$5/1000
results
Resolve YouTube handles, channel URLs, or UC IDs into channel profiles — subscribers, views, description, and branding fields for creator DBs.
Resolve YouTube handles, channel URLs, or UC IDs into channel profiles — subscribers, views, description, and branding fields for creator DBs.
Turn channel identifiers into structured creator records for your warehouse or CRM.
On Scrapy.io, Scraping Dino YouTube Channel Profiles by Scraping Dino is built for scraping youtube workflows — run from the Store, schedule recurring jobs, or POST to scrapingdino.p.scrapy.io from your stack.
@handles, channel URLs, or UC… IDsYouTube is the largest public video catalog — channel stats, upload cadence, comments, and recommendation graphs power creator research, competitive intelligence, and audience insight. A scraping youtube job on Scrapy.io hydrates channel URLs, video IDs, or search queries into structured JSON without maintaining your own headless browser farm.
Scraping Dino YouTube Channel Profiles supports batch inputs (channels, video IDs, or keywords) with per-target caps so nightly jobs stay within budget. Export to JSON, CSV, or Excel, or POST the same payload to scrapingdino.p.scrapy.io from your backend.
Scraping Dino YouTube tools chain naturally: resolve channels, list uploads or Shorts, scrape comments on top performers, or expand related videos for graph analysis — all with warehouse-friendly schemas.
This scraping youtube on Scrapy.io exports structured fields including:
For your first run, keep caps low (maxResults, maxReviews, etc.) until you validate row shape in the Output preview.
Teams discover Scraping Dino YouTube Channel Profiles while researching scraping youtube and related terms such as youtube scraper, scrape youtube, youtube scrape, youtube scraping. This listing is structured to answer common questions — including — with concrete Input and Output examples you can run on Scrapy.io without maintaining your own scraper infrastructure.
If you arrived from SEO or paid search, start with the Input JSON example below, run once on the free tier, then scale with schedules or the publisher API once row shape and cost look right.
Use this checklist before your first production run of Scraping Dino YouTube Channel Profiles:
maxResults, maxReviews, or equivalent limits so a full batch stays within budgetscrapingdino.p.scrapy.io/youtube-channel-scraper/v1/api or create a scheduled jobMost teams keep a "golden" input file in git for Scraping Dino YouTube Channel Profiles so staging and production use identical payloads. Update that file when you add keywords, targets, or communities — not the orchestration code around it.
Accepts @handles, channel URLs, or UC channel IDs.
Configure the run in the Scrapy.io input form or pass JSON to the publisher API.
{
"channels": [
"@GoogleDevelopers"
]
}| Field | Type | Required | Description |
|---|---|---|---|
channels | string[] | Yes | Channel IDs, @handles, or YouTube channel URLs |
Results appear in the Scrapy.io run Output tab. Channel rows and Errors.
Each successful row is designed for warehouse loads: stable column names, explicit error rows, and caps you control in the input form.
[
{
"type": "channel",
"channelId": "UCxxxxxxxx",
"title": "Example Channel",
"subscriberCount": 1250000,
"videoCount": 420,
"viewCount": 98000000,
"url": "https://www.youtube.com/@example"
}
]Download the full dataset as JSON, CSV, or Excel from the Output tab, or fetch results programmatically via the publisher API after the run completes.
keep subscriber and branding fields current
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Scraping Dino with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
monitor rival channels’ growth
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Scraping Dino with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
verify channel basics before outreach
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Scraping Dino with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
seed vertical creator directories
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Scraping Dino with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
Channel resolution framed for database sync, not browsing. Prefer Scraping Dino when channel cards must stay fresh on a schedule beside your other YouTube jobs.
Scraping Dino YouTube Channel Profiles is rarely the only step in a data workflow. Teams typically:
channelIdSee Related Scraping Dino tools below for same-publisher companions you can chain without leaving the Scrapy.io billing account.
