To solve the problem of 403 errors in web scraping, here are the detailed steps you can take:

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Step 1: Understand the 403 Forbidden Error: This HTTP status code means the server understands your request but refuses to authorize it. It’s often a defense mechanism against bots.
Step 2: User-Agent Rotation:
- Identify Your Current User-Agent: Use a tool like httpbin.org/user-agent to see what your scraper is sending.
- Gather a List of Common Browser User-Agents: Search online for “most common browser user-agents” or “user-agent strings for web scraping.”
- Implement Rotation: In your Python code using requests, set a User-Agent header for each request. For example: headers = {'User-Agent': 'Mozilla/5.0 Windows NT 10.0. Win64. x64 AppleWebKit/537.36 KHTML, like Gecko Chrome/91.0.4472.124 Safari/537.36'}. Rotate this header with each request or after a certain number of requests. Libraries like fake-useragent can simplify this.
Step 3: Proxy Servers:
- Understand Why Proxies Help: They mask your original IP address, making it seem like requests are coming from different locations.
- Choose a Proxy Type: Residential proxies more expensive, higher trust are generally better than data center proxies cheaper, easier to detect.
- Integrate Proxies: If using requests in Python: proxies = {'http': 'http://user:pass@ip:port', 'https': 'https://user:pass@ip:port'}. Pass this to requests.geturl, proxies=proxies. Rotate these frequently.
Step 4: Respect robots.txt: Before scraping, always check the robots.txt file e.g., example.com/robots.txt. This file outlines rules for bots. Disregarding it can lead to blocks and ethical issues.
Step 5: Add Other Request Headers:
- Accept-Language: Mimic a real browser, e.g., 'Accept-Language': 'en-US,en.q=0.9'.
- Referer: Make it appear you came from a legitimate page, e.g., 'Referer': 'https://www.google.com/'.
- Accept-Encoding: 'Accept-Encoding': 'gzip, deflate, br'.
- Connection: 'Connection': 'keep-alive'.
Step 6: Introduce Delays and Randomization:
- Time Delays time.sleep: Don’t hammer the server. Add random delays between requests, e.g., time.sleeprandom.uniform2, 5.
- Randomize Request Patterns: Vary the order or timing of your requests slightly.
Step 7: Handle Cookies and Sessions:
- Maintain Sessions: Use requests.Session to persist cookies across requests. This helps mimic a real user’s browsing experience.
- Inspect and Use Cookies: Sometimes, websites set specific cookies that authenticate your request. You might need to inspect network traffic to identify these and include them.
Step 8: Headless Browsers for advanced cases:
- When to Use: If basic header/proxy rotation isn’t enough, and the site uses advanced JavaScript rendering or sophisticated anti-bot measures.
- Tools: Libraries like Selenium or Playwright can control a real browser headless Chrome/Firefox, executing JavaScript and handling dynamic content. This is resource-intensive but very effective.
Step 9: CAPTCHA Solving Services:
- When Needed: If the website presents CAPTCHAs as a defense.
- Services: Third-party services e.g., 2Captcha, Anti-Captcha can integrate with your scraper to solve CAPTCHAs programmatically. This adds cost.
Step 10: Error Handling and Retries: Implement robust try-except blocks to catch 403 errors. When a 403 occurs, rotate your IP/User-Agent, increase delays, and retry the request.

Remember, while these techniques can bypass 403 errors, always act ethically.

Excessive scraping or violating terms of service can lead to permanent bans or legal issues.

Focus on gathering information for beneficial, permissible purposes, and consider if there’s an API available first.

Table of Contents

Understanding the 403 Forbidden Error in Web Scraping

The “403 Forbidden” HTTP status code is a frequent hurdle for web scrapers.

It signifies that the server understands the request but refuses to authorize it.

Unlike a 404 Not Found or 500 Server Error, a 403 means the resource exists, but you, as the client, lack the necessary permissions to access it.

From an ethical standpoint, it’s crucial to acknowledge that a 403 often indicates a website’s explicit desire to prevent automated access to certain content.

While there are technical methods to bypass these, one must always weigh the permissibility and the implications of such actions. Cloudscraper 403

Why Do Websites Issue 403 Errors?

Websites employ 403 errors as a frontline defense against various unwanted activities, particularly web scraping.

Their primary aim is to protect resources, maintain server stability, and prevent data exploitation.

Server Protection: Excessive requests from a single IP address can strain server resources, leading to slow performance or even denial of service. By blocking suspicious activity, servers can maintain their uptime and responsiveness for legitimate users.
Data Security and Privacy: For sensitive data, a 403 error acts as a gatekeeper, preventing unauthorized access. This is especially true for user-specific data or content that requires authentication.
Content Licensing and Copyright: Websites may have licensing agreements for their content that restrict automated data extraction. Issuing 403s helps them enforce these agreements and protect their intellectual property. According to a 2022 survey by Cheq, 68% of businesses reported suffering significant financial losses due to bot attacks, highlighting the economic impact that such unauthorized access can have.
Terms of Service ToS Violations: Many websites explicitly prohibit automated scraping in their ToS. A 403 is one way they enforce these rules, sending a clear message that such activity is not permitted.
Anti-Bot Mechanisms: Sophisticated anti-bot solutions analyze request patterns, headers, and client behavior to identify and block non-human traffic. When these systems flag your scraper as a bot, a 403 is often the immediate consequence. In fact, studies show that nearly 90% of all website traffic is now attributable to bots, with a significant portion being malicious, underscoring the need for robust anti-bot measures.

Common Scenarios Leading to 403 Errors

Understanding the common triggers for 403 errors can help in diagnosing and addressing the issue in your scraping endeavors.

Missing or Suspicious User-Agent: The User-Agent header identifies your client e.g., Chrome, Firefox. If this header is missing or indicates a known bot e.g., Python-requests/2.26.0, many websites will immediately flag it and return a 403.
Rate Limiting Exceeded: Sending too many requests in a short period from the same IP address is a classic trigger. Websites implement rate limits to prevent server overload. Once you hit this limit, subsequent requests from your IP may be met with a 403. Many websites set a limit of around 60 requests per minute from a single IP, but this varies widely.
IP Address Blacklisting: If your IP address has been previously identified as malicious or associated with excessive scraping, it might be blacklisted, resulting in persistent 403 errors.
Lack of Necessary Headers: Beyond the User-Agent, other headers like Referer, Accept-Language, Accept-Encoding, or Connection can be crucial. If these are missing or inconsistent with typical browser behavior, your request might be flagged.
Cookie/Session Mismatch: Websites often use cookies to track user sessions. If your scraper doesn’t handle cookies correctly or presents an invalid session, it can appear as an unauthorized access attempt.
Geographical Restrictions: Some content is geo-restricted. If your IP address originates from a disallowed region, a 403 might be served. For instance, according to data from Statista, over 30% of online content worldwide is subject to some form of geo-restriction.
Honeypot Traps: Websites sometimes embed hidden links or elements specifically designed to trap bots. If your scraper follows these, it immediately signals automated behavior and can lead to a block.

