany 2 Aug 21, 2022
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano

PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) an

PyMC 7.2k Dec 30, 2022
BigDL - Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems

Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems.

Vo Cong Thanh 1 Jan 06, 2022
This module is used to create Convolutional AutoEncoders for Variational Data Assimilation

VarDACAE This module is used to create Convolutional AutoEncoders for Variational Data Assimilation. A user can define, create and train an AE for Dat

Julian Mack 23 Dec 16, 2022
Exploratory Data Analysis for Employee Retention Dataset

Exploratory Data Analysis for Employee Retention Dataset Employee turn-over is a very costly problem for companies. The cost of replacing an employee

kana sudheer reddy 2 Oct 01, 2021
Synthetic Data Generation for tabular, relational and time series data.

An Open Source Project from the Data to AI Lab, at MIT Website: https://sdv.dev Documentation: https://sdv.dev/SDV User Guides Developer Guides Github

The Synthetic Data Vault Project 1.2k Jan 07, 2023
This creates a ohlc timeseries from downloaded CSV files from NSE India website and makes a SQLite database for your research.

NSE-timeseries-form-CSV-file-creator-and-SQL-appender- This creates a ohlc timeseries from downloaded CSV files from National Stock Exchange India (NS

PILLAI, Amal 1 Oct 02, 2022
Gathering data of likes on Tinder within the past 7 days

tinder_likes_data Gathering data of Likes Sent on Tinder within the past 7 days. Versions November 25th, 2021 - Functionality to get the name and age

Alex Carter 12 Jan 05, 2023
Analysis of a dataset of 10000 passwords to find common trends and mistakes people generally make while setting up a password.

Analysis of a dataset of 10000 passwords to find common trends and mistakes people generally make while setting up a password.

Aryan Raj 7 Sep 04, 2022
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io

PyStan PyStan is a Python interface to Stan, a package for Bayesian inference. Stan® is a state-of-the-art platform for statistical modeling and high-

Stan 229 Dec 29, 2022
Using Data Science with Machine Learning techniques (ETL pipeline and ML pipeline) to classify received messages after disasters.

Using Data Science with Machine Learning techniques (ETL pipeline and ML pipeline) to classify received messages after disasters.

1 Feb 11, 2022
Flexible HDF5 saving/loading and other data science tools from the University of Chicago

deepdish Flexible HDF5 saving/loading and other data science tools from the University of Chicago. This repository also host a Deep Learning blog: htt

UChicago - Department of Computer Science 255 Dec 10, 2022
Python package for processing UC module spectral data.

UC Module Python Package How To Install clone repo. cd UC-module pip install . How to Use uc.module.UC(measurment=str, dark=str, reference=str, heade

Nicolai Haaber Junge 1 Oct 20, 2021
ForecastGA is a Python tool to forecast Google Analytics data using several popular time series models.

ForecastGA is a tool that combines a couple of popular libraries, Atspy and googleanalytics, with a few enhancements.

JR Oakes 36 Jan 03, 2023
CleanX is an open source python library for exploring, cleaning and augmenting large datasets of X-rays, or certain other types of radiological images.

cleanX CleanX is an open source python library for exploring, cleaning and augmenting large datasets of X-rays, or certain other types of radiological

Candace Makeda Moore, MD 20 Jan 05, 2023
MIR Cheatsheet - Survival Guidebook for MIR Researchers in the Lab

MIR Cheatsheet - Survival Guidebook for MIR Researchers in the Lab

SeungHeonDoh 3 Jul 02, 2022
OpenARB is an open source program aiming to emulate a free market while encouraging players to participate in arbitrage in order to increase working capital.

Overview OpenARB is an open source program aiming to emulate a free market while encouraging players to participate in arbitrage in order to increase

Tom 3 Feb 12, 2022
Option Pricing Calculator using the Binomial Pricing Method (No Libraries Required)

Binomial Option Pricing Calculator Option Pricing Calculator using the Binomial Pricing Method (No Libraries Required) Background A derivative is a fi

sammuhrai 1 Nov 29, 2021
A collection of learning outcomes data analysis using Python and SQL, from DQLab.

Data Analyst with PYTHON Data Analyst berperan dalam menghasilkan analisa data serta mempresentasikan insight untuk membantu proses pengambilan keputu

6 Oct 11, 2022