Yahoo Finance Proxy - Google Cloud Function

This project provides a simple, serverless proxy that uses a Google Cloud Function to expose two endpoints from the Yahoo Finance API. The endpoints allow you to search for stocks and ETFs and retrieve their latest price data.

Features

• Search Endpoint (/search): Search for financial instruments by name, ticker, ISIN, or description.
• Price Endpoint (/price): Get the latest price and recent performance data for a specific ticker.
• Serverless: Deployed as a Google Cloud Function for easy scaling and management.
• Validated: Includes a full suite of unit tests and linting to ensure code quality.

Endpoints

/search

• Method: GET
• Query Parameters:
  • query (required): The search term to look for.
• Success Response (200 OK):
  • A JSON array of matching stocks, sorted by trading volume.
  • Example: GET /search?query=tesla

    [
      {
        "name": "Tesla, Inc.",
        "isin": "US88160R1014",
        "ticker": "TSLA",
        "description": "Tesla, Inc. designs, develops, manufactures, and sells electric vehicles...",
        "type": "EQUITY",
        "volume": 150000000
      }
    ]

• Error Responses:
  • 400 Bad Request: If the query parameter is missing.
  • 502 Bad Gateway: If the Yahoo Finance API is unavailable.

/price

• Method: GET
• Query Parameters:
  • ticker (required): The stock ticker to look up.
• Success Response (200 OK):
  • A JSON object with the latest price and percentage changes.
  • Example: GET /price?ticker=AAPL

    {
      "ticker": "AAPL",
      "last_price": 170.0,
      "change_1d_percent": "6.25%",
      "change_7d_percent": "13.33%",
      "change_30d_percent": "13.33%",
      "change_1y_percent": "70.00%"
    }

• Error Responses:
  • 400 Bad Request: If the ticker parameter is missing.
  • 404 Not Found: If the ticker is invalid or has no data.
  • 500 Internal Server Error: If an unexpected error occurs.

Deployment

Prerequisites

1. Google Cloud SDK: Make sure you have the gcloud CLI installed and authenticated.
2. Project ID: Have your Google Cloud Project ID ready.
3. Permissions: Ensure your account has the necessary permissions to deploy Cloud Functions.

Steps

1. Clone the Repository:

   git clone <repository-url>
   cd <repository-directory>

2. Configure the Deployment Script:

   • Open the deploy.sh script.
   • Set the PROJECT_ID variable to your Google Cloud Project ID.
   • (Optional) Customize the FUNCTION_NAME and REGION if needed.

3. Run the Deployment Script:

   chmod +x deploy.sh
   ./deploy.sh

4. Verify the Deployment:

   • After the script finishes, it will output the URL of your deployed function.
   • You can test the endpoints using a tool like curl or your browser:

     # Test the search endpoint
     curl "<your-function-url>/search?query=google"
     
     # Test the price endpoint
     curl "<your-function-url>/price?ticker=GOOGL"

Local Development and Testing

To run the function locally or run the tests, follow these steps:

1. Install Dependencies:

   pip install -r requirements.txt -r tests/test_requirements.txt

2. Run the Linter:

   flake8 main.py tests/test_main.py

3. Run the Unit Tests:

   PYTHONPATH=. pytest

Running the Function Locally

To run the function on your local machine for development and testing, you can use the Google Cloud Functions Framework.

1. Install the Functions Framework:

   pip install functions-framework

2. Run the Local Server: The entry point to the application is the handler function in main.py. To start a local server, run the following command from the root of the repository:

   functions-framework --target=handler

   The server will start on http://localhost:8080.

3. Test the Endpoints: You can now send requests to the local server using curl or any other HTTP client.

   • Search Endpoint:

     curl "http://localhost:8080/search?query=Apple"

   • Price Endpoint:

     curl "http://localhost:8080/price?ticker=AAPL"