Ethical Considerations and Permissible Alternatives

Before into technical solutions for bypassing 403 errors, it’s paramount to reflect on the ethical and permissible implications of web scraping.

As responsible individuals, our actions should align with principles of honesty, integrity, and respect for others’ property. Python screenshot

Engaging in activities that disrespect website terms of service or consume excessive resources without permission can be viewed as an impingement on the rights of others.

The Impermissibility of Aggressive Scraping

Aggressive web scraping, particularly when it disregards website terms of service, server load, or intellectual property rights, can be problematic.

This is not merely a technical challenge but also an ethical dilemma.

Disregard for Terms of Service ToS: Many websites explicitly state in their ToS that automated scraping is prohibited. Bypassing a 403 error when the ToS forbids scraping is akin to ignoring a clear boundary set by the website owner. This can be seen as a breach of trust and an act of taking something that is not freely offered for such use. A notable example is the LinkedIn vs. hiQ Labs case, where a court ruled that public data on LinkedIn was not protected by the Computer Fraud and Abuse Act, yet LinkedIn’s ToS still restricted scraping, leading to ongoing legal debates about the enforceability of ToS in data access.
Excessive Server Load and Resource Consumption: Repeated, rapid requests can overwhelm a server, leading to slow performance or even crashes for legitimate users. This is a form of digital harm, disrupting services for others. It is akin to flooding a public space and making it unusable for its intended purpose. In 2023, cybersecurity firm Cloudflare reported that large-scale bot attacks could generate up to 2.8 billion requests per hour, capable of crippling even robust server infrastructures.
Intellectual Property Infringement: Scraping and then republishing copyrighted content without permission can lead to legal issues related to intellectual property. Even if the data is “publicly available,” its reproduction or commercial use might require specific licensing.
Data Privacy Concerns: While the immediate concern with 403s is access, persistent scraping can sometimes inadvertently gather or expose personal data, even if anonymized. This raises significant privacy concerns.

Permissible and Ethical Alternatives to Scraping

Instead of resorting to aggressive scraping techniques that could be ethically questionable, consider these permissible and beneficial alternatives that align with respectful and lawful data acquisition.

Official APIs Application Programming Interfaces: The most ethical and often most efficient way to access a website’s data is through its official API. Many websites provide APIs specifically for developers to access their data in a structured and controlled manner.
- Benefits: APIs are designed for automated access, come with clear documentation, usually offer structured data JSON, XML, and are less prone to breaking due to website changes. They also often include authentication mechanisms API keys that legitimize your access.
- Examples: Twitter API, Google Maps API, GitHub API, and countless others. For instance, Twitter’s API processes over 500 million tweets daily, demonstrating the scale and reliability of official data access channels.
RSS Feeds: For content updates news, blog posts, RSS feeds are an excellent, lightweight alternative. They provide a structured stream of new content, designed for subscription and syndication.
- Benefits: Easy to parse, real-time updates, minimal server load, and explicitly designed for automated consumption.
Partnering with Website Owners: If you need significant data that isn’t available via API, consider reaching out to the website owner directly. Propose a partnership or data-sharing agreement.
- Benefits: This builds trust, ensures you have legitimate access, and can lead to a mutually beneficial relationship. It’s also the most respectful approach. A study by the Data & Marketing Association found that companies with strong data-sharing partnerships report 15% higher revenue growth.
Public Datasets: Many organizations and governments publish vast datasets for public use. Before attempting to scrape, check if the data you need is already available in a compiled, ready-to-use format.
- Sources: Data.gov US government data, Kaggle data science community datasets, academic research repositories, World Bank Open Data, etc. Kaggle alone hosts over 200,000 public datasets, covering a wide array of topics.
Paid Data Services: Some companies specialize in providing aggregated, clean data from various sources. If your project has a budget, purchasing data from a reputable provider can save time, effort, and ethical dilemmas.
- Benefits: High-quality, validated data, legal compliance, and often tailored to specific industry needs.
Respectful, Rate-Limited Scraping with permission: In cases where no API or public dataset exists, and you’ve obtained explicit permission, apply extremely slow and rate-limited scraping. This means:
- Adhering to robots.txt strictly.
- Implementing very long, random delays between requests e.g., minutes, not seconds.
- Identifying yourself clearly in your User-Agent string e.g., MyCompanyNameBot/1.0 [email protected].
- Scraping only non-sensitive, publicly visible data that is not behind any login or paywall.
- Being prepared to stop immediately if requested by the website owner.

Ultimately, the best approach is always to seek legitimate and permissible means of data acquisition. Python parse html

This not only ensures ethical conduct but also often leads to more stable, reliable, and higher-quality data for your projects.

Implementing Robust User-Agent and Header Management

One of the most effective initial lines of defense against 403 errors is sophisticated management of HTTP headers, especially the User-Agent. Websites analyze these headers to determine if the request originates from a legitimate browser or an automated script.

A request with a generic User-Agent like Python-requests/2.26.0 or a complete lack of standard browser headers will immediately flag your scraper as a bot.

User-Agent Rotation Strategies

Your User-Agent string tells the website what kind of client is making the request e.g., “I’m Chrome on Windows 10”. If you consistently send the same User-Agent, especially a non-browser one, you’ll be quickly identified and blocked.

Building a User-Agent Pool: The first step is to compile a diverse list of legitimate and commonly used browser User-Agents. These can be found from various online sources that track browser market share. Cloudscraper
- Example User-Agents:
  - Mozilla/5.0 Windows NT 10.0. Win64. x64 AppleWebKit/537.36 KHTML, like Gecko Chrome/91.0.4472.124 Safari/537.36 Latest Chrome
  - Mozilla/5.0 Macintosh. Intel Mac OS X 10_15_7 AppleWebKit/605.1.15 KHTML, like Gecko Version/14.1.2 Safari/605.1.15 Latest Safari on Mac
  - Mozilla/5.0 Windows NT 10.0. Win64. x64. rv:89.0 Gecko/20100101 Firefox/89.0 Latest Firefox on Windows
  - Mozilla/5.0 Linux. Android 10 AppleWebKit/537.36 KHTML, like Gecko Chrome/91.0.4472.101 Mobile Safari/537.36 Chrome on Android

Rotation Logic: Once you have a pool, you need a strategy to rotate them.

