How to Reduce Your Bright Data Bandwidth Usage

Bright Data is a top-tier proxy provider—but its bandwidth costs can escalate quickly if not carefully managed. Whether you're scraping product pages, monitoring SEO trends, or extracting social media data, excessive proxy traffic can burn through your budget. That’s why learning to monitor, optimize, and enhance your proxy setup is vital to efficient operations.

This guide will walk you through reducing your Bright Data bandwidth usage by first optimizing proxy requests using plain Python, and then showing how to supercharge efficiency using Scrapfly Proxy Saver. We'll cover everything from understanding Bright Data's proxy types, to tuning your scripts, to applying advanced optimizations with minimal configuration.

Understanding and Creating a Bright Data Proxy

Bright Data proxies come in several types—residential, datacenter, ISP, and mobile—each tailored for different scraping environments. Residential proxies mimic real users by routing requests through real devices, offering high stealth. Datacenter proxies offer better performance at a lower cost but are more detectable.

To start using a Bright Data proxy, you first need to create a zone:

http://brd-customer-USERNAME-zone-ZONENAME:PASSWORD@brd.superproxy.io:PORT

Steps to Create a Proxy Zone:

1. Log in to your Bright Data dashboard.
2. Navigate to Proxy Zones and click Add Zone.
3. Choose the desired proxy type: Residential, Datacenter, ISP, or Mobile.
4. Customize parameters such as rotation strategy, country targeting, and session persistence.
5. Copy the generated credentials and use them in your scraping scripts.

These proxy zones determine how your traffic is routed and how you're billed for bandwidth and requests. Understanding the differences between each type helps you choose the most cost-effective and appropriate one for your scraping goals.

Using Bright Data Proxies in Python

After creating your zone, you’ll receive a formatted proxy URL. You can use this with Python's standard urllib module for basic requests:

import urllib.request

proxy = 'http://brd-customer-USERNAME-zone-ZONENAME:PASSWORD@brd.superproxy.io:22225'
url = 'https://scrapfly.io/proxy-saver'

opener = urllib.request.build_opener(
    urllib.request.ProxyHandler({'http': proxy, 'https': proxy})
)

try:
    response = opener.open(url)
    print(response.read().decode())
except Exception as e:
    print(f"Error: {e}")

This setup ensures that all HTTP and HTTPS requests are routed through your configured Bright Data proxy. However, each request will include full page payloads, images, and headers—leading to significant bandwidth usage if not controlled.

Reducing Bandwidth in Python

Python gives you granular control over your requests. Here's how you can reduce overhead before reaching for external tools:

Reuse Connections with Sessions

Using a requests.Session() object maintains a persistent connection across multiple requests:

import requests

session = requests.Session()
session.proxies.update({
    'http': proxy,
    'https': proxy
})

for url in ['https://scrapfly.io/proxy-saver', 'https://scrapfly.io/blog/how-to-optimize-proxies/']:
    response = session.get(url)
    print(len(response.content))

This significantly reduces connection establishment time and redundant TCP handshakes.

Request Less Data

You don’t need every byte the server sends. Customize headers to exclude images, scripts, or compress output:

headers = {
    "User-Agent": "Mozilla/5.0",
    "Accept": "text/html",
    "Accept-Encoding": "gzip"
}

response = session.get("https://scrapfly.io/proxy-saver", headers=headers)

Cache Static Responses

If you're visiting static or semi-static pages, cache responses locally:

import os, hashlib

def get_cached_response(url):
    filename = f"/tmp/{hashlib.md5(url.encode()).hexdigest()}.cache"
    if os.path.exists(filename):
        with open(filename, 'rb') as f:
            return f.read()
    response = session.get(url)
    with open(filename, 'wb') as f:
        f.write(response.content)
    return response.content

Caching can reduce bandwidth by up to 90% when working with rarely updated pages.

