


Overcoming Selenium's Default Full Page Load Wait
Selenium's default behavior is to wait for a page to fully load before proceeding. This can be problematic when encountering slow or unresponsive scripts, especially when scraping or automating tasks. Here's a solution to limit the wait time and bypass AJAX file loading:
Configure PageLoadStrategy
Selenium provides the ability to customize the page load strategy using the pageLoadStrategy parameter. It supports three values:
- normal: (Default) Wait for full page load.
- eager: Wait only for interactive elements.
- none: Do not wait for page load.
Implementation
To configure pageLoadStrategy, use the DesiredCapabilities class:
Python (Firefox)
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities caps = DesiredCapabilities().FIREFOX caps["pageLoadStrategy"] = "eager" driver = webdriver.Firefox(desired_capabilities=caps)
Python (Chrome)
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities caps = DesiredCapabilities().CHROME caps["pageLoadStrategy"] = "eager" driver = webdriver.Chrome(desired_capabilities=caps)
Note: Eager page load strategy is not fully supported by ChromeDriver yet. However, you can overcome this issue by configuring PhantomJS or Firefox.
By setting the pageLoadStrategy to eager, Selenium waits only for the page to become responsive, avoiding delays caused by slow scripts. This allows for faster execution of your scripts and smoother automation without compromising the stability of the browser.
The above is the detailed content of How to Make Selenium Scripts Faster by Limiting Page Load Wait Time?. For more information, please follow other related articles on the PHP Chinese website!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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