👽 Reddit Subreddit Scraper – Posts, Comments & Engagement Data Extraction

The Reddit Subreddit Scraper pulls posts and comments from any subreddit into a structured dataset, complete with scores, upvote ratios, author metadata, flair, awards and timestamps. Point it at a single community or a list of hundreds, choose a sort order and a time window, and it returns the raw Reddit post objects — every field the platform exposes on a listing — ready for analysis.

Built for social listening, market research, sentiment analysis and content teams, this Reddit scraper handles the whole spectrum from a quick look at r/AskReddit to a bulk crawl driven by an uploaded CSV of communities. It supports all five Reddit feed orders — hot, new, top, rising and controversial — with a time filter for the ranked feeds, and it can optionally fetch the top comments beneath every post so you get the conversation, not just the headline.

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📊 What Data Can You Extract with This Reddit Scraper?

Each post record mirrors Reddit's own listing object, so the field set is broad. It organises into seven practical groups.

Category	Fields	What it tells you
🆔 Post identity	id, name, title, permalink, url, domain, subreddit, subreddit_id, subreddit_name_prefixed	The post's identifiers, its headline, where it lives and what it links to
📈 Engagement	score, ups, downs, upvote_ratio, num_comments, num_crossposts, view_count, likes	The full vote and discussion picture, including the ratio that reveals contested posts
👤 Author	author, author_fullname, author_premium, author_flair_text, author_flair_type, author_patreon_flair, author_is_blocked, is_submitter	Who posted, their flair, and their account status within the community
📝 Content	selftext, selftext_html, body, thumbnail, media, media_embed, secure_media, is_video, is_self, is_original_content, media_only	The text of the post or comment plus any attached media
🏷️ Flair & classification	link_flair_text, link_flair_richtext, link_flair_type, link_flair_background_color, link_flair_text_color, category, content_categories, discussion_type	How the community categorises the post — often the fastest way to segment a subreddit
🛡️ Moderation state	stickied, pinned, locked, archived, over_18, spoiler, quarantine, hidden, removed_by_category, removal_reason, mod_reason_title, distinguished, contest_mode, is_robot_indexable	Whether a post is promoted, restricted, removed or otherwise special
🏅 Awards & timing	all_awardings, total_awards_received, gilded, gildings, awarders, top_awarded_type, created, created_utc, edited	Award activity and precise creation and edit timestamps

The single most underrated field is upvote_ratio. Score alone conflates popularity with consensus — a post at +500 with a 0.55 ratio is a community argument, while +500 at 0.97 is settled agreement. For anyone doing sentiment or reputation work on Reddit data, that distinction changes the conclusion.

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🌟 Key Features of the Reddit Subreddit Scraper

Feature	Description
📚 Bulk subreddit input	Scrape one community via subreddit, many via the subreddits array, or hundreds by uploading a .txt/.csv through subredditsFile
🧾 Flexible file parsing	TXT files take one subreddit per line; CSV files auto-detect a subreddit column, so exports from other tools work as-is
🔀 All five feed orders	sort covers hot, new, top, rising and controversial, matching every ranking Reddit itself offers
🕰️ Time-windowed ranking	timeFilter narrows top and controversial feeds to the last hour, day, week, month, year or all time
💬 Optional comment fetching	includeComments adds the top comments beneath each post, returned as their own records with a _post_id linking them back
🎚️ Comment depth control	maxCommentsPerPost caps comment volume per post, using a single fast request for up to 500 and two for 501–1000
🧮 Volume control	maxPostsPerSubreddit limits how many posts each community contributes, with Reddit's own ceiling of roughly 1,000 per feed
📦 Complete raw objects	Posts arrive with Reddit's full field set rather than a trimmed subset, so nothing is lost before you decide what matters
🛡️ Automatic proxy rotation	Requests are routed through rotating proxies automatically, with no proxy configuration required from you

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🚀 Why Choose This Reddit Scraper?

