🪙 Huobi (HTX) Crypto Tickers Scraper

🚀 Export every Huobi (HTX) spot ticker in seconds. Filter 600+ trading pairs by quote asset, sort by 24h volume, change, or last price, and get clean OHLC, bid/ask, and 24h trade count fields. No API key, no registration, no rate-limit headaches.

🕒 Last updated: 2026-05-13 · 📊 21 fields per record · 🪙 600+ pairs · 💱 7 quote currencies

The Huobi (HTX) Crypto Tickers Scraper queries the official Huobi public market endpoints and returns 21 fields per record, including last price, 24h open, high and low, base and quote volume, 24h trade count, best bid and ask with sizes, computed spread in basis points, and ISO timestamps. The actor joins the live ticker feed with the symbols catalog so every record carries clean baseAsset and quoteAsset values rather than a single concatenated symbol string.

Huobi was rebranded to HTX and remains one of the longest-running centralized exchanges by listing count, with strong coverage of USDT, USDC, BTC, ETH, HUSD, TRX, and HT pairs. This Actor exports the full spot catalog in one request. Results come back ready to download as CSV, Excel, JSON, or XML.

🎯 Target Audience	💡 Primary Use Cases
Quant teams, crypto analysts, arbitrage bots, market-microstructure researchers, portfolio dashboards, fintech apps, journalists	Price snapshots, volume leaderboards, trade-count proxies, arbitrage detection, HT and HUSD pair coverage, training datasets

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📋 What the Huobi (HTX) Tickers Scraper does

Three filtering and sorting workflows in a single run:

• 🌐 Full-catalog export. Every live spot pair on Huobi (HTX) in one dataset.
• 💱 Quote-asset filter. Restrict to USDT, USDC, BTC, ETH, HUSD, TRX, or HT markets.
• 📊 Multi-field sorting. Order by quote volume, base volume, 24h percent change, last price, or symbol.

Each record includes symbol, baseAsset, quoteAsset, lastPrice, openPrice, priceChange, priceChangePercent, 24h high and low, bidPrice and bidSize, askPrice and askSize, computed spreadAbs and spreadBps, volume24h, quoteVolume24h, tradeCount24h, tickerTime, and a scrapedAt timestamp.

💡 Why it matters: the 24h trade count is rare on public ticker feeds and is a strong proxy for genuine retail activity vs synthetic volume. Capturing it on every record lets you spot pairs where reported volume looks suspicious next to a thin trade count.

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🎬 Full Demo

🚧 Coming soon: a 3-minute walkthrough showing how to go from sign-up to a downloaded Huobi (HTX) ticker dataset.

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⚙️ Input

Input	Type	Default	Behavior
quoteAsset	string (enum)	""	One of usdt, usdc, btc, eth, husd, trx, ht. Empty = all pairs.
maxItems	integer	10	Records to return. Free plan caps at 10, paid plan at 1,000,000.
sortBy	string (enum)	"quoteVolume"	One of quoteVolume, volume, changePercent, lastPrice, symbol.

Example: top 50 USDT pairs by 24h quote volume.

{
    "maxItems": 50,
    "quoteAsset": "usdt",
    "sortBy": "quoteVolume"
}

Example: every HT-quoted pair sorted by 24h percent change.

{
    "maxItems": 100,
    "quoteAsset": "ht",
    "sortBy": "changePercent"
}

⚠️ Good to Know: Huobi symbols are lower-case (btcusdt, not BTCUSDT), so the quote-asset filter values are also lower-case. The Actor preserves this casing in the output symbol field for direct API compatibility, and exposes split baseAsset and quoteAsset for ergonomic joins.

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📊 Output

Each ticker record contains 21 fields. Download the dataset as CSV, Excel, JSON, or XML.

