Skip to content
/ yars Public
forked from datavorous/yars

Yet Another Reddit Scrapper (without API keys) | Scrap search results, posts and images from subreddits filtered by hot, new etc and bulk download any user's data.

License

Notifications You must be signed in to change notification settings

Nabby109/yars

This branch is 7 commits behind datavorous/yars:main.

Repository files navigation

YARS (Yet Another Reddit Scraper)

GitHub stars

YARS is a Python package designed to simplify the process of scraping Reddit for posts, comments, user data, and other media. The package also includes utility functions. It is built using Python and relies on the requests module for fetching data from Reddit’s public API. The scraper uses simple .json requests, avoiding the need for official Reddit API keys, making it lightweight and easy to use.

Features

  • Reddit Search: Search Reddit for posts using a keyword query.
  • Post Scraping: Scrape post details, including title, body, and comments.
  • User Data Scraping: Fetch recent activity (posts and comments) of a Reddit user.
  • Subreddit Posts Fetching: Retrieve posts from specific subreddits with flexible options for category and time filters.
  • Image Downloading: Download images from posts.
  • Results Display: Utilize Pygments for colorful display of JSON-formatted results.

Warning

Use with rotating proxies, or Reddit might gift you with an IP ban.
I could extract max 2552 posts at once from 'r/all' using this.
Here is a 7.1 MB JSON file containing the top 100 posts from 'r/nosleep', which included post titles, body text, all comments and their replies, post scores, time of upload etc.

Dependencies

  • requests
  • Pygments

Installation

  1. Clone the repository:

    git clone https://github.com/datavorous/YARS.git
    

    Navigate inside the src folder.

  2. Install uv (if not already installed):

    pip install uv
    
  3. Run the application:

    uv run example.py
    

    It'll setup the virtual env, install the necessary packages and run the example.py program.

Usage

We will use the following Python script to demonstrate the functionality of the scraper. The script includes:

  • Searching Reddit
  • Scraping post details
  • Fetching user data
  • Retrieving subreddit posts
  • Downloading images from posts

Code Overview

from yars import YARS
from utils import display_results, download_image

miner = YARS()

Step 1: Searching Reddit

The search_reddit method allows you to search Reddit using a query string. Here, we search for posts containing "OpenAI" and limit the results to 3 posts. The display_results function is used to present the results in a formatted way.

search_results = miner.search_reddit("OpenAI", limit=3)
display_results(search_results, "SEARCH")

Step 2: Scraping Post Details

Next, we scrape details of a specific Reddit post by passing its permalink. If the post details are successfully retrieved, they are displayed using display_results. Otherwise, an error message is printed.

permalink = "https://www.reddit.com/r/getdisciplined/comments/1frb5ib/what_single_health_test_or_practice_has/".split('reddit.com')[1]
post_details = miner.scrape_post_details(permalink)
if post_details:
    display_results(post_details, "POST DATA")
else:
    print("Failed to scrape post details.")

Step 3: Fetching User Data

We can also retrieve a Reddit user’s recent activity (posts and comments) using the scrape_user_data method. Here, we fetch data for the user iamsecb and limit the results to 2 items.

user_data = miner.scrape_user_data("iamsecb", limit=2)
display_results(user_data, "USER DATA")

Step 4: Fetching Subreddit Posts

The fetch_subreddit_posts method retrieves posts from a specified subreddit. In this example, we fetch 11 top posts from the "generative" subreddit from the past week.

subreddit_posts = miner.fetch_subreddit_posts("generative", limit=11, category="top", time_filter="week")
display_results(subreddit_posts, "EarthPorn SUBREDDIT New Posts")

Step 5: Downloading Images

For the posts retrieved from the subreddit, we try to download their associated images. The download_image function is used for this. If the post doesn't have an image_url, the thumbnail URL is used as a fallback.

for z in range(3):
    try:
        image_url = subreddit_posts[z]["image_url"]
    except:
        image_url = subreddit_posts[z]["thumbnail_url"]
    download_image(image_url)

Complete Code Example

from yars import YARS
from utils import display_results, download_image

miner = YARS()

# Search for posts related to "OpenAI"
search_results = miner.search_reddit("OpenAI", limit=3)
display_results(search_results, "SEARCH")

# Scrape post details using its permalink
permalink = "https://www.reddit.com/r/getdisciplined/comments/1frb5ib/what_single_health_test_or_practice_has/".split('reddit.com')[1]
post_details = miner.scrape_post_details(permalink)
if post_details:
    display_results(post_details, "POST DATA")
else:
    print("Failed to scrape post details.")

# Fetch recent activity of user "iamsecb"
user_data = miner.scrape_user_data("iamsecb", limit=2)
display_results(user_data, "USER DATA")

# Fetch top posts from the subreddit "generative" from the past week
subreddit_posts = miner.fetch_subreddit_posts("generative", limit=11, category="top", time_filter="week")
display_results(subreddit_posts, "EarthPorn SUBREDDIT New Posts")

# Download images from the fetched posts
for z in range(3):
    try:
        image_url = subreddit_posts[z]["image_url"]
    except:
        image_url = subreddit_posts[z]["thumbnail_url"]
    download_image(image_url)

You can now use these techniques to explore and scrape data from Reddit programmatically.

Contributing

Contributions are welcome! For feature requests, bug reports, or questions, please open an issue. If you would like to contribute code, please open a pull request with your changes.

Our Notable Contributors

About

Yet Another Reddit Scrapper (without API keys) | Scrap search results, posts and images from subreddits filtered by hot, new etc and bulk download any user's data.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%