No API credentials, no OAuth app. Reddit's official API requires registering an application, managing tokens and living inside a rate-limit budget. This Reddit scraper reads public listings directly, so you go from a subreddit name to a dataset without any developer onboarding.

Bulk input that matches how research actually works. Most social listening projects begin with a list of communities in a spreadsheet, not one name. Between the subreddits array and subredditsFile upload, you can hand the scraper a CSV of several hundred subreddits and let it work through them.

Posts and comments in one run. Turning on includeComments returns comment records alongside posts, each carrying _post_id, parent_id and depth. That means you can reconstruct entire threads and analyse replies in context rather than as detached snippets.

The complete Reddit object, not a summary. Fields like upvote_ratio, link_flair_text, total_awards_received, removed_by_category and is_original_content all survive into the dataset. Analyses that would be impossible with a five-field export — flair-based segmentation, moderation studies, award economics — are straightforward here.

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📥 Input

{
  "subreddit": "AskReddit",
  "maxPostsPerSubreddit": 100,
  "subreddits": ["dataisbeautiful", "webdev"],
  "sort": "hot",
  "timeFilter": "all",
  "includeComments": false,
  "maxCommentsPerPost": 1000
}

🔧 Reddit Scraper Input Fields

Field	Type	Required	Default	Description
subreddit	string	No	—	A single subreddit name or URL.
maxPostsPerSubreddit	integer	No	100	Maximum number of posts to scrape per subreddit (Reddit limits to ~1,000).
subreddits	array	No	[]	Add multiple subreddit names or URLs. Use 'Bulk edit' to paste a list, or upload a .txt/.csv file. Any format accepted.
subredditsFile	string	No	—	Upload a .txt or .csv file, or paste a URL. TXT: one subreddit per line. CSV: auto-detects 'subreddit' column.
sort	string	No	hot	How to sort posts in the feed. One of hot, new, top, rising, controversial.
timeFilter	string	No	all	Time range for 'top' and 'controversial' sort orders. Ignored for other sorts. One of hour, day, week, month, year, all.
includeComments	boolean	No	false	Fetch top comments for each post. Charged at $0.001 per comment.
maxCommentsPerPost	integer	No	1000	Maximum comments to fetch per post when comments are enabled. Uses a single fast request for up to 500, two requests for 501-1000.

💡 Input Examples

Top posts of the week from one community

{
  "subreddit": "dataisbeautiful",
  "sort": "top",
  "timeFilter": "week",
  "maxPostsPerSubreddit": 200
}

Multi-subreddit monitoring of new posts

{
  "subreddits": ["webdev", "javascript", "reactjs", "node"],
  "sort": "new",
  "maxPostsPerSubreddit": 50
}

Posts with their comment threads

{
  "subreddit": "AskReddit",
  "sort": "hot",
  "maxPostsPerSubreddit": 25,
  "includeComments": true,
  "maxCommentsPerPost": 300
}

---

📤 Output

{
  "approved_at_utc": null,
  "subreddit": "AskReddit",
  "selftext": "",
  "author_fullname": "t2_sz6c2b129",
  "location_lat": null,
  "saved": false,
  "mod_reason_title": null,
  "gilded": 0,
  "clicked": false,
  "title": "If it weren't for modern medicine, how would you have died?",
  "link_flair_richtext": [],
  "subreddit_name_prefixed": "r/AskReddit",
  "hidden": false,
  "pwls": 6,
  "link_flair_css_class": null,
  "downs": 0,
  "top_awarded_type": null,
  "hide_score": false,
  "name": "t3_1vkycb2",
  "quarantine": false,
  "link_flair_text_color": "dark",
  "upvote_ratio": 1
}