Supercharge with Scrapfly Proxy Saver

Scrapfly Proxy Saver automates bandwidth-saving strategies without touching your codebase. It functions as a middleware between your scraping script and Bright Data, applying smart compression, routing, and stubbing on the fly.

Unlock Bandwidth & Latency Efficiency with Proxy Saver

Proxy Saver is designed for scale. Its optimizations deliver more value as your traffic grows. Even simple scraping tasks benefit from reduced costs and faster responses.

Key Features:

• Connection reuse to reduce TCP overhead
• Global public caching of common content
• Redirection and CORS caching
• Automatic blocking of telemetry and ad scripts
• Stubbing for large media like images and CSS
• Optimized TLS handshake and TCP connection pooling
• DNS pre-warming for quick domain resolution
• Failover and retry logic for higher reliability

All of these features are activated by default, but you can fine-tune behavior using parameters in the proxy username.

Example Integration with Python

import requests

proxy = {
    'http': 'http://proxyId-abc123-Timeout-10-FpImpersonate-chrome_win_130@proxy-saver.scrapfly.io:3333',
    'https': 'http://proxyId-abc123-Timeout-10-FpImpersonate-chrome_win_130@proxy-saver.scrapfly.io:3333'
}

response = requests.get('https://httpbin.dev/anything', proxies=proxy, verify=False)
print(response.json())

Configuration Options

Combine multiple settings like: proxyId-xyz-FpImpersonate-chrome_win_130-Timeout-8

Passing Parameters to Bright Data

Use the | separator to pass downstream proxy config:

proxyId-abc123|country-us:API_KEY@proxy-saver.scrapfly.io:3333

This allows full control over Scrapfly optimization and Bright Data zone behavior simultaneously.

Special Note on Rotating IPs

If you're using Bright Data with session rotation, enable the "Rotating Proxy" mode in Scrapfly’s dashboard to ensure traffic patterns are preserved and connection optimizations are adjusted accordingly.

Understanding Proxy Types

Choosing the right proxy type is just as important as using it efficiently. Each scraping scenario benefits from different proxy capabilities, and making the right selection can greatly impact your results.

Residential Proxies

Residential proxies use IP addresses provided by ISPs and linked to physical locations. They offer excellent authenticity and are ideal for accessing geo-blocked or sensitive content. However, they tend to be more expensive and should be used judiciously.

You can checkout our article about residential proxies:

Top 5 Residential Proxy Providers for Web Scraping

Comparison of top residential proxy providers for web scraping. Blocking rates, performance and general overview of what makes a good proxy.

Datacenter Proxies

Datacenter proxies originate from cloud-based data centers. They are fast and cost-effective but easier to detect. They work well for non-sensitive, high-volume tasks where occasional blocks are tolerable.

You can checkout our article about datacenter proxies:

The Best Datacenter Proxies in 2025: A Complete Guide

Explore the best datacenter proxies for 2025 including IPRoyal, shared vs dedicated options, and how to buy unlimited bandwidth proxies.

FAQs

How do I create a Bright Data proxy?

You create a zone in the dashboard, select your proxy type, and configure settings like geo-targeting and session duration.

How does Scrapfly Proxy Saver reduce bandwidth?

It compresses data, stubs static content, and caches responses. You can save up to 30% or more on data transfer.

Can I use Proxy Saver with Bright Data?

Yes. Just plug your Bright Data proxy into the Proxy Saver dashboard and route traffic through Scrapfly's endpoint.

Summary

Controlling proxy bandwidth usage is crucial for keeping scraping operations efficient and affordable. Start by optimizing your Bright Data usage with smart Python practices—like connection reuse, selective content fetching, and local caching. Then, amplify those gains using Scrapfly Proxy Saver’s powerful middleware that automates compression, fingerprint impersonation, connection reuse, and more.

Whether you’re scraping a few pages or handling millions of requests per day, these techniques ensure your proxy usage remains fast, efficient, and cost-effective.