Reddit Scraper | All In One | Cheapest ($0.99/1K Result)

Reddit Scraper 🤖

Reddit Scraper turns any keyword, community, or Reddit link into a clean, ready-to-use dataset of posts and comments. Whether you are a marketer tracking what people say about your brand, a researcher studying online conversations, or a business owner looking for real customer feedback, this Reddit Scraper does the collecting for you — no coding, no account setup, and no waiting.

Point it at what you care about, press Run, and download the results as a spreadsheet or JSON file. Because no developer account or API key is needed, the Reddit Scraper works as a simple Reddit API alternative for anyone who just wants the data.

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🚀 Why Choose This Reddit Scraper?

Feature	What It Means for You
✅ No Account or API Key Needed	A true Reddit API alternative — skip developer registration and start collecting right away
✅ Three Ways to Search	Works as a Reddit search scraper, a subreddit scraper, or a link-based Reddit post scraper, all in one run
✅ Posts and Comments Together	The built-in Reddit comment scraper captures full discussions, not just the original post
✅ Automatic Insights	Optional Reddit sentiment analysis and topic labels tell you the mood and subject of every post
✅ Reliable Results	Handles interruptions and retries on its own, so long runs finish without babysitting
✅ Spreadsheet-Ready	Rich, well-labeled columns let you export Reddit data to CSV, Excel, or JSON in one click

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🔑 Key Features of the Reddit Scraper

• 🔎 Search All of Reddit by Keyword — enter any words or phrases and the Reddit Scraper finds matching discussions site-wide, acting as a complete Reddit search scraper
• 📂 Focus on One Community — aim the subreddit scraper at r/food, r/stocks, or any community, with optional keywords to narrow it further
• 🔗 Start From Your Own Links — already have the threads you want? Paste them in and the Reddit post scraper collects exactly those
• 💬 Full Discussion Capture — the Reddit comment scraper follows replies deep into each thread and saves them as their own rows
• 📊 Popularity Signals — see how fast a post is gaining upvotes and comments, and which threads count as high-engagement
• 😀 Mood Detection — switch on Reddit sentiment analysis to label every post and comment as positive, negative, neutral, mixed, or uncertain
• 🏷️ Automatic Topic Labels — posts are sorted into categories like Finance, Gaming, Politics, or Technology, which speeds up Reddit keyword research
• 📅 Exact Date Ranges — set separate date windows for posts and comments so you can scrape Reddit data for one specific week, month, or single day
• 🌐 Wider Coverage Option — collects more unique posts per search than a single ordinary search would return
• 🛡️ Adult Content Filter — keep NSFW posts in or out, so your Reddit data extraction stays appropriate for your audience
• 🎯 Precision Matching — require every keyword, or the exact phrase, when close-enough results are not good enough
• 🔌 Send Results Onward — optionally hand a run summary to tools you already use, such as Slack, Notion, or GitHub

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📝 Input

You can set everything up with the simple form in the Apify Console. If you prefer to paste settings directly, here is what a full configuration looks like:

{
  "queries": ["Cheesecake", "Swimming Pool"],
  "sort": "relevance",
  "timeframe": "all",
  "subredditName": "food",
  "subredditKeywords": ["recipe"],
  "subredditSort": "top",
  "subredditTimeframe": "year",
  "urls": [
    "https://www.reddit.com/r/food/comments/abc123/homemade_cheesecake/"
  ],
  "scrapeComments": true,
  "maxComments": 25,
  "dateFrom": "2026-01-01",
  "dateTo": "2026-06-30",
  "includeNsfw": false,
  "strictSearch": false,
  "strictTokenFilter": false,
  "maxPosts": 100,
  "maximize_coverage": true,
  "sentiment_analysis": true,
  "content_analysis": true
}

Input Settings

Setting	Type	Default	What It Does
queries	list	—	Words or phrases to search across all of Reddit. Each one runs its own Reddit search scraper pass.
sort	text	relevance	How results are ranked: relevance, hot, top, new, or comments.
timeframe	text	all	How far back to look: all, year, month, week, day, or hour.
subredditName	text	—	The community to focus on, written as food or r/food.
subredditKeywords	list	—	Optional words to search inside that community. Leave empty to browse its posts.
subredditSort	text	relevance	How results are ranked inside the chosen community.
subredditTimeframe	text	all	How far back to look inside the chosen community.
urls	list	—	Reddit post links you want collected directly.
scrapeComments	yes/no	false	Switch on the Reddit comment scraper to gather replies for every post.
maxComments	number	10	The most comments to collect from each post.
dateFrom / dateTo	text	—	Keep only posts published inside this date range (YYYY-MM-DD).
commentDateFrom / commentDateTo	text	—	A separate date range applied to comments only.
forceSortNewForTimeFilteredRuns	yes/no	false	Favor the newest results whenever a date range is set, so recent threads are not missed.
includeNsfw	yes/no	false	Include posts marked as adult or 18+.
strictSearch	yes/no	false	Keep only posts where every one of your keywords appears.
strictTokenFilter	yes/no	false	Keep only posts containing your exact phrase.
maxPosts	number	10	The most posts to collect for each keyword, community, or link.
maximize_coverage	yes/no	false	Work harder to find more unique posts for each search.
sentiment_analysis	yes/no	false	Add Reddit sentiment analysis scores and mood labels to posts and comments.
content_analysis	yes/no	false	Add a topic label (Finance, Sports, Gaming, Politics, and more) to each post.
mcpConnectors	list	—	Optional: tools that should receive a summary when the run finishes.

