🇺🇸 US Treasury Auctions Scraper

🚀 Export US Treasury auction results in seconds. Bills, notes, bonds, TIPS, and FRNs with yields, tendered, and accepted amounts straight from the Fiscal Data API.

🕒 Last updated: 2026-06-05 · 📊 10 fields per record · Public API · Real-time

The US Treasury Auctions turns the fiscaldata.treasury.gov public endpoint into a clean, structured dataset. Scrape US Treasury auction results including bills, notes, bonds, TIPS, and FRNs with high yield, total tendered, and total accepted amounts.

🎯 Target Audience	💡 Primary Use Cases
📊 Quant analysts	Pull series into backtests and dashboards
💼 Finance teams	Snapshot rates, balances, and statistics
🤖 ML engineers	Build economic feature datasets
📰 Financial journalists	Verify official numbers fast
👩‍💻 Developers	Mirror the source into your own DB without writing client code
🎓 Researchers	Reproducible economic data pulls

📋 What the US Treasury Auctions Scraper does

• Calls the official US Treasury Auctions endpoint with the parameters you supply.
• Parses the response and flattens each record into one row.
• Casts numeric fields to numbers so they import cleanly into BI tools.
• Surfaces upstream errors as a clean error record instead of crashing.
• Streams results to the Apify dataset for instant download.

💡 Why it matters: Official sources publish raw feeds that are hard to consume. This actor normalises the response so the data drops straight into pandas, BigQuery, or a Google Sheet.

🎬 Full Demo

🚧 Coming soon.

⚙️ Input

Field	Type	Required	Description
securityType	string	No	Filter by security type.
startDate	string	No	Filter auctions on/after YYYY-MM-DD.
maxItems	integer	No	Free users 10, paid users up to 1,000,000. Prefill 10.

Example 1:

{
  "startDate": "2026-01-01",
  "maxItems": 10
}

⚠️ Good to Know: Free users are auto-limited to 10 records as a preview. Paid users get up to 1,000,000.

📊 Output

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

Field	Type	Description
🏷️ Security Type security_type	string	Bill, Note, Bond, TIPS, FRN.
⏱️ Term term	string	Original term.
📅 Auction Date auction_date	string	Auction date.
📅 Issue Date issue_date	string	Issue date.
🔧 CUSIP cusip	string	CUSIP identifier.
📈 High Yield high_yield	number	High yield (percent).
💰 Total Tendered total_tendered	number	Total amount tendered.
✅ Total Accepted total_accepted	number	Total amount accepted.
🕒 scrapedAt	string	When this row was fetched.
❌ error	string	Set if the upstream response was an error.

Sample record:

{
  "security_type": "Bill",
  "term": "4-Week",
  "auction_date": "2026-06-03",
  "issue_date": "2026-06-05",
  "cusip": "912797HK4",
  "high_yield": 5.295,
  "total_tendered": 197654000000,
  "total_accepted": 75000000000,
  "scrapedAt": "2026-06-05T13:00:00.000Z",
  "error": null
}

✨ Why choose this Actor

| 🆓 | Works with the free Apify tier. | | 🧹 | Clean, snake_case keys ready for BI. | | 🔢 | Auto-casts numeric strings to real numbers. | | 🛟 | Surfaces upstream errors as a clean error record. | | 💾 | Push to dataset, instant CSV / Excel / JSON / XML / HTML export. |

📈 How it compares to alternatives

Approach	Setup time	Clean keys	Numeric casting	Error handling
Roll your own fetch	30 min +	❌	❌	❌
Custom Python script	1 hr install + script	✅	partial	partial
This Actor	5 sec, no install	✅	✅	✅

🚀 How to use

1. Click Try for free.
2. Adjust the inputs or leave defaults.
3. Click Start. Within seconds, your dataset is ready, download as CSV, Excel, JSON, or XML, or pipe to your warehouse.

💼 Business use cases

📊 Backtesting and quant research. Pull series for your watchlist into a single table, feed pandas, run your strategy.

💼 Treasury and risk. Schedule a daily run and pipe to your finance dashboard.

📰 Newsroom fact-checking. Reporters can verify a published number for a story in 30 seconds.

🤖 ML feature engineering. Build a clean training set of economic features for any model.

🔌 Automating US Treasury Auctions Scraper

• Make and Zapier: trigger this actor on a schedule, push results to Airtable, Google Sheets, or Slack.
• Cron schedule: native Apify scheduler, run on any cadence.
• Webhooks: get a POST to your endpoint the moment a run finishes.
• Pipe to BigQuery / Snowflake / Postgres: native Apify integrations move datasets straight into your warehouse.

🌟 Beyond business use cases

🎓 Education. Teach a finance class with reproducible, real-world datasets.

🧪 Personal research. Track your own portfolio, compute custom indicators, plot them in your favourite tool.

🤝 Non-profit and open data. Build public dashboards without writing client code.

🧰 Tinkering and prototyping. Spin up a feed in 5 seconds to test a new chart library.

🤖 Ask an AI assistant about this scraper

Pop this README into ChatGPT, Claude, or any AI assistant and ask it to map your specific workflow to the actor inputs. The schema, examples, and field list above contain everything an LLM needs to design a working pipeline.

❓ Frequently Asked Questions

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

❓ Is there a rate limit? Sources may rate-limit. This actor surfaces any rate-limit notes as a clean error record.

❓ Are values cast to numbers? Yes.

❓ Can I schedule runs? Yes, use Apify native scheduler or hook this up to Make / Zapier / cron.

❓ Is this scraping or API? API. The endpoint is fully public; we are only normalising the response.

❓ Will the schema change? Core fields are stable. New upstream fields will be passed through as added.

❓ What format can I download? CSV, Excel, JSON, JSONL, XML, RSS, or HTML straight from the Apify dataset UI.

❓ Can I use this commercially? Yes, subject to the source terms of service.

❓ Why is my run only 10 items? Free plan preview limit. Upgrade for up to 1,000,000.

❓ How fresh is the data? As fresh as the upstream endpoint publishes.

🔌 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 API or webhook endpoint. Trigger runs from a calendar event, a form submission, a cron job, or pipe results straight into BigQuery, Snowflake, or a Postgres warehouse.

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