Reddit Scraping API with Python: Complete Guide

This guide shows how to use the FetchLayer Reddit API with Python. PRAW still works for developers who already have an approved Reddit OAuth app, but new developers generally cannot obtain approval. With FetchLayer, you don’t need Reddit credentials, OAuth setup, or a Reddit account—just an API key and the requests library.

Setup

1. Get a free API key (no credit card)
2. Install requests: pip install requests

API Client

import os
import requests

API_KEY = os.environ["FETCHLAYER_API_KEY"]
BASE_URL = "https://api.fetchlayer.dev/reddit"

def reddit(endpoint: str, **kwargs) -> dict:
    res = requests.post(
        f"{BASE_URL}/{endpoint}",
        headers={"Authorization": f"Bearer {API_KEY}"},
        json=kwargs,
    )
    res.raise_for_status()
    return res.json()

Search Reddit

data = reddit("search", query="best Python web framework", sort="top", limit=10)

for post in data["results"]:
    print(f"[{post['score']}] {post['title']} — r/{post['subreddit']}")

# Search within a specific subreddit
data = reddit("search", query="FastAPI vs Django", subreddit="Python", sort="relevance")

Get Subreddit Posts

data = reddit("community-posts", subreddit="Python", sort="top", time="week", limit=20)

for post in data["posts"]:
    print(f"[{post['score']}] {post['title']}")

Scrape a Post with Comments

thread = reddit(
    "post",
    url="https://www.reddit.com/r/Python/comments/abc123/some_post/",
    pages=2,
)

print(f"{thread['title']} — {len(thread['comments'])} comments")

for comment in thread["comments"][:5]:
    print(f"  {comment['author']}: {comment['body'][:100]}...")

Get User Profile

profile = reddit("user-profile", username="spez")

print(f"{profile['username']} — {profile['totalKarma']} karma — {profile['accountAge']}")

PRAW vs FetchLayer

If you’re coming from PRAW, here’s the comparison:

PRAW equivalent vs FetchLayer:

# PRAW (works only with an already-approved Reddit OAuth app)
import praw
reddit_client = praw.Reddit(client_id="...", client_secret="...", user_agent="...")
for post in reddit_client.subreddit("Python").hot(limit=10):
    print(post.title)

# FetchLayer (just an API key)
data = reddit("community-posts", subreddit="Python", sort="hot", limit=10)
for post in data["posts"]:
    print(post["title"])

Full Example: Sentiment Monitor

import os
import requests
from collections import Counter

API_KEY = os.environ["FETCHLAYER_API_KEY"]
BASE_URL = "https://api.fetchlayer.dev/reddit"

def reddit(endpoint: str, **kwargs) -> dict:
    res = requests.post(
        f"{BASE_URL}/{endpoint}",
        headers={"Authorization": f"Bearer {API_KEY}"},
        json=kwargs,
    )
    res.raise_for_status()
    return res.json()

def monitor_keyword(keyword: str, subreddits: list[str]):
    """Search for a keyword across subreddits and summarize results."""
    all_posts = []

    for sub in subreddits:
        data = reddit("search", query=keyword, subreddit=sub, sort="new", limit=10)
        for post in data.get("results", []):
            post["_subreddit"] = sub
            all_posts.append(post)

    # Sort by score
    all_posts.sort(key=lambda p: p["score"], reverse=True)

    # Summary
    subreddit_counts = Counter(p["_subreddit"] for p in all_posts)

    print(f"\nFound {len(all_posts)} posts for '{keyword}'")
    print(f"Top subreddits: {dict(subreddit_counts.most_common(5))}")
    print(f"\nTop 5 posts:")

    for post in all_posts[:5]:
        print(f"  [{post['score']}] {post['title']}")
        print(f"  r/{post['_subreddit']} — {post.get('numComments', 0)} comments")
        print(f"  {post['url']}\n")

if __name__ == "__main__":
    monitor_keyword(
        "your-product-name",
        ["startups", "SaaS", "webdev", "Python", "programming"]
    )

FETCHLAYER_API_KEY=sk-your-key python monitor.py

What’s Next

• Reddit API with Node.js
• Reddit API with TypeScript
• Reddit API with Bun
• Reddit API with Go
• How to Scrape Reddit in 2026 — all scraping methods
• FetchLayer API Reference