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📦 Output

Every row in your results is either a post ("kind": "post") or a comment ("kind": "comment"), so they are easy to separate, sort, and export Reddit data to CSV. Here is one post row:

[
  {
    "kind": "post",
    "query": "Cheesecake",
    "id": "1k9x2ab",
    "title": "Homemade New York cheesecake, first attempt",
    "body": "Used a water bath and let it cool in the oven for an hour...",
    "author": "bakerdave_91",
    "score": 4821,
    "upvote_ratio": 0.97,
    "num_comments": 214,
    "subreddit": "food",
    "subreddit_name_prefixed": "r/food",
    "subreddit_subscribers": 25400000,
    "created_utc": "2026-04-11T09:04:27.000Z",
    "url": "https://www.reddit.com/r/food/comments/1k9x2ab/homemade_new_york_cheesecake/",
    "permalink": "/r/food/comments/1k9x2ab/homemade_new_york_cheesecake/",
    "old_reddit_url": "https://old.reddit.com/r/food/comments/1k9x2ab/homemade_new_york_cheesecake/",
    "flair": "Homemade",
    "media_type": "image",
    "has_media": true,
    "gallery_images": [],
    "gallery_count": 0,
    "domain": "i.redd.it",
    "over_18": false,
    "is_self": false,
    "locked": false,
    "archived": false,
    "age_hours": 36.5,
    "score_per_hour": 132.0822,
    "comments_per_hour": 5.863,
    "engagement_total": 5035,
    "comment_to_score_ratio": 0.0444,
    "is_high_engagement": true,
    "title_length": 41,
    "body_length": 188,
    "word_count": 38,
    "content_flags": [],
    "is_deleted_or_removed": false,
    "total_awards_received": 3,
    "num_crossposts": 1,
    "sentiment_score": 7,
    "sentiment_score_normalized": 0.58,
    "sentiment_confidence": 0.71,
    "sentiment_label": "positive",
    "content_category_label": "Desserts and Baking",
    "content_category_path": ["Food & Drink", "Desserts and Baking"],
    "content_category_confidence": 0.86,
    "retrieved_at": "2026-04-12T21:33:04.512Z"
  }
]

Post Columns

Column	Type	What It Contains
kind	text	post or comment — lets you split the two apart in one step
query	text	The keyword, community, or link that produced this row
id	text	Reddit's own ID for the post
title / body	text	The post headline and its written content
body_html	text	The same content with its original formatting
author	text	Who posted it (shows [deleted] if the account is gone)
author_flair_text	text	The badge or tag next to the author's name, if any
score	number	Net upvotes at the moment of collection
upvote_ratio	number	Share of votes that were upvotes — a quick quality signal
num_comments	number	How many comments the post has
subreddit	text	The community the post belongs to
subreddit_subscribers	number	How many members that community has
created_utc	text	When the post was published
url / permalink	text	The full link and the short Reddit path
old_reddit_url	text	The same thread on the classic Reddit layout
flair	text	The category tag the community applied
media_type	text	text, link, image, video, gif, or gallery
has_media	yes/no	Whether the post includes a picture, video, or gallery
gallery_images	list	Every image in a gallery post, with captions and sizes
media_assets	list	Direct links to the attached images and videos
age_hours	number	How old the post was when collected
score_per_hour	number	How quickly it is gaining upvotes — great for spotting trends
comments_per_hour	number	How quickly the discussion is growing
engagement_total	number	Upvotes and comments added together
comment_to_score_ratio	number	How much debate a post attracts relative to approval
is_high_engagement	yes/no	Flags standout posts automatically
title_length / body_length / word_count	number	Length measures, handy for Reddit keyword research
content_flags	list	Any of nsfw, spoiler, deleted, or locked
sentiment_score	number	Mood strength, when sentiment is switched on
sentiment_label	text	positive, negative, neutral, mixed, or uncertain
content_category_label	text	Topic label such as Investing or Gaming
content_category_path	list	The full topic path, from broad to specific
retrieved_at	text	When this row was collected

