$0.5/1000
results
Extract subreddit metadata — about info, rules, similar communities, and optional comments — for community due diligence and maps.
Extract subreddit metadata — about info, rules, similar communities, and optional comments — for community due diligence and maps.
One run that profiles a community: who it is, how it’s moderated, and what sits nearby.
On Scrapy.io, Scraping Dino Subreddit Intelligence by Scraping Dino is built for reddit subreddit scraper workflows — run from the Store, schedule recurring jobs, or POST to scrapingdino.p.scrapy.io from your stack.
maxResultsReddit is one of the largest public conversation graphs on the web — product feedback, competitor mentions, support pain, and niche community signals all surface there before they hit traditional media. A reddit subreddit scraper workflow on Scrapy.io lets analysts and engineers pull that signal into the same warehouse tables as CRM, ads, and support data instead of copying links by hand.
Scraping Dino Subreddit Intelligence is built for repeatable extraction: you define inputs once (URLs, queries, usernames, or subreddit names), cap volume with maxResults, and export JSON or CSV on a schedule. That matters when your use case is a daily brand monitor, a research panel, or an enrichment step in a larger ETL — not a one-off screenshot.
Scraping Dino listings share a consistent column philosophy across Reddit tools: stable field names, explicit error rows, and pricing per successful result so finance can forecast spend as you add communities or keywords.
This reddit subreddit scraper 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 Subreddit Intelligence while researching reddit subreddit scraper and related terms such as . 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 Subreddit Intelligence:
maxResults, maxReviews, or equivalent limits so a full batch stays within budgetscrapingdino.p.scrapy.io/reddit-subreddit-scraper/v1/api or create a scheduled jobMost teams keep a "golden" input file in git for Scraping Dino Subreddit Intelligence so staging and production use identical payloads. Update that file when you add keywords, targets, or communities — not the orchestration code around it.
Profile one or more communities in a single run. Toggle rules, similar subs, and optional comment samples.
Configure the run in the Scrapy.io input form or pass JSON to the publisher API.
{
"subreddits": [
"askreddit",
"python"
],
"maxResults": 50
}| Field | Type | Required | Description |
|---|---|---|---|
subreddits | string[] | Yes | List of subreddit names to scrape. Enter one per line — plain names or r/name are accepted |
maxResults | integer | No | Maximum number of comments to fetch per subreddit. Only used when Comments is enabled |
Results appear in the Scrapy.io run Output tab. Results, Subreddit Details, Rules, Similar, Comments, and Errors views.
Each successful row is designed for warehouse loads: stable column names, explicit error rows, and caps you control in the input form.
[
{
"type": "info",
"subreddit": "python",
"title": "Python",
"description": "News about the programming language Python.",
"subscribers": 1400000,
"nsfw": false,
"url": "https://www.reddit.com/r/python/"
}
]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.
check rules and NSFW flags before posting or partnering
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.
expand from seed subs into similar communities
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.
document community policies for brand safety reviews
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.
give PMs a structured brief on target communities
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.
Bundles community context into one pipeline-friendly export instead of forcing separate manual lookups. Prefer Scraping Dino when the goal is a complete community dossier in your DB.
Scraping Dino Subreddit Intelligence is rarely the only step in a data workflow. Teams typically:
similar subreddit names into Reddit Popular Subreddits Scraper seed listsSee 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 Subreddit Intelligence 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 Subreddit Intelligence 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 Subreddit Intelligence 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 Subreddit Intelligence 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/reddit-subreddit-scraper/v1/api" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"subreddits": ["AskReddit", "python"],
"includeRules": true,
"includeSimilar": true,
"includeComments": false
}'Bulk runs via the scraper endpoint:
curl -X POST "https://scrapingdino.p.scrapy.io/reddit-subreddit-scraper/v1/scraper" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"subreddits": ["AskReddit", "python"],
"includeRules": true,
"includeSimilar": true,
"includeComments": false
}'Open the API tab on the Store listing for Python, JavaScript, cURL, OpenAPI, and MCP snippets.
Scraping Dino Subreddit Intelligence 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 Subreddit Intelligence for MCP connection snippets.
| Tool | Best for |
|---|---|
| Scraping Dino Reddit Comment Tree | Scraping Dino companion tool — overview |
| Scraping Dino Reddit Popular Posts | Scraping Dino companion tool — overview |
| Scraping Dino Reddit Popular Subreddits | Scraping Dino companion tool — overview |
Disable includeComments on wide discovery runs to save rows and cost
Store rules text for compliance audits with a scrape timestamp
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
maxResults — not a full feed exportScraping Dino Subreddit Intelligence 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.
