Reddit Comments Scraper - Post and All Comments

Get a Reddit post and every comment on it. Start with post URLs. Each post comes first, then all of its comments as flat records. Each comment has the ID of its post, the ID of its parent, and its depth, so you can rebuild the whole thread. You do not need a Reddit account.

Read a few comments or the full thread of a post. Large threads work. Without a limit, comments go to the dataset while they load, so a thread with 15,000 comments needs no special setup.

What can you do with it?

• Sentiment and topic analysis. Feed comment text, scores, and dates into your models.
• Full discussion archives. Save every reply of a thread, also a thread with tens of thousands of comments.
• Brand and product research. Read what people say about a product in the comments of a launch post or a review thread.
• Community research. See which comments get the most votes, and how a discussion develops by depth.
• Training data. Build conversation datasets. Each reply points to its parent, so the tree is complete.
• Moderation review. Read a whole thread in one place, with the distinguished and stickied flags.
• Monitoring. Run the Actor on a schedule for a set of posts, and keep the comments with a new id.

What data does it extract?

Posts and comments are in the same dataset. Use the type field to tell them apart.

Data	When you get it
Post ID, title, text, link, domain, and permalink	Every post
Subreddit name, ID, type, and subscriber count	Every post
Post author, author flair, and Premium flag	Every post
Score, upvote ratio, comment count, crosspost count, and award count	Every post
Created time and edit state	Every post
Post flags: over 18, spoiler, stickied, locked, archived, quarantine, and more	Every post
Post flair with its colors	When the post has flair
Thumbnail, preview images, gallery images, and video	When the post has them
HTML text of the post	When depth is detailed
Comment ID, text, score, created time, edit state, and permalink	Every comment
Post ID, parent ID, and depth	Every comment
Comment author, author flair, Premium flag, and the post author flag	Every comment
Controversiality, award count, and hidden score flag	Every comment
Stickied, distinguished, and collapsed flags	Every comment
HTML text of the comment	When depth is detailed

Reddit does not have every field for every item. A field without data is null.

Quick start

1. Enter one or more Reddit post URLs in Post URLs or IDs.
2. Leave Max comments per post at 0 to get every comment.
3. Click Start. Download the results as JSON, CSV, Excel, or HTML.

The same input as JSON:

{
  "postUrls": ["https://www.reddit.com/r/MachineLearning/comments/1qo6sai/"]
}

The Output tab has a Posts table and a Comments table. In the API, read the dataset items and filter on type.

Examples by use case

Every comment of one post. This also works for a post with thousands of comments:

{
  "postUrls": ["https://www.reddit.com/r/MachineLearning/comments/1qo6sai/"],
  "maxCommentsPerPost": 0
}

The first 100 comments of several posts. One run reads all the posts. The dataset keeps the order of your list. Each post comes before its comments:

{
  "postUrls": [
    "https://www.reddit.com/r/MachineLearning/comments/1rc3nez/",
    "t3_1w10tax",
    "https://redd.it/1w1wt1s"
  ],
  "maxCommentsPerPost": 100
}

The best comments of a big thread. The top sort and a limit give you the highest scored top-level comments first, then their replies, up to the limit:

{
  "postUrls": ["https://www.reddit.com/r/MachineLearning/comments/1qo6sai/"],
  "commentSort": "top",
  "maxCommentsPerPost": 200
}

The newest comments. Use this to monitor a post that is still active:

{
  "postUrls": ["https://www.reddit.com/r/MachineLearning/comments/1qo6sai/"],
  "commentSort": "new",
  "maxCommentsPerPost": 100
}

HTML text. Set depth to detailed to get the HTML text of the post and of each comment, with links and formatting:

{
  "postUrls": ["https://www.reddit.com/r/MachineLearning/comments/1qo6sai/"],
  "depth": "detailed",
  "maxCommentsPerPost": 50
}

The post only. Set maxCommentsPerPost to 1 to get the post record and one comment. There is no setting for zero comments.

