Comment threads are where Reddit's real signal lives. The headline is marketing copy, but the replies decide whether a claim holds up under scrutiny. This tutorial shows how to fetch a Reddit post and its full threaded comment tree with a single API call, then work with the flat, depth-annotated comment array to render, filter, or aggregate.
Prerequisites
- Python 3.8 or higher
- requests library
- A Scavio API key
- A Reddit post URL you want to analyze
Walkthrough
Step 1: Pick a Reddit post URL
Any canonical Reddit post URL works. The /comments/<id>/ path is enough.
Python
POST_URL = "https://www.reddit.com/r/Python/comments/1smb9du/fastapi_vs_django/"Step 2: Fetch the post and comments
POST to /api/v1/reddit/post with the URL. Response includes the post plus the flat comment array.
Python
import os, requests
r = requests.post(
"https://api.scavio.dev/api/v1/reddit/post",
headers={"Authorization": f"Bearer {os.environ['SCAVIO_API_KEY']}"},
json={"url": POST_URL},
timeout=30,
)
data = r.json()["data"]Step 3: Render comments with depth indentation
Each comment has a depth field starting at 0 for top-level replies. Multiply depth by two spaces for a readable tree.
Python
for c in data["comments"]:
indent = " " * c["depth"]
print(f"{indent}[{c['score']:>4}] u/{c['author']}: {c['body'][:100]}")Step 4: Aggregate by depth for quick analysis
Use depth to summarize top-level sentiment separately from deep replies.
Python
from collections import defaultdict
by_depth = defaultdict(list)
for c in data["comments"]:
by_depth[c["depth"]].append(c["score"])
for depth, scores in sorted(by_depth.items()):
print(f"depth {depth}: {len(scores)} comments, avg score {sum(scores)/len(scores):.1f}")Python Example
Python
import os, requests
API_KEY = os.environ["SCAVIO_API_KEY"]
def fetch_post(url: str):
r = requests.post(
"https://api.scavio.dev/api/v1/reddit/post",
headers={"Authorization": f"Bearer {API_KEY}"},
json={"url": url},
timeout=30,
)
r.raise_for_status()
return r.json()["data"]
data = fetch_post("https://www.reddit.com/r/Python/comments/1smb9du/")
print(data["post"]["title"])
for c in data["comments"][:20]:
print(" " * c["depth"] + f"u/{c['author']}: {c['body'][:80]}")JavaScript Example
JavaScript
const API_KEY = process.env.SCAVIO_API_KEY;
async function fetchPost(url) {
const r = await fetch("https://api.scavio.dev/api/v1/reddit/post", {
method: "POST",
headers: {
Authorization: `Bearer ${API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({ url }),
});
const { data } = await r.json();
return data;
}
const data = await fetchPost("https://www.reddit.com/r/Python/comments/1smb9du/");
console.log(data.post.title);
for (const c of data.comments.slice(0, 20)) {
console.log(" ".repeat(c.depth) + `u/${c.author}: ${c.body.slice(0, 80)}`);
}Expected Output
JSON
FastAPI vs Django in 2026 -- what the teams are actually using
u/senior_py: We moved to FastAPI for the API surface and kept Django for admin
u/django_dev: Django ORM is still unmatched for anything with relational depth.
u/another_dev: Agreed -- the admin is a force multiplier for internal tools.