🛡️ Rated Network Ethereum Validators Scraper

🚀 Export Rated Network Ethereum staking records in seconds. Pull the full product or entity catalog into clean structured rows ready for analytics and downstream tooling.

🕒 Last updated 2026-06-05 · 📊 12 fields per record · Rated Network coverage · Real-time

The Rated Network Ethereum Validators Scraper turns the public Rated Network catalog into a clean structured feed. It calls the public storefront or platform API, normalizes the response, and surfaces one record per item.

Coverage spans the live Ethereum staking surface of Rated Network. Every record carries the most important attributes upstream exposes, normalized into a flat row.

🎯 Target Audience	💡 Primary Use Cases
📊 Data analysts	Mirror Rated Network data into structured rows
🏢 Pricing teams	Track listings across runs
🤖 ML engineers	Build training sets from Ethereum staking catalogs
📰 Journalists	Verify Ethereum staking facts in seconds
🎓 Researchers	Build longitudinal datasets of Ethereum staking
👩‍💻 Developers	Pipe Rated Network listings into your own warehouse

📋 What the Rated Network Ethereum Validators Scraper does

• Calls the public Rated Network endpoint that powers the live page.
• Normalizes the response into one flat row per entity with stable field names.
• Applies optional client-side filters described in the input schema.
• Surfaces upstream rate-limit or error notes as a clean error record.
• Pushes structured rows into your dataset, ready for export in any of the supported download formats.

💡 Why it matters Direct access to the live Rated Network catalog without writing scraping code.

🎬 Full Demo

🚧 Coming soon.

⚙️ Input

Field	Type	Required	Description
searchQuery	string	No	Optional client-side text filter applied to operator name. Leave empty to return all validators.
network	enum	No	Choose which Ethereum network to query.
operator	string	No	Filter to a specific node operator. Empty returns all operators.
maxItems	integer	No	Free plan caps at 10 items. Paid plans go up to 1,000,000. Prefill 10.

Example 1

{
  "searchQuery": "milk",
  "maxItems": 25
}

Example 2

{
  "maxItems": 50,
  "network": "mainnet"
}

⚠️ Good to Know The upstream endpoint may rate-limit aggressive use. Schedule recurring runs at a sane cadence and keep maxItems reasonable.

📊 Output

Each record is a flat object. The error field is always last.

Field	Type	Description
🔢 Validator Index validator_index	number	validator_index value from the upstream record.
🏢 Operator operator	string	operator value from the upstream record.
🎯 Effectiveness effectiveness	number	effectiveness value from the upstream record.
✅ Attestations attestations	number	attestations value from the upstream record.
📣 Proposals proposals	number	proposals value from the upstream record.
🔄 Sync Committee sync_committee_performance	number	sync_committee_performance value from the upstream record.
💰 MEV Earned mev_earned	number	mev_earned value from the upstream record.
🏆 Rewards rewards	number	rewards value from the upstream record.
🌐 Network network	string	network value from the upstream record.
🟢 Status status	string	status value from the upstream record.
🕒 scrapedAt	string	When this row was collected.
❌ error	string	Populated only on upstream errors.

Sample record

{
  "validator_index": 12345,
  "operator": "Lido",
  "effectiveness": 99.2,
  "attestations": 12450,
  "proposals": 14,
  "sync_committee_performance": 100,
  "mev_earned": 0.42,
  "rewards": 1.84,
  "network": "mainnet",
  "status": "active",
  "scrapedAt": "2026-06-05T07:00:00.000Z",
  "error": null
}

✨ Why choose this Actor

| 🆓 | Works without an API key for public endpoints. | | 🧹 | Flat schema with stable field names. | | 🔢 | Numeric fields cast to real numbers. | | 🛟 | Upstream errors surface as a clean error record. | | 🔌 | Plays well with Apify schedules and webhooks. | | 💾 | One push to the dataset, multiple download formats. |

📈 How it compares to alternatives

Approach	Setup time	Field normalization	Rate-limit handling
Roll your own fetch	30 minutes plus	manual	manual
Headless browser	hours	partial	partial
This Actor	5 seconds	full	yes

🚀 How to use

1. Click Try for free.
2. Configure the input fields described above.
3. Click Start.
4. Download your dataset in your preferred export format.

💼 Business use cases

📊 Market intelligence. Monitor Rated Network Ethereum staking listings across time to spot trends.

💼 Operations. Mirror upstream catalog into internal tooling for inventory or compliance.

📰 Reporting. Pull verifiable facts from the live Rated Network surface for stories and briefs.

🤖 Machine learning. Build clean training sets from Ethereum staking data without writing scrapers.

🔌 Automating Rated Network Ethereum Validators Scraper

• Make and Zapier trigger the actor and route results into Airtable, Google Sheets, or Slack.
• Cron native Apify scheduler runs the actor on any cadence you want.
• Webhooks POST run results straight to your warehouse loader.
• Slack and Discord push a daily digest into your team channel.

🌟 Beyond business use cases

🎓 Education. Teach data analysis with fresh Ethereum staking datasets.

🧪 Personal research. Track your own watchlist over time.

🤝 Non-profit and open data. Build public dashboards for civic interest projects.

🧰 Tinkering. Pipe Rated Network data into a side project or bot.

🤖 Ask an AI assistant about this scraper

Paste this README into ChatGPT, Claude, or any AI assistant. The schema, examples, and field list above contain everything an LLM needs to map your workflow to actor inputs.

❓ Frequently Asked Questions

❓ Do I need an API key? No. The endpoint used is public.

❓ How fresh is the data? Every run hits the live endpoint.

❓ Can I filter results? Yes via the input schema fields.

❓ Can I limit the result count? Yes via maxItems. Free plan caps at 10.

❓ Will the schema change? Stable core fields. Optional fields may be added if upstream exposes new metadata.

❓ Is this scraping or API? Public API normalization.

❓ Does it handle rate limits? Yes. Upstream rate-limit notes surface as an error record.

❓ Does it follow pagination? Yes when maxItems exceeds one page worth of results.

❓ Can I schedule runs? Yes via Apify scheduler, Make, Zapier, or cron.

❓ Can I integrate with my warehouse? Yes. Apify pipes datasets to BigQuery, Snowflake, Postgres, or any webhook target.

🔌 Integrate with any app

Apify ships native integrations with Make, Zapier, Slack, Discord, Google Drive, Google Sheets, Gmail, Airbyte, Keboola, Telegram, GitHub, and any REST or webhook endpoint. Trigger from a calendar event, a form submission, or a cron job. Pipe results into BigQuery, Snowflake, or Postgres.

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