5 Best Ways to Get Real-Time Currency Exchange Rates in Python

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💡 Problem Formulation: Traders, businesses, and travelers are among those needing real-time currency exchange rates for accurate financial assessments and planning. This article is designed to solve the problem of accessing live currency conversion rates using Python. For example, if the input is a request to find the exchange rate between the US Dollar (USD) and the Euro (EUR), the desired output is the current exchange rate value against these currencies.

Method 1: Using forex-python Library

The forex-python library is an easy-to-use tool which provides several functionalities to work with different financial indicators including currency exchange. It interfaces with various free APIs for real-time rates and can be used effortlessly to get the latest exchange rates.

Here’s an example:

from forex_python.converter import CurrencyRates

c = CurrencyRates()
rate = c.get_rate('USD', 'EUR')
print(rate)

Output: 0.8915 (Note: this value changes with the real-time exchange rate.)

This code snippet creates an instance of the CurrencyRates class and uses its get_rate method to fetch the current exchange rate from USD to EUR, printing the result. The forex-python library takes care of all HTTP requests and parsing the response.

Method 2: Using requests and a Free API Service (ex: ExchangeRate-API)

For greater control over the currency exchange process, you can use the requests library along with a free API service such as ExchangeRate-API. This requires signing up for an API key but allows for more custom requests and direct integration with your application.

Here’s an example:

import requests

api_key = 'Your-API-Key'
url = f'https://v6.exchangerate-api.com/v6/{api_key}/latest/USD'
response = requests.get(url)
data = response.json()
print(data['conversion_rates']['EUR'])

Output: 0.8915 (Note: this value changes with the real-time exchange rate.)

This code sends a GET request to the ExchangeRate-API service endpoint for the latest USD exchange rates. The resulting JSON response is parsed to extract the exchange rate for the EUR, which is printed out.

Method 3: Using pandas and pandas_datareader

The pandas library in conjunction with pandas_datareader can be utilized to obtain financial data, including exchange rates. This method leverages the datareader to fetch data from various financial sources to obtain up-to-date currency conversion rates.

Here’s an example:

import pandas as pd
from pandas_datareader import data as pdr

exchange_rate = pdr.get_data_fred('DEXUSEU')
latest_rate = exchange_rate.iloc[-1]
print(latest_rate)

Output: DEXUSEU 0.8915 (Note: the exchange rate will vary with real-time data.)

This code example utilizes the pandas_datareader’s get_data_fred function to fetch the latest exchange rates between the USD and EUR from FRED (Federal Reserve Economic Data). The last record is considered to be the most current exchange rate.

Method 4: Using openexchangerates.org API

Open Exchange Rates provides a simple and robust API for live and historical foreign exchange (forex) rates. Using their API endpoints, you can retrieve real-time exchange rate data by making HTTP requests, after obtaining an API key.

Here’s an example:

import requests

app_id = 'Your-APP-ID'
url = f'https://openexchangerates.org/api/latest.json?app_id={app_id}'
response = requests.get(url)
data = response.json()
print(data['rates']['EUR'])

Output: 0.8915 (Note: this value will fluctuate based on current market conditions.)

In this code snippet, an HTTP GET request is sent to openexchangerates.org using the requests library. The retrieved data, in JSON format, includes live currency exchange rates, from which we extract and print the EUR rate.

Bonus One-Liner Method 5: Using curl in Python

For a quick and dirty one-liner shell command within Python, you can use the subprocess module to invoke curl, which makes an HTTP request to a currency exchange API service like exchangeratesapi.io.

Here’s an example:

import subprocess

command = 'curl "https://api.exchangeratesapi.io/latest?base=USD"'
result = subprocess.run(command, shell=True, stdout=subprocess.PIPE)
print(result.stdout)

Output: {“rates”:{“EUR”:0.8915},”base”:”USD”,”date”:”2023-04-01″} (Output will vary with live rates)

This terminal command uses curl to fetch the current currency exchange rate from USD to other currencies, including EUR, and then prints the response. The actual HTTP request handling is done via the shell, making this method less robust and secure compared to native Python solutions.

Summary/Discussion

  • Method 1: Using forex-python Library. Strengths: Easy to use, does not require an API key. Weaknesses: Limited by the free APIs it uses, which might have rate limits or be less reliable.
  • Method 2: Using requests and a Free API Service. Strengths: Provides more control over API usage, can access more comprehensive data. Weaknesses: Requires obtaining an API key, and you may face rate limiting based on your subscription.
  • Method 3: Using pandas and pandas_datareader. Strengths: Integrates well with other financial data analysis workflows in pandas. Weaknesses: Limited to the sources that pandas_datareader can access, data may not be in real-time.
  • Method 4: Using openexchangerates.org API. Strengths: Reliable and simple API with wide currency support. Weaknesses: Requires an API key, the free plan may come with limitations.
  • Method 5: Bonus One-Liner. Strengths: Quick invocation of a command without writing extensive code. Weaknesses: Security risks with shell=True, less control over response handling.