Comment Columns

Column	Type	What It Contains
kind	text	Always comment for reply rows
id / body	text	The comment's ID and its text
author	text	Who wrote the comment
score	number	The comment's upvotes at collection time
postId / postUrl	text	Which post it belongs to — use this to match comments back to posts
parentId	text	The exact post or comment it replies to
parent_kind	text	Whether it replies to a post or another comment
root_comment_id	text	The comment that started this branch of the conversation
depth	number	How deep in the reply chain it sits
is_submitter	yes/no	true when the original poster wrote this reply
controversiality	number	Reddit's own signal for divisive comments
collapsed / collapsed_reason	yes/no, text	Whether Reddit hid the comment by default, and why
stickied / distinguished	yes/no, text	Pinned or moderator-marked comments
sentiment_label	text	The comment's mood, when sentiment is switched on
post_content_category_label	text	The topic label of the parent post
age_hours / word_count	number	How old the comment is and how long it is

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🚀 How to Use the Reddit Scraper (Step by Step)

1. Sign in — go to console.apify.com and open the Actors tab.
2. Open the actor — search for Reddit Scraper and click its card.
3. Choose what to collect — add keywords, a community name, or Reddit links. You can use all three at once.
4. Add comments if you want them — switch on Include Comments from Each Post and choose how many per post.
5. Narrow it down — set your date range, decide on adult content, and turn on precision matching if needed.
6. Set your size — pick how many posts to collect. Start small to check the results, then increase it.
7. Turn on extras — enable mood detection, topic labels, and wider coverage.
8. Press Run — the progress updates live while it works.
9. Download — open the OUTPUT tab and save your results as CSV, Excel, JSON, XML, or RSS.

That is all it takes. No coding, no setup, and a finished Reddit dataset in minutes.

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🎯 What Makes This Reddit Scraper Different

• 🧠 Runs Unattended — the Reddit Scraper recovers from interruptions by itself, so big collections finish without you watching
• 🌐 Finds More Than a Normal Search — the wider-coverage option pulls in unique posts that a single ordinary search would never show you
• 🧹 No Duplicates — the same thread never appears twice, so your Reddit data extraction stays clean and countable
• 📈 Trend Signals Built In — speed-of-growth columns help you catch a rising conversation while it is still rising
• 🗂️ Insights Included — mood and topic labels are generated for you at no extra cost and with no third-party services involved
• 🔁 Combine Everything — keywords, a community, and specific links can all run together in a single job
• 📝 Clear Progress Updates — you can always see what the Reddit Scraper is working on and how far along it is

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💡 Best Use Cases for the Reddit Scraper

• 📊 Market and Audience Research — use the subreddit scraper to learn how a specific community really talks about your product category
• 🗣️ Brand and Reputation Monitoring — run the Reddit Scraper on your brand name regularly and watch whether the mood improves or declines
• 🔬 Academic and Social Research — scrape Reddit data for exact date ranges to build datasets you can repeat and cite
• 💰 Investment and Market Sentiment — follow communities like r/stocks with mood detection switched on
• 🎯 Finding Customers and Demand — spot the threads where people describe the exact problem your product solves
• 🔑 Content and SEO Planning — use real post titles and questions to guide your Reddit keyword research and content calendar
• 🛠️ Product Feedback — gather honest, unfiltered opinions about your product or your competitors
• 📥 Reporting and Dashboards — export Reddit data to CSV and drop it straight into a spreadsheet or reporting tool

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🔧 Good to Know

• What you can start from
  • Keywords and phrases, searched across all of Reddit
  • A community name, written as food or r/food
  • Direct links to Reddit posts
• How deep it goes
  • Comment threads are followed up to 15 levels of replies
• Download formats
  • CSV, Excel, JSON, XML, and RSS
• Recommended memory
  • 4 GB gives the smoothest experience on larger jobs
• Please note
  • ❌ Private, quarantined, and banned communities cannot be collected
  • ❌ Deleted or removed content is marked with is_deleted_or_removed rather than recovered
  • ℹ️ Mood and topic labels are quick automatic estimates — excellent for sorting and filtering, but not a replacement for expert human review

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🤝 Support & Feature Requests

Need a hand, or have an idea for the Reddit Scraper?

• 💡 Feature Requests — want user profile collection, scheduled runs, or custom topic categories? Just ask.
• 📧 Contact — email us at scraperhubapi@gmail.com.

Your feedback shapes what we build next and helps keep this the most useful Reddit Scraper on the Apify Store.

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Start today with the most complete Reddit Scraper available — no account, no coding, no limits.

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Disclaimer

This Reddit Scraper collects information only from publicly available sources. It does not access private communities, password-protected content, or any private user information. You are responsible for following applicable data privacy laws and for respecting Reddit's terms of service and content policies.

For data removal requests, please contact scraperhubapi@gmail.com. Always use these tools responsibly, ethically, and for legitimate purposes only.