Most production deployments follow the same shape:
postUrl, placeId, videoId, reviewId, …) plus scrape date where history mattersScraping Dino YouTube Channel Profiles separates successful rows from per-input errors, so staging logic can WHERE type != 'error' (or the equivalent filter for your tool) without failing the whole batch. Join across Scraping Dino tools on those stable keys to build multi-step datasets without re-scraping upstream steps.
Maintaining Reddit, Maps, or YouTube extractors in-house means handling rate limits, HTML or API changes, proxy rotation, and observability — work that rarely differentiates your product. Scraping Dino YouTube Channel Profiles on Scrapy.io outsources that operational burden: you supply inputs, Scrapy.io runs the job, and you pay per successful row.
Scraping Dino listings add warehouse-first documentation (clear caps, field lists, and pipeline patterns) so data teams can onboard without reading executor source code. When requirements change, update the input JSON or schedule — not your scraper fleet.
Scraping Dino YouTube Channel Profiles runs on Scrapy.io support multiple ways to get data out:
For production pipelines, most teams land JSON in object storage, normalize in dbt or Spark, and schedule recurring runs so the Store listing becomes just another data source — not a manual step.
Run Scraping Dino YouTube Channel Profiles once from the Store to validate inputs, then promote the same JSON payload to a scheduled job on Scrapy.io. Common patterns:
scrapingdino.p.scrapy.io on a queueScraping Dino tools use pay-per-result billing, so scheduled jobs stay predictable when you cap maxResults, maxReviews, or equivalent limits in the input form.
curl -X POST "https://scrapingdino.p.scrapy.io/youtube-channel-scraper/v1/api" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"channels": ["@GoogleDevelopers", "https://www.youtube.com/@NASA"]
}'Bulk runs via the scraper endpoint:
curl -X POST "https://scrapingdino.p.scrapy.io/youtube-channel-scraper/v1/scraper" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"channels": ["@GoogleDevelopers", "https://www.youtube.com/@NASA"]
}'Open the API tab on the Store listing for Python, JavaScript, cURL, OpenAPI, and MCP snippets.
Scraping Dino YouTube Channel Profiles is available through the Scrapy.io MCP server — configure your API key in Cursor, Claude Desktop, or another MCP client, then invoke the tool from agent workflows. This is useful for ad-hoc research ("scrape these ten URLs and summarize the Output") without writing boilerplate HTTP code.
For production, prefer the publisher API or scheduled runs; use MCP for exploratory analysis and internal tooling where a human or agent supplies inputs interactively. See the API tab on Scraping Dino YouTube Channel Profiles for MCP connection snippets.
| Tool | Best for |
|---|---|
| Scraping Dino YouTube Channel Shorts | Scraping Dino companion tool — overview |
| Scraping Dino YouTube Channel Videos | Scraping Dino companion tool — overview |
| Scraping Dino YouTube Comments | Scraping Dino companion tool — overview |
Batch creator lists from campaign spreadsheets
Refresh subscriber counts on a weekly schedule
Inspect per-row errors in the Errors output view instead of failing an entire batch
When Maps, Reddit, or YouTube batches repeat the same error, raise Issues on this Scraping Dino listing with your run ID and a sample input
Scraping Dino YouTube Channel Profiles collects publicly available data only. You are responsible for complying with platform terms, applicable laws, and data-protection regulations (including GDPR when personal data is involved). Consult your legal team for your specific use case.
$5.00 per 1,000 channels. You are charged only for successfully scraped rows. See Scrapy.io pricing for plan details.
Yes. Use webhooks, scheduled runs, or the publisher API to push data into your warehouse, CRM, or automation stack.
Yes. POST to https://scrapingdino.p.scrapy.io/youtube-channel-scraper/v1/api with your API key. See the API tab on the Store listing for ready-made snippets.
Yes. Configure the Scrapy.io MCP endpoint with your API key to query Scraping Dino YouTube Channel Profiles from AI assistants and agent workflows.
