Trending Stocks with Python, Reddit, Twitter, and ChatGPT

Create a Reddit app and configure Praw with client ID and secret to download submissions and comments, mapping tickers to their related comments for stock discussions.

Loop through configured subreddits to fetch submissions and their comments, print titles, and log results with read-only access and adjustable limits.

Identify potential stock tickers mentioned in Reddit submission titles and comments using pattern recognition, capitalization rules, and punctuation filtering, then validate against Yahoo Finance.

Learn to extract stock tickers from Reddit using Python, regex, and a three-letter minimum rule, then validate with Yahoo Finance and rank results by most frequent comments.

Learn to create a Twitter app, obtain a bearer token, and fetch tweets from a stock list using Python requests, while understanding API limits and a modular workflow.

Identify stock tickers in Twitter posts by dollar-prefixed, uppercase symbols. Move text-cleaning and ticker extraction into a shared utils module and replace hardcoded config with configurable tweet counts.

Combine tweets by ticker into a single list with counts to rank the most mentioned stocks, using Twitter endpoints and tweet fields to fetch language and author data.

Remove duplicate tweets by checking if a tweet is not in the ticker tweets before adding, eliminating repeated Tesla and Nvidia entries and streamlining the add logic.

Combine Reddit and Twitter data into a single tickers list with combined comments and tweets, and compute a total count for each ticker while handling missing data.

Combine reddit and twitter data with minimum comment counts, validate tickers via yahoo finance data using a validate_ticker utility, and filter valid tickers for GPT summaries.

Create an OpenAI account and obtain an API key, install the OpenAI Python package, and use a prompt to a completion request to generate a concise summary.

Combine Reddit comments and tweets into one sentence, then prompt GPT to summarize what people are saying about each ticker. Store the results in a final summary list for use.

Convert stock summaries into an email using a Python string template, substituting dynamic table rows and subreddits with data pulled from Yahoo and current prices.

Learn to send html emails from Python using the smtp lib with Gmail, configuring app passwords, mime multipart bodies, and starttls authentication.

Learn how to upload logs to aws s3 by creating a bucket, configuring IAM permissions, and using boto3 to store logs securely.

Thank you for purchasing this course and for feedback to improve videos. Apply the concepts to scraping Reddit and Twitter, using ChatGPT to summarize data, and send emails beyond stocks.