Why are parsing mistakes so costly and how to avoid them?

Imagine: you run a parser to collect data on competitors' prices or find useful information to analyze. Everything goes well, until at some point the site blocks the requests and you lose access to the data. Or worse - you face legal trouble for violating the site's rules.

Parsing automates a routine: collecting data for business or analytics. For example:

• For marketers: monitoring prices, analyzing trends, or collecting reviews.
• For analysts: data for reports and forecasts.
• For developers: creating databases.

Parsing requires customization. One error is enough to:

• IP is blacklisted;
• the collected data turned out to be incomplete or inappropriate;
• the specialist faces accusations of violating the user agreement.

Let's break down six mistakes developers make when automating parsing. You will learn:

• how to avoid IP blocking;
• what to do with captcha and dynamic sites;
• how to store and organize data.

To each point added recommendations that will make parsing safe and effective. If you want to cut costs, protect yourself from mistakes and get the most out of parsing, read on.

First mistake: ignoring the rules of the site

What's going on:
Collecting data from sites that prohibit automation in the robots.txt file or user agreement.

Why it matters?
Sites set restrictions on automated access. They are specified in the robots.txt file or in the user agreement. For ignoring the rules are banned by IP or even sued.

To avoid this, check the robots.txt file. It is usually available at https://example.com/robots.txt. Pay attention to the Disallow lines, indicating the prohibition of parsing certain sections of the site.

Example:

User-agent: *

Disallow: /private/

Allow: /public/

In this example, parsing is allowed for /public, but not allowed for /private.

If it is important to collect data, contact the site owners. Often companies are willing to provide APIs or other access methods if you ask them directly.

Following site rules is not only a matter of ethics, but also a way to avoid bans and legal problems. Spend some time studying robots.txt and user agreements - it will keep you out of trouble.

Second mistake: parsing from one IP address without rotation

What's going on:
Data is being collected via queries from a single IP. This is one of the most common reasons for parser bans.

Sites track the frequency of requests from each IP. If the request limit is exceeded, anti-bot defenses are triggered, such as temporary bans or disabling access altogether.

Example:
You send 500 requests per minute from one IP. After a couple of minutes, the site recognizes you as a bot and bans you. Now you lose the ability to collect data, and unblocking can take hours or even days.

How to avoid:

1. Use proxies
   Proxies help “mask” requests by sending them from different IPs.

• Residential proxies. These look like regular user IPs. Suitable for the most complex tasks.
• Mobile proxies. The most difficult type to detect, as requests go through real mobile networks.
• Server proxies. The most budget-friendly option.

2. Rotate IP
   Set up a system that changes the IP every few requests. This will create the effect as if the data is being requested by different users.
3. Set up pauses between requests

• Set delays (e.g., 2-5 seconds) between requests.
• Use intervals to simulate the actions of a real user.

4. Avoid bulk requests
   Split parsing into several stages to avoid peak loads.

Using a single IP is an easy way to get banned. Set up rotation, use proxies and monitor the frequency of requests so that parsing is stable.

Third mistake: ignoring captcha

What's going on:
Attempting parsing without considering captcha.

Why it's important?
Captcha is the site's first line of defense against automated actions. It verifies that requests are sent by a human and not a bot. If the parser cannot process the captcha, the site closes further access.

The infamous captcha

Example:
You request data from a website, but instead of information you get a page with a captcha. The parser “hangs” or keeps sending meaningless queries, which leads to a ban.

How to avoid:

1. Use services to solve captcha
   Modern services allow you to automate captcha recognition:

• 2Captcha: will work for most text and image captchas.

The 2captcha logo hints that the service can pick locks

• AntiCaptcha: supports reCAPTCHA, hCaptcha and other complex types.
• CapSolver: optimized for high speed captcha recognition.

2. Principle of operation:

• The parser receives a page with a captcha.
• Sends the captcha to the recognition service.
• Receives a response and continues working.

3. Look for APIs without captcha
   Many sites only use captcha on user pages. Try searching for their API - it's often a faster and more convenient way to access data.
4. Reducing the likelihood of captcha

• Limit the number of requests from a single IP.
• Configure delays between requests.
• Use IP rotation.

Ignoring captcha is a sure way to run into problems. Use off-the-shelf services, reduce the probability of its occurrence and optimize the parser to overcome this protection.

Fourth mistake: incorrect processing of dynamic data

How it happens:
Parsing tries to collect data from HTML, but it's loaded using Javascript.

Why it matters?
Many sites use dynamic content loading via JavaScript (AJAX). This means that the data is loaded asynchronously after the initial page load. Simple parsers such as BeautifulSoup may not recognize this data because they don't handle JavaScript.

