Stock Predictor

Predict the price of a stock using the power of machine learning!

Table of Contents

• Installation (Server Side)
• Environment Variables (Server Side)
• Usage (Client Side)
• Example Request
• Example Response
• Compiling

Installation (Server Side)

1. Clone the repository.

   git clone https://github.com/BastianAsmussen/StockPredictor.git

2. Create a .env file.

   $ touch .env
   
   # Add the following to the .env file.
   # WORKERS=4
   # IP="127.0.0.1"
   # PORT=8080

3. Compile the project.

   cargo build --release

4. Getting logger information. (Optional)

Linux

source RUST_LOG=stock_predictor # Set the environment variable.

Windows

set RUST_LOG=stock_predictor # Set the environment variable.
 ```
6. Run the project.
### Linux
```sh
./target/release/stock_predictor

Windows

.\target\release\stock_predictor.exe

Environment Variables (Server Side)

Variable	Description
WORKERS	The number of workers (threads) to use for the HTTP server.
IP	The IP address to use for the HTTP server.
PORT	The port to use for the HTTP server.

Usage (Client Side)

1. Send a GET request to the server.

   curl -X GET "http://127.0.0.1:8080/predict" -H "Content-Type: application/json" -d '{ "symbol": "AAPL", "days": 7 }'

Example Request

{
  "symbol": "AAPL",
  "days": 7
}

Request Fields

Field	Type	Description
symbol	string	The stock symbol.
days	int	The number of days to predict into the future.

Example Response

{
  "request": {
    "symbol": "AAPL",
    "days": 7
  },
  "error": null,
  "predictions": [
    191.48390197753906,
    192.28878784179688,
    192.40756225585938,
    192.34530639648438,
    192.67547607421875,
    193.71231079101562,
    193.5487518310547
  ],
  "modelRmse": 0.00010840992763405666
}

Response Fields

Field	Type	Description
request	object	The request that was sent to the server.
error	string	The error message if an error occurred.
predictions	array	The predicted prices.
modelRmse	float64	The root mean squared error of the model.

Compiling

1. Clone the repository.

   git clone https://github.com/BastianAsmussen/Stock-Predictor.git as stock_predictor

2. Change directory to the project folder.

   cd stock_predictor

3. Compile the project.

   cargo build --release

4. Getting logger information. (Optional)

   Linux

   source RUST_LOG=stock_predictor # Set the environment variable.

   Windows

   set RUST_LOG=stock_predictor # Set the environment variable.

5. Run the project.

   Linux

   ./target/release/stock_predictor

   Windows

   .\target\release\stock_predictor.exe