Scraping Dino maintains deep Maps, Reddit, and YouTube coverage — star the tool in Reviews if exports are landing in your warehouse and mention which dataset you rely on most.
Turn channel identifiers into structured creator records for your warehouse or CRM.
On Scrapy.io, Scraping Dino YouTube Channel Profiles by Scraping Dino is built for scraping youtube workflows — run from the Store, schedule recurring jobs, or POST to scrapingdino.p.scrapy.io from your stack.
@handles, channel URLs, or UC… IDsYouTube is the largest public video catalog — channel stats, upload cadence, comments, and recommendation graphs power creator research, competitive intelligence, and audience insight. A scraping youtube job on Scrapy.io hydrates channel URLs, video IDs, or search queries into structured JSON without maintaining your own headless browser farm.
Scraping Dino YouTube Channel Profiles supports batch inputs (channels, video IDs, or keywords) with per-target caps so nightly jobs stay within budget. Export to JSON, CSV, or Excel, or POST the same payload to scrapingdino.p.scrapy.io from your backend.
Scraping Dino YouTube tools chain naturally: resolve channels, list uploads or Shorts, scrape comments on top performers, or expand related videos for graph analysis — all with warehouse-friendly schemas.
This scraping youtube on Scrapy.io exports structured fields including:
For your first run, keep caps low (maxResults, maxReviews, etc.) until you validate row shape in the Output preview.
Teams discover Scraping Dino YouTube Channel Profiles while researching scraping youtube and related terms such as youtube scraper, scrape youtube, youtube scrape, youtube scraping. This listing is structured to answer common questions — including — with concrete Input and Output examples you can run on Scrapy.io without maintaining your own scraper infrastructure.
If you arrived from SEO or paid search, start with the Input JSON example below, run once on the free tier, then scale with schedules or the publisher API once row shape and cost look right.
Use this checklist before your first production run of Scraping Dino YouTube Channel Profiles:
maxResults, maxReviews, or equivalent limits so a full batch stays within budgetscrapingdino.p.scrapy.io/youtube-channel-scraper/v1/api or create a scheduled jobMost teams keep a "golden" input file in git for Scraping Dino YouTube Channel Profiles so staging and production use identical payloads. Update that file when you add keywords, targets, or communities — not the orchestration code around it.
Accepts @handles, channel URLs, or UC channel IDs.
Configure the run in the Scrapy.io input form or pass JSON to the publisher API.
{
"channels": [
"@GoogleDevelopers"
]
}| Field | Type | Required | Description |
|---|---|---|---|
channels | string[] | Yes | Channel IDs, @handles, or YouTube channel URLs |
Results appear in the Scrapy.io run Output tab. Channel rows and Errors.
Each successful row is designed for warehouse loads: stable column names, explicit error rows, and caps you control in the input form.
[
{
"type": "channel",
"channelId": "UCxxxxxxxx",
"title": "Example Channel",
"subscriberCount": 1250000,
"videoCount": 420,
"viewCount": 98000000,
"url": "https://www.youtube.com/@example"
}
]Download the full dataset as JSON, CSV, or Excel from the Output tab, or fetch results programmatically via the publisher API after the run completes.
keep subscriber and branding fields current
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Scraping Dino with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
monitor rival channels’ growth
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Scraping Dino with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
verify channel basics before outreach
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Scraping Dino with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
seed vertical creator directories
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Scraping Dino with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
Channel resolution framed for database sync, not browsing. Prefer Scraping Dino when channel cards must stay fresh on a schedule beside your other YouTube jobs.
Scraping Dino YouTube Channel Profiles is rarely the only step in a data workflow. Teams typically:
channelIdSee Related Scraping Dino tools below for same-publisher companions you can chain without leaving the Scrapy.io billing account.
