Web Trader is a trading website that consolidates data from Nasdaq, allowing the user to search up the ticker symbol and price of any stock. I employed HTML and CSS to format all the pages and used Python for the back end development. All of the user information, transactions, holdings, and balances are stored in a SQLite3 database. Not only can users search up stocks, they can buy and sell using their own funds. The goal is to end up with a large profit.

• Clone (or download) the repository:

git clone [email protected]:Paulinakhew/web_trader.git

• Download all the necessary packages:

• MacOS Users

$ pip3 install -r requirements.txt

• Linux Users

$ pip install -r requirements.txt

• Create the sqlite3 database:

$ python3 schema.py

• Seed the database:

$ python3 seed.py

• Install pre-commit hook:

pre-commit install

• Run the app locally:

$ python3 controller.py

• Paste http://127.0.0.1:5000 into your web browser and have fun! 🤩

This is the login menu where you can login or create a new user account.

This is the main menu that opens after you log in.

The dashboard is where you can see all of your previous transactions as well as current holdings.

This page lets the user lookup ticker symbols and the last prices of stocks.

The buy and sell menu lets the user input the ticker symbol and quantity of the stock that they want to purchase/sell.

The database is created using SQLite3. There are five tables in total, each serving a different purpose. For example, the transactions table is used to store the date, number of shares, and ticker symbols of all the users' purchases. This is the code for the transactions table:

CREATE TABLE transactions(
    pk INTEGER PRIMARY KEY AUTOINCREMENT,
    ticker_symbol TEXT,
    num_shares FLOAT,
    owner_username INTEGER,
    last_price FLOAT,
    date TEXT,
    FOREIGN KEY(owner_username) REFERENCES user(username)
);

I used the flask_restful extension to create an api. The endpoints are as follows:

'/users'
'/transactions'
'/transactions/<username>'
'/holdings/<username>'

I use GitHub actions and Pytest to test the project. You can see the tests here. I also have the API Key for the Intrinio API set up as a Secret. Secrets are environment variables that are encrypted and only exposed to selected actions. Anyone with collaborator access to this repository can use these secrets in a workflow.

Instead of storing passwords as plaintext, I stored the salt and the hash of the password. When users try to log in, the hashed password is compared to the hash in the database.

pwdhash = hashlib.pbkdf2_hmac(
    'sha512',
    password.encode('utf-8'),
    salt.encode('ascii'),
    100000
)

Feel free to create a GitHub issue for this repository if you have any new ideas!