Proxy Returns Incorrect Data: Causes and Solutions

You configured a scraper, started data collection, and ended up with prices from another region, outdated content, or someone else's page entirely. Let's explore why a proxy might return incorrect data and how to fix it.

1. Caching on the Proxy Side

The most common reason for outdated data is caching. Some proxy servers save website responses to reduce load and speed up performance. As a result, you receive data that is a week old instead of current information.

How to Recognize the Problem

• Data does not change upon repeated requests
• Prices or product availability do not match reality
• The Age header in the response shows a large value

Solution

Add headers that forbid caching:

import requests

headers = {
    'Cache-Control': 'no-cache, no-store, must-revalidate',
    'Pragma': 'no-cache',
    'Expires': '0'
}

response = requests.get(
    'https://example.com/prices',
    proxies={'http': proxy, 'https': proxy},
    headers=headers
)

If the provider still caches, append a random parameter to the URL:

import time

url = f'https://example.com/prices?_nocache={int(time.time())}'

2. Geolocation Mismatch

You request a proxy from Germany but receive prices in rubles. Or vice versa—you need Russian data, but the site shows content for the USA. This happens for several reasons.

Why Geolocation Does Not Match

Solution

Synchronize all request parameters with the desired geolocation:

# For scraping a German site
headers = {
    'Accept-Language': 'de-DE,de;q=0.9,en;q=0.8',
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)...'
}

# A clean session without cookies
session = requests.Session()
session.cookies.clear()

response = session.get(
    'https://example.de/preise',
    proxies={'http': german_proxy, 'https': german_proxy},
    headers=headers
)

Check the actual IP geolocation before scraping:

def check_proxy_geo(proxy):
    response = requests.get(
        'http://ip-api.com/json/',
        proxies={'http': proxy, 'https': proxy},
        timeout=10
    )
    data = response.json()
    return data.get('country'), data.get('city')

3. Issues with IP Rotation

When using residential proxies with automatic IP rotation, the IP changes between requests. This is useful for bypassing limits but creates problems when data consistency is required.

Typical Symptoms

• Pagination returns duplicates or skips items
• The shopping cart clears between requests
• Authorization drops mid-session
• A/B tests on the site show different page versions

Solution: Sticky Sessions

Most proxy providers support "sticky sessions"—the IP is maintained for a specific duration. This is usually configured via a parameter in the connection string:

# Example format with session ID (syntax depends on the provider)
proxy = 'http://user-session-abc123:pass@gate.provider.com:7777'

# All requests with the same session ID go through the same IP
for page in range(1, 10):
    response = requests.get(
        f'https://example.com/catalog?page={page}',
        proxies={'http': proxy, 'https': proxy}
    )

Important: A sticky session usually lasts 1-30 minutes. Plan your data collection so that related requests fit within this window.

4. Session and Cookie Violations

Modern websites actively use cookies for personalization. If your scraper doesn't handle them correctly, you will receive incorrect data—or be blocked entirely.

Common Mistakes

1. Ignoring Set-Cookie — the site cannot track the session
2. Reusing cookies with a different IP — suspicious behavior
3. Missing initial request — navigating directly to an internal page without "entering" via the homepage

The Correct Approach

import requests

def create_browser_session(proxy):
    session = requests.Session()
    session.proxies = {'http': proxy, 'https': proxy}
    
    # Simulate the first visit — receive cookies
    session.get('https://example.com/', headers={
        'User-Agent': 'Mozilla/5.0...',
        'Accept': 'text/html,application/xhtml+xml...',
        'Accept-Language': 'en-US,en;q=0.9'
    })
    
    # Now you can scrape with a valid session
    return session

session = create_browser_session(proxy)
data = session.get('https://example.com/api/prices').json()

5. Encoding and Compression Errors

Sometimes the data arrives correctly but is displayed incorrectly due to encoding or compression issues. This is especially relevant when working with Cyrillic and Asian languages.

Symptoms

• Gibberish instead of text: Цена instead of "Цена" (Price)
• Empty response when gzip is enabled
• Binary garbage instead of HTML

Solution

import requests

response = requests.get(url, proxies=proxies)

# Method 1: Automatic encoding detection
response.encoding = response.apparent_encoding
text = response.text

# Method 2: Forced encoding
text = response.content.decode('utf-8')

# Method 3: Disable compression (if the proxy breaks gzip)
headers = {'Accept-Encoding': 'identity'}
response = requests.get(url, proxies=proxies, headers=headers)

6. Hidden Blocks and Captchas

Not all blocks are obvious. A site might return HTTP 200 but substitute real data with a placeholder, cached content, or a page containing a captcha embedded within the standard HTML.