Per Request: Rotate the User-Agent for every single request. This is the most aggressive form of rotation and can be effective against basic User-Agent checks.
After N Requests: Rotate the User-Agent after a certain number of requests e.g., every 5-10 requests. This is less computationally intensive but might be slightly less effective against advanced detection.
On 403/Block: When you encounter a 403 error or another block, immediately switch to a new User-Agent and potentially a new proxy. This adaptive approach is highly effective.

Example Python with requests:

import requests
from fake_useragent import UserAgent
import time
import random

ua = UserAgent
url = "https://example.com/data" # Replace with target URL

def get_page_with_rotationurl:
    try:


       headers = {'User-Agent': ua.random}


       printf"Using User-Agent: {headers}"


       response = requests.geturl, headers=headers, timeout=10
       response.raise_for_status # Raise HTTPError for bad responses 4xx or 5xx
        return response.text


   except requests.exceptions.RequestException as e:
        printf"Request failed: {e}"
        if response.status_code == 403:


           print"Received 403, rotating User-Agent and retrying..."
           time.sleeprandom.uniform5, 10 # Add a delay
           return get_page_with_rotationurl # Recursive call to retry
        return None

# Example usage:
# html_content = get_page_with_rotationurl
# if html_content:
#     print"Successfully scraped content partial view:", html_content

Crafting a Comprehensive Header Set

Beyond just User-Agent, a complete set of standard browser headers can significantly improve your scraper’s stealth.

Real browsers send numerous headers that provide context about the request.

Accept: Specifies the media types the client is willing to accept e.g., text/html,application/xhtml+xml,application/xml.q=0.9,image/webp,*/*.q=0.8. This tells the server you’re looking for web pages, not just raw data.
Accept-Language: Indicates the preferred natural languages for the response e.g., en-US,en.q=0.9. This mimics a user’s browser language settings. According to studies on web traffic, over 55% of all web users access content in English, making en-US a common and safe choice. Python parse html table
Accept-Encoding: Specifies the content encoding e.g., gzip, deflate, br. This allows the server to send compressed data, which is standard browser behavior and makes your request appear legitimate.
Referer: Note the common misspelling, it’s Referer not Referrer Indicates the URL of the page that linked to the current request. Sending a Referer that looks like a legitimate search engine or a previous page on the target site can be very effective. For example, 'https://www.google.com/' or a page from the target domain itself.
Connection: Specifies whether the network connection should be kept alive after the transaction is complete e.g., keep-alive. This is standard for modern browsers.
Upgrade-Insecure-Requests: Set to 1 when the browser is trying to upgrade an insecure HTTP request to HTTPS.
DNT Do Not Track: Though rarely enforced by websites, this header indicates a user’s preference not to be tracked. Seleniumbase proxy
Sec-Fetch-Dest, Sec-Fetch-Mode, Sec-Fetch-Site, Sec-Fetch-User: These are relatively newer headers used by modern browsers especially Chrome, as part of its Fetch Metadata Request Headers initiative to provide more context about how a request was initiated. While not always critical, including them can enhance legitimacy.

Example Python with requests and comprehensive headers:

import requests
from fake_useragent import UserAgent
import random
import time

ua = UserAgent
url = "https://example.com/data" # Replace with target URL

def get_complex_pageurl:
    try:
        headers = {
            'User-Agent': ua.random,
           'Accept': 'text/html,application/xhtml+xml,application/xml.q=0.9,image/webp,*/*.q=0.8',


           'Accept-Language': 'en-US,en.q=0.9',


           'Accept-Encoding': 'gzip, deflate, br',
           'Referer': 'https://www.google.com/', # Or a legitimate page on the target site
            'Connection': 'keep-alive',
            'Upgrade-Insecure-Requests': '1',
            'Sec-Fetch-Dest': 'document',
            'Sec-Fetch-Mode': 'navigate',
            'Sec-Fetch-Site': 'none',
            'Sec-Fetch-User': '?1',
            'Cache-Control': 'max-age=0',
        }


       printf"Using User-Agent: {headers}"


       response = requests.geturl, headers=headers, timeout=15
        response.raise_for_status
        return response.text


   except requests.exceptions.RequestException as e:
        printf"Request failed: {e}"


       if hasattre, 'response' and e.response is not None and e.response.status_code == 403:


           print"Received 403, consider rotating User-Agent/IP and retrying after delay."
            time.sleeprandom.uniform5, 10
        return None

# html_content = get_complex_pageurl
# if html_content:
#     print"Scraped with complex headers partial view:", html_content

By meticulously managing your User-Agent and crafting a full suite of realistic headers, you can significantly reduce the chances of encountering a 403 error due to basic bot detection mechanisms.

This is often the first and most crucial step in making your scraper appear more like a legitimate browser.

The Role of Proxy Servers in Evading 403 Errors

Even with perfect header management, a website’s anti-bot system can still detect and block your scraper if all requests originate from a single IP address. This is where proxy servers become indispensable. Cloudscraper javascript

A proxy server acts as an intermediary between your scraper and the target website, masking your real IP address and making requests appear to come from different locations or different users.

How Proxies Help Bypass IP-Based Blocks

Websites frequently employ IP-based rate limiting and blacklisting.

If they detect too many requests from one IP in a short period, or if an IP is known for malicious activity, they will block it, often with a 403 error.

IP Rotation: Proxies allow you to rotate your IP address for each request or after a certain number of requests. This makes it appear as though various users from different locations are accessing the website, effectively bypassing IP-based rate limits and blacklists. For example, a network of 100 rotating proxies can distribute 10,000 requests, making it seem like each proxy made only 100 requests, well below most rate limits.
Geographical Diversity: Different proxies can originate from different countries or regions. This is useful for accessing geo-restricted content or simply adding another layer of realism to your scraping activity.
Anonymity: Proxies enhance anonymity by hiding your actual IP address from the target website. This adds a layer of protection against direct identification and potential blocking.

