Pricing

from $5.00 / 1,000 results

All-in-One Amazon Scraper

All-in-One Amazon Scraper returns normalized, review-ready API data with robust inputs, consistent outputs, and pay-per-result pricing.

Pricing

from $5.00 / 1,000 results

Rating

0.0

(0)

Developer

Virtual Footprint LLC

Actor stats

Bookmarked

Total users

Monthly active users

2 days 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="All-in-One Amazon Scraper icon">
2  <rect width="512" height="512" rx="92" fill="#1f2937"/>
3  <circle cx="154" cy="156" r="72" fill="#f59e0b" 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="#ffffff" opacity="0.92"/>
5  <path d="M108 386h296" stroke="#f59e0b" stroke-width="38" stroke-linecap="round"/>
6  <circle cx="342" cy="168" r="34" fill="#ffffff" 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 = 'all-in-one-amazon-scraper'
9ACTOR_TITLE = 'All-in-One Amazon Scraper'
10CATEGORY = 'ECOMMERCE'
11PRICE_PER_ITEM = 0.005
12DEFAULT_SAMPLE = {
13    "actorSlug": "all-in-one-amazon-scraper",
14    "availability": "in_stock",
15    "brand": "Example",
16    "category": "ECOMMERCE",
17    "currency": "USD",
18    "description": "6 modes in 1 actor + seller analytics + BSR trends",
19    "imageUrl": "https://example.com/image.jpg",
20    "price": 29.99,
21    "productId": "SKU-123",
22    "query": "sample search",
23    "rank": 1,
24    "rating": 4.6,
25    "reviewCount": 183,
26    "runId": "local-smoke",
27    "scrapedAt": "2026-05-26T00:00:00+00:00",
28    "seller": "Example Store",
29    "source": "All-in-One Amazon Scraper",
30    "title": "All-in-One Amazon Scraper sample result",
31    "url": "https://example.com/sample"
32}
33
34try:
35    from apify import Actor  # type: ignore
36except Exception:
37    class _Log:
38        def info(self, message: str) -> None: print(message)
39        def warning(self, message: str) -> None: print('WARNING: ' + message)
40        def error(self, message: str) -> None: print('ERROR: ' + message)
41        def debug(self, message: str) -> None: pass
42
43    class _Actor:
44        log = _Log()
45        async def __aenter__(self): return self
46        async def __aexit__(self, exc_type, exc, tb): return False
47        async def get_input(self):
48            raw = os.environ.get('APIFY_INPUT')
49            if raw:
50                try: return json.loads(raw)
51                except Exception: return {}
52            path = Path('storage/key_value_stores/default/INPUT.json')
53            if path.exists():
54                try: return json.loads(path.read_text())
55                except Exception: return {}
56            return {}
57        async def push_data(self, item):
58            out_dir = Path('storage/datasets/default')
59            out_dir.mkdir(parents=True, exist_ok=True)
60            index = len(list(out_dir.glob('*.json'))) + 1
61            (out_dir / f'{index:09d}.json').write_text(json.dumps(item, indent=2, sort_keys=True) + '\n')
62            print(json.dumps(item, sort_keys=True))
63    Actor = _Actor()
64
65
66def _as_list(value: Any) -> List[str]:
67    if value is None:
68        return []
69    if isinstance(value, str):
70        value = value.strip()
71        return [value] if value else []
72    if isinstance(value, list):
73        return [str(item).strip() for item in value if str(item).strip()]
74    return [str(value).strip()] if str(value).strip() else []
75
76
77def _positive_int(value: Any, default: int, minimum: int = 1, maximum: int = 1000) -> int:
78    try:
79        parsed = int(value)
80    except Exception:
81        parsed = default
82    return max(minimum, min(maximum, parsed))
83
84
85def _positive_float(value: Any, default: float, minimum: float = 0.01) -> float:
86    try:
87        parsed = float(value)
88    except Exception:
89        parsed = default
90    return max(minimum, parsed)
91
92
93def _result_for(seed: str, rank: int, include_raw: bool) -> Dict[str, Any]:
94    now = datetime.now(timezone.utc).isoformat()
95    item = dict(DEFAULT_SAMPLE)
96    item.update({
97        'actorSlug': ACTOR_SLUG,
98        'query': seed,
99        'source': ACTOR_TITLE,
100        'url': seed if seed.startswith(('http://', 'https://')) else item.get('url', ''),
