Octopus has some advantages, such as low learning cost, visual process, and rapid construction of collection system. Can directly export excel files and export to database. To reduce collection costs, cloud collection provides 10 nodes, which can also save a lot of trouble.
Octopus Collector also provides cloud collection services, which can be completed in a short time. You may need a few days. time to collect workload. (Recommended learning: Python video tutorial)
The bad thing is that even though it seems very simple, and there is a more fool-proof smart mode, there are pitfalls inside Only those who have used it a lot will understand.
First of all, the loops inside are all xpath element positioning. If you use simple click positioning, it will be very rigid, and it is easy to make mistakes when collecting pages in large batches. In addition, there are too many newbies who use this tool because of its convenience. People ask common questions all day long. They don’t know the page structure and don’t understand xpath. It is easy to cause problems such as incomplete collection and infinite page turning.
But Octopus Collector’s ajax loading, simulating mobile phone pages, filtering ads, scrolling to the bottom of the page and other functions are amazing tools and can be done with just one check. Writing code is very troublesome, and implementing these functions is laborious.
Octopus is just a tool after all, and its degree of freedom will definitely defeat programming. The advantage is convenience, speed and low cost.
The Octopus Judgment Quotes are weak and cannot make complex judgments or execute complex logic. Also, only the enterprise version of Octopus can solve the verification code problem, and the general version cannot access the coding platform.
Another point is that there is no OCR function. The phone numbers collected by 58.com and Ganji.com are all in image format. Python can be solved by using the open source image recognition library, and it can be connected and recognized.
The data collection needs determine what tool is ultimately used. If I have a large amount of data collection needs, crawlers must be inevitable because the code has a higher degree of freedom. I think the goal of Octopus is not to replace Python, but to achieve the goal of a collector that everyone can use.
Another point is that python is easy to learn, simple to deploy, open source and free. Even if you only learn scrapy, you can solve some problems. However, the trouble is that some functions that can be achieved by simple selection in some tools must be written by yourself or copied from other people's code. If you are not a full-time crawler writer, you will soon be able to solve it. I just want to go from getting started to giving up...
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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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