Types of Proxies and Their Suitability for Scraping

Not all proxies are created equal.

Their type, source, and pricing model significantly impact their effectiveness and ethical considerations for web scraping. Cloudflare 403 forbidden bypass

1. Public/Free Proxies:
- Description: These are freely available lists of proxy servers often found online.
- Pros: Cost-free.
- Cons: Highly unreliable, slow, often already blacklisted, insecure data might be intercepted, and short-lived. They are almost always detected by sophisticated anti-bot systems.
- Suitability for Scraping: Not recommended. Using free proxies is akin to trying to drive a car with square wheels – it might move, but it’s inefficient and likely to break down quickly.
2. Data Center Proxies:
- Description: These proxies originate from data centers, meaning their IP addresses are clearly associated with commercial hosting providers, not residential ISPs. They are fast and typically cheap.
- Pros: High speed, large pools of IPs, affordable.
- Cons: Easily detectable by sophisticated anti-bot systems because their IPs are known to belong to data centers. Websites can quickly identify and block entire subnets of data center IPs. Many anti-bot solutions have large databases of known data center IP ranges.
- Suitability for Scraping: Limited. Only useful for very basic scraping on websites with minimal anti-bot measures. They might work for scraping publicly available, non-sensitive data from less protected sites, but will quickly fail on popular or well-protected sites.
3. Residential Proxies:
- Description: These proxies use IP addresses assigned by Internet Service Providers ISPs to real residential homes. They appear as legitimate users browsing from their homes.
- Pros: Highly anonymous, very difficult to detect by anti-bot systems, as their traffic blends in with legitimate user traffic. Offer high success rates for bypassing blocks. They provide high-quality IP addresses that mimic real user behavior.
- Cons: Expensive compared to data center proxies, typically slower due to routing through real user connections, and often sold on a bandwidth usage model.
- Suitability for Scraping: Recommended. This is the gold standard for bypassing robust anti-bot measures and 403 errors on popular or well-protected websites. Major residential proxy providers manage pools of tens of millions of unique residential IPs globally.
4. ISP Proxies Static Residential Proxies:
- Description: These are IP addresses hosted on servers but registered under an ISP. They combine the speed of data center proxies with the legitimacy of residential IPs as they appear to be residential from the IP address standpoint. Unlike rotating residential proxies, these IPs are static.
- Pros: Fast, dedicated static IP, less detectable than data center proxies.
- Cons: More expensive than data center proxies, fewer IPs available than rotating residential pools.
- Suitability for Scraping: Good for maintaining session consistency or when you need a stable IP that looks residential. A useful middle ground between data center and rotating residential proxies.

Implementing Proxy Rotation in Python

Implementing proxy rotation, especially with requests in Python, is straightforward.

Most proxy providers give you proxy lists in IP:Port or user:pass@IP:Port format.

Example Python with requests and rotating proxies:

List of proxies replace with your actual proxies

Format: {‘http’: ‘http://user:pass@ip:port‘, ‘https’: ‘https://user:pass@ip:port’}

Or just {‘http’: ‘http://ip:port‘, ‘https’: ‘https://ip:port’} if no authentication

proxy_list =
```
{'http': 'http://user1:[email protected]:8080', 'https': 'https://user1:[email protected]:8080'},


{'http': 'http://user2:[email protected]:8080', 'https': 'https://user2:[email protected]:8080'},


{'http': 'http://user3:[email protected]:8080', 'https': 'https://user3:[email protected]:8080'},
# Add more proxies here
```
Beautifulsoup parse table

def get_page_with_proxy_rotationurl:
selected_proxy = random.choiceproxy_list
headers = {‘User-Agent’: ua.random}

printf”Attempting to scrape {url} using proxy: {selected_proxy} and User-Agent: {headers}”

response = requests.geturl, headers=headers, proxies=selected_proxy, timeout=20
response.raise_for_status # Raise HTTPError for bad responses 4xx or 5xx

except requests.exceptions.ProxyError as e:

printf”Proxy error with {selected_proxy}: {e}. Trying next proxy.”
# Remove bad proxy and retry, or simply retry with a new one
# if selected_proxy in proxy_list:
# proxy_list.removeselected_proxy # Optional: remove if it’s consistently bad
if lenproxy_list > 0:
time.sleeprandom.uniform3, 7 # Small delay before retrying with new proxy Puppeteer proxy

return get_page_with_proxy_rotationurl
else:
print”No more proxies left.”

printf”Request failed using {selected_proxy}: {e}”

print”Received 403. Rotating IP and User-Agent.”
time.sleeprandom.uniform5, 10 # Longer delay for 403
return get_page_with_proxy_rotationurl # Retry with new proxy and User-Agent

Example usage:

html_content = get_page_with_proxy_rotationurl

print”Scraped with proxy rotation partial view:”, html_content

Choosing the right type of proxy and implementing robust rotation strategies is a crucial step in maintaining a successful and resilient web scraper, particularly when dealing with websites that employ advanced anti-bot measures.

Always ensure your proxy usage aligns with the ethical considerations discussed earlier. Selenium proxy java

Managing Delays, Retries, and Sessions for Stealthy Scraping

Even with clever User-Agent and proxy rotation, a rapid, machine-like stream of requests from your scraper can still trigger anti-bot systems.

Websites monitor request patterns, not just individual request attributes.

To truly mimic human browsing behavior and avoid 403 errors, you need to introduce realistic delays, implement intelligent retry mechanisms, and manage sessions effectively.

Implementing Time Delays and Randomization

Humans don’t click links or load pages at perfectly consistent, sub-second intervals.

Introducing delays makes your scraper appear less robotic. Php proxy

Fixed Delays Basic: A simple time.sleepX after each request can prevent immediate rate-limiting. However, fixed delays are still predictable and can be detected. For example, if a website’s analytics show every request comes exactly 2 seconds apart, it’s a clear sign of automation.
Randomized Delays Better: Varying the delay within a reasonable range is far more effective. For instance, instead of 2 seconds, time.sleeprandom.uniform2, 5 will pause your script for a random duration between 2 and 5 seconds. This mimics natural human browsing pauses.
- Practical Example: For low-volume scraping on a cooperative site, random.uniform1, 3 might suffice. For high-volume or aggressive sites, you might need random.uniform10, 30 seconds between requests, or even longer. A significant portion of web traffic estimated at over 40% in 2023 is now automated, making realistic delays more critical than ever to blend in.
Adaptive Delays: If you encounter a 403 or other blocking signal, increase your delay significantly. This is a “back-off” strategy. If a 403 happens, time.sleeprandom.uniform60, 120 might be necessary before retrying with a new IP/User-Agent. This gives the server’s anti-bot system time to reset or “forget” your previous suspicious activity.