Choose the posts

Put one or more entries in postUrls. Each entry is one of these:

• A post URL. A link that has /comments/ and the post ID, such as https://www.reddit.com/r/MachineLearning/comments/1qo6sai/title/. The subreddit part of the URL is not used. Only the ID counts. A link to a single comment also gives the whole post.
• A short link. A redd.it link, such as https://redd.it/1qo6sai.
• A fullname. The t3_ prefix and the ID, such as t3_1qo6sai.
• A bare ID. The ID alone, such as 1qo6sai. It must have 4 letters or numbers, or more.

You can mix all four in one run. A post that you list two times is read once.

• Not found. A post that does not exist or is removed. The log shows Skipping post and the ID, and the other posts still run. If no post can be read, the run still ends with the status Succeeded and an empty dataset.
• Not a post. An entry that has none of the four forms. The log shows how many entries were skipped, and the other posts still run.
• No usable entry. If none of your entries is a post reference, the run fails with a message that names postUrls.

Choose the comments

How many comments

maxCommentsPerPost sets the most comments for each post. 0, the default, gets the whole thread.

With a limit, the Actor keeps the comments level by level. The top-level comments come first, in the order of the sort. Then come the replies to them, then the next level, until the limit is reached. This way every comment that you get has its parent in the dataset too.

Comment order

commentSort sets the sort that Reddit uses for the comment tree.

Value	Order
confidence	Best. This is the Reddit default.
top	Highest score first.
new	Newest first.
controversial	Most divided votes first.
old	Oldest first.
qa	The Q&A sort of Reddit.

The sort changes which comments you reach first. It also changes which comments you can reach in a very large thread. Read How many comments can I get? before you collect a thread with more than 10,000 comments.

Saving order

The dataset has the post first. Then come its comments. A parent comment is always saved before its replies.

Input reference

Field	Type	Default	Description
postUrls	string[]	required	Post URLs, redd.it links, t3_ fullnames, or bare post IDs. At least one entry.
maxCommentsPerPost	integer	0	Maximum comments for each post, with all replies counted. 0 gets every comment.
commentSort	string	confidence	confidence, top, new, controversial, old, or qa.
depth	string	basic	basic or detailed. detailed adds the HTML text of the post and of each comment.
proxyConfiguration	object	Apify Proxy on	Proxy settings managed by Apify.

Unknown input fields are ignored. Apify rejects a value of the wrong type before the run starts. Examples are an empty postUrls list, a negative maxCommentsPerPost, and a commentSort that is not in the list above.

Output

The dataset has two kinds of item. A post has type set to post. A comment has type set to comment. A comment is never inside a post, so a thread of any size fits in the dataset.

Each comment has three fields that give the thread:

Field	Meaning
linkId	The fullname of the post, such as t3_1qo6sai. It is the same for every comment of a post.
parentId	The fullname of the item above. It is the post for a top-level comment. It is another comment, such as t1_o1z5yr1, for a reply.
depth	The level of the comment. A top-level comment has 0. A reply to it has 1.

To rebuild the tree, group the comments by parentId.

Fields by topic

• Post. ID, title, text, link, domain, and permalink.
• Subreddit. Name, ID, type, and subscriber count.
• Author. Name, ID, flair, and the Premium flag.
• Votes and counts. Score, upvote ratio, comment count, crosspost count, and award count.
• Dates. The created time as a UTC number and as an ISO 8601 string, and the edit time.
• Flags. Over 18, spoiler, stickied, locked, archived, quarantine, and distinguished.
• Flair. Text, type, CSS class, and colors of the post flair.
• Media. Thumbnail, preview images, gallery images, and video with HLS and DASH links.
• Thread. The post ID, the parent ID, and the depth of a comment.
• Run. The UTC time at which the Actor saved the post.

Post example

Square brackets mark values removed from the documentation.

Comment example

This comment is a reply at depth 1. Its parentId is another comment.