$0.50 per 1,000 rows. 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/reddit-subreddit-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 Subreddit Intelligence 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.
One run that profiles a community: who it is, how it’s moderated, and what sits nearby.
On Scrapy.io, Scraping Dino Subreddit Intelligence by Scraping Dino is built for reddit subreddit scraper workflows — run from the Store, schedule recurring jobs, or POST to scrapingdino.p.scrapy.io from your stack.
maxResultsReddit is one of the largest public conversation graphs on the web — product feedback, competitor mentions, support pain, and niche community signals all surface there before they hit traditional media. A reddit subreddit scraper workflow on Scrapy.io lets analysts and engineers pull that signal into the same warehouse tables as CRM, ads, and support data instead of copying links by hand.
Scraping Dino Subreddit Intelligence is built for repeatable extraction: you define inputs once (URLs, queries, usernames, or subreddit names), cap volume with maxResults, and export JSON or CSV on a schedule. That matters when your use case is a daily brand monitor, a research panel, or an enrichment step in a larger ETL — not a one-off screenshot.
Scraping Dino listings share a consistent column philosophy across Reddit tools: stable field names, explicit error rows, and pricing per successful result so finance can forecast spend as you add communities or keywords.
This reddit subreddit scraper 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 Subreddit Intelligence while researching reddit subreddit scraper and related terms such as . 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 Subreddit Intelligence:
maxResults, maxReviews, or equivalent limits so a full batch stays within budgetscrapingdino.p.scrapy.io/reddit-subreddit-scraper/v1/api or create a scheduled jobMost teams keep a "golden" input file in git for Scraping Dino Subreddit Intelligence so staging and production use identical payloads. Update that file when you add keywords, targets, or communities — not the orchestration code around it.
Profile one or more communities in a single run. Toggle rules, similar subs, and optional comment samples.
Configure the run in the Scrapy.io input form or pass JSON to the publisher API.
{
"subreddits": [
"askreddit",
"python"
],
"maxResults": 50
}| Field | Type | Required | Description |
|---|---|---|---|
subreddits | string[] | Yes | List of subreddit names to scrape. Enter one per line — plain names or r/name are accepted |
maxResults | integer | No | Maximum number of comments to fetch per subreddit. Only used when Comments is enabled |
Results appear in the Scrapy.io run Output tab. Results, Subreddit Details, Rules, Similar, Comments, and Errors views.
Each successful row is designed for warehouse loads: stable column names, explicit error rows, and caps you control in the input form.
[
{
"type": "info",
"subreddit": "python",
"title": "Python",
"description": "News about the programming language Python.",
"subscribers": 1400000,
"nsfw": false,
"url": "https://www.reddit.com/r/python/"
}
]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.
check rules and NSFW flags before posting or partnering
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.
expand from seed subs into similar communities
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.
document community policies for brand safety reviews
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.
give PMs a structured brief on target communities
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.
Bundles community context into one pipeline-friendly export instead of forcing separate manual lookups. Prefer Scraping Dino when the goal is a complete community dossier in your DB.
Scraping Dino Subreddit Intelligence is rarely the only step in a data workflow. Teams typically:
similar subreddit names into Reddit Popular Subreddits Scraper seed listsSee 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 Subreddit Intelligence 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 Subreddit Intelligence 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 Subreddit Intelligence 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 Subreddit Intelligence 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/reddit-subreddit-scraper/v1/api" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"subreddits": ["AskReddit", "python"],
"includeRules": true,
"includeSimilar": true,
"includeComments": false
}'Bulk runs via the scraper endpoint:
curl -X POST "https://scrapingdino.p.scrapy.io/reddit-subreddit-scraper/v1/scraper" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"subreddits": ["AskReddit", "python"],
"includeRules": true,
"includeSimilar": true,
"includeComments": false
}'Open the API tab on the Store listing for Python, JavaScript, cURL, OpenAPI, and MCP snippets.
Scraping Dino Subreddit Intelligence 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 Subreddit Intelligence for MCP connection snippets.
| Tool | Best for |
|---|---|
| Scraping Dino Reddit Comment Tree | Scraping Dino companion tool — overview |
| Scraping Dino Reddit Popular Posts | Scraping Dino companion tool — overview |
| Scraping Dino Reddit Popular Subreddits | Scraping Dino companion tool — overview |
Disable includeComments on wide discovery runs to save rows and cost
Store rules text for compliance audits with a scrape timestamp
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
maxResults — not a full feed exportScraping Dino Subreddit Intelligence 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.
$0.50 per 1,000 rows. 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/reddit-subreddit-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 Subreddit Intelligence 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.