🧾 Reddit Post Output Fields

Field	Type	Description
id	string | null	Unique identifier of the item.
name	string | null	Name of the item (Reddit fullname, e.g. t3_…).
title	string | null	Title of the item.
author	string | null	Author of the item.
author_fullname	string | null	Name of the author fullname.
subreddit	string | null	Subreddit the item belongs to.
subreddit_id	string | null	Identifier of the subreddit.
subreddit_name_prefixed	string | null	Subreddit name prefixed of the item.
subreddit_subscribers	integer | null	Subreddit subscribers of the item.
subreddit_type	string | null	Subreddit type of the item.
selftext	string | null	Text of the selftext.
selftext_html	string | null	Selftext HTML of the item.
score	integer | null	Score assigned to the item.
ups	integer | null	Number of upvotes.
downs	integer | null	Number of downvotes.
upvote_ratio	integer | null	Upvote ratio of the item.
num_comments	integer | null	Num comments of the item.
num_crossposts	integer | null	Num crossposts of the item.
view_count	integer | null	Number of views.
permalink	string | null	Permanent link to the item.
url	string | null	Canonical URL of the scraped item.
domain	string | null	Domain name of the item.
thumbnail	string | null	Thumbnail image URL.
media, media_embed, secure_media, secure_media_embed	object | null	Media attached to or embedded in the post.
is_video, is_self, is_original_content, media_only, is_reddit_media_domain, is_meta	boolean | null	Content type flags.
link_flair_text, link_flair_richtext, link_flair_type, link_flair_css_class, link_flair_background_color, link_flair_text_color	mixed	Post flair and its styling.
author_flair_text, author_flair_richtext, author_flair_type, author_flair_css_class, author_flair_background_color, author_flair_text_color, author_flair_template_id	mixed	Author flair and its styling.
author_premium, author_patreon_flair, author_is_blocked, is_submitter	boolean | null	Author account attributes.
all_awardings, awarders, gildings, gilded, total_awards_received, top_awarded_type	mixed	Award activity on the post.
stickied, pinned, locked, archived, hidden, saved, clicked, visited, spoiler, over_18, quarantine, contest_mode, hide_score, send_replies, no_follow, is_crosspostable, can_gild, can_mod_post, allow_live_comments, is_robot_indexable, is_created_from_ads_ui	boolean | null	State and permission flags.
removed_by, removed_by_category, removal_reason, banned_by, banned_at_utc, approved_by, approved_at_utc, mod_note, mod_reason_by, mod_reason_title, mod_reports, user_reports, num_reports, report_reasons, distinguished	mixed	Moderation and reporting state.
category, content_categories, discussion_type, suggested_sort, treatment_tags, pwls, wls	mixed	Classification and ranking metadata.
location_name, location_lat, location_long	mixed	Location metadata, where Reddit supplies it.
created, created_utc, edited	mixed	Creation and edit timestamps.
websocket_url, likes	mixed	Live-update endpoint and viewer vote state.

🧾 Reddit Comment Output Fields

When includeComments is enabled, comment records are pushed alongside posts. They carry their own shape:

Field	Type	Description
_type	string | null	Type of the item — distinguishes comments from posts.
_post_id	string | null	Identifier of the post the comment belongs to.
_subreddit	string | null	Subreddit the item belongs to.
_status	string | null	Status of the item.
body	string | null	Body text of the item.
author	string | null	Author of the item.
authorId	string | null	Identifier of the author.
authorAccountType	string | null	Author account type of the item.
authorIsCakeDay	boolean | null	Whether author is cake day.
authorIcon, authorFlair	mixed	Author avatar and flair.
score	integer | null	Score assigned to the item.
depth	integer | null	Depth of the item within the thread.
parent_id / parentId	string | null	Identifier of the parent comment or post.
childCount	integer | null	Number of child comments.
createdAt, editedAt, created_utc	mixed	Comment timestamps.
isStickied, isLocked, isScoreHidden, isDeleted, isArchived, isRemoved, isInitiallyCollapsed, isCommercialCommunication	boolean | null	Comment state flags.
distinguishedAs, removedByCategory	mixed	Moderation markers.
languageCode, contentTypeHint	string | null	Detected language and content type hint.

