Regular matching is usually used when crawling the web content of a single website. However, the structures of different websites are so strange that it is difficult to match them with a unified regular expression. The author of "General Web Page Text Extraction Algorithm Based on Line Block Distribution Function" summarized the general methods of extracting article text from web pages, proposed a text extraction algorithm based on line block distribution, and provided implementations in PHP, Java, etc. The main principles of this algorithm are based on two points: 1. Text area density: after removing all tags in HTML, the character density in the text area is higher and there are fewer multiple lines of blanks; 2. Line block length: the content in non-text areas is average Shorter in individual labels (line blocks). The algorithm steps are as follows: 1. Remove all tags, including styles, Js script content, etc., but retain the original line breaks\n2. Split the web page content by lines, and define the line block $block_i$ as the first $[i, i + blockSize ]$ The sum of lines of text and gives the distribution function of line block length based on line numbers: 3. The text appears in the longest line block, intercept the range from both sides to the line block length of 0: 4. If you need to extract the pictures that appear in the text area , you only need to keep 1 when removing the tag in the first step. [python tutorial] Web page text and content image extraction algorithm #Introduction: Regular matching is usually used when crawling the web content of a single website. However, the structures of different websites are so strange that it is difficult to use unified regular expressions. formula to match. The author of "General Web Page Text Extraction Algorithm Based on Line Block Distribution Function" summarized the general methods of extracting article text from web pages, proposed a text extraction algorithm based on line block distribution, and provided implementations in PHP, Java, etc. The main principles of this algorithm are based on two points: 2. Example of php extracting web page text_PHP tutorial Introduction: Example of php extracting the body content of a web page. Example of php extracting the text content of a web page because the difficulty lies in how to identify and retain the article part of the web page, and delete other useless information, and it must be universal and cannot be like a train 3. Where is the text information of web pages generally stored_html/css_WEB-ITnose Introduction: Where is the text information of web pages generally stored? 4. Example of php extracting the body content of a web page Introduction: Example of php extracting the body content of a web page. Example of php extracting the text content of a web page because the difficulty lies in how to identify and retain the article part of the web page, and delete other useless information, and it must be universal and cannot be like a train 5. In-depth analysis of the source code of using python to capture the text of web pages Introduction: Usually when you open a web page, in addition to the text content of the article, there is usually a lot of navigation. , advertising and other information. The purpose of this article is to explain how to extract the text content of an article from a web page and transition away other irrelevant information. 6. javascript collection of methods to change font size [original]_javascript skills Introduction: Provide the text of the web page, Switching function between small, medium and large fonts. Use js code to set the fontSize attribute of div style. 7. js Get the height and width of dom (visible area and part, etc.)_javascript skills Introduction : The width or height of the visible area of the web page, the width or height of the full body text of the web page, and the left or right part of the body text of the web page. Please see below for details. I hope it will be helpful to everyone. [Related Q&A recommendations] : objective-c - iOS web page text extraction open source library ##javascript - What is the implementation principle of Evernote's Chrome plug-in clipping
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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.

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.


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