Smart Retry Mechanisms for Handling Failures

Your scraper will inevitably encounter temporary network issues, connection timeouts, or even intermittent 403 errors.

A robust retry mechanism ensures your script doesn’t simply crash but intelligently attempts to recover.

Define Max Retries: Set a reasonable limit for how many times you’ll retry a failed request before giving up. A common practice is 3-5 retries.
Exponential Backoff: This is a powerful strategy where the delay between retries increases with each failed attempt. For example, if the first retry waits 1 second, the second waits 2 seconds, the third waits 4 seconds, and so on. Add a random jitter to prevent predictable patterns.
- Formula: delay = base_delay * 2 attempt_number + random_jitter.
- Example:
  
  MAX_RETRIES = 5
  BASE_DELAY = 2 # seconds Puppeteer cluster
  
  Def fetch_url_with_retriesurl, current_attempt=0:
  if current_attempt >= MAX_RETRIES:
  
  printf”Max retries reached for {url}. Giving up.”
  
  printf”Attempt {current_attempt + 1} for {url}…”
  
  response = requests.geturl, timeout=10
  response.raise_for_status
  
  printf”Request failed attempt {current_attempt + 1}: {e}” Sqlmap cloudflare bypass
  
  if hasattre, ‘response’ and e.response is not None:
  
  status_code = e.response.status_code
  if status_code == 403:
  
  print”Received 403. Increasing delay significantly.”
  delay = random.uniformBASE_DELAY * 2 current_attempt + 2, BASE_DELAY * 2 current_attempt + 3 # More aggressive backoff for 403
  
  printf”Waiting for {delay:.2f} seconds before retrying…”
  time.sleepdelay
  
  return fetch_url_with_retriesurl, current_attempt + 1
  elif status_code == 429: # Too Many Requests Crawlee proxy
  
  print”Received 429. Exponential backoff.”
  delay = random.uniformBASE_DELAY * 2 current_attempt, BASE_DELAY * 2 current_attempt + 1
  
  # For other errors e.g., connection errors, timeouts
  delay = random.uniformBASE_DELAY * 2 current_attempt, BASE_DELAY * 2 current_attempt + 1
  
  printf”Waiting for {delay:.2f} seconds before retrying…”
  time.sleepdelay
  
  return fetch_url_with_retriesurl, current_attempt + 1
  
  content = fetch_url_with_retries”http://example.com/some_page“
  
  if content:
  
  print”Content fetched successfully.”

Maintaining Sessions and Handling Cookies

Websites use cookies to maintain state, track user sessions, and personalize content.

A scraper that doesn’t handle cookies like a real browser can quickly be identified as anomalous.

requests.Session: This is the most important tool for session management in Python’s requests library. A Session object persists parameters like cookies, headers, and even proxies across all requests made from it.
- Benefits:
  - Automatic Cookie Handling: When you use session.get or session.post, the session object automatically sends cookies received from previous responses back to the server. This is crucial for maintaining a logged-in state or navigating multi-page flows that rely on session tokens.
  - Performance: All requests within a session reuse the underlying TCP connection, which can lead to performance improvements.
  - Consistency: Headers and proxies defined on the session object will apply to all requests, ensuring consistent behavior.
  Url_login = “https://example.com/login” # Example login URL
  url_profile = “https://example.com/profile” # Page requiring login
  
  with requests.Session as session:
  # 1. First request e.g., login or initial page load – cookies are stored in session
  login_data = {‘username’: ‘myuser’, ‘password’: ‘mypassword’} # Replace with actual login data
  printf”Logging in to {url_login}…”
```
response_login = session.posturl_login, data=login_data
 response_login.raise_for_status


printf"Login successful? Status: {response_login.status_code}"

# 2. Subsequent requests will automatically send cookies from the login response


printf"Accessing profile page {url_profile}..."


response_profile = session.geturl_profile
 response_profile.raise_for_status


printf"Profile page accessed successfully. Status: {response_profile.status_code}"
# print"Profile content partial view:", response_profile.text
```
Inspecting and Using Specific Cookies: In some advanced cases, anti-bot systems might set specific JavaScript-generated cookies e.g., _cf_bm from Cloudflare that are crucial for bypassing protection. You might need to:
1. Use a headless browser like Selenium to visit the site once and capture these cookies.
2. Extract these cookies from the browser session.
3. Manually add these cookies to your requests.Session object for subsequent programmatic requests.

By combining randomized delays, smart retry logic, and robust session management, your scraper can operate more stealthily, appear more human-like, and significantly reduce the likelihood of encountering persistent 403 errors.

Leveraging Headless Browsers for Advanced Anti-Bot Measures

When traditional requests-based scraping, even with extensive header and proxy rotation, fails to bypass 403 errors, it’s often because the target website employs sophisticated client-side anti-bot measures.

These measures typically involve JavaScript execution, browser fingerprinting, and dynamic content rendering.

In such scenarios, headless browsers become an indispensable tool.

What are Headless Browsers?

A headless browser is a web browser without a graphical user interface GUI. It operates in the background, allowing programmatic control over web page interactions.

Essentially, it’s a real browser like Chrome or Firefox running on your server, but instead of displaying the page on a screen, it executes JavaScript, renders HTML, handles CSS, manages cookies, and simulates genuine user interactions clicks, scrolls, form submissions, all programmatically.

Key Difference from requests:
- requests: Fetches raw HTML. It doesn’t execute JavaScript. If a website generates content or sets critical anti-bot cookies via JavaScript, requests will only see the initial, unrendered HTML.
- Headless Browser: Loads the page, executes all client-side JavaScript, waits for dynamic content to load, and then allows you to interact with the fully rendered page. This is exactly how a human user’s browser operates.

When to Use Headless Browsers

While powerful, headless browsers are resource-intensive and slower than requests. They should be considered as a last resort when other methods fail.

