Reddit Sentiment Scrape & Visualization

I’m putting together a small sentiment-analysis project and need help pulling a sample of at least 100 Reddit posts, analysing their tone, and presenting the results visually. The content source is Reddit (my chosen social-media platform), so the scraper must be tuned for the site’s structure and its robots.txt rules. Please build the crawler in Python—either with requests + BeautifulSoup or with Scrapy—and include polite delays so we never hammer Reddit’s servers.

Once the texts are collected, run sentiment classification on each entry with NLTK or TextBlob. A simple positive / neutral / negative labelling scheme is fine, as long as every row in the output data has its corresponding score or label.

Finally, create a visual summary of the findings. A bar or pie chart in matplotlib or seaborn that shows the distribution of each sentiment category is exactly what I’m after. Save that chart to a .jpg file as proof the code works.

Deliverables
• Jupyter Notebook or standalone .py script containing the scraper, sentiment pipeline, and plotting code
• CSV file with the raw posts and their sentiment labels
• JPG (or PNG) of the sentiment chart

I’ll test the notebook/script by running it on my end, so please keep any API keys or credentials abstracted out and document where I should place them. Clear, concise comments in the code will be appreciated.