Javascript does not load the site immediately, but as you scroll down the page

Example:
You are trying to retrieve a list of products from an online store, but the data is not loaded immediately. The parser sees only a blank page or stubs, not actual product information.

How to avoid:

1. Use tools that support dynamic pages

• Selenium: Browser automator that can load JavaScript pages like a real browser.
• Puppeteer: A Node.js library for managing Chromium. It allows you to capture dynamic content and interact with the site in real time.
• Playwright: An alternative to Puppeteer with support for multiple browsers (Chromium, Firefox, WebKit).

2. Look for and use APIs

• If a site uses dynamic data loading, it often comes through an API. You can track requests through the developer tools in your browser and find the API that the site uses to retrieve the data. This will allow you to collect data without having to interact with the web page directly.

3. Working with dynamic content through rendering

• In the case of Selenium or Puppeteer, it is important to set the correct wait time to wait for all elements on the page to fully load before you start parsing the data.

For parsing dynamic data, it's important to use tools that can render JavaScript. Selenium, Puppeteer, and Playwright are great options for working with such pages. Also, don't forget to consider using an API if the site allows it.

Fifth mistake: lack of a data storage strategy

What is going on:
Collecting large amounts of data without thoughtful storage, leading to chaos and loss of information.

Why it matters?
When collecting large amounts of data, it's important to make sure it's stored properly. Without a good structure, data can become useless or worse, lead to loss. Also, with huge volumes, the file system or database can become overloaded, slowing down the parser and making further processing difficult.

Example:
You have collected data on hundreds of thousands of products from different sites, but all of them are stored in one CSV file without categorization. When you need to find a specific product, you have to manually search for it among thousands of strings. This is not only inconvenient, but also time-consuming.

CSV file in which it is convenient to store data

How to avoid:

1. Use structured storage formats

• CSV: Good for small amounts of data when each item has the same structure.
• JSON: Ideal for storing data with different structures, for example, when different elements may have different fields.
• Databases: If the data is large, use databases such as PostgreSQL or MongoDB, which will provide fast access and management of large amounts of data.

2. Create a clear storage structure

• Categorize data by date, source, data type, etc.
• Organize data into tables or collections to make it easier to find and process information.
• For databases, use indexes to speed up searching by key fields.

3. Backup and security

• Be sure to make regular backups of your data, especially if you work with sensitive information.
• When using cloud solutions, make sure your data is secure: use encryption and secure communication channels.

4. Separate data by volume
   If you have multiple data sources or are collecting information over a long period of time, split the data into multiple files or tables. For example, you can create separate files by date for daily collection.

To prevent the collected data from becoming chaos, it is important to think about the structure of the data in advance and choose a suitable storage format. Structured data makes it easier to process and search, and ensures stability in the long term.

Sixth mistake: incorrect setting of time intervals

What's happening:
Running requests too often, causing the site to shut down access.

Why it matters?
Too fast a frequency of requests from a single IP can easily be recognized as automated activity, leading to blocking or temporary suspension of access. Sites use different ways to protect themselves from bots, and one of the simplest is to track the frequency of requests. If requests come in too quickly or in one thread, they can activate anti-bot systems.

Example:
You run a parser that makes 1,000 requests per minute. As a result, the site detects abnormal activity and blocks your IP, even though you weren't trying to break the rules. This not only slows down the process, but also results in loss of access.

How to avoid:

1. Customize pauses between requests
   Adding a delay between requests helps avoid suspicion of automated behavior. For example, you can set pauses of 2-3 seconds between requests for sites with basic security.
2. Use randomized delays
   Randomizing the time between requests gives the impression that there is a real person behind the requests. For example, you can set pauses from 1 to 5 seconds randomly.
3. Determine the intervals depending on the site's defenses
   For sites with more sophisticated anti-bot defenses, you can increase the delay between requests or use more advanced methods to bypass the defenses. For example, mobile proxies or IP rotation can help reduce blocking risks.
4. Dynamically adjust query rates
   Use algorithms that adapt the query rate based on how quickly the site responds. If the site starts responding with delays or errors, reduce the query rate.
5. Analyze logs
   Keep a close eye on the site's responses. If you start getting a 429 (Too Many Requests) or 403 (Forbidden) response code, this is a clear signal that the frequency of requests is too high. Set up adaptive spacing.

Queries that are too frequent are a quick way to get banned. Adjusting pauses between requests and using random delays helps avoid detection and blocking. Don't forget that the stability of parsing directly depends on how “human” the traffic looks.