Stock Analyzer

Overview

Stock Analyzer is a full-stack tool built to collect, analyze, and surface professional stock recommendations. Originally created as a personal project to make investing less intimidating, it scrapes data from sites like MarketBeat and Barchart, stores it in a MongoDB database, and makes it accessible via a Google Sheet and a Discord bot called StockChecker.

Features

• Aggregates analyst recommendations and price targets from multiple sources
• Normalizes scores using a 5-point weighted scale
• Stores and updates data in MongoDB
• Auto-populates a Google Sheet for visibility and reporting
• Discord bot interface for real-time queries and rankings

⚠️ Note: This project is no longer actively maintained due to expired AWS credits and early-stage design decisions. That said, writing this makes me want to fix it up and bring it back better than ever.

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Example Output

Below is a screenshot of the StockChecker Discord bot responding to a !sc highest query, showing top stock picks based on weighted analyst sentiment:

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File Descriptions

main.py

Main driver script for gathering data and populating outputs.

Responsibilities:

• Reads stock tickers from data/tickers.txt
• Initializes scraping session
• Collects and processes recommendation data
• Populates Google Sheets and optionally writes to MongoDB

Function: main(numberStart=0, numberEnd=6000) : Initializes the Google Sheets API using the provided credentials and returns the worksheet object.

• populate_sheet(wks, stock): Populates the Google Sheet with the provided stock data. It checks if the stock ticker already exists in the sheet and updates or adds new data accordingly.
• populate_db(stock): Stores the provided stock data in a MongoDB database.

Supporting Files

data/tickers.txt

• A file containing a list of stock tickers to be analyzed.

creds/credentials.json

• A JSON file containing the credentials required to authenticate with the Google Sheets API.

creds/creds.json

• A JSON file containing the connection string for the MongoDB database.

Usage

1. Setup Google API Credentials:

   • Ensure you have a credentials.json file with the necessary Google API credentials.
   • Place this file in the creds directory.

2. Setup MongoDB Credentials:

   • Ensure you have a creds.json file with the necessary MongoDB connection string.
   • Place this file in the creds directory.

3. Run the Main Script:

   python main.py