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Comparison

Best Currency API for Python Developers (2026)

By Madhushan May 24, 2026 12 min read
Reviewed by Madhushan, Fintech Developer — May 2026
Python programming code on screen

Python dominates in fintech, data science, and backend development. If your Python application needs exchange rate data — whether for a Django e-commerce store, a Flask microservice, a data pipeline, or a Jupyter notebook — you need a currency API that integrates cleanly with the Python ecosystem.

The problem: most currency APIs were not built with Python developers in mind. They offer no SDK, no type hints, and force you to write boilerplate HTTP code with requests or httpx for every call. Some have Python wrappers maintained by third parties that break when the API changes. Others cap their free tier at 100 requests per month, which is barely enough for local development.

This article compares the 6 most popular currency exchange rate APIs for Python in 2026 and shows you exactly how to integrate each one. Spoiler: AllRatesToday is the clear winner for Python developers, with an official PyPI package, real-time mid-market rates, and a free tier that does not require a credit card.

Side-by-Side Comparison

Here is an honest look at how the top 6 currency APIs stack up for Python developers:

API Python SDK Free Tier Real-Time Historical Data
AllRatesToday Official (PyPI) Free tier, no CC Yes (60s) Yes
Open Exchange Rates Community only 1,000 req/mo Hourly Paid only
Fixer.io No 100 req/mo No (daily) Paid only
CurrencyAPI Official 300 req/mo No (daily) Paid only
Frankfurter No Unlimited No (daily ECB) Yes (ECB only)
ExchangeRate-API No 1,500 req/mo No (daily) Paid only

Key takeaway: AllRatesToday is the only API on this list that offers an official Python SDK on PyPI, real-time rates updated every 60 seconds, historical data on the free tier, and no credit card requirement.

1. AllRatesToday — Best Overall for Python

AllRatesToday was built API-first with official SDKs for Python, JavaScript, and PHP. The Python package is published on PyPI, maintained by the AllRatesToday team, and provides a clean, Pythonic interface with proper type annotations.

Install the SDK

pip install allratestoday

Or with a virtual environment (recommended):

python -m venv venv
source venv/bin/activate  # Linux/macOS
pip install allratestoday

Get a single exchange rate

from allratestoday import AllRatesToday

client = AllRatesToday("YOUR_API_KEY")

# Fetch real-time USD to EUR rate
rate = client.get_rate("USD", "EUR")
print(f"1 USD = {rate} EUR")

Convert an amount

result = client.convert("USD", "EUR", 1000)
print(f"$1,000 = €{result['result']}")
print(f"Rate used: {result['rate']}")
print(f"Timestamp: {result['time']}")

Fetch historical rates

history = client.get_historical_rates("USD", "EUR", "30d")

for point in history["rates"]:
    print(f"{point['time']}: {point['rate']}")

Using requests directly (no SDK)

If you prefer raw HTTP calls, the REST API is straightforward:

import requests

API_KEY = "YOUR_API_KEY"
BASE_URL = "https://allratestoday.com/api/v1"

# Get USD to EUR rate
response = requests.get(
    f"{BASE_URL}/rates",
    params={"source": "USD", "target": "EUR"},
    headers={"Authorization": f"Bearer {API_KEY}"}
)

data = response.json()
print(f"1 USD = {data['rate']} EUR")
print(f"Updated: {data['time']}")

Batch rates for multiple currencies

import requests

API_KEY = "YOUR_API_KEY"

# Get all rates against USD
response = requests.get(
    "https://allratestoday.com/api/v1/rates",
    params={"source": "USD"},
    headers={"Authorization": f"Bearer {API_KEY}"}
)

rates = response.json()
for currency, rate in rates["rates"].items():
    print(f"USD/{currency}: {rate}")

PyPI: allratestoday — View on GitHub

2. Open Exchange Rates

Open Exchange Rates has been around since 2012 and is one of the more established currency APIs. However, it has no official Python SDK. You need to use requests or a third-party wrapper like openexchangerates (community maintained).

import requests

APP_ID = "YOUR_APP_ID"

response = requests.get(
    "https://openexchangerates.org/api/latest.json",
    params={"app_id": APP_ID, "base": "USD"}
)

data = response.json()
eur_rate = data["rates"]["EUR"]
print(f"1 USD = {eur_rate} EUR")

3. Fixer.io

Fixer was popular in the early days but has fallen behind. It was acquired by APILayer and now sits behind a paywall for most useful features. There is no Python SDK.

import requests

API_KEY = "YOUR_API_KEY"

# Note: free tier is HTTP only, not HTTPS
response = requests.get(
    "http://data.fixer.io/api/latest",
    params={
        "access_key": API_KEY,
        "base": "EUR",  # Free tier: EUR base only
        "symbols": "USD,GBP,JPY"
    }
)

data = response.json()
print(data["rates"])

4. CurrencyAPI

CurrencyAPI (currencyapi.com) offers an official Python package, which puts it ahead of most competitors on developer experience. However, the free tier is very limited at 300 requests per month.