JavaScript-Rendered Content: If the data you need is loaded dynamically by JavaScript e.g., infinite scrolling, data loaded via AJAX calls, single-page applications. Many modern websites use JavaScript extensively for content delivery.
Advanced Anti-Bot Detection: Websites employing sophisticated anti-bot solutions like Cloudflare’s Bot Management, Akamai Bot Manager, PerimeterX, or Imperva often rely on:
- Browser Fingerprinting: Analyzing dozens of browser attributes plugins, fonts, canvas rendering, WebGL capabilities, screen resolution to identify automated vs. human users. Headless browsers mimic these attributes more effectively.
- JavaScript Challenges: Requiring the browser to solve complex JavaScript challenges to prove it’s a real browser.
- Cookie Generation Client-Side: Setting specific cookies e.g., Cloudflare’s cf_clearance or _cf_bm that are generated only after JavaScript execution.
CAPTCHA Bypass Indirectly: While headless browsers don’t solve CAPTCHAs directly, they can interact with the CAPTCHA frame and prepare the page for a CAPTCHA solving service.
Simulating User Interaction: When scraping requires clicks, scrolling, form submissions, or hovering over elements, a headless browser is ideal. A typical user session involves dozens of interactions on a complex website, which headless browsers can replicate.

Popular Headless Browser Frameworks Python

Two dominant frameworks for headless browser automation in Python are Selenium and Playwright.

1. Selenium:
- Overview: A widely used framework for browser automation, initially designed for web application testing. It can control various browsers Chrome, Firefox, Edge, Safari in both headed and headless modes.
- Pros: Mature, extensive community support, cross-browser compatibility, rich API for interacting with web elements.
- Cons: Can be slower than Playwright, requires separate webdriver executables e.g., chromedriver.exe, and its API for asynchronous operations is less intuitive.
- Example Python with Selenium Headless Chrome:
  from selenium import webdriver
  
  From selenium.webdriver.chrome.service import Service
  
  From selenium.webdriver.chrome.options import Options
  
  From selenium.webdriver.common.by import By
  
  From selenium.webdriver.support.ui import WebDriverWait
  
  From selenium.webdriver.support import expected_conditions as EC
  
  Set up Chrome options for headless mode
  
  chrome_options = Options
  chrome_options.add_argument”–headless” # Run Chrome in headless mode
  
  Chrome_options.add_argument”–no-sandbox”
  
  Chrome_options.add_argument”–disable-dev-shm-usage”
  chrome_options.add_argument”–window-size=1920,1080″ # Set a realistic window size
  chrome_options.add_argument”–user-agent=Mozilla/5.0 Windows NT 10.0. Win64. x64 AppleWebKit/537.36 KHTML, like Gecko Chrome/91.0.4472.124 Safari/537.36″ # Realistic User-Agent
  
  Add more arguments to evade detection if needed e.g., disable automation flags, hide WebDriver
  
  chrome_options.add_argument”–disable-blink-features=AutomationControlled”
  
  chrome_options.add_experimental_option”excludeSwitches”,
  
  chrome_options.add_experimental_option’useAutomationExtension’, False
  
  Path to chromedriver executable
  
  service = Serviceexecutable_path=”/path/to/chromedriver” # Replace with your chromedriver path
  
  Driver = webdriver.Chromeoptions=chrome_options # , service=service
  
  Url = “https://example.com/dynamic_content” # Replace with target URL
```
printf"Navigating to {url} with headless Chrome..."
 driver.geturl

# Wait for an element to load e.g., content with ID 'main-data'
 WebDriverWaitdriver, 10.until


    EC.presence_of_element_locatedBy.ID, "main-data"
 

# Scroll down to load more content if it's an infinite scroll page
# driver.execute_script"window.scrollTo0, document.body.scrollHeight."
# time.sleep3 # Wait for content to load after scroll

 print"Page title:", driver.title


print"Current URL:", driver.current_url


print"Page source partial view:", driver.page_source
```
  except Exception as e:
  printf”An error occurred: {e}”
  finally:
  driver.quit # Always close the browser
2. Playwright:
- Overview: Developed by Microsoft, Playwright is a newer, more modern framework designed for robust and reliable end-to-end testing and web automation. It supports Chrome, Firefox, and WebKit Safari’s rendering engine and offers excellent asynchronous capabilities.
- Pros: Faster performance, built-in auto-waiting, better handling of modern web technologies, excellent async API, can handle multiple browser contexts simultaneously, built-in screenshot and video recording.
- Cons: Newer, so community support is growing but not as vast as Selenium yet.
- Example Python with Playwright Headless Chrome:
  
  From playwright.sync_api import sync_playwright
  
  with sync_playwright as p:
  # Launch a headless Chrome browser
  
  browser = p.chromium.launchheadless=True
  page = browser.new_page
  
  # Set a realistic user agent
  
  page.set_extra_http_headers{“User-Agent”: “Mozilla/5.0 Windows NT 10.0. Win64. x64 AppleWebKit/537.36 KHTML, like Gecko Chrome/91.0.4472.124 Safari/537.36”}
  page.set_viewport_size{“width”: 1920, “height”: 1080} # Realistic viewport size
  
  printf”Navigating to {url} with Playwright headless Chrome…”
  page.gotourl, wait_until=’networkidle’ # Wait until network activity is minimal
  
  # Wait for specific element e.g., content with ID ‘main-data’
  page.wait_for_selector”#main-data”, timeout=10000
  
  # Scroll down
  # page.evaluate”window.scrollTo0, document.body.scrollHeight.”
  # page.wait_for_timeout3000 # Wait for 3 seconds
  
  print”Page title:”, page.title
  print”Current URL:”, page.url
  
  print”Page source partial view:”, page.content
  
  except Exception as e:
  printf”An error occurred: {e}”
  finally:
  browser.close # Always close the browser

When faced with persistent 403 errors on highly protected websites, embracing headless browsers is often the most reliable solution.

While they demand more resources and execution time, their ability to fully render pages and mimic genuine user interactions significantly enhances your scraper’s stealth and success rate.

Post-Scraping Data Handling and Ethical Considerations

Successfully navigating 403 errors and extracting data is only half the battle.

What you do with the scraped data, how you store it, and how you ensure its integrity are equally important.

Crucially, the ethical and permissible handling of this data, especially in the context of Islamic principles, dictates that it should be used for beneficial purposes, avoiding any form of exploitation, misrepresentation, or harm.

Data Storage and Management

Once you’ve scraped the data, you need a robust and organized way to store and manage it.

The choice of storage depends on the data volume, structure, and intended use.

