Web Scraping With PHP vs. Python: Which to Choose?

June 28, 2024 · 17 min read

Are you trying to choose between PHP and Python for your next web scraping project?

While Python is a more popular pick for the job, PHP has its own set of advantages, especially if you’re already familiar with the language.

In this article, we'll compare PHP and Python's features, pros, and cons to help you make an educated decision and build an ultimately successful scraper.

Quick Answer: Should You Choose Python or PHP for Your Next Web Scraping Project?

The choice between web scraping with PHP or Python depends on your project requirements and expertise. Both languages have unique features for effective data extraction.

The real question should be, "Which language aligns best with my needs?"

Python is an object-oriented, high-level programming language with built-in modules that include functions and classes. It allows you to extract data from the web right off the bat. With many dedicated libraries and an active developer community, it’s also considered the most popular language for web scraping.

PHP is a server-side scripting language. While it's less commonly used for web scraping than Python, it's still a good choice for the job. Some of its built-in functions, such as file_get_contents(), allow you to fetch web content easily. However, it isn't a beginner-friendly language in terms of learning curve and syntax, and its web scraping ecosystem isn't as extensive as Python's.

So, which should you choose?

In most cases, the answer is Python because of its beginner-friendly syntax and a rich ecosystem of web scraping libraries.

Go with PHP if your application is written in PHP and you'd like your scraper to fit your existing projects and skills.

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PHP vs Python: Comparison

Let's see an overview of Python and PHP's characteristics, strengths, and weaknesses:

Python PHP
Best for Large-scale scraping and JavaScript rendering PHP-specific projects and developer expertise
Ease of use Beginner-friendly syntax and easy to learn Slightly steeper learning curve for web scraping
Performance Fast Moderate
Scraping libraries Rich ecosystem Limited choice
Data processing Offers libraries like NumPy and Pandas for efficient data processing Limited data processing with libraries
Community support Large and active web scraping community Limited community support around web scraping
JavaScript rendering Offers various libraries for rendering JavaScript, including Playwright, Splash, and Selenium Limited, but offers libraries for rendering JavaScript, Selenium being the most popular

Now, let's get into each factor in detail.

Python Is Easier to Learn for Web Scraping

Thanks to its readable syntax, Python is considered one of the easiest languages to learn.

Python's active users and developers make up a resource-rich support base, even for beginners. You can easily find quick answers and troubleshoot potential issues. Additionally, Python web scraping libraries provide high-level abstractions and intuitive APIs that make it easy to get started.

PHP is influenced by C and Perl. Its syntax is less readable than Python, with symbols that make PHP code seem verbose. Also, its not-so-robust web scraping ecosystem can make getting started challenging. However, it's also generally considered one of the easiest languages to learn and boasts good documentation.

Python Has Better Performance Than PHP

Python isn't the fastest language in terms of raw execution speed. That's because it's dynamically typed, which means it compiles fast and runs slow.

The performance issue mostly occurs with CPU-bound tasks (limited by the CPU's speed). Web scraping is I/O-bound (waiting for network requests or file I/O), and some of Python's features make it efficient for this type of task.

Firstly, Python supports asynchronous web scraping through libraries like asyncio. This allows the web scraper to perform other tasks while waiting for other I/O operations to complete. Additionally, Python lets you use multi-threading and multi-processing to handle I/O-bound operations concurrently.

PHP generally offers good performance for web applications. However, there may be better choices for large-scale and high-performance tasks outside of web development.

Python Wins With Its Rich Web Scraping Library Landscape

Python's web scraping library landscape is so rich that many of its tools have been adapted for other languages due to their popularity. You can find a library for every aspect of web scraping, from accessing website content to retrieving raw data and parsing HTML. Some of the popular libraries include Python Requests, BeautifulSoup, and Scrapy.

While similar libraries, such as Goutte and Guzzle, exist in PHP, they're not as prominent as their Python counterparts.

Keep in mind that while libraries save time and effort as they provide you with pre-built functions, they can also increase external dependencies and overall project size.

Python Is Better for Data Analysis

Web scraping and data analysis are closely related. Web scraping provides the raw data that data analysts convert into valuable insights. Depending on your use case, you may need powerful data analysis capabilities.

Python is a popular choice for data analysis due to several factors, including its clear and beginner-friendly syntax and rich libraries like Numpy and Pandas, which provide intuitive solutions for manipulating and visualizing data.

Python also enjoys one of the largest data analysis communities and a large variety of resources, including extensive documentation and tutorials. Python also integrates well with databases and a host of valuable statistical tools for data analysis.

Python Leads in Community Support

Community support is another important factor when choosing the right language for your project. The more resources are available, the easier it is to get started and troubleshoot any potential bugs.

Python leads in this regard as it's currently the most popular programming language, according to the TIOBE index. It has a vibrant and active community for web scraping and other programming areas.

While PHP also enjoys an active community, it revolves around web development.

They Can Both Render Javascript

The language's ability to render Javascript is crucial for web scraping. Most modern websites rely on JavaScript to display content or update data dynamically, so your scraper must execute JavaScript like a browser to access the website's content.

Both Python and PHP offer libraries that enable you to render JavaScript code and retrieve the desired data. Some Python solutions include Playwright, Splash, and Selenium, each providing APIs that allow you to automate web interactions.
Similarly, you can use Selenium with PHP to render dynamic content. Other libraries include Chrome PHP and Symfony Panther. However, rendering JavaScript with PHP is limited.


When it comes to web scraping, Python is a clear winner in every category. Its easy-to-learn syntax, rich library ecosystem, and extensive community make it the most popular and obvious choice.

However, if you're already in a PHP environment, stick with PHP for web scraping as well. PHP is also a solid choice for scraping thanks to its flexibility, ease of deployment, and dedicated libraries.

If you're ready to get started with either language, check out these guides:

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