apidojo-io/apidojo-skills

scraping-youtube-videos-by-keyword

Scrapes YouTube videos matching any keyword or search query using apidojo's YouTube scraper on Apify.

查看源码

使用方法

  1. 复制安装命令,在自己的智能体环境安装前先检查源码包。
  2. 从原始文档核对所需工具、凭据和支持的宿主。
  3. 说明输入材料与期望交付物,并对照来源检查输出。
npx skills add https://github.com/apidojo-io/apidojo-skills --skill scraping-youtube-videos-by-keyword

开始前需了解

  • 安装不包含模型订阅、API 额度或访问文件的权限。
  • 仓库星数和安装量反映活跃情况,不等于独立质量或安全测试。
仓库原始内容

按源仓库内容呈现,保留标题、案例、代码、表格、链接以及原文引用的演示图片。

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_TOKEN environment variable set
  • Optional: Apify MCP server installed

Inputs

ParameterTypeRequiredDefaultNotes
startUrlsarrayOptional[]YouTube URLs — channels, playlists, Shorts, search results
youtubeHandlesarrayOptional[]YouTube channel handles (e.g. @kurzgesagt)
getTrendingbooleanOptionalfalseRetrieve trending videos
keywordsarrayOptional[]Search keywords
glstringOptionalusCountry code for results (e.g. US, GB)
hlstringOptionalenLanguage code (e.g. en, de)
uploadDatestringOptionalallUpload date filter: any, hour, today, week, month, year
durationstringOptionalallDuration filter: any, short, long
featuresstringOptionalallFeature filter: 4k, hd, live, cc, 3d, hdr, etc.
sortstringOptionalrSort order for search results
maxItemsnumberOptionalUnlimitedMaximum videos to return
customMapFunctionstringOptional—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 dataset

Step 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 json
APIFY_TOKEN must be set in environment or .env file.

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, description

Troubleshooting

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.

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