🧾 Schema

Field	Type	Example
🆔 symbol	string	"btcusdt"
🔗 url	string	"https://www.htx.com/trade/btcusdt/"
🪙 baseAsset	string | null	"btc"
💱 quoteAsset	string | null	"usdt"
💰 lastPrice	number | null	79127.68
🟢 openPrice	number | null	78845.59
📈 priceChange	number | null	282.09
📊 priceChangePercent	number | null	0.3578
🔺 highPrice24h	number | null	79164.46
🔻 lowPrice24h	number | null	78779.56
🟦 bidPrice	number | null	79127.67
📦 bidSize	number | null	0.093877
🟧 askPrice	number | null	79127.68
📦 askSize	number | null	0.42305
↔️ spreadAbs	number | null	0.01
🎯 spreadBps	number | null	0.0013
📉 volume24h	number | null	2660.5247718143805
💵 quoteVolume24h	number | null	214036703.3703723
🧮 tradeCount24h	number | null	28642
🕓 tickerTime	ISO 8601 | null	"2026-05-13T08:37:00.000Z"
🕒 scrapedAt	ISO 8601	"2026-05-13T08:37:02.000Z"

📦 Sample records

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✨ Why choose this Actor

	Capability
🌐	Full spot catalog. 600+ live trading pairs across 7 quote currencies in one run.
🧮	24h trade count. Rare on public ticker feeds, useful for separating retail flow from synthetic volume.
🔖	Clean baseAsset and quoteAsset. Joined from the live Huobi symbols catalog, never guessed.
📊	Server-side sorting. Quote volume, base volume, change percent, last price, or symbol order.
⚡	Fast. 10 tickers in under 5 seconds, full catalog in under a minute.
🎯	Computed spreads. Absolute spread and basis-point spread calculated per record.
🚫	No API key. Works against public Huobi (HTX) endpoints. No login required.

📊 The 24h trade count alongside volume is the cleanest public signal for flagging suspicious volume on long-tail listings.

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📈 How it compares to alternatives

Approach	Cost	Coverage	Refresh	Filters	Setup
⭐ Huobi (HTX) Tickers Scraper (this Actor)	$5 free credit, then pay-per-use	600+ pairs	Live per run	quote asset, sort	⚡ 2 min
Direct Huobi REST polling	Free, with rate limits	Same	Real-time	Build your own	🐢 Hours
Paid market data APIs	$99+/month	Multi-exchange	Streaming	Many	⏳ Hours
CSV exports from analytics sites	Free, often stale	Subset	Hourly or daily	None	🕒 Variable

Pick this Actor when you want native trade-count fields, quote-asset filtering, and zero pipeline maintenance.

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🚀 How to use

1. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Go to the Huobi (HTX) Crypto Tickers Scraper page on the Apify Store.
3. 🎯 Set input. Pick a quote asset (or leave empty for all pairs), choose a sort order, and set maxItems.
4. 🚀 Run it. Click Start and let the Actor collect your data.
5. 📥 Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.

⏱️ Total time from signup to downloaded dataset: 3-5 minutes. No coding required.

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💼 Business use cases

🤖 Trading bots and arbitrage Cross-exchange spread monitoring against Binance, Bybit, OKX Triangular arbitrage scans across USDT, BTC, ETH, HT quotes Volume-quality filters using trade-count vs reported volume Latency-tolerant pricing for swing strategies	📊 Analytics and dashboards Volume leaderboards with trade-count sanity checks Microstructure dashboards comparing spread vs activity Historical snapshots stitched from scheduled runs Treasury and portfolio rebalancing inputs
🪙 Listings and trackers New-listing alerts when symbols appear on HTX Native HT and HUSD pair coverage Long-tail altcoin discovery via 24h volume sort Delisting detection by diffing successive runs	🧪 Research and journalism Quant research datasets for backtests Stories on volume quality at long-running exchanges Stablecoin depeg or spread anomalies Educational material with real exchange data

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🔌 Automating Huobi (HTX) Tickers Scraper

Control the scraper programmatically for scheduled runs and pipeline integrations:

• 🟢 Node.js. Install the apify-client NPM package.
• 🐍 Python. Use the apify-client PyPI package.
• 📚 See the Apify API documentation for full details.

The Apify Schedules feature lets you trigger this Actor on any cron interval. Every minute, hourly, or daily refreshes keep downstream price tables in sync automatically.

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🌟 Beyond business use cases

Live ticker data powers more than trading desks. The same structured records support research, education, civic projects, and personal initiatives.

