Historical FX rates and time series in one call

One call to /v1/range returns a data array with one row per published day in your window, for as many currencies as you pass in symbols. No looping required. Each row carries its own date, rates, source, and is_forward_filled.

The range endpoint

GET /v1/range takes four query parameters: base, symbols, start_date, and end_date. All four are required. symbols is a comma-separated list of currency codes. The response has a data key: an array of daily rows, plus has_more and next_cursor for paging through long ranges.

$ curl -G "https://api.exchangerate.dev/v1/range" \
    -H "Authorization: Bearer exr_live_..." \
    --data-urlencode "base=USD" \
    --data-urlencode "symbols=EUR,GBP" \
    --data-urlencode "start_date=2026-06-10" \
    --data-urlencode "end_date=2026-06-13"

Each element of data is a self-contained daily row with its own date, rates, source, and is_forward_filled:

{
  "result": "success",
  "base": "USD",
  "start_date": "2026-06-10",
  "end_date": "2026-06-13",
  "data": [
    { "date": "2026-06-10", "rates": { "EUR": 0.86663, "GBP": 0.74727 },
      "source": "ecb_daily", "is_forward_filled": false },
    { "date": "2026-06-11", "rates": { "EUR": 0.86678, "GBP": 0.74829 },
      "source": "ecb_daily", "is_forward_filled": false },
    { "date": "2026-06-12", "rates": { "EUR": 0.86453, "GBP": 0.74613 },
      "source": "ecb_daily", "is_forward_filled": false }
  ],
  "has_more": false,
  "next_cursor": null
}

Note that the Saturday (2026-06-13) is absent. Reference sources publish on business days only, so the range returns the published days in the window rather than one row per calendar day.

Python example

The same request in Python with requests. Iterate the data array, reading each row by key:

import requests

API = "https://api.exchangerate.dev/v1"
KEY = "exr_live_..."   # free key at https://exchangerate.dev/signup

params = {
    "base": "USD",
    "symbols": "EUR,GBP",
    "start_date": "2026-06-10",
    "end_date": "2026-06-13",
}

resp = requests.get(
    f"{API}/range",
    headers={"Authorization": f"Bearer {KEY}"},
    params=params,
    timeout=10,
)
resp.raise_for_status()
data = resp.json()

for row in data["data"]:
    filled = row["is_forward_filled"]
    print(row["date"], row["rates"]["EUR"], row["rates"]["GBP"], "filled" if filled else "")

The is_forward_filled flag

Every row carries is_forward_filled. For a normal business day it is false: that day had a published fix. It is true only when a row repeats the prior value because no fix was published on a day the range still includes, such as a recognised public holiday. Weekends are simply not present as rows.

/v1/range vs looping /v1/{date}/{base}

For a single day, /v1/{date}/{base} is the right call: it is simple, cacheable, and carries is_forward_filled at the response root. For anything spanning more than one date, /v1/range returns the whole series in one round trip.

History back to 1999

The ECB EXR series and FRED daily data go back to 1999 for many pairs. You can pass any start_date in that range. The source field on each row tells you which dataset powered it: ecb_daily, fred_daily, or live.

Loading into pandas

The data array loads into a DataFrame with pd.json_normalize, which flattens the nested rates object into rates.EUR, rates.GBP, and so on:

import pandas as pd

# data["data"] is the list of daily rows from the API
df = pd.json_normalize(data["data"])
df["date"] = pd.to_datetime(df["date"])
df = df.set_index("date").sort_index()

# keep only rows that were actually published that day
df = df[~df["is_forward_filled"]]

print(df[["rates.EUR", "rates.GBP"]].tail())