원본 Skill 문서
원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.
Scraping YouTube Videos by Keyword
Raw YouTube video dataset for any search query. Returns video-level metadata including engagement metrics and channel info.
Prerequisites
APIFY_TOKENenvironment variable set- Optional: Apify MCP server installed
Inputs
| Parameter | Type | Required | Default | Notes |
|---|---|---|---|---|
startUrls | array | Optional | [] | YouTube URLs — channels, playlists, Shorts, search results |
youtubeHandles | array | Optional | [] | YouTube channel handles (e.g. @kurzgesagt) |
getTrending | boolean | Optional | false | Retrieve trending videos |
keywords | array | Optional | [] | Search keywords |
gl | string | Optional | us | Country code for results (e.g. US, GB) |
hl | string | Optional | en | Language code (e.g. en, de) |
uploadDate | string | Optional | all | Upload date filter: any, hour, today, week, month, year |
duration | string | Optional | all | Duration filter: any, short, long |
features | string | Optional | all | Feature filter: 4k, hd, live, cc, 3d, hdr, etc. |
sort | string | Optional | r | Sort order for search results |
maxItems | number | Optional | Unlimited | Maximum videos to return |
customMapFunction | string | Optional | — | JavaScript function to transform each output object |
Workflow
Progress:
- [ ] Step 1: Build search query
- [ ] Step 2: Run youtube-scraper
- [ ] Step 3: Poll for SUCCEEDED
- [ ] Step 4: Deliver video datasetStep 2: Run the Actor
Recommended — run_actor.js (handles waiting, output, and file saving automatically):
bash
# Quick answer (prints table to chat)
node scripts/run_actor.js \
--actor "apidojo~youtube-scraper" \
--input '{"param": "value"}'
# Save as CSV
node scripts/run_actor.js \
--actor "apidojo~youtube-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.csv --format csv
# Save as JSON
node scripts/run_actor.js \
--actor "apidojo~youtube-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.json --format jsonAPIFY_TOKENmust be set in environment or.envfile.
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~youtube-scraper"
Input:
{
"searchKeywords": "<query>",
"maxResults": 50,
"sortBy": "relevance"
}REST API fallback:
bash
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~youtube-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"searchKeywords": "<query>", "maxResults": 50}'Save id as RUN_ID. Poll until status = SUCCEEDED:
bash
curl "https://api.apify.com/v2/actor-runs/$RUN_ID?token=$APIFY_TOKEN" | grep '"status"'Fetch results:
bash
curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN&format=json"Step 3: Handle Edge Cases
- < 20 results: Query may be too narrow; broaden search term.
- Age-restricted content in results: These may have limited metadata — flag rows with missing
viewCount. - Duplicate video IDs: Deduplicate by
videoId.
Output Format
# YouTube Video Dataset: "<query>"
Videos collected: N | Sort: <sortBy>
| Video ID | Title | Channel | Views | Likes | Comments | Duration | Published |
|----------|-------|---------|-------|-------|----------|----------|-----------|
| ... | ... | ... | ... | ... | ... | ... | ... |
Available fields: videoId, title, channelName, channelId, viewCount, likeCount,
commentCount, duration, publishedAt, videoUrl, thumbnailUrl, descriptionTroubleshooting
Fewer results than requested: YouTube search may have limited results for niche queries. Missing like counts: YouTube hides dislikes but likes are still available; some videos hide all counts.