🎓 Research and academia Microstructure papers on spread vs trade-count dynamics Volume-quality studies across long-running venues Reproducible datasets with versioned scheduled pulls Coursework on time-series and volatility modeling	🎨 Personal and creative Hobby trading dashboards and portfolio trackers Side projects that ping Telegram or Discord on price moves Visualizations and infographics for crypto blogs Toy datasets for learning pandas, DuckDB, or Polars
🤝 Non-profit and civic Transparency reports on volume quality and liquidity Investigative journalism on reported volume vs trades Educational materials for financial-literacy programs Open datasets for academic crypto research consortia	🧪 Experimentation Train classifiers on regime detection Prototype agent pipelines that watch spreads and trades Backtest mean-reversion ideas with real ticks Test alert systems against historical snapshots

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🤖 Ask an AI assistant about this scraper

Open a ready-to-send prompt about this ParseForge actor in the AI of your choice:

• 💬 ChatGPT
• 🧠 Claude
• 🔍 Perplexity
• 🅒 Copilot

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❓ Frequently Asked Questions

🧩 How does it work?

The Actor calls the public Huobi common/symbols and market/tickers endpoints, joins symbol metadata, applies your quote-asset and sort filters server-side, and emits one clean record per pair. No browser automation, no captchas, no credentials.

📏 How fresh is the data?

Every run hits the live tickers endpoint, so the dataset reflects the spot market at the moment of the run. The tickerTime field shows the exact server time of the snapshot.

🧮 What is tradeCount24h?

The number of executed trades over the prior 24h window. It's a useful sanity check on reported volume - a high quote volume next to a thin trade count is a classic signal of wash or synthetic trading.

🔁 How often is the dataset refreshed?

The Actor refreshes on every run. Schedule it on any cron interval, from every minute to daily.

🪙 Does it include new listings?

Yes. The Actor pulls the live symbols catalog on every run, so freshly listed pairs appear automatically.

🏷️ Why are symbols lower-case?

Huobi (HTX) returns lower-case symbols natively (btcusdt, not BTCUSDT). The Actor preserves this casing in the symbol field for direct API compatibility, while exposing split baseAsset and quoteAsset for ergonomic joins.

⏰ Can I schedule regular runs?

Yes. Use Apify Schedules to run this Actor on any cron interval and keep a downstream database in sync.

⚖️ Is this data legal to use?

Huobi (HTX) publishes ticker data on public endpoints intended for application access. Review the venue terms for your specific use case, but raw ticker snapshots are generally considered public market data.

💼 Can I use this data commercially?

Yes. Raw market data is widely used in commercial products. You are responsible for complying with venue terms and any downstream regulatory requirements.

💳 Do I need a paid Apify plan to use this Actor?

No. The free Apify plan is enough for testing and small runs (10 records per run). A paid plan lifts the limit and gives you access to scheduling, higher concurrency, and larger datasets.

🆘 What if I need help?

Our support team is here to help. Contact us through the Apify platform or use the Tally form linked below.

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🔌 Integrate with any app

Huobi (HTX) Tickers Scraper connects to any cloud service via Apify integrations:

• Make - Automate multi-step workflows
• Zapier - Connect with 5,000+ apps
• Slack - Get price alerts in your channels
• Airbyte - Pipe ticker data into your warehouse
• GitHub - Trigger runs from commits and releases
• Google Drive - Export datasets straight to Sheets

You can also use webhooks to trigger downstream actions when a run finishes. Push fresh prices into your trading backend, or alert your team in Slack.

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🔗 Recommended Actors

• 📊 Binance Crypto Prices Scraper - Spot and futures prices from the largest centralized exchange
• 🟣 Bybit Tickers Scraper - Spot and derivatives tickers from Bybit
• 🐙 Kraken Crypto Exchange Scraper - Spot pairs and OHLC from Kraken
• 🦎 CoinGecko Cryptocurrency Scraper - Cross-exchange aggregated prices, market cap, and ranks
• 🐝 CoinPaprika Crypto Tickers Scraper - Multi-exchange ticker rollups

💡 Pro Tip: browse the complete ParseForge collection for more exchange and market-data scrapers.

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🆘 Need Help? Open our contact form to request a new scraper, propose a custom data project, or report an issue.

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⚠️ Disclaimer: this Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Huobi, HTX, or any of their affiliates. All trademarks mentioned are the property of their respective owners. Only publicly available market data is collected.