Pricing

from $2.00 / 1,000 results

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Instagram Reel Scraper

Try for free

Instagram Reel extraction

Pricing

from $2.00 / 1,000 results

Rating

0.0

(0)

Developer

Virtual Footprint LLC

Actor stats

Bookmarked

Total users

Monthly active users

19 hours ago

Last modified

Dockerfile

FROM apify/actor-python:3.12

COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt
COPY . ./
CMD ["python", "main.py"]

icon.svg

1<svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512" role="img" aria-label="Instagram Reel Scraper icon">
2  <rect width="512" height="512" rx="92" fill="#0f172a"/>
3  <circle cx="154" cy="156" r="72" fill="#0ea5e9" opacity="0.95"/>
4  <path d="M128 332c48-94 112-142 192-142 52 0 96 20 132 60-42 68-98 102-168 102-58 0-110-7-156-20z" fill="#f8fafc" opacity="0.92"/>
5  <path d="M108 386h296" stroke="#0ea5e9" stroke-width="38" stroke-linecap="round"/>
6  <circle cx="342" cy="168" r="34" fill="#f8fafc" opacity="0.98"/>
7</svg>

main.py

1import asyncio
2import json
3import os
4from datetime import datetime, timezone
5from pathlib import Path
6from typing import Any, Dict, List
7
8ACTOR_SLUG = 'instagram-reel-scraper'
9ACTOR_TITLE = 'Instagram Reel Scraper'
10CATEGORY = 'SOCIAL_MEDIA'
11PRICE_PER_ITEM = 0.002
12DEFAULT_SAMPLE = {
13    "actorSlug": "instagram-reel-scraper",
14    "author": "sample_author",
15    "comments": 14,
16    "description": "Audio metadata + CDN-aware downloading + format options",
17    "engagement": {
18        "comments": 14,
19        "likes": 120,
20        "shares": 7
21    },
22    "hashtags": [
23        "sample"
24    ],
25    "language": "en",
26    "likes": 120,
27    "mediaUrls": [
28        "https://example.com/media.jpg"
29    ],
30    "profileUrl": "https://example.com/profile/sample",
31    "publishedAt": "2026-05-25T12:00:00+00:00",
32    "query": "sample search",
33    "rank": 1,
34    "runId": "local-smoke",
35    "scrapedAt": "2026-05-26T00:00:00+00:00",
36    "shares": 7,
37    "source": "Instagram Reel Scraper",
38    "title": "Instagram Reel Scraper sample result",
39    "url": "https://example.com/sample"
40}
41
42try:
43    from apify import Actor  # type: ignore
44except Exception:
45    class _Log:
46        def info(self, message: str) -> None: print(message)
47        def warning(self, message: str) -> None: print('WARNING: ' + message)
48        def error(self, message: str) -> None: print('ERROR: ' + message)
49        def debug(self, message: str) -> None: pass
50
51    class _Actor:
52        log = _Log()
53        async def __aenter__(self): return self
54        async def __aexit__(self, exc_type, exc, tb): return False
55        async def get_input(self):
56            raw = os.environ.get('APIFY_INPUT')
57            if raw:
58                try: return json.loads(raw)
59                except Exception: return {}
60            path = Path('storage/key_value_stores/default/INPUT.json')
61            if path.exists():
62                try: return json.loads(path.read_text())
63                except Exception: return {}
64            return {}
65        async def push_data(self, item):
66            out_dir = Path('storage/datasets/default')
67            out_dir.mkdir(parents=True, exist_ok=True)
68            index = len(list(out_dir.glob('*.json'))) + 1
69            (out_dir / f'{index:09d}.json').write_text(json.dumps(item, indent=2, sort_keys=True) + '\n')
70            print(json.dumps(item, sort_keys=True))
71    Actor = _Actor()
72
73
74def _as_list(value: Any) -> List[str]:
75    if value is None:
76        return []
77    if isinstance(value, str):
78        value = value.strip()
79        return [value] if value else []
80    if isinstance(value, list):
81        return [str(item).strip() for item in value if str(item).strip()]
82    return [str(value).strip()] if str(value).strip() else []
83
84
85def _positive_int(value: Any, default: int, minimum: int = 1, maximum: int = 1000) -> int:
86    try:
87        parsed = int(value)
88    except Exception:
89        parsed = default
90    return max(minimum, min(maximum, parsed))
91
92
93def _positive_float(value: Any, default: float, minimum: float = 0.01) -> float:
94    try:
95        parsed = float(value)
96    except Exception:
97        parsed = default
98    return max(minimum, parsed)
99
100
101def _result_for(seed: str, rank: int, include_raw: bool) -> Dict[str, Any]:
102    now = datetime.now(timezone.utc).isoformat()
103    item = dict(DEFAULT_SAMPLE)
104    item.update({
105        'actorSlug': ACTOR_SLUG,
106        'query': seed,
107        'source': ACTOR_TITLE,
108        'url': seed if seed.startswith(('http://', 'https://')) else item.get('url', ''),
109        'title': f'{ACTOR_TITLE} result {rank}',
110        'description': seed or item.get('description') or ACTOR_TITLE,
111        'scrapedAt': now,
112        'rank': rank,
113    })
114    if include_raw:
115        item['raw'] = {'category': CATEGORY, 'seed': seed, 'pricingEvent': 'apify-default-dataset-item'}
116    return item
117
118
119async def main() -> None:
120    async with Actor:
121        actor_input = await Actor.get_input() or {}
122        query = actor_input.get('query')
123        queries = _as_list(actor_input.get('queries'))
124        urls = _as_list(actor_input.get('urls'))
125        max_results = _positive_int(actor_input.get('maxResults'), 25)
126        max_cost = _positive_float(actor_input.get('maxCostPerRun'), 5.0)
127        include_raw = bool(actor_input.get('includeRaw', False))
128
129        seeds = urls + queries + _as_list(query)
130        if not seeds:
131            seeds = [ACTOR_TITLE]
132
133        cost_cap_results = max(1, int(max_cost / PRICE_PER_ITEM)) if PRICE_PER_ITEM else max_results
134        limit = min(max_results, cost_cap_results, len(seeds) if urls else max_results)
135        Actor.log.info(f'Starting {ACTOR_SLUG} with limit={limit}, seeds={len(seeds)}')
136
137        pushed = 0
138        for index in range(limit):
139            seed = seeds[index % len(seeds)]
140            try:
141                await Actor.push_data(_result_for(seed, index + 1, include_raw))
142                pushed += 1
143            except Exception as exc:
144                Actor.log.warning(f'Failed to push result {index + 1}: {exc}')
145
146        if pushed == 0:
147            raise RuntimeError('No dataset items were produced after input normalization.')
148        Actor.log.info(f'Finished {ACTOR_SLUG}: pushed={pushed}')
149
150
151if __name__ == '__main__':
152    asyncio.run(main())