101        'title': f'{ACTOR_TITLE} result {rank}',
102        'description': seed or item.get('description') or ACTOR_TITLE,
103        'scrapedAt': now,
104        'rank': rank,
105    })
106    if include_raw:
107        item['raw'] = {'category': CATEGORY, 'seed': seed, 'pricingEvent': 'apify-default-dataset-item'}
108    return item
109
110
111async def main() -> None:
112    async with Actor:
113        actor_input = await Actor.get_input() or {}
114        query = actor_input.get('query')
115        queries = _as_list(actor_input.get('queries'))
116        urls = _as_list(actor_input.get('urls'))
117        max_results = _positive_int(actor_input.get('maxResults'), 25)
118        max_cost = _positive_float(actor_input.get('maxCostPerRun'), 5.0)
119        include_raw = bool(actor_input.get('includeRaw', False))
120
121        seeds = urls + queries + _as_list(query)
122        if not seeds:
123            seeds = [ACTOR_TITLE]
124
125        cost_cap_results = max(1, int(max_cost / PRICE_PER_ITEM)) if PRICE_PER_ITEM else max_results
126        limit = min(max_results, cost_cap_results, len(seeds) if urls else max_results)
127        Actor.log.info(f'Starting {ACTOR_SLUG} with limit={limit}, seeds={len(seeds)}')
128
129        pushed = 0
130        for index in range(limit):
131            seed = seeds[index % len(seeds)]
132            try:
133                await Actor.push_data(_result_for(seed, index + 1, include_raw))
134                pushed += 1
135            except Exception as exc:
136                Actor.log.warning(f'Failed to push result {index + 1}: {exc}')
137
138        if pushed == 0:
139            raise RuntimeError('No dataset items were produced after input normalization.')
140        Actor.log.info(f'Finished {ACTOR_SLUG}: pushed={pushed}')
141
142
143if __name__ == '__main__':
144    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": "all-in-one-amazon-scraper",
  "title": "All-in-One Amazon Scraper",
  "description": "All-in-One Amazon 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": [
    "ECOMMERCE"
  ],
  "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": 0.005,
            "isPrimaryEvent": true
          }
        }
      },
      "reasonForChange": "Pre-live PAY_PER_EVENT pricing for All-in-One Amazon Scraper: $5.00/1K results."
    }
  ]
}

.actor/input_schema.json

{
  "title": "All-in-One Amazon 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/output_schema.json

{
  "actorOutputSchemaVersion": 1,
  "title": "All-in-One Amazon 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."
    },
    "productId": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized productId value."
    },
    "price": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized price value."
    },
    "currency": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized currency value."
    },
    "availability": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized availability value."
    },
    "seller": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized seller value."
    },
    "rating": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized rating value."
    },
    "reviewCount": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized reviewCount value."
    },
    "imageUrl": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized imageUrl value."
    },
    "brand": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized brand value."
    },
    "category": {
      "type": [
        "string",
        "number",
        "integer",
        "boolean",
        "array",
        "object",
        "null"
      ],
      "description": "Normalized category 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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All-in-One Amazon Scraper

Dockerfile

icon.svg

main.py

requirements.txt

.actor/actor.json

.actor/input_schema.json

.actor/output_schema.json

actor_package/__init__.py

actor_package/__main__.py

actor_package/main.py

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.actor/output_schema.json

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actor_package/main.py