写PHP越来越感觉很吃力,想到了转行。。。转行做什么
今天公司开会说急需要做一类似代销批发平台,功能很多。总结起来:
1)经销商注册、认证、下单、支付。(不同级别经销商价格、返点不一样,能下的货物也不一样)
2)跟进客服1对1审核、跟进、回答。(分权限:某个客服对应某几个经销商)
3)还有就是财务专员查看核对功能、支付安全,数据热备份之类的。。。
力不从心,效率很低
开会的时候听到这么多需求功能就觉得自己应付很吃力,心里预算做一个这样的系统会很久很久…… 甚至遥遥无期…… 一两年前的“不适合再做技术”的感觉又突然那么强烈。现在整个公司一个WEB程序员,我敢肯老总预留的制作时间是最多一个月。做一个批发货系统有这么容易这么快吗?界面、后台、支付、安全、做好之后还必须得修改几下。界面必须做,一个真正可以用的平台,界面肯定是必须得美化,不可能到时候光秃秃的几个列表给经销商看吧。公司只有1个PHP程序员,如果人手确实不够为什么不自己向上面申请多招?最后这个web平台需结合erp那边,想到公司的erp程序员是一个人做了整个公司的erp系统自己更觉得有点自叹不如,混不下去。下载了ecshop来改,对于smarty又觉得非常吃力,以往自己做小型PHP的都是include ‘模板文件’;从不用smarty。问公司的另一个做客户端程序员的程序员要多久,他说这个很容易非常简单,以前做过,他自己一个人一个月不到就做好了。。。。
做了5年技术,还是只会PHP
做了5年多的PHP,但JAVA、C++、 .Net、 安卓一点儿都不会,起个大早赶个晚集,还是只会PHP。JS也不精通:拖曳的那个手写不出来都是复制别人的改、OOP、MVC、Cakephp、thinkphp基本上不用,用的是dede - dz 的框架底、flash无刷新图片上传还没弄过一直用传统的form post FILES、网银支付接口更是没有弄过、没有团队合作过,因为每次进的公司都是最多1个PHP程序员。每次做新的功能,都觉得很吃力。转眼已经24了,现在对技术开始有点木了,以前做了2年的前端PHP做得快要吐了,装不下新的东西,对新的技术完全没有了兴趣。只觉得做技术越来越吃力 力不从心,真有点想转行,但是没有勇气,偶偶冲动地想想后又继续死撑下去。
如果转行,可以做什么?后路在哪里
一直喜欢的是运作网站,想通过运作网站来盈利养活自己。一个人做过很多网站运作(从程序到模板界面到推广到内容),但没赚到过钱,觉得流量真心不值钱盈利太难,该何去何从
希望得到大家的回帖点评或邮件,我的邮箱admin@zbphp.com 。

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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