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💻 How to Use the Reddit Subreddit Scraper (Step by Step)

Step 1: Choose how to supply your subreddits

There are three routes into the scraper and they can be combined. Use subreddit for a single community — a bare name like AskReddit or a full URL both work. Use the subreddits array when you have a handful, pasting them through the Bulk edit view. For anything larger, subredditsFile accepts an uploaded .txt or .csv, or a URL pointing at one; TXT files take one community per line and CSV files auto-detect a subreddit column, so exports from other research tools usually need no reformatting at all.

Step 2: Pick a sort order that matches your question

sort fundamentally changes what you get back. Use new for monitoring — it gives you a chronological stream and is the right choice for brand mentions or issue tracking. Use top for research into what a community values most. hot is Reddit's blended relevance ranking and gives a good sense of current attention. rising surfaces posts gaining traction quickly, which is what you want for trend spotting. controversial finds the posts where voting is genuinely split.

Step 3: Set the time window

timeFilter applies only to top and controversial, and it is ignored for the other sorts. The default of all gives you the highest-scoring posts in a subreddit's entire history — excellent for understanding a community's canon, but useless for tracking current sentiment. For anything time-sensitive, set week or month. Combining top with day is a reliable pattern for daily digest workflows.

Step 4: Control post volume

maxPostsPerSubreddit defaults to 100 and caps how much each community contributes. Reddit itself limits a single feed to roughly 1,000 posts, so that is the practical ceiling regardless of what you request. When crawling many subreddits, a lower per-subreddit cap gives you broader coverage for the same total volume — usually more useful than exhausting one community.

Step 5: Decide whether you need comments

Leave includeComments off when you only need post-level metrics; it keeps runs fast and datasets small. Turn it on when the analysis depends on what people actually said — sentiment work, question mining, support-issue discovery. maxCommentsPerPost then controls depth. The description notes that up to 500 comments uses a single fast request while 501–1000 uses two, so 500 is a natural efficiency boundary if you are tuning for speed.

Step 6: Run and inspect a sample

Start the actor and open the Dataset tab as results arrive. Check a few rows for the fields your analysis depends on: is selftext populated, or is the subreddit mostly link posts? Is link_flair_text in use, which would give you free segmentation? Is upvote_ratio varying meaningfully? A quick look at 25 rows tells you whether the run configuration is right before you scale up.

Step 7: Separate posts from comments and export

If comments are enabled, split the dataset on _type before analysis — posts and comments have different shapes and should live in different tables. Join comments back to posts on _post_id, and use parent_id with depth to rebuild reply trees. Export as CSV, JSON or XLSX, or schedule the run and pipe finished datasets into your warehouse via webhook.

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🔌 API Access & Integrations

Run the Reddit scraper and get dataset items back in the same request:

curl -X POST "https://api.apify.com/v2/acts/scrapers-hub~reddit-subreddit-posts-scrapers/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "subreddit": "AskReddit",
    "sort": "top",
    "timeFilter": "week",
    "maxPostsPerSubreddit": 50
  }'

The same run in Python:

from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN")

run = client.actor("scrapers-hub/reddit-subreddit-posts-scrapers").call(run_input={
    "subreddits": ["webdev", "javascript", "reactjs"],
    "sort": "new",
    "maxPostsPerSubreddit": 100,
    "includeComments": True,
    "maxCommentsPerPost": 200,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    if item.get("_type"):
        print("comment:", item["author"], item["score"])
    else:
        print("post:", item["title"], item["score"], item["upvote_ratio"])

Finished datasets connect to Zapier, Make, Google Sheets and Slack, and Apify webhooks can notify your own service the moment a Reddit scraping run completes.

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💡 Best Use Cases for Reddit Data

🗣️ Brand and product social listening

Monitor the subreddits where your category is discussed using sort set to new, then search title and selftext for your brand and competitor names. score, num_comments and upvote_ratio tell you whether a mention is a passing remark or a thread the community rallied around, which is what determines whether it needs a response.

📉 Sentiment and opinion analysis

Enable comments and run sentiment models over the body field, weighting each comment by score so that community-endorsed opinions count more than lone replies. depth lets you distinguish top-level reactions from deep argument threads, which usually carry very different tone.