Signs of a Hidden Block

• The response size is suspiciously small or identical across different pages
• The HTML contains words like: captcha, challenge, blocked, access denied
• Expected elements (prices, descriptions, buttons) are missing
• JavaScript redirect to another page

Response Validation

def is_valid_response(response, expected_markers):
    """Checks if the response contains real data"""
    
    text = response.text.lower()
    
    # Check for blocking
    block_signals = ['captcha', 'blocked', 'access denied', 
                     'rate limit', 'try again later']
    for signal in block_signals:
        if signal in text:
            return False, f'Blocked: {signal}'
    
    # Check for expected data presence
    for marker in expected_markers:
        if marker.lower() not in text:
            return False, f'Missing: {marker}'
    
    # Check size (too small = placeholder)
    if len(response.content) < 5000:
        return False, 'Response too small'
    
    return True, 'OK'

# Usage
valid, reason = is_valid_response(response, ['price', 'add to cart'])
if not valid:
    print(f'Invalid response: {reason}')
    # Change proxy, wait, retry

For sites with serious bot protection, mobile proxies offer a better level of trust than datacenter ones.

7. Step-by-Step Diagnostics

When a proxy returns incorrect data, use this algorithm to find the cause:

Step 1: Isolate the Problem

# Compare responses: without proxy vs with proxy
def compare_responses(url, proxy):
    direct = requests.get(url)
    proxied = requests.get(url, proxies={'http': proxy, 'https': proxy})
    
    print(f'Direct:  {len(direct.content)} bytes, status {direct.status_code}')
    print(f'Proxied: {len(proxied.content)} bytes, status {proxied.status_code}')
    
    # Save both responses for comparison
    with open('direct.html', 'w') as f:
        f.write(direct.text)
    with open('proxied.html', 'w') as f:
        f.write(proxied.text)

Step 2: Check Response Headers

response = requests.get(url, proxies=proxies)

# Key headers for diagnostics
important_headers = ['content-type', 'content-encoding', 
                     'cache-control', 'age', 'x-cache', 
                     'cf-ray', 'server']

for header in important_headers:
    value = response.headers.get(header, 'not set')
    print(f'{header}: {value}')

Step 3: Checklist of Checks

Step 4: Full Diagnostic Script

import requests
import json

def diagnose_proxy(proxy, target_url):
    report = {}
    
    # 1. Check connectivity
    try:
        r = requests.get('http://httpbin.org/ip', 
                        proxies={'http': proxy, 'https': proxy},
                        timeout=15)
        report['proxy_ip'] = r.json().get('origin')
        report['proxy_works'] = True
    except Exception as e:
        report['proxy_works'] = False
        report['error'] = str(e)
        return report
    
    # 2. Geolocation
    r = requests.get('http://ip-api.com/json/',
                    proxies={'http': proxy, 'https': proxy})
    geo = r.json()
    report['country'] = geo.get('country')
    report['city'] = geo.get('city')
    
    # 3. Request to the target site
    r = requests.get(target_url,
                    proxies={'http': proxy, 'https': proxy},
                    timeout=30)
    report['status_code'] = r.status_code
    report['content_length'] = len(r.content)
    report['cached'] = 'age' in r.headers or 'x-cache' in r.headers
    
    # 4. Check for blocking
    block_words = ['captcha', 'blocked', 'denied', 'cloudflare']
    report['possibly_blocked'] = any(w in r.text.lower() for w in block_words)
    
    return report

# Usage
result = diagnose_proxy('http://user:pass@proxy:port', 'https://target-site.com')
print(json.dumps(result, indent=2))

Conclusion

Incorrect data from a proxy is almost always a solvable issue. In most cases, the cause lies in caching, geolocation mismatch, or incorrect session handling. Use the diagnostic script from this article to quickly find the source of the problem.

For tasks where geolocation accuracy and a low blocking rate are critical, residential proxies with sticky session support are optimal—learn more at proxycove.com.