How to Fix 403 Error in Web Scraping

Encountering ominous 403 Forbidden errors puts an abrupt halt on web scraping productivity. This common HTTP response code signals a denial of access, often due to an anti-bot system detecting and blocking your requests.

If you rely solely on simple scraping libraries like Python Requests, scraping any meaningful data from robust sites becomes next to impossible thanks to these access blocks. But with the right techniques, you can craft scrapers that blend in seamlessly and bypass protections to extract the content you need.

  • Rotating proxies
  • Mimicking browser headers
  • Leveraging browser automation tools
  • Introducing human-like delays
  • Using specialized proxy services
  • Implementing stealth plugins
  • Running scrapers in headless mode

Combined intelligently, these techniques form a battle-tested toolkit to access even heavily fortified websites. By the end, you’ll have the knowledge to scrape freely and say goodbye to pesky bot blocks!

The Costs of 403 Errors

Before diving into fixes, let's highlight the underlying risks of leaving 403 errors unresolved. Beyond mere annoyance, frequent blocking seriously impacts businesses relying on web scrapers to feed crucial data.

According to surveys by ScrapingBee, over 60% of companies using web scrapers experience blocking-related failures at least weekly, with 403 errors among the most common culprit. Fixing blocking issues eats up over 20% of developers' time.

The costs extend to lost revenue, lack of business insights, and decreased competitiveness when site access vanishes. For marketing agencies, blocked scrapers even risk breaking client contracts and service agreements.

But the biggest long-term risk is failing to adapt scraper tactics alongside rapidly evolving bot mitigation technology on websites. Minor effort now prevents major consequences down the road.

This in-depth guide equips you with those essential adaptation skills. Let's first understand what triggers those 403s before learning how to avoid them.

Common Causes of 403 Errors

While the 403 Forbidden response appears cryptic on the surface, several bot behavioral patterns tend to provoke access blocks:

Aggressive request velocity – Scrapers instinctively bombard sites with traffic, but this is a red flag signaling automation. Most will block after thresholds are exceeded.

Repetitive access patterns – Repeating the exact same crawling steps across a site stands out compared to varied human exploration.

Unnatural headers – Unlike browsers, scraper tools have distinctive default request headers exposing their automated nature.

Lack of JavaScript execution – Heavily JS sites expect real browsers to execute it, not just parse static HTML.

Predictable traffic fingerprints – Scrapers tend to follow unique patterns detectable from their traffic signatures.

Centralized IP addresses – Scraping excessively from a small pool of IPs will get them flagged and banned.

Now that you know what gets scrapers flagged, let's go through techniques to avoid sticking out like a bot!

Tip #1: Rotate Proxies to Prevent IP Bans

One of the quickest ways for scrapers to encounter 403s is concentrating requests through a single IP or small range of IPs. Most sites limit requests per IP, blocking those that exceed thresholds.

Rotating across multiple IP addresses is critical for any effective web scraper to distribute traffic and evade blocks. Residential proxies with real home and mobile device IPs work best, as datacenter IPs are easily flagged as suspicious.

Let's walk through a Python proxy rotation example using Requests:

import requests
from proxies_list import proxies # Local file with proxies

target_url = ''  

for proxy in proxies:
    response = requests.get(target_url, proxies={"http": proxy, "https": proxy})
    if response.status_code == 200:    
  except Exception:
    print("Proxy connection error, rotating...")

This loops through our proxy list, making a request with each one before moving onto the next on any errors.

The best approach is using a dedicated proxy service like Smartproxy which handles acquisition and rotation of thousands of residential IPs for you. Their Python SDK also makes integration seamless:

from smartproxy import Proxy // Import Smartproxy SDK

proxy = Proxy() // Init new Proxy instance 

target_page = ''

for _ in range(10): 
  response = proxy.session.get(target_page) // Proxy used automatically

No need to code your own proxy rotation – Smartproxy's SDK handles it automatically!

But which proxy rotation patterns work best? Here are two proven approaches…

1. Rotate after each request – Fetching from a different proxy on every request maximizes IP variety and minimizes repetitive access.

2. Rotate per website – Using one proxy for all requests to a site still varies access by site. This works well to isolate blocking to only flagged sites.

Adjust patterns based on your specific use case, and combine with other methods for best results!

Tip #2: Set Browser-Like Headers

Even with proxy rotation, scrapers can still get flagged based on unnatural request headers that differ from real browsers. Default headers emitted by tools like Requests scream “bot!” to servers.

Setting authentic browser-mimicking headers is vital to avoiding red flags. For example, this is Requests' conspicuous default:

User-Agent: python-requests/2.26.0
Accept-Encoding: gzip, deflate  
Accept: */*
Connection: keep-alive

Versus typical Chrome desktop browser headers:

User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/ Safari/537.36
Accept-Language: en-US,en;q=0.9
Cache-Control: max-age=0  
Accept: text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8
Sec-Fetch-Dest: document
Sec-Fetch-Mode: navigate
Sec-Fetch-Site: none

Obvious bot red flags! Let's fix by supplying our own custom headers:

headers = {
  'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/ Safari/537.36',

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

  # Other headers


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

We overwritten the defaults with authentic Chrome browser values. See our complete web scraping headers guide for more details.

But which headers matter most? These 5 are absolutely critical to mimic:

  • User-Agent – Essential for identifying as a real browser.
  • Accept / Accept-Language – Reveals expected content types.
  • Referer – Shows previous page URL revealing web flow.
  • DNT – “Do Not Track” header tells servers not to log data.
  • Upgrade-Insecure-Requests – Signals enforcing HTTPS security.

Double check your headers match real values! Subtle anomalies like typos can expose your scraper.

Tip #3: Render JavaScript with a Browser

Due to the prevalence of interactive JavaScript websites, a scraper without JS capabilities will fail to gather complete data. Python Requests and similar libraries parse only raw HTML.

Browser automation tools like Selenium execute JavaScript to mimic real user interactions. For example:

from selenium import webdriver

browser = webdriver.Chrome()

url = ''

print(browser.page_source) # Includes rendered JavaScript

This launches Chrome via Selenium, loads the page, and prints the full post-JS HTML source.

See our complete web scraping with Selenium guide for many more examples to integrate it into your scrapers.

But popularity has made Selenium easy to detect. Advanced options like proxy rotation and plugins are required to hide it these days.

Tip #4: Implement Random Delays Between Requests

Mimicking human browsing behavior goes a long way in avoiding looking like a bot. Scrapers tend to hit websites aggressively without any delay between requests.

Introducing random intervals makes the crawler appear more natural and evades abuse monitors:

import requests  
import random
import time

urls = ['url1', 'url2', 'url3'...]

for url in urls:

  # Random delay between 1-3 seconds  
  response = requests.get(url)
  # Scrape page...

This adds a randomized delay before each request, avoiding bot-like rapid requests. Expand on this concept with additional human patterns.

An example is probabilistically visiting additional pages at random, beyond your core scraping logic. This adds human meandering behavior.

Tip #5: Leverage Smartproxy for Web Scraping

Implementing all of the evasion techniques covered so far requires significant development time when building scrapers. This is where services like Smartproxy excel – they handle the entirety of mimicking human behavior programmatically.

Smartproxy manages thousands of proxies, automatic rotation, residential IPs, realistic headers, custom delays, and all other key evasion capabilities so you can focus on writing scraping logic.

Here is an example using their Python SDK:

from smartproxy import Proxy // Import SDK

proxy = Proxy() // Create new Proxy instance

url = '' 

for _ in range(10):
  response = proxy.session.get(url) // Use proxy for request

Just like that, your scraper now has access to Smartproxy's pool of 72,000+ IPs across 190+ locations that automatically rotate to avoid blocks. No more wasted time debugging proxies!

Their IPs cover the globe:

Region IPs
North America 19,000+
Europe 32,000+
Asia 4,000+

Packages start at $75/month for 5GB of traffic, all the way up to $1,100/month for 300GB. See Smartproxy's pricing page for full details.

Compared to developing in-house solutions, proxy API services grant immediate access to enterprise-grade tools.

Tip #6: Leverage Anti-Bot Browser Plugins

In some cases, your needs mandate directly integrating scrapers into real browsers. Anti-bot plugins like Undetectable ChromeDriver help mask browsers under automation to avoid flagging:

from selenium import webdriver
from undetectable_chromedriver import options


driver = webdriver.Chrome(options=options)

# Open URL and scrape...

This configures Chrome in a hardened mode that prevents it from being detected as a remote Selenium browser.

Plugins like Cloudscraper integrate with Requests to handle JavaScript challenges as well:

import cloudscraper

scraper = cloudscraper.CloudScraper() 
response = scraper.get(url)

Leveraging purpose-built tools supplements your own custom evasion techniques for added protection.

Tip #7: Configure Scrapers to Run Headlessly

For browser-based scraping, running full Chrome or Firefox visibly can consume substantial computing resources. A lighter-weight option is configuring them to run headlessly.

Headless mode hides the browser UI but still executes JavaScript to render sites fully. For example:

from selenium import webdriver 

options = webdriver.ChromeOptions()

driver = webdriver.Chrome(options=options)

url = ''

print(driver.page_source) # Headless browser DOM

Scrapers mimicking user actions but without the overhead of a visible browser are less suspicious to sites.

See our in-depth guide on headless scraping for examples with Selenium, Playwright, and Puppeteer.

Conclusion: Combine Multiple Evasion Techniques

By now you're equipped with a swiss army knife of techniques to overcome restrictive bot blocks and 403 access denials. To summarize:

  • Rotate residential proxies to distribute requests and prevent IP bans
  • Mimic browser headers meticulously to blend in with organic traffic
  • Use browsers like Selenium to render JavaScript fully before parsing
  • Add random delays between actions to avoid robotic rapid scraping
  • Leverage tools like Smartproxy to manage proxies and sessions
  • Try anti-bot browser plugins to mask webdrivers and handle JS challenges
  • Scrape headlessly when possible to reduce resource usage and visibility

No single solution is failproof. But combining multiple evasion tools significantly raises your odds of scraping successfully.

The key is varying your approaches to match the evolving landscape of bot mitigation and access restrictions. Start with the basics, then scale up your techniques as difficulties increase.

For maximized scale and simplicity, services like Smartproxy take care of the heavy lifting so you can scrape freely. Their enterprise proxy network and residential IPs are battle-tested to access 10,000+ sites and apps.

Scraping intelligently requires constant learning. But using the comprehensive techniques in this guide, you now have the toolkit to overcome even the toughest blocks.

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