For almost four decades, TraderMade has been at the forefront of empowering diverse users, ranging from banks and tech startups to individuals worldwide, with top-tier Forex data. Amidst the evolving technical landscape, one constant has prevailed: our commitment to providing the highest quality Forex data.

The Evolution of Excellence

In the pre-internet era, TraderMade pioneered the sale of charts to banks. Today, with thousands of global users, we've adapted to the changing times while steadfastly prioritizing accuracy and reliability in Forex data.

The Five Pillars of Quality Forex Data

Accuracy: Integrating a subpar Forex API can cripple your trading platform. Stale and skewed data leads to uninformed decisions. TraderMade's rates are consistently up-to-date, accurately portraying the foreign exchange market.

Latency: In the modern age, users demand real-time updates in milliseconds. TraderMade delivers real-time Forex data through WebSockets, FIX protocol, and REST API instantly, ensuring you receive the latest exchange rate movements.

Frequency: Avoid synthetic updates and stale data. Our high-frequency tick Forex data feed provides hundreds of real-time quotes per minute, requiring dedication and effort to maintain accuracy.

Robustness: Even the best feed is only helpful with a resilient infrastructure. Our AWS-based system ensures 99.99% uptime, granting flexibility and scalability to handle high volumes of user traffic seamlessly.

Support: In an era of automation, technical glitches can leave you stranded. TraderMade takes pride in swift response times, addressing customer queries within minutes or hours, setting us apart with unparalleled support.

The Worth of Quality Forex Data

While many market data companies cater to big firms with hefty data costs, TraderMade is rewriting the narrative. Due to high costs, small and medium enterprises, researchers, and startups should not be excluded. Our mission is to enable access to accurate Forex data backed by cutting-edge technology at a reasonable price.

For SMEs: We offer flexible subscription plans tailored to practical data needs, reducing costs for low usage and fewer instruments.

For Researchers and Startups: Access heavily discounted Forex data, empowering you to explore and innovate without breaking the bank.

Let us briefly understand the programmatic process to obtain or retrieve Forex data via TraderMade's Forex API using Python in the following short tutorial.

Prerequisites:

1. Basic Python Knowledge

2. Familiarity with Python fundamentals will enhance your understanding of the tutorial.

3. TraderMade API Key

4. Sign up on TraderMade to obtain your exclusive API key. It's your ticket to the fast-paced world of real-time Forex data.

Let's Dive In:

Step 1: Setting Up the Python Environment

Ensure Python is installed on your machine. If not, head to Python's official website for a quick installation. You can also use Google Colab.

Step 2: Installing the Requests Library

Open your Google Colab or command prompt and install the requests library by typing:

pip install requests

Step 3: Crafting Your Python Script

Copy and paste the following code into your preferred code editor:

import requests

# Callback function to write data into a list

def write_callback(response, user_data):

user_data.append(response.decode('utf-8'))

def main():

api_url = "https://marketdata.tradermade.com/api/v1/live?currency=EURUSD,AUDUSD&api_key=API_KEY"

response_data = []

try:

response = requests.get(api_url, stream=True)

if response.status_code == 200:

for chunk in response.iter_content(chunk_size=1024):

write_callback(chunk, response_data)

response_text = "".join(response_data)

print("Received response:", response_text)

else:

print(f"Request failed with status code {response.status_code}")

except Exception as e:

print("An error occurred:", str(e))

if name == "__main__":

main()

Step 4: Replace YOUR_API_KEY

Replace YOUR_API_KEY in the api_url with the API key you received upon signing up with TraderMade.

Step 5: Running Your Script

Execute your code by running the following command in your terminal:

python your_script_name.py

Here’s the Output

{

"endpoint": "live",

"quotes": [

{

"ask": 1.07828,

"base_currency": "EUR",

"bid": 1.07826,

"mid": 1.07827,

"quote_currency": "USD"

},

{

"ask": 0.66063,

"base_currency": "AUD",

"bid": 0.66062,

"mid": 0.66063,

"quote_currency": "USD"

}

],

"requested_time": "Fri, 08 Dec 2023 11:53:19 GMT",

"timestamp": 1702036400

}

What You'll Gain:

• Live Data Integration: Learn the art of integrating live Forex data seamlessly into your Python scripts.

• Real-Time Stream Handling: Dive into efficiently handling streaming data, ensuring optimal memory usage.

• Error Resilience: Master the skills of robust error handling, ensuring your script gracefully manages unexpected situations.

In Conclusion

Congratulations! You've just opened the door to possibilities in Forex trading with Python. This tutorial is your launchpad – leverage this newfound knowledge to build sophisticated digital solutions and analyze market trends.

This article has unraveled the five critical factors defining high-quality Forex data. TraderMade is a beacon of reliability, providing accurate data that satisfies these factors. Choose us as your data partner and unlock the Forex data at a fraction of the cost, tailored to your unique data requirements.

Elevate your experience with TraderMade – where quality meets affordability. Happy coding!