🔥 Trend detection and content ideation

rising combined with a short timeFilter surfaces posts accelerating right now. Tracking which link_flair_text categories dominate rising posts over time is a reliable early signal of shifting community interest, and num_crossposts shows which ideas are spreading beyond their home subreddit.

🧪 Academic and market research

The raw Reddit object supports serious quantitative work: created_utc for time series, upvote_ratio for consensus measurement, total_awards_received and gilded for studying award economics, and removed_by_category plus distinguished for moderation research. Bulk subreddit input via subredditsFile makes large comparative studies practical.

🎯 Audience and community intelligence

subreddit_subscribers, author_flair_text and author_premium describe who a community is made of. Comparing posting patterns across dozens of subreddits, pulled in one run from a CSV, quickly shows where your target audience is genuinely active rather than merely present.

🛠️ Customer support and pain-point mining

Software and hardware subreddits are full of unfiltered problem reports. Filter posts where num_comments is high relative to score — a signal of unresolved discussion — then read the comment body text to extract recurring complaints, feature requests and workarounds your own support tickets never surface.

📰 Newsroom and editorial monitoring

Journalists use top with timeFilter set to day across a watchlist of subreddits to see what a community is talking about right now. permalink and url give citable links, author provides an attribution starting point, and over_18, spoiler and quarantine flag content that needs editorial care.

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⚙️ Tips for Better Reddit Scraping Results

• Remember the ~1,000 post ceiling. Reddit caps how deep a single feed goes, so requesting more from one subreddit will not help. Use several sort orders or time windows to reach different slices of the same community instead.
• Set timeFilter deliberately. It is silently ignored for hot, new and rising, which surprises people who set it and see no change. It only bites on top and controversial.
• Use flair as a free classifier. In well-moderated subreddits link_flair_text is a hand-curated category label. Grouping by it is faster and often more accurate than running your own topic model.
• Cap comments before scaling up. Comment volume grows much faster than post volume. Test with maxCommentsPerPost at 100 to gauge dataset size before committing to a large multi-subreddit run.
• Deduplicate on id, not title. Crossposts and recurring weekly threads share titles across communities; the post id is the only reliable unique key.
• Schedule new runs for monitoring. A frequent run against the new feed catches posts before they are deleted or removed, which a weekly top run would miss entirely.

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🛠️ Troubleshooting

Why did my Reddit scraper run return no posts? Check the subreddit name first — private, banned and quarantined communities return nothing publicly. Also confirm the combination of sort and timeFilter actually has results; top with timeFilter set to hour in a quiet subreddit can legitimately be empty.

I set timeFilter but the results did not change. timeFilter applies only to top and controversial. With hot, new or rising it is ignored by design, because those feeds are not ranked over a time window.

Why do I get fewer posts than maxPostsPerSubreddit? Reddit limits a feed to roughly 1,000 posts and many subreddits simply do not have that many in the selected window. Smaller or newer communities will return everything they have and stop.

Comments are missing even though includeComments is on. Posts with no replies produce no comment records, and locked, archived or heavily moderated threads may expose very few. Check num_comments on the parent post: if it is zero, there is nothing to fetch.

Some fields are null on every row. Reddit populates its listing object inconsistently. Fields such as view_count, likes, banned_by and approved_by are typically null for anonymous public reads, since they only carry values in an authenticated moderator context. Build your pipeline to tolerate nulls throughout.

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❓ Frequently Asked Questions About Reddit Scraping

Is scraping Reddit legal? This Reddit scraper reads only publicly visible subreddit listings — no login, no private communities, no direct messages. Collecting public data is broadly permissible in many jurisdictions, but you remain responsible for complying with Reddit's Terms of Service, the User Agreement and any laws that apply to your use of the data.

Do I need Reddit API credentials? No. The actor works from public Reddit endpoints, so there is no OAuth application to register, no client secret to manage and no developer rate-limit quota tied to your account.