# pip install currencyapi
import currencyapi

client = currencyapi.Client("YOUR_API_KEY")

result = client.latest(
    base_currency="USD",
    currencies=["EUR", "GBP", "JPY"]
)

for code, info in result["data"].items():
    print(f"USD/{code}: {info['value']}")

5. Frankfurter

Frankfurter is a free, open-source API that wraps European Central Bank (ECB) data. It requires no API key, which makes it easy to get started. But it only covers about 30 currencies and updates once per business day when the ECB publishes rates at 16:00 CET.

import requests

# No API key needed
response = requests.get(
    "https://api.frankfurter.app/latest",
    params={"from": "USD", "to": "EUR,GBP,JPY"}
)

data = response.json()
print(f"Date: {data['date']}")
for currency, rate in data["rates"].items():
    print(f"USD/{currency}: {rate}")

6. ExchangeRate-API

ExchangeRate-API offers a simple REST interface with no SDK. The free tier gives 1,500 requests per month but only provides daily rates.

import requests

API_KEY = "YOUR_API_KEY"

response = requests.get(
    f"https://v6.exchangerate-api.com/v6/{API_KEY}/latest/USD"
)

data = response.json()
eur_rate = data["conversion_rates"]["EUR"]
print(f"1 USD = {eur_rate} EUR")
print(f"Last updated: {data['time_last_update_utc']}")

Using Exchange Rates in Pandas and Data Science

If you work with data in Python, you probably use pandas. Here is how to pull exchange rate data into a DataFrame using AllRatesToday:

import pandas as pd
from allratestoday import AllRatesToday

client = AllRatesToday("YOUR_API_KEY")

# Get historical rates for the past 90 days
history = client.get_historical_rates("USD", "EUR", "90d")

# Convert to DataFrame
df = pd.DataFrame(history["rates"])
df["time"] = pd.to_datetime(df["time"])
df.set_index("time", inplace=True)

# Basic statistics
print(df.describe())
print(f"\nAverage rate: {df['rate'].mean():.4f}")
print(f"Min rate: {df['rate'].min():.4f}")
print(f"Max rate: {df['rate'].max():.4f}")
print(f"Volatility (std): {df['rate'].std():.4f}")

Plotting exchange rate trends

import matplotlib.pyplot as plt

df["rate"].plot(
    figsize=(12, 6),
    title="USD/EUR Exchange Rate - Last 90 Days",
    ylabel="Rate",
    color="#2ed06e",
    linewidth=2
)

plt.tight_layout()
plt.savefig("usd_eur_trend.png", dpi=150)
plt.show()

Django Integration Example

A common use case is displaying localized prices in a Django e-commerce application. Here is a reusable utility:

# pricing/exchange.py
from allratestoday import AllRatesToday
from django.conf import settings
from django.core.cache import cache

client = AllRatesToday(settings.ALLRATESTODAY_API_KEY)

def get_exchange_rate(source: str, target: str) -> float:
    """Get exchange rate with 5-minute cache."""
    cache_key = f"fx_rate_{source}_{target}"
    rate = cache.get(cache_key)

    if rate is None:
        rate = client.get_rate(source, target)
        cache.set(cache_key, rate, timeout=300)  # Cache for 5 minutes

    return rate

def convert_price(amount: float, source: str, target: str) -> float:
    """Convert a price from one currency to another."""
    rate = get_exchange_rate(source, target)
    return round(amount * rate, 2)
# In your Django view or template tag
from pricing.exchange import convert_price

# Convert $99.99 USD to EUR
price_eur = convert_price(99.99, "USD", "EUR")
print(f"€{price_eur}")

Flask Microservice Example

Build a lightweight currency conversion endpoint with Flask:

from flask import Flask, request, jsonify
from allratestoday import AllRatesToday

app = Flask(__name__)
client = AllRatesToday("YOUR_API_KEY")

@app.route("/convert")
def convert():
    source = request.args.get("from", "USD")
    target = request.args.get("to", "EUR")
    amount = float(request.args.get("amount", 1))

    result = client.convert(source, target, amount)

    return jsonify({
        "from": source,
        "to": target,
        "amount": amount,
        "converted": result["result"],
        "rate": result["rate"],
        "timestamp": result["time"]
    })

if __name__ == "__main__":
    app.run(debug=True)

Test it:

curl "http://localhost:5000/convert?from=USD&to=EUR&amount=500"

FastAPI Async Example

For async Python applications, you can use httpx with the AllRatesToday REST API:

from fastapi import FastAPI
import httpx

app = FastAPI()
API_KEY = "YOUR_API_KEY"

@app.get("/rate/{source}/{target}")
async def get_rate(source: str, target: str):
    async with httpx.AsyncClient() as http:
        response = await http.get(
            "https://allratestoday.com/api/v1/rates",
            params={"source": source, "target": target},
            headers={"Authorization": f"Bearer {API_KEY}"}
        )
        data = response.json()
        return {
            "source": source,
            "target": target,
            "rate": data["rate"],
            "time": data["time"]
        }

Why AllRatesToday Wins for Python

After comparing all six APIs, here is why AllRatesToday is the best choice for Python developers:

Quick Reference

Start Building with Python and Real-Time Rates

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