说下我的情况：
我随便照本书学完 Python，基础和常用模块使用没太大问题，但不知道下一步该看什么书或怎么继续学习了。
网上有些人建议拿实际项目练，但学校里没有用以练习的项目，Git 虽会用，但从未在 Git 上做过项目，也不知道该怎么起步。不像学 Java 和 Java Web 可以看书搭站继续学，Python 学完基础后除了写小程序快外不知道该用它做什么。
各位前辈能给我提一些建议么？什么方面的建议都可以，这种情况应该怎么继续去学习。
Learning Python: Is 2 Hours of Daily Study Sufficient?Apr 18, 2025 am 12:22 AMIs 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.
Python for Web Development: Key ApplicationsApr 18, 2025 am 12:20 AMKey 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 vs. C : Exploring Performance and EfficiencyApr 18, 2025 am 12:20 AMPython 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.
Python in Action: Real-World ExamplesApr 18, 2025 am 12:18 AMPython's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.
Python's Main Uses: A Comprehensive OverviewApr 18, 2025 am 12:18 AMPython is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.
The Main Purpose of Python: Flexibility and Ease of UseApr