How many posts can I scrape from a subreddit? Up to roughly 1,000 per feed, which is Reddit's own ceiling. maxPostsPerSubreddit defaults to 100 and lets you request less. To get more from a single community, run several jobs with different sort and timeFilter combinations.

Can I scrape multiple subreddits at once? Yes. Use the subreddits array for a handful, or upload a .txt or .csv through subredditsFile for large lists. CSV files auto-detect a subreddit column, and TXT files take one name per line.

Does the Reddit scraper collect comments? Yes, when includeComments is enabled. Comments come back as separate records identified by _type, linked to their post via _post_id, with parent_id and depth available for rebuilding the thread structure.

How many comments does it fetch per post? Up to maxCommentsPerPost, which defaults to 1000. The description notes that up to 500 comments is handled by a single fast request and 501–1000 uses two requests.

What is the difference between score and ups? score is the net figure Reddit displays. ups and downs are the underlying vote components, though Reddit fuzzes these publicly. For measuring agreement rather than raw popularity, upvote_ratio is the more informative field.

Can I scrape a subreddit by URL instead of by name? Yes. Both subreddit and the entries in subreddits accept a name or a full URL, and the actor normalises either form.

Which sort order should I use for monitoring? new. It returns posts chronologically, so a scheduled run captures everything published since the last one. hot and top re-rank continuously and will show you the same high performers repeatedly.

How do I get posts from the last week only? Set sort to top or controversial and timeFilter to week. For chronological coverage of the same period, use sort set to new and filter on created_utc after the run.

Can I scrape NSFW or private subreddits? NSFW posts are returned and flagged via over_18, so you can filter them in or out. Private and banned subreddits are not publicly accessible and cannot be scraped.

Why is view_count null? Reddit only exposes view counts to moderators of the community in question. For anonymous public reads it is null, along with several other moderator-only fields.

Can I export Reddit data to Excel or Google Sheets? Yes. Apify datasets export to CSV, XLSX, JSON and XML from the Console, and the dataset API can be read straight into Google Sheets or any BI tool that consumes CSV or JSON over HTTP.

How do I rebuild a comment thread from the dataset? Filter to comment records, group by _post_id, then link each comment to its parent using parent_id. depth gives you the nesting level directly, and childCount tells you how many replies a comment received.

How often should I run the Reddit scraper? For active monitoring of fast-moving subreddits, hourly or a few times a day against the new feed. For trend research and reporting, a daily top run with timeFilter set to day is usually the right cadence.

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🆘 Support & Feedback

If the Reddit scraper misbehaves — a field stops populating, a subreddit fails to resolve, a file upload is not parsed as expected — report it on the actor's Issues tab so it can be reproduced and fixed.

Need a custom build? Different output shaping, user-profile crawling, search-based collection, or a schema tailored to your analytics stack — email scraperhubapi@gmail.com and describe what you are trying to achieve.

If this Reddit scraper is useful in your research or monitoring work, a rating and a short review on the actor page helps other teams discover it and guides which improvements get built next.

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⚖️ Disclaimer

This Reddit scraper collects only publicly available content from public subreddit listings. It does not log into accounts, access private communities, read direct messages or bypass any authentication.

You are responsible for how the collected data is used, including compliance with Reddit's User Agreement and Terms of Service, applicable copyright in user-generated content, and any research-ethics requirements that apply to your institution or organisation.

Reddit posts and comments are written by identifiable individuals and pseudonymous usernames can constitute personal data. If you process fields such as author, author_fullname, body or selftext, you act as a data controller under the GDPR, the UK GDPR, the CCPA or the equivalent regime where you operate. That means establishing a lawful basis, minimising what you retain, aggregating or pseudonymising wherever the analysis allows, and honouring deletion requests. Content removed by a user or a moderator after collection should be removed from your own copies too.

This actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Reddit, Inc. To request removal of data collected through this actor, contact scraperhubapi@gmail.com with the relevant details and the request will be actioned promptly.