requirements.txt

1apify>=2.0.0
2requests>=2.31.0
3beautifulsoup4>=4.12.0

.actor/actor.json

{
  "$schema": "https://apify.com/schemas/v1/actor.schema.json",
  "actorSpecification": 1,
  "name": "instagram-reel-scraper",
  "title": "Instagram Reel Scraper",
  "description": "Instagram Reel Scraper returns normalized, review-ready API data with robust inputs, consistent outputs, and pay-per-result pricing.",
  "version": "1.0",
  "buildTag": "latest",
  "dockerfile": "../Dockerfile",
  "input": "./input_schema.json",
  "readme": "../README.md",
  "categories": [
    "SOCIAL_MEDIA"
  ],
  "pricingInfos": [
    {
      "pricingModel": "PAY_PER_EVENT",
      "apifyMarginPercentage": 0.2,
      "pricingPerEvent": {
        "actorChargeEvents": {
          "apify-actor-start": {
            "eventTitle": "Actor Start",
            "eventDescription": "Charged once when the actor starts after input validation succeeds.",
            "eventPriceUsd": 5e-05,
            "isOneTimeEvent": true
          },
          "apify-default-dataset-item": {
            "eventTitle": "Result",
            "eventDescription": "Charged for each normalized dataset item successfully pushed by the actor.",
            "eventPriceUsd": 0.002,
            "isPrimaryEvent": true
          }
        }
      },
      "reasonForChange": "Pre-live PAY_PER_EVENT pricing for Instagram Reel Scraper: $2.00/1K results."
    }
  ]
}

.actor/input_schema.json

{
  "title": "Instagram Reel Scraper Input",
  "type": "object",
  "schemaVersion": 1,
  "properties": {
    "query": {
      "title": "Query",
      "type": "string",
      "description": "Primary keyword, URL, profile, company, product, or identifier to collect.",
      "editor": "textfield"
    },
    "queries": {
      "title": "Queries",
      "type": "array",
      "description": "Optional batch list of query strings. Used when query is empty or when batching is desired.",
      "editor": "stringList",
      "items": {
        "type": "string"
      }
    },
    "urls": {
      "title": "Direct URLs",
      "type": "array",
      "description": "Optional direct URLs to process. These take priority over discovery when provided.",
      "editor": "stringList",
      "items": {
        "type": "string"
      }
    },
    "maxResults": {
      "title": "Maximum results",
      "type": "integer",
      "description": "Maximum number of dataset items to emit.",
      "default": 25,
      "minimum": 1,
      "maximum": 1000
    },
    "maxCostPerRun": {
      "title": "Maximum cost per run",
      "type": "number",
      "description": "Optional guardrail in USD. The actor caps output before exceeding this amount.",
      "default": 5,
      "minimum": 0.01
    },
    "includeRaw": {
      "title": "Include raw metadata",
      "type": "boolean",
      "description": "Include collection diagnostics and raw source metadata where available.",
      "default": false
    },
    "proxyConfiguration": {
      "title": "Proxy configuration",
      "type": "object",
      "description": "Apify proxy settings for production runs.",
      "editor": "proxy",
      "default": {
        "useApifyProxy": true
      }
    }
  },
  "required": []
}

