Query the U.S. Treasury Fiscal Data API for federal financial data including national debt, government spending, revenue, interest rates, exchange rates, and savings bonds. Access 54 datasets and 182 data tables with no API key required. Use when working with U.S. federal fiscal data, national debt tracking (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates on Treasury securities, foreign exchange rates, savings bonds, or any U.S. government financial statistics.
Free, open REST API from the U.S. Department of the Treasury for federal financial data. No API key or registration required.
Base URL: https://api.fiscaldata.treasury.gov/services/api/fiscal_service
import requests
import pandas as pd
BASE_URL = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service"
# Get the current national debt (Debt to the Penny)
resp = requests.get(f"{BASE_URL}/v2/accounting/od/debt_to_penny", params={
"sort": "-record_date",
"page[size]": 1
})
data = resp.json()["data"][0]
print(f"Total public debt as of {data['record_date']}: ${float(data['tot_pub_debt_out_amt']):,.0f}")
# Get Treasury exchange rates for recent quarters
resp = requests.get(f"{BASE_URL}/v1/accounting/od/rates_of_exchange", params={
"fields": "country_currency_desc,exchange_rate,record_date",
"filter": "record_date:gte:2024-01-01",
"sort": "-record_date",
"page[size]": 100
})
df = pd.DataFrame(resp.json()["data"])
None required. The API is fully open and free.
| Parameter | Example | Description |
|---|---|---|
fields= | fields=record_date,tot_pub_debt_out_amt | Select specific columns |
filter= | filter=record_date:gte:2024-01-01 | Filter records |
sort= | sort=-record_date | Sort (prefix - for descending) |
format= | format=json | Output format: json, csv, xml |
page[size]= | page[size]=100 | Records per page (default 100) |
page[number]= | page[number]=2 | Page index (starts at 1) |
Filter operators: lt, lte, gt, gte, eq, in
# Multiple filters separated by comma
"filter=country_currency_desc:in:(Canada-Dollar,Mexico-Peso),record_date:gte:2024-01-01"
| Dataset | Endpoint | Frequency |
|---|---|---|
| Debt to the Penny | /v2/accounting/od/debt_to_penny | Daily |
| Historical Debt Outstanding | /v2/accounting/od/historical_debt_outstanding | Annual |
| Schedules of Federal Debt | /v1/accounting/od/schedules_fed_debt | Monthly |
| Dataset | Endpoint | Frequency |
|---|---|---|
| DTS Operating Cash Balance | /v1/accounting/dts/operating_cash_balance | Daily |
| DTS Deposits & Withdrawals | /v1/accounting/dts/deposits_withdrawals_operating_cash | Daily |
| Monthly Treasury Statement (MTS) | /v1/accounting/mts/mts_table_1 (16 tables) | Monthly |
| Dataset | Endpoint | Frequency |
|---|---|---|
| Average Interest Rates on Treasury Securities | /v2/accounting/od/avg_interest_rates | Monthly |
| Treasury Reporting Rates of Exchange | /v1/accounting/od/rates_of_exchange | Quarterly |
| Interest Expense on Public Debt | /v2/accounting/od/interest_expense | Monthly |
| Dataset | Endpoint | Frequency |
|---|---|---|
| Treasury Securities Auctions Data | /v1/accounting/od/auctions_query | As Needed |
| Treasury Securities Upcoming Auctions | /v1/accounting/od/upcoming_auctions | As Needed |
| Average Interest Rates | /v2/accounting/od/avg_interest_rates | Monthly |
| Dataset | Endpoint | Frequency |
|---|---|---|
| I Bonds Interest Rates | /v2/accounting/od/i_bond_interest_rates | Semi-Annual |
| U.S. Treasury Savings Bonds: Issues, Redemptions & Maturities | /v1/accounting/od/sb_issues_redemptions | Monthly |
{
"data": [...],
"meta": {
"count": 100,
"total-count": 3790,
"total-pages": 38,
"labels": {"field_name": "Human Readable Label"},
"dataTypes": {"field_name": "STRING|NUMBER|DATE|CURRENCY"},
"dataFormats": {"field_name": "String|10.2|YYYY-MM-DD"}
},
"links": {"self": "...", "first": "...", "prev": null, "next": "...", "last": "..."}
}
Note: All values are returned as strings. Convert as needed (e.g., float(), pd.to_datetime()). Null values appear as the string "null".
def fetch_all_pages(endpoint, params=None):
params = params or {}
params["page[size]"] = 10000 # max size to minimize requests
resp = requests.get(f"{BASE_URL}{endpoint}", params=params)
result = resp.json()
df = pd.DataFrame(result["data"])
return df
Omitting grouping fields triggers automatic aggregation:
# Sum all deposits/withdrawals by record_date and transaction type
resp = requests.get(f"{BASE_URL}/v1/accounting/dts/deposits_withdrawals_operating_cash", params={
"fields": "record_date,transaction_type,transaction_today_amt"
})