Most production deployments follow the same shape:
postUrl, placeId, videoId, reviewId, …) plus scrape date where history mattersScraping Dino YouTube Channel Profiles separates successful rows from per-input errors, so staging logic can WHERE type != 'error' (or the equivalent filter for your tool) without failing the whole batch. Join across Scraping Dino tools on those stable keys to build multi-step datasets without re-scraping upstream steps.
Maintaining Reddit, Maps, or YouTube extractors in-house means handling rate limits, HTML or API changes, proxy rotation, and observability — work that rarely differentiates your product. Scraping Dino YouTube Channel Profiles on Scrapy.io outsources that operational burden: you supply inputs, Scrapy.io runs the job, and you pay per successful row.
Scraping Dino listings add warehouse-first documentation (clear caps, field lists, and pipeline patterns) so data teams can onboard without reading executor source code. When requirements change, update the input JSON or schedule — not your scraper fleet.
Scraping Dino YouTube Channel Profiles runs on Scrapy.io support multiple ways to get data out:
For production pipelines, most teams land JSON in object storage, normalize in dbt or Spark, and schedule recurring runs so the Store listing becomes just another data source — not a manual step.
Run Scraping Dino YouTube Channel Profiles once from the Store to validate inputs, then promote the same JSON payload to a scheduled job on Scrapy.io. Common patterns:
scrapingdino.p.scrapy.io on a queueScraping Dino tools use pay-per-result billing, so scheduled jobs stay predictable when you cap maxResults, maxReviews, or equivalent limits in the input form.
curl -X POST "https://scrapingdino.p.scrapy.io/youtube-channel-scraper/v1/api" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"channels": ["@GoogleDevelopers", "https://www.youtube.com/@NASA"]
}'Bulk runs via the scraper endpoint:
curl -X POST "https://scrapingdino.p.scrapy.io/youtube-channel-scraper/v1/scraper" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"channels": ["@GoogleDevelopers", "https://www.youtube.com/@NASA"]
}'Open the API tab on the Store listing for Python, JavaScript, cURL, OpenAPI, and MCP snippets.
Scraping Dino YouTube Channel Profiles is available through the Scrapy.io MCP server — configure your API key in Cursor, Claude Desktop, or another MCP client, then invoke the tool from agent workflows. This is useful for ad-hoc research ("scrape these ten URLs and summarize the Output") without writing boilerplate HTTP code.
For production, prefer the publisher API or scheduled runs; use MCP for exploratory analysis and internal tooling where a human or agent supplies inputs interactively. See the API tab on Scraping Dino YouTube Channel Profiles for MCP connection snippets.
| Tool | Best for |
|---|---|
| Scraping Dino YouTube Channel Shorts | Scraping Dino companion tool — overview |
| Scraping Dino YouTube Channel Videos | Scraping Dino companion tool — overview |
| Scraping Dino YouTube Comments | Scraping Dino companion tool — overview |
Batch creator lists from campaign spreadsheets
Refresh subscriber counts on a weekly schedule
Inspect per-row errors in the Errors output view instead of failing an entire batch
When Maps, Reddit, or YouTube batches repeat the same error, raise Issues on this Scraping Dino listing with your run ID and a sample input
Scraping Dino YouTube Channel Profiles collects publicly available data only. You are responsible for complying with platform terms, applicable laws, and data-protection regulations (including GDPR when personal data is involved). Consult your legal team for your specific use case.
$5.00 per 1,000 channels. You are charged only for successfully scraped rows. See Scrapy.io pricing for plan details.
Yes. Use webhooks, scheduled runs, or the publisher API to push data into your warehouse, CRM, or automation stack.
Yes. POST to https://scrapingdino.p.scrapy.io/youtube-channel-scraper/v1/api with your API key. See the API tab on the Store listing for ready-made snippets.
Yes. Configure the Scrapy.io MCP endpoint with your API key to query Scraping Dino YouTube Channel Profiles from AI assistants and agent workflows.
Scraping Dino maintains deep Maps, Reddit, and YouTube coverage — star the tool in Reviews if exports are landing in your warehouse and mention which dataset you rely on most.