Field notes

• id is the Reddit ID. Use it to remove the comments that you already have, for example when you run a monitor on a schedule.
• fullName has a prefix. t3_ is a post. t1_ is a comment.
• createdUtc is a Unix time in seconds. created is the same time in ISO 8601.
• selftext and body have the plain text. selftextHtml and bodyHtml are null unless depth is detailed.
• numComments is the count that Reddit shows for the post. It can be larger than the number of comments that the run saves. See the FAQ.
• isSubmitter is true when the comment author is the author of the post.
• scoreHidden is true when the subreddit hides the score of new comments.
• controversiality is null when Reddit does not give it.

FAQ

How many comments can I get?

The Actor saves every comment that Reddit shows for the post. With 0, there is no limit from the Actor.

Your count can be smaller than numComments, for two reasons:

• numComments counts the comments that moderators or users removed, and Reddit does not show them. In one test, a post had numComments of 100 and Reddit showed 83 comments.
• Reddit does not show all of a very large thread under one sort. In one test, a post had 18,787 comments in its count. The confidence sort gave about 14,000. Each other sort gave a different part, and the six sorts together gave about 17,000.

To reach more comments of a very large thread, run it again with another commentSort. Join the results on id to remove the duplicates.

Why did I get fewer comments than maxCommentsPerPost?

maxCommentsPerPost is an upper limit. The post can have fewer comments than the limit. See the answer above.

The log says "Reddit did not load N more comment(s)". What does it mean?

Reddit did not answer the request for some part of the thread. The Actor tries again several times and slows down before it gives up on that part. The comments that Reddit showed are in the dataset. Run the post again to get the rest.

How long does a run take?

The time depends on the shape of the thread. A thread of 15,289 comments took about 2 minutes with the default Apify Proxy. A thread with very long reply chains is slower, because each chain needs its own request. In our slowest test, the Actor saved about 8 comments each second.

A run stops at the run timeout in the run options. The comments that the Actor saved before the stop stay in the dataset.

Does it use a lot of memory?

No. A run of 15,289 comments used about 170 MB.

Do I need a proxy?

The Actor uses Apify Proxy by default. A proxy lets many requests run at the same time, and this makes large threads much faster. Without a proxy, large threads are slow.

How do I get only the new comments?

The Actor has no date filter. Run it on a schedule with commentSort set to new and a limit that is larger than the number of new comments between two runs. Remove the comments that you already have with the id field, or keep the comments with a created time after your last run.

Can I find posts by keyword, subreddit, or user?

No. This Actor needs the post URL or ID. To find posts by keyword, subreddit, or user, use Reddit Scraper.

Is this the same as the post mode of Reddit Scraper?

The input fields are the same: postUrls, commentSort, maxCommentsPerPost, depth, and proxyConfiguration. The output has the same fields. Fields that this Actor does not use, such as mode, are ignored, so an old input still runs. One default is different. maxCommentsPerPost is 0 here, so you get the whole thread unless you set a limit.

A feature or field that I need is missing. What can I do?

Tell us in the Issues tab. Describe what you need and give an example post.

Where can I report a problem?

Open an issue in the Issues tab. Include the run ID and the input, so that we can reproduce it.

Similar Actors

• Reddit Scraper. Reddit posts by keyword, subreddit, or user, subreddit discovery, and post comments.
• Yelp Reviews Scraper. Yelp reviews and business data from business URLs, aliases, or IDs.
• Trustpilot Reviews Scraper. Trustpilot business reviews, with company replies, from business URLs or domains.
• Google Maps Reviews Scraper. Google Maps reviews with place context, from place URLs or Place IDs.
• TripAdvisor Reviews. TripAdvisor reviews of restaurants, hotels, attractions, and cruises.
• Glassdoor Reviews Scraper. Glassdoor company reviews with ratings, pros and cons, and employer responses.
• Yellow Pages Reviews Scraper. Reviews of Yellow Pages businesses in the US, UK, and Canada.