环境:CentOS 7、PHP 5.4.16
原本是编译PHP 7,遇到两个问题,之后用PHP 5.4.16进行了验证,这两个问题依然存在。
简化的编译命令是:
<code>./configure --prefix=/usr --enable-fpm --enable-mbstring=shared make && make install</code>
1.扩展文件目录:
请问,是否可以在编译过程中指定扩展文件的目录。
用yum安装PHP的时候,扩展目录是:
<code>/usr/lib64/php/modules</code>
而进行编译安装的时候,扩展目录是
<code>/usr/lib/php/extensions/no-debug-non-zts-20100525</code>
尝试用--extension-dir
做编译参数,不被支持。
请问,是否进行编译安装的时候,无法控制扩展目录?
2.编译目录中的.a文件:
编译之后,进入扩展目录,可以发现,除了一般需要的.so文件之外,每个扩展还存在一个.a文件。
比如:
请问,这个.a文件是干什么用的?是否可以通过编译参数不生成这个文件?
另外:当完成PHP编译,单独编译扩展的时候则不会有.a文件。
回复内容:
环境:CentOS 7、PHP 5.4.16
原本是编译PHP 7,遇到两个问题,之后用PHP 5.4.16进行了验证,这两个问题依然存在。
简化的编译命令是:
<code>./configure --prefix=/usr --enable-fpm --enable-mbstring=shared make && make install</code>
1.扩展文件目录:
请问,是否可以在编译过程中指定扩展文件的目录。
用yum安装PHP的时候,扩展目录是:
<code>/usr/lib64/php/modules</code>
而进行编译安装的时候,扩展目录是
<code>/usr/lib/php/extensions/no-debug-non-zts-20100525</code>
尝试用--extension-dir
做编译参数,不被支持。
请问,是否进行编译安装的时候,无法控制扩展目录?
2.编译目录中的.a文件:
编译之后,进入扩展目录,可以发现,除了一般需要的.so文件之外,每个扩展还存在一个.a文件。
比如:
请问,这个.a文件是干什么用的?是否可以通过编译参数不生成这个文件?
另外:当完成PHP编译,单独编译扩展的时候则不会有.a文件。

PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

PHP originated in 1994 and was developed by RasmusLerdorf. It was originally used to track website visitors and gradually evolved into a server-side scripting language and was widely used in web development. Python was developed by Guidovan Rossum in the late 1980s and was first released in 1991. It emphasizes code readability and simplicity, and is suitable for scientific computing, data analysis and other fields.

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

PHP remains important in the modernization process because it supports a large number of websites and applications and adapts to development needs through frameworks. 1.PHP7 improves performance and introduces new features. 2. Modern frameworks such as Laravel, Symfony and CodeIgniter simplify development and improve code quality. 3. Performance optimization and best practices further improve application efficiency.

PHPhassignificantlyimpactedwebdevelopmentandextendsbeyondit.1)ItpowersmajorplatformslikeWordPressandexcelsindatabaseinteractions.2)PHP'sadaptabilityallowsittoscaleforlargeapplicationsusingframeworkslikeLaravel.3)Beyondweb,PHPisusedincommand-linescrip

PHP type prompts to improve code quality and readability. 1) Scalar type tips: Since PHP7.0, basic data types are allowed to be specified in function parameters, such as int, float, etc. 2) Return type prompt: Ensure the consistency of the function return value type. 3) Union type prompt: Since PHP8.0, multiple types are allowed to be specified in function parameters or return values. 4) Nullable type prompt: Allows to include null values and handle functions that may return null values.

In PHP, use the clone keyword to create a copy of the object and customize the cloning behavior through the \_\_clone magic method. 1. Use the clone keyword to make a shallow copy, cloning the object's properties but not the object's properties. 2. The \_\_clone method can deeply copy nested objects to avoid shallow copying problems. 3. Pay attention to avoid circular references and performance problems in cloning, and optimize cloning operations to improve efficiency.

PHP is suitable for web development and content management systems, and Python is suitable for data science, machine learning and automation scripts. 1.PHP performs well in building fast and scalable websites and applications and is commonly used in CMS such as WordPress. 2. Python has performed outstandingly in the fields of data science and machine learning, with rich libraries such as NumPy and TensorFlow.


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