Reddit Read-Only Skill
Acceso sin autenticación (endpoints JSON públicos)
import requests
import time
# Reddit permite acceder a JSON añadiendo .json a cualquier URL
# No requiere API key para lectura básica
HEADERS = {"User-Agent": "MyAgent/1.0 (by u/yourusername)"}
def get_subreddit_posts(
subreddit: str,
sort: str = "hot", # hot, new, top, rising
limit: int = 25,
time_filter: str = "day" # hour, day, week, month, year, all (solo para "top")
) -> list:
"""Obtener posts de un subreddit"""
url = f"https://www.reddit.com/r/{subreddit}/{sort}.json"
params = {"limit": limit, "t": time_filter}
response = requests.get(url, headers=HEADERS, params=params)
response.raise_for_status()
posts = []
for post in response.json()["data"]["children"]:
d = post["data"]
posts.append({
"title": d["title"],
"author": d["author"],
"score": d["score"],
"upvote_ratio": d["upvote_ratio"],
"num_comments": d["num_comments"],
"url": d["url"],
"permalink": f"https://reddit.com{d['permalink']}",
"selftext": d.get("selftext", "")[:500],
"created_utc": d["created_utc"],
"flair": d.get("link_flair_text", ""),
})
return posts
Búsqueda en Reddit
def search_reddit(
query: str,
subreddit: str = None, # None = buscar en todo Reddit
sort: str = "relevance", # relevance, hot, new, top, comments
time_filter: str = "year",
limit: int = 25,
) -> list:
"""Buscar posts por palabras clave"""
if subreddit:
url = f"https://www.reddit.com/r/{subreddit}/search.json"
params = {"q": query, "restrict_sr": "1", "sort": sort, "t": time_filter, "limit": limit}
else:
url = "https://www.reddit.com/search.json"
params = {"q": query, "sort": sort, "t": time_filter, "limit": limit}
response = requests.get(url, headers=HEADERS, params=params)
return [
{
"title": p["data"]["title"],
"subreddit": p["data"]["subreddit"],
"score": p["data"]["score"],
"comments": p["data"]["num_comments"],
"permalink": f"https://reddit.com{p['data']['permalink']}",
"text": p["data"].get("selftext", "")[:300],
}
for p in response.json()["data"]["children"]
]
Obtener comentarios de un post
def get_post_comments(permalink: str, limit: int = 20) -> list:
"""Obtener comentarios top de un post"""
# Convertir permalink relativo → URL JSON
if not permalink.startswith("http"):
permalink = f"https://reddit.com{permalink}"
if not permalink.endswith(".json"):
permalink += ".json"
response = requests.get(permalink, headers=HEADERS, params={"limit": limit})
data = response.json()
if len(data) < 2:
return []
comments = []
for comment in data[1]["data"]["children"]:
if comment["kind"] == "t1": # Solo comentarios reales (no "more")
d = comment["data"]
comments.append({
"author": d["author"],
"body": d["body"][:500],
"score": d["score"],
"depth": d["depth"],
})
return comments
Monitorizar subreddits para research
def monitor_subreddits(
subreddits: list[str],
keyword: str,
min_score: int = 10
) -> list:
"""Encontrar posts relevantes en múltiples subreddits"""
relevant = []
for subreddit in subreddits:
posts = search_reddit(query=keyword, subreddit=subreddit)
for post in posts:
if post["score"] >= min_score:
relevant.append({**post, "subreddit": subreddit})
time.sleep(1) # Rate limit
return sorted(relevant, key=lambda x: x["score"], reverse=True)
# Ejemplo: monitorizar opiniones sobre ciberseguridad
cyber_posts = monitor_subreddits(
subreddits=["cybersecurity", "netsec", "sysadmin", "devops"],
keyword="ISO 27001 implementation",
min_score=50
)
def subreddit_sentiment_sample(subreddit: str, limit: int = 50) -> dict:
"""Análisis básico de sentimientos del top de un subreddit"""
posts = get_subreddit_posts(subreddit, sort="top", limit=limit, time_filter="week")
total_score = sum(p["score"] for p in posts)
avg_comments = sum(p["num_comments"] for p in posts) / len(posts) if posts else 0
# Palabras más frecuentes en títulos
from collections import Counter
import re
words = " ".join(p["title"] for p in posts).lower()
words = re.sub(r'[^\w\s]', '', words).split()
stopwords = {"the", "a", "an", "is", "in", "to", "and", "or", "of", "it", "i", "this", "that"}
word_freq = Counter(w for w in words if w not in stopwords and len(w) > 3)
return {
"subreddit": subreddit,
"posts_analyzed": len(posts),
"avg_score": round(total_score / len(posts), 1) if posts else 0,
"avg_comments": round(avg_comments, 1),
"top_words": dict(word_freq.most_common(10)),
"top_posts": posts[:5],
}
Buscar con la API oficial (PRAW)
# pip install praw
# Más potente pero requiere credenciales (gratis)
import praw
import os
reddit = praw.Reddit(
client_id=os.getenv("REDDIT_CLIENT_ID"),
client_secret=os.getenv("REDDIT_CLIENT_SECRET"),
user_agent="MyAgent/1.0"
)
# PRAW con autenticación — más capacidades
sub = reddit.subreddit("cybersecurity")
# Top posts de la semana
for post in sub.top(time_filter="week", limit=10):
print(f"{post.score:5d} | {post.title[:80]}")
# Buscar sobre un tema
for post in reddit.subreddit("all").search("GDPR compliance", sort="top", time_filter="year"):
print(f"r/{post.subreddit} | {post.score} pts | {post.title}")
Referencias