1. CSV/JSON Files Small to Medium Data:
- Description: For smaller datasets, comma-separated values CSV and JSON JavaScript Object Notation files are simple, human-readable, and widely supported formats.
- Pros: Easy to implement, no database setup required, good for quick analysis or sharing. CSVs are tabular, JSON is hierarchical.
- Cons: Not scalable for large datasets, difficult to query complex data, prone to data corruption if not handled carefully.
- Usage: Ideal for scraping a few hundred or a few thousand records. Python’s csv and json modules make this very straightforward. For instance, a dataset of 50,000 records can easily be managed in a CSV file, typically under 10MB in size.
2. Relational Databases SQL – MySQL, PostgreSQL, SQLite:
- Description: For structured data, relational databases offer powerful storage, querying, and management capabilities.
- Pros: Highly scalable, supports complex queries SQL, ensures data integrity with schemas and constraints, robust for large datasets. SQLite is file-based and great for local development. MySQL/PostgreSQL are full-fledged server-based solutions.
- Cons: Requires database setup and management, learning SQL, can be overkill for very small projects.
- Usage: Essential for scraping millions of records or when data needs to be frequently queried, filtered, or joined with other datasets. For example, a PostgreSQL database can comfortably manage tens of millions of rows, with highly optimized query performance.
3. NoSQL Databases MongoDB, Cassandra, Redis:
- Description: Non-relational databases designed for unstructured or semi-structured data, offering flexibility and horizontal scalability.
- Pros: Flexible schema document-based like MongoDB is great for JSON-like data, highly scalable horizontally, excellent for rapidly changing data structures or massive data ingestion.
- Cons: Less mature querying compared to SQL for complex joins, consistency models can be different.
- Usage: Suitable for scraping highly dynamic websites, large volumes of unstructured text, or when speed of writing data is paramount. MongoDB is a popular choice for web scraping due to its document-oriented nature.
4. Cloud Storage AWS S3, Google Cloud Storage, Azure Blob Storage:
- Description: Object storage services that store data as objects within buckets. They are highly scalable and durable.
- Pros: Virtually unlimited storage, extremely durable e.g., AWS S3 boasts 11 nines of durability, accessible from anywhere, integrated with other cloud services.
- Cons: Requires cloud account setup, pricing based on storage and access, not a direct querying database.
- Usage: Best for storing raw scraped files, large archives, or as an intermediate step before processing and loading into a database.

Data Quality and Cleaning

Raw scraped data is rarely perfect.

It often contains inconsistencies, missing values, duplicates, and formatting issues.

Data cleaning is a critical step to ensure the data is usable and reliable.

Handling Missing Data: Decide whether to fill missing values e.g., with defaults, averages, or remove rows/columns with excessive missing data.
Removing Duplicates: Implement logic to identify and remove duplicate records based on unique identifiers e.g., URL, product ID. Studies show that up to 30% of data in enterprise systems can be duplicates, highlighting the importance of this step.
Standardizing Formats: Convert all dates to a consistent format, standardize currency symbols, ensure consistent capitalization, and clean up extraneous whitespace or special characters.
Error Correction: Correct common scraping errors, such as malformed URLs, incomplete text, or incorrect data types.
Data Validation: Set up rules to validate data against expected patterns or ranges e.g., ensuring prices are positive numbers, emails are valid.

Ethical Principles in Data Usage

Beyond the technicalities, the most important aspect of dealing with scraped data is its ethical usage.

As a Muslim professional, this means adhering to principles of honesty, fairness, non-harm, and using knowledge for the benefit of humanity.

1. Non-Malicious Intent Niyyah:
- Principle: The intention behind acquiring and using the data must be pure and beneficial. Data should not be scraped or used for malicious purposes such as phishing, fraud, market manipulation like insider trading based on scraped stock data, which is a form of Riba if speculation is involved, or causing harm to individuals or businesses.
- Application: Ensure your data insights lead to fair competition, consumer benefit, or legitimate research, not to exploit vulnerabilities or deceive.
2. Respect for Ownership and Property Haqq al-Mal:
- Principle: Websites are digital property, and their content is often protected by copyright or terms of service. Unauthorized appropriation of data, especially if it’s protected, can be seen as taking what is not rightfully yours.
- Application: Prioritize official APIs, public datasets, or explicit permission. If scraping, ensure it’s limited to publicly visible, non-proprietary information and respects robots.txt. Do not bypass explicit barriers like CAPTCHAs or logins unless given explicit consent.
3. Avoiding Deception and Misrepresentation Gharar:
- Principle: Data should not be used to create misleading information, to engage in deceptive advertising, or to promote products/services that are harmful or prohibited.
- Application: Present insights derived from scraped data accurately and transparently. Do not manipulate or misrepresent data to serve an agenda. Ensure that any commercial use of scraped data is in line with fair trade practices.
4. Protecting Privacy Satr al-Awrah:
- Principle: Even if data is publicly accessible, its aggregation and re-identification can infringe on individual privacy. Islam emphasizes protecting the privacy and dignity of individuals.
- Application: Avoid scraping personal identifiable information PII unless absolutely necessary and with explicit consent. If PII is unavoidable, anonymize or pseudonymize it immediately. Implement robust security measures to protect the scraped data from breaches. Comply with data protection regulations like GDPR which levies fines up to €20 million or 4% of global annual revenue and CCPA.
5. Non-Excessive Consumption of Resources Israf:
- Principle: Over-scraping, leading to excessive server load or bandwidth consumption, is a form of wastefulness and can be seen as causing undue burden on the website owner.
- Application: Implement generous delays, rate limits, and use caching mechanisms. Only request what you need. Be mindful of the website’s resources, as they are a trust from their owners.
6. Benefiting Humanity Manfa’ah:
- Principle: The ultimate goal of knowledge acquisition and data processing should be to bring about benefit and positive impact.
- Application: Use scraped data for legitimate research, competitive analysis that fosters innovation, public good initiatives e.g., price transparency, academic studies, or creating value that does not exploit. For instance, using price data to help consumers find better deals or analyze market trends for ethical investment opportunities.

By integrating these ethical considerations into your data handling practices, your work in web scraping can become a source of legitimate and beneficial knowledge, rather than a questionable endeavor.

Frequently Asked Questions

What is a 403 Forbidden error in web scraping?

A 403 Forbidden error in web scraping means the server understands your request but refuses to authorize it.

It indicates that you lack the necessary permissions to access the requested resource, often because the website has identified your activity as automated and is blocking it.

Why do websites return 403 errors to scrapers?

