What is web data collection?
Web data collection, aka web scraping, is the process of collecting and analyzing accurate data comprehensions from online sources for research and development by applying standard online data collection techniques. In recent technological developments, programming languages have been used for efficient online data collection. However, not all programming languages are built for collecting web data.
Scraping and extracting data from websites into usable formats consists of complex procedures designed to facilitate automation and improve efficiency and productivity. Some automated tools are used for automating the web scraping process. These tools help the web scraper fulfill some purposes, like:
Some uses of web data collection tools
1. Lead Generation.
2. Contact Information Extraction.
3. News Monitoring.
4. Data Collection for Market Research, etc.
A web data collection process involves;
1. Giving the automated web scraper URLs to load.
2. Load completed HTML code for the source page/website where data is to be extracted from.
3. Extract all or specific data selected by the user.
4. Finally, transfer extracted data into a unique format that can be used for research and analysis.
Having all of these processes automated saves time, and cost, and improves work productivity.
Factors to Consider When Selecting Tools for Web Data Collection
Web scraping can be a complex process when available data is unstructured or websites put restrictions on collecting data from their sites. Having the best system and tools in place is highly important for this data extraction task. These are some features to consider before choosing the best tools for web scraping.
1. Data delivery
3. Reliable Customer Support
4. Data quality
Managing websites with anti-scraping restrictions
This is one of the most vital factors. Having tools that can help scale through these restrictions will help your web collection greatly. Web data collection depends very much on automation. It lets data collectors or professionals get through their tasks almost swiftly, but it also presents problems as websites are generally alerted of automatic web actions. They defend their websites with anti-scraping systems that block any IP addresses entering their sites suspiciously or compel them to pass through CAPTCHAs.
This measure, however, can be avoided by using a Puppeteer proxy. A Puppeteer is a powerful node library that offers a high-level application programming interface (API) to control Chromium or Chrome-based browsers over the developer’s tools restrictions and regulations. By default, the puppeteer operates headless, but configurations can be made as per user preferences to run non-headless (full Chrome or chromium).
How a puppeteer can help you
Here are some helpful features of a Puppeteer:
- Test various Chrome extensions simultaneously.
- Automate form submission, keyboard input, User Interface testing, etc.
- Take screenshots and PDFs of web pages.
- Generate pre-altered content by using a single-page application (SPA).
- Perform real-time performance analysis for issue detection.
What Is a Proxy?
A proxy server operates as an intermediary or gateway between the user’s browser and the internet, i.e., when the user browses the internet through a proxy instead of requesting data collection access directly from websites. The entry request is sent to the proxy from your browser and from your proxy server to the website, and the reverse happens when the data goes back to the proxy user.
The advantage of using a proxy server when browsing the web is that your IP address stays camouflaged, and websites cannot detect the origin of a proxy request.
Why do you need a proxy server with a puppeteer?
A puppeteer proxy can be used for the following reasons:
1. To carry out an anonymous web scraping task.
2. To open webs with geographical restrictions.
3. To have undetectable location origins.
4. To automate data scraping tasks and avoid bans by simulating real user behavioral patterns.
5. To speed things up and increase the number of common requests without getting blocked.
A Puppeteer Proxy offers HTTPS support and controls proxy requests, site code errors, and cookies. You are only required to configure a specification on the proxy source to begin testing different URLs on a signal proxy.
Additional tools needed to scale web scraping
These additional tools help in automating web scraping. Each of them has some distinctive features that make them unique compared to others.
1. Common Crawl
6. Content Grabber Scraper API
Our top 5 programming languages for web scraping
There are diverse programming languages available today, with each having their own unique abilities in simplicity, functions, performance, and productivity level. However, these are the top five programming languages best suited for efficiently automating your web data collection procedures and are also able to handle and analyze large amounts of data:
Python is currently the most popular coding language. It is most effective for web scraping due to its all-in-one function for web data collection. It can be programmed easily without any errors because it is a simple language that is easy to understand and use.
This is an open-source language with a user-friendly interface. It is easy to understand and apply. The unique feature of Ruby is that it has multiple languages, such as Eiffel, Smalltalk, Perl, Lip, Ada, etc. Ruby is built to stabilize functional programming with the aid of imperative programming.
4. C & C++
C and C++ are excellent execution solutions, although their services can be expensive when performing web scraping tasks and thus are not recommended unless for a specific demand focused on just data extraction.
PHP is generally not ideal for creating web scraping automation programs. However, they come in handy when visual data forms need to be extracted at a fast processing speed.
Keeping this in mind, decisions can be made quickly when choosing the best-suited programming language for your web data collection endeavor. No ultimate language can solve all the difficulties you encounter when collecting data online. However, if you are new to data scraping, we recommend beginning with either Python or R due to their vast purpose.