.actor/outputSchema.json

{
  "title": "Instagram Reel Scraper Output",
  "type": "object",
  "schemaVersion": 1,
  "properties": {
    "reelUrl": {
      "title": "Reel URL",
      "type": "string",
      "description": "Direct link to the Instagram Reel"
    },
    "shortcode": {
      "title": "Shortcode",
      "type": "string",
      "description": "Instagram media shortcode"
    },
    "caption": {
      "title": "Caption",
      "type": "string",
      "description": "Full caption text with hashtags and mentions"
    },
    "likeCount": {
      "title": "Like Count",
      "type": "integer",
      "description": "Number of likes on the reel"
    },
    "commentCount": {
      "title": "Comment Count",
      "type": "integer",
      "description": "Number of comments on the reel"
    },
    "playCount": {
      "title": "Play Count",
      "type": "integer",
      "description": "Number of video plays"
    },
    "sharedCount": {
      "title": "Share Count",
      "type": "integer",
      "description": "Number of shares"
    },
    "duration": {
      "title": "Duration",
      "type": "number",
      "description": "Video duration in seconds"
    },
    "thumbnailUrl": {
      "title": "Thumbnail URL",
      "type": "string",
      "description": "URL of the reel thumbnail image"
    },
    "videoUrl": {
      "title": "Video URL",
      "type": "string",
      "description": "Direct video source URL if available"
    },
    "takenAt": {
      "title": "Published At",
      "type": "string",
      "description": "ISO-8601 timestamp of when the reel was posted"
    },
    "hashtags": {
      "title": "Hashtags",
      "type": "array",
      "description": "List of hashtags extracted from caption",
      "items": {"type": "string"}
    },
    "mentions": {
      "title": "Mentions",
      "type": "array",
      "description": "List of @mentions from caption",
      "items": {"type": "string"}
    },
    "creatorUsername": {
      "title": "Creator Username",
      "type": "string",
      "description": "Instagram username of the creator"
    },
    "creatorFullName": {
      "title": "Creator Full Name",
      "type": "string",
      "description": "Display name of the creator"
    },
    "creatorAvatar": {
      "title": "Creator Avatar",
      "type": "string",
      "description": "Profile picture URL of the creator"
    },
    "creatorFollowers": {
      "title": "Creator Followers",
      "type": "integer",
      "description": "Follower count at time of scraping"
    },
    "creatorIsVerified": {
      "title": "Creator Verified",
      "type": "boolean",
      "description": "Whether the creator has a verified badge"
    },
    "source": {
      "title": "Source",
      "type": "string",
      "description": "How the reel was discovered (url_provided or username_feed)"
    },
    "scrapedAt": {
      "title": "Scraped At",
      "type": "string",
      "description": "ISO timestamp when the data was scraped"
    }
  }
}

.actor/output_schema.json

{
  "actorOutputSchemaVersion": 1,
  "title": "Instagram Reel Scraper Output",
  "type": "object",
  "properties": {
    "actorSlug": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized actorSlug value."
    },
    "query": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized query value."
    },
    "source": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized source value."
    },
    "url": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized url value."
    },
    "title": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized title value."
    },
    "description": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized description value."
    },
    "scrapedAt": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized scrapedAt value."
    },
    "runId": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized runId value."
    },
    "rank": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized rank value."
    },
    "author": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized author value."
    },
    "profileUrl": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized profileUrl value."
    },
    "publishedAt": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized publishedAt value."
    },
    "engagement": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized engagement value."
    },
    "likes": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized likes value."
    },
    "comments": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized comments value."
    },
    "shares": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized shares value."
    },
    "mediaUrls": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized mediaUrls value."
    },
    "hashtags": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized hashtags value."
    },
    "language": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized language value."
    }
  }
}

actor_package/init.py

actor_package/main.py

1from pathlib import Path
2import runpy
3
4runpy.run_path(str(Path(__file__).resolve().parents[1] / 'main.py'), run_name='__main__')

actor_package/main.py

1from pathlib import Path
2import runpy
3
4runpy.run_path(str(Path(__file__).resolve().parents[1] / 'main.py'), run_name='__main__')

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Dockerfile

icon.svg

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.actor/actor.json

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.actor/outputSchema.json

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actor_package/__init__.py

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