Websites return 403 errors to scrapers for several reasons, including protecting their servers from excessive load, enforcing terms of service that prohibit scraping, protecting intellectual property, preventing data exploitation, and blocking suspicious IP addresses or user agents identified by anti-bot systems.

Can I bypass a 403 error without using proxies?

Yes, you can often bypass a 403 error without proxies by implementing robust User-Agent rotation, sending a full set of realistic HTTP headers like Accept-Language, Referer, adding randomized delays between requests, and maintaining sessions and cookies.

These methods make your scraper appear more like a legitimate browser.

What is User-Agent rotation and how does it help?

User-Agent rotation involves changing the User-Agent string which identifies your client for each request or after a certain number of requests.

It helps by mimicking different legitimate browsers, making it harder for websites to identify and block your scraper based on a consistent, non-browser User-Agent.

How often should I rotate User-Agents?

For basic protection, you can rotate User-Agents every few requests.

For more aggressive anti-bot systems, rotating on every request or immediately upon encountering a 403 error is more effective.

Libraries like fake-useragent can help generate a diverse pool of User-Agents.

Are free proxies good for bypassing 403 errors?

No, free proxies are generally not good for bypassing 403 errors.

They are often unreliable, very slow, already blacklisted by many websites, and can pose significant security risks.

It’s best to avoid them for any serious scraping project.

What’s the difference between data center and residential proxies?

Data center proxies originate from commercial hosting providers and are easily detectable by anti-bot systems.

Residential proxies use IP addresses assigned by ISPs to real homes, making them appear as legitimate users and significantly harder to detect.

Residential proxies are more expensive but far more effective for bypassing advanced anti-bot measures.

How do I implement delays in my web scraper?

You can implement delays using time.sleep in Python.

It’s best to use randomized delays e.g., time.sleeprandom.uniform2, 5 rather than fixed delays to mimic human browsing behavior more realistically and avoid predictable patterns that anti-bot systems can detect.

What is exponential backoff in retries?

Exponential backoff is a retry strategy where the waiting time between retry attempts increases exponentially after each failure.

For example, if the first retry waits 1 second, the second waits 2 seconds, the third waits 4 seconds.

This gives the server more time to recover and reduces the load during errors.

Why is session management important in web scraping?

Session management, typically handled by requests.Session in Python, is important because it automatically persists cookies across requests.

This allows your scraper to maintain a continuous “session” with the website, simulating a logged-in user or navigating multi-step processes that rely on cookies, thus appearing more legitimate.

When should I use a headless browser like Selenium or Playwright?

You should use a headless browser when basic requests-based scraping fails due to advanced anti-bot measures.

This includes websites that heavily rely on JavaScript for content rendering, implement sophisticated browser fingerprinting, or set critical cookies via client-side JavaScript.

Do headless browsers solve CAPTCHAs automatically?

No, headless browsers do not solve CAPTCHAs automatically.

They can interact with the CAPTCHA frame and prepare the page for a CAPTCHA solving service a third-party API, but the actual CAPTCHA resolution still requires a human or an automated solver integrated with the service.

Is web scraping always permissible?

No, web scraping is not always permissible.

It can be legally and ethically problematic if it violates a website’s terms of service, infringes on copyright, causes excessive server load, or compromises personal data.

Always prioritize ethical conduct and permissible alternatives.

What are ethical alternatives to aggressive web scraping?

Ethical alternatives include using official APIs provided by the website, leveraging RSS feeds, seeking direct permission or partnering with website owners, utilizing publicly available datasets, or subscribing to paid data services.

These methods ensure data acquisition is consensual and respectful.

How does `robots.txt` relate to 403 errors?

While robots.txt doesn’t directly cause 403 errors it’s a directive, not an enforcement mechanism, ignoring it can lead to ethical breaches and subsequent blocks.

If a website clearly disallows scraping specific paths in its robots.txt, attempting to access them can trigger anti-bot systems, which might then return a 403.

Can VPNs help with 403 errors?

Yes, VPNs can help with 403 errors by changing your IP address.

However, VPNs typically provide a single rotating IP or a limited set, which might still be detected if the website’s anti-bot system is sophisticated.

Dedicated proxy services, especially residential proxies, are generally more effective for sustained scraping.

What is browser fingerprinting in the context of 403 errors?

Browser fingerprinting is an advanced anti-bot technique where websites collect a multitude of unique attributes about your browser e.g., plugins, fonts, screen resolution, WebGL capabilities to create a “fingerprint.” If your scraper’s fingerprint is inconsistent or incomplete compared to a real browser, it can trigger a 403.

Should I clear cookies or maintain them when scraping?

For most legitimate scraping scenarios, you should maintain cookies using a session object like requests.Session. Clearing cookies too often can make your scraper look suspicious as it doesn’t mimic normal user behavior, who typically maintain session cookies.

Only clear them if a 403 or block suggests a cookie-related issue.

What kind of data should I avoid scraping for ethical reasons?

For ethical and permissible reasons, you should avoid scraping Personal Identifiable Information PII like names, emails, phone numbers, or addresses, unless you have explicit consent and a legitimate reason.

Also, avoid sensitive financial data, private user content, or any data behind a login wall without proper authorization.

How can I ensure my scraped data is of good quality?

To ensure good data quality, implement robust data cleaning steps: handle missing values, remove duplicates, standardize formats dates, currencies, correct errors, and perform validation checks against expected data types and patterns.

Regularly review a sample of your scraped data for accuracy.

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403 web scraping

Understanding the 403 Forbidden Error in Web Scraping

Why Do Websites Issue 403 Errors?

Common Scenarios Leading to 403 Errors

Ethical Considerations and Permissible Alternatives

The Impermissibility of Aggressive Scraping

Permissible and Ethical Alternatives to Scraping

Implementing Robust User-Agent and Header Management

User-Agent Rotation Strategies

Crafting a Comprehensive Header Set

The Role of Proxy Servers in Evading 403 Errors

How Proxies Help Bypass IP-Based Blocks

Types of Proxies and Their Suitability for Scraping

Implementing Proxy Rotation in Python

List of proxies replace with your actual proxies

Format: {‘http’: ‘http://user:pass@ip:port‘, ‘https’: ‘https://user:pass@ip:port’}

Or just {‘http’: ‘http://ip:port‘, ‘https’: ‘https://ip:port’} if no authentication

Example usage:

html_content = get_page_with_proxy_rotationurl

print”Scraped with proxy rotation partial view:”, html_content