What Can Ordinary People Do with Python?

Web scraping, also known as web spiders, refers to a script program that crawls the web to extract the desired content according to certain rules. As we know, each webpage usually contains links to other webpages, and web spiders access other URLs sequentially to obtain the required content.

As a general search engine web collector; (Google, Baidu)

As a vertical search engine.

Scientific research: Empirical research in fields such as online human behavior, online community evolution, human dynamics research, quantitative sociology, complex networks, and data mining requires large amounts of data, and web scraping is a powerful tool for collecting relevant data.

Peeping, hacking, sending spam…

Web scraping is the first and also the easiest step for search engines.

C, C++: High efficiency, fast, suitable for general search engines to crawl the entire web. The downside is that development is slow and the code can be verbose.

Script languages: Perl, Python, Java, Ruby. Simple, easy to learn, good text processing allows for detailed extraction of webpage content, but efficiency is often not high, suitable for focused crawling of a few websites.

Web scrapers written in C#, Java are not much different; the principle is to make good use of regular expressions. However, it is a platform issue. Later, I learned that many scrapers are written in Python, and I became fascinated. Python has many advantages, summarizing two key points:

1. The interface for fetching web pages

Compared with other static programming languages like Java, C#, C++, Python’s interface for fetching web documents is more concise; compared with other dynamic scripting languages like Perl and Shell, Python’s urllib2 package provides a more complete API for accessing web documents. (Of course, Ruby is also a good choice.)

In addition, sometimes web scraping requires simulating browser behavior; many websites block rigid scraping. This requires us to simulate user agent behavior and construct appropriate requests, such as simulating user login, simulating session/cookie storage and settings. Python has excellent third-party packages to help you with this, such as Requests and Mechanize.

2. Processing after web scraping

Scraped web pages often need processing, such as filtering HTML tags and extracting text. Python’s BeautifulSoup provides a simple document processing function, allowing most document processing to be completed with very little code.

In fact, many languages and tools can achieve the above functions, but Python can do it the fastest and cleanest.

Web development is quite understandable; it refers to developing web applications that can be operated directly through a browser without needing to install desktop applications.

Web frameworks are middleware platforms developed to improve the efficiency of web application development. Developers do not need to start coding from scratch, but can develop programs by calling the framework to save time and costs.

1. Basic Python knowledge: Basic concepts such as conditional statements, loops, functions, and classes;

2. Basic database knowledge: Where is the data stored? It is in the database, and CRUD (Create, Read, Update, Delete) operations will be used.

Additionally, frameworks like Django and Flask based on Python have become very popular in web development recently.

These web frameworks can help you write server-side code (backend code) in Python. This code runs on your server, not on the user’s device and browser (frontend code).

Artificial Intelligence (AI) is a new field of technology that studies and develops theories, methods, techniques, and application systems to simulate, extend, and enhance human intelligence.

Artificial Intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce a new type of intelligent machine that can respond in a way similar to human intelligence. Research in this field includes robotics, language recognition, image recognition, natural language processing, and expert systems. Since its inception, AI has matured in theory and technology, and its application fields continue to expand. It is conceivable that future AI-driven technological products will be the “containers” of human wisdom and may even surpass human intelligence.

For those hoping to enter the AI and big data industry, putting all your eggs in the Python basket is not only safe but essential.

In other words, if you want to become a pioneer of the next era—the era of artificial intelligence—rather than being chased forward by this era, just focus on mastering Python.

Of course, Python is not without its problems and shortcomings; you can and should have one or even several other languages to complement Python. However, Python will undoubtedly hold the position of the primary language for data analysis and AI.

I even believe that due to Python’s established position, and the industry’s future need for a large number of practitioners, along with Python rapidly becoming the preferred teaching language for programming courses in primary and secondary schools worldwide, this open-source dynamic scripting language has a very good chance of becoming the first truly universal programming language in the near future.