17 Web Scraping Best Practices and Tips
- Tony Paul
- Jun 24, 2021
- 10 min read
Updated: 3 days ago
Web scraping is often the first program aspiring programmers write to get familiar with using libraries. I certainly did that — I wrote a simple web scraper using Beautiful Soup and Python.
When you're working on a scraping project for a business use case, you need to follow best practices. These best practices involve both programmatic and non‑programmatic aspects. Following them also helps you stay on an ethical track. We've listed the web scraping best practices you must follow. Take a look at this infographic for a quick scan.
Read the full blog for the full picture.
1. Check if an API is available
What is an API?
An API (Application Programming Interface) helps you get the data you need via a simple computer program while hiding the complexity from data consumers.
If an API is available, you pass a search query into the API and it returns the data as a response. You can take this data and use it. Consider three possible cases:
a) API is available, and the data attributes are sufficient: Use the API service to extract the data.
b) API is available, but the data attributes are insufficient for the use case: You need to use web scraping to get the missing data.
c) API is not available: Scraping is the only way to gather the information you need.
2. Be gentle
Every time you make a request, the target website has to use server resources to return a response. So the volume and frequency of your requests should be minimal to avoid disrupting the website’s servers. Hitting the server too often affects the user experience for real visitors.
There are a few ways to handle this:
If possible, scrape during off‑peak hours when the server load is lower.
Limit the number of parallel / concurrent requests to the target website.
Spread requests across multiple IPs.
Add delays between successive requests.
3. Respect robots.txt
robots.txt is a text file website administrators publish to guide automated crawlers on how to access their site. It often includes rules like which paths are disallowed, which user agents are targeted, and suggested crawl rates.
Two practical notes:
robots.txt is guidance, not a license. A site can still restrict usage via Terms of Service or other controls.
If robots.txt disallows what you need, treat it as a signal to pause and look for an API, a partnership route, or explicit permission.
If you're attempting web scraping, it’s a good idea to check the robots.txt file first. It’s usually available in the root directory. I’d also recommend reading the website’s Terms of Service.
4. Don’t follow the same crawling pattern
Even though both humans and bots consume data from a web page, there are inherent differences.
Real humans are slow and unpredictable. Bots are fast and predictable.
Anti‑scraping systems look for traffic that’s unnaturally fast, perfectly regular, and inconsistent with real browsing.
So instead of building a scraper that behaves like a metronome, aim for human‑like pacing and navigation that matches the site’s normal flow (within the boundaries of permission and policy). This is less about “tricking” a site and more about being predictable, polite, and stable at scale.
Once we explained this to a customer, he joked:
“So you’re making a scraper look like a drunken monkey.”
The funny version aside, the real goal is: don’t create traffic that looks like a stress test.
5. Route your requests through proxies
When your request hits the server of a target website, they can log it. The website will have a record of your activity. Most sites have an acceptable threshold for how many requests they’ll tolerate from a single IP address. If you exceed that threshold, they may block the IP.
A common way to reduce this risk is to route your requests through a proxy network and rotate IPs.
You can find free (but unreliable) IPs for hobby projects. But for serious business use cases, you need a smart and reliable proxy network.
There are several methods that can be used to change your outgoing IP:
a) VPN
A VPN changes your original IP address to a new one and conceals your real IP. It helps you access location‑based content. VPNs aren’t really designed for large‑scale scraping, but for a small‑scale use case, a VPN can be sufficient.
b) TOR
TOR (The Onion Router) routes your traffic through a worldwide volunteer network with thousands of relays. You can use it to conceal your location. TOR is very slow, and it can affect scraping speed. Putting heavy load on the TOR network might not be ethical either. I would not recommend TOR for large‑scale web scraping.
c) Proxy services
Proxy services are IP masking systems built with business users in mind. They usually provide a large pool of IP addresses to route your requests, which helps with scale and reliability.
Depending on your use case and budget, you can choose from shared proxies, residential proxies, or datacenter proxies. Residential proxies are expensive and typically used as a last resort. Residential IPs are often the most effective at blending in with normal user traffic.
6. Rotate user agents and request headers
User agents
When your browser connects to a website, it identifies itself through the user agent, telling the server things like: “Hi, I’m Mozilla Firefox on macOS” or “Hi, I’m Chrome on an iPhone.”
Here is the common format of a user agent string:
User-Agent: Mozilla/5.0 (<system-information>) <platform> (<platform-details>) <extensions>
Example of a real user agent:
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36
If you make a simple request using Python’s requests library and don’t set a user agent, many websites will detect that you’re not a real browser and block you. Rotating common user agents between requests is a practical best practice.
User‑agent rotation is often overlooked.
7. Request headers
When you hit a website, you shouldn’t just say “give me the data.” You should provide enough context so the server can return the right response. That context is sent through HTTP request headers.
Five request headers every programmer doing scraping should know:
User-Agent: Specifies what user agent is being used.
Accept-Language: Specifies which language the user understands.
Accept-Encoding: Specifies which compression algorithms the server can use.
Accept: Specifies what content types are acceptable in the response.
Referer: Specifies the referring page URL (the previous page). The safest approach is to keep this consistent with your actual navigation path (don’t invent referrers you didn’t come from).
A practical approach is to inspect responses using a tool like Postman and tune additional headers to better mimic real browser traffic.
8. Cache to avoid unnecessary requests
If you can track which pages your scraper already visited, you can reduce time and unnecessary load. That’s where caching helps.
It’s a good idea to cache HTTP requests and responses. For a one‑time scrape, you can write responses to files. If you scrape repeatedly, store them in a database.
Another source of unnecessary requests is loose scraper logic in pagination scenarios. Spend time finding efficient combinations that get maximum coverage instead of brute‑forcing every possible combination.
Also, for business scrapes, add a few operational basics:
Checkpointing: resume safely if the job fails mid‑run.
Observability: log status codes, retries, blocks, and latency so you can detect issues early.
Data validation: schema checks, dedupe rules, and sanity checks (e.g., sudden price drops, missing fields) to catch site changes fast.
9. Beware of honeypot traps
Honeypot traps (or honeypot links) are links placed on a site to detect scrapers. Humans can’t see them, but scrapers often can. If your scraper accesses a honeypot link, the server can confidently classify you as a bot and start blocking IPs — or send your scraper into a wild goose chase that drains your resources.
When I was learning scraping with Python requests, I once ran into a honeypot trap. It took a lot of time to figure out what was going wrong.
Honeypot links often use CSS tricks (like hiding elements). You can use that to avoid following hidden links.
10. Treat CAPTCHAs as a stop sign
CAPTCHAs are a common way websites separate real users from automation. In many cases, a CAPTCHA is the site telling you: “slow down” or “use an approved access path.”
For business use cases, the best practice is:
First choice: use an API, licensed feed, or written permission.
Second choice: reduce request rates, add caching, and avoid unnecessary page loads.
Only if you have explicit permission and a compliant workflow: consider CAPTCHA handling as part of an agreed process.
If you’re scraping without permission, “solving CAPTCHAs” can quickly cross into policy and legal risk.
11. Schedule responsibly (off‑peak when possible)
If you can choose timing, scraping during off‑peak hours reduces load and lowers the chance you degrade real user experience.
Use schedulers like cron (or a workflow tool) and always include a hard stop / kill switch so you can pause quickly if something changes.
12. Use a headless browser
Web servers can often identify whether a request came from a real browser, which can lead to IP blocks.
Headless browsers can help because they behave much more like real browsers. A headless browser is a browser without a GUI. Some scraping tasks require browser automation (especially when the site relies heavily on JavaScript).
Common browser automation tools include Selenium, Puppeteer, Playwright, PhantomJS, CasperJS, and others.
13. The legal issues you should be looking at
The purpose of compliance is to protect your business from lawsuits, claims, fines, penalties, negative PR, and investigations. Compliance also ensures organisations don’t overuse scraping activities or misuse the data they acquire.
Before scraping, look at possible compliance issues. From sending anonymous requests to performing advanced scraping operations, this can get complicated.
a) Is the data behind a login?
Login‑gated data is high‑risk. Accessing it without explicit permission often violates Terms of Service and can create legal exposure (and your account may be suspended).
If you do have permission, treat it like an integration project:
keep credentials secure
limit scope to what’s approved
log access
implement strict rate limits
document the authorization
b) Does it violate copyright?
Some websites host copyrighted content. Common examples include music and videos. If you scrape that data and use it, you could face copyright infringement claims. Copyright violations can be serious and may involve heavy penalties.
c) Does it violate trespass to chattels?
If you overload a server with excessive parallel requests, you could unintentionally turn scraping into something that resembles a DDoS attack. If scraping causes damage by overloading the server, you could be held responsible and face legal claims (often discussed under “trespass to chattels”).
d) Does it violate GDPR?
GDPR restricts scraping activity involving personal data (PII). You should audit your scraping logic to avoid collecting unnecessary personal data and to filter or exclude PII.
14. Monitor reliability like a production system
A business scraper isn’t a script — it’s a data pipeline. Treat it like one.
At minimum, track and alert on:
Availability: success rate, HTTP status code distribution, timeouts.
Blocking signals: CAPTCHA frequency, 403/429 spikes, sudden redirect loops.
Performance: latency, average page load time (for headless runs), retry rates.
Data health: record counts, missing-field rates, duplicate rates, outlier detection.
If something drifts, you want to know in minutes — not when a stakeholder asks why yesterday’s feed is empty.
15. Design for site changes (because they will happen)
Sites change layouts, class names, and JSON payloads constantly.
Build with change in mind:
Prefer stable selectors (semantic attributes, labels, structured data) over brittle CSS chains.
Add contract tests (a few known pages) that run daily and fail loudly when parsing breaks.
Keep parsers modular (one page type = one parser) so fixes don’t ripple everywhere.
Store raw HTML / response snapshots for a small sample, so debugging doesn’t require re-running the crawl.
16. Make data quality part of the scraper, not an afterthought
Businesses don’t buy “scraped pages.” They buy decision-ready data.
Add lightweight quality controls:
Schema validation: required fields, types, allowed values.
Normalization: currencies, units, date formats, whitespace, encoding.
Deduping rules: canonical URLs, product IDs, stable keys.
Sanity checks: “impossible” values (negative prices, 10x jumps) flagged for review.
Also, capture lineage:
source URL
scrape timestamp
geo/proxy region (if relevant)
parser/version ID
When someone asks “where did this number come from?”, you should be able to answer.
17. Add a simple governance checklist before any scrape goes live
A short checklist prevents 90% of avoidable incidents:
Purpose & scope: what data, why you need it, retention period.
Access path: API/licensed feed/permission/allowed public pages.
Robots + ToS review: documented decision and owner.
Rate limits: concurrency, delays, and a clear crawl budget.
PII review: what you collect, what you exclude, and how you handle deletion requests.
Escalation plan: who gets paged, and when you pause the crawl.
If you run multiple client projects, this checklist becomes your internal “launch gate.”
Final thoughts
If you’re scraping for a business use case, best practices can save you time, money, and resources — and help you avoid legal trouble. Be a good citizen and follow the basics.
Automation libraries can help you extract data, but they won’t save you from compliance issues. From reading terms of service to choosing the right method, you have to stay vigilant.
If you don’t want to worry about these issues and just want the data, leave it to us. We will get the data for you — with documented crawl plans, reliability monitoring, and a compliance‑first process. Contact Datahut to learn how.
FAQs
1. What are the most important web scraping best practices?
The most important web scraping best practices include respecting robots.txt policies, implementing request throttling, rotating user agents and IPs responsibly, handling errors gracefully, maintaining clean data pipelines, and ensuring legal and ethical compliance. Scalability, monitoring, and documentation are also critical for long-term scraping success.
2. How can I avoid getting blocked while web scraping?
To avoid getting blocked:
Use rate limiting and request delays
Rotate IP addresses carefully
Implement user-agent rotation
Mimic natural browsing patterns
Avoid sending excessive concurrent requests
Additionally, monitor HTTP status codes (403, 429) and adjust scraping behavior dynamically.
3. Is web scraping legal?
Web scraping legality depends on factors such as the type of data collected, the website’s terms of service, jurisdiction, and how the data is used. Scraping publicly available data is often permissible, but scraping personal, copyrighted, or restricted data can create legal risks. Always conduct a compliance review before starting large-scale scraping projects.
4. How do I handle dynamic websites while scraping?
Dynamic websites that rely on JavaScript can be scraped using:
Headless browsers like Puppeteer or Playwright
Browser automation frameworks
API endpoint inspection
Network traffic monitoring
For performance at scale, hybrid approaches (API scraping + browser rendering only when required) are recommended.
5. How do I ensure data quality in web scraping projects?
To ensure high data quality:
Validate extracted fields
Remove duplicates
Normalize formats (dates, currencies, categories)
Set automated alerts for structural changes
Monitor data drift
Regular audits and schema validation significantly reduce downstream analysis errors.
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