Vexaloom LabsUse TikTok Comment & Reply Thread Extractor with Python
Pull comments and reply threads from TikTok videos by URL or post ID, with pinned/hearted-by-author flags, commenter details, and like counts. No TikTok account or cookies required.
1. Choose the data you need
Review the published README for supported collection modes, examples, and limits. The recipe below uses the current published input definition.
2. Prepare a source-based input
This JSON contains published prefills and required-field defaults. Review every value for your task before running it; it is not a promise of successful collection.
{
"deepWalk": false,
"includeCommenterDetails": false,
"includeCommenterStats": false,
"includeReplies": true,
"includeVideoMetadata": false,
"maxCommenterLookups": 100,
"maxCommentsPerPost": 5,
"maxItems": 0,
"maxRepliesPerComment": 5,
"maxVideosPerProfile": 5,
"minLikes": 0,
"postUrls": [
"https://www.tiktok.com/@khaby.lame/video/7574844184952081686"
]
}
Download input.example.json and save your reviewed copy as input.json.
| Field | Type | Required | Description |
|---|---|---|---|
postUrls | array | optional | TikTok video or photo URLs to scrape comments from (e.g. https://www.tiktok.com/@user/video/123...). |
postIds | array | optional | Numeric TikTok video IDs (15-20 digits) as an alternative to URLs. |
profiles | array | optional | TikTok usernames or profile URLs. The actor scrapes comments from their newest videos, up to 'Max videos per profile'. |
maxVideosPerProfile | integer | optional | How many of each profile's newest videos to scrape comments from. |
maxCommentsPerPost | integer | optional | Maximum number of rows per video, counting replies when 'Include replies' is on. The actor walks the comment section as deep as TikTok serves it. |
includeReplies | boolean | optional | Fetch the reply thread under each root comment and emit each reply as its own row right after its parent. |
maxRepliesPerComment | integer | optional | Cap the replies fetched for any single root comment. Set to 0 for all replies (still bounded by 'Max comment rows per video'). |
maxItems | integer | optional | Global cap on the number of rows in the run (comments + replies). Set to 0 for no global cap. |
minLikes | integer | optional | Only keep comments and replies with at least this many likes. Comments below the threshold are skipped before their replies are fetched. |
includeVideoMetadata | boolean | optional | Add a 'video' object (caption, author, view/like/comment counts) to every row. |
includeCommenterDetails | boolean | optional | Add the commenter's region code and bio to user.region / user.bio, matched by comment ID from TikTok's app-style view of the page. |
includeCommenterStats | boolean | optional | Add exact follower, following, heart and video counts to user.* for every commenter. Each commenter's public profile is looked up once; private or banned accounts are omitted. |
maxCommenterLookups | integer | optional | Cap on how many commenters are enriched when 'Include commenter follower counts' is on. Set to 0 for no cap. |
deepWalk | boolean | optional | Read TikTok's app-style view of the comment list, which reaches far more comments on many videos, and restore image/sticker data from the standard view per comment. Off keeps the standard walk. |
3. Start an Actor run
Set APIFY_TOKEN in your environment. Python 3.10 or newer is sufficient; this recipe uses no third-party packages.
Execution may incur charges. Review current pricing on Apify. The request asks for a 120-second timeout and a charge limit; these settings are subject to Apify’s pricing and do not guarantee an all-inclusive spending cap.
import json
import os
import urllib.request
# Save the schema-derived example as input.json; review and edit it first.
with open("input.json", encoding="utf-8") as stream:
actor_input = json.load(stream)
token = os.environ["APIFY_TOKEN"]
request = urllib.request.Request(
"https://api.apify.com/v2/acts/vHUfV4HYEI8naCh9G/runs?timeout=120&maxTotalChargeUsd=0.50",
data=json.dumps(actor_input).encode("utf-8"),
headers={"Authorization": "Bearer " + token, "Content-Type": "application/json"},
method="POST",
)
# This starts a potentially billable run. Do not automatically retry this POST.
with urllib.request.urlopen(request, timeout=40) as response:
run = json.load(response)["data"]
print("Run ID:", run["id"])
print("Status:", run["status"])
# Inspect and download results in Apify Console once the run succeeds.
4. Inspect the actual results
Open the run in Apify Console and wait for a successful completion. Use the published output schema to locate results and the dataset schema to understand declared views. Missing or optional record fields must not be treated as guaranteed values.
One record per TikTok comment or reply, with text, like/reply counts, pinned/hearted flags, reply-thread links, and commenter details.
Questions before you run
Which inputs are required?
No top-level fields are marked required in the published schema. Conditional requirements can still apply; check the README.
What does this guide verify?
The fields, prefills, and schema links are rendered from the published build. This is a usage recipe, not a paid live extraction test. Source availability and collection results can vary.
What if the run request times out?
Check Apify Console before retrying. The first request may already have created a run. Do not automatically repeat a run-creation POST.
Generated from source build 5xR7gMTgKlauNkvWC and its README and schemas. Source changes regenerate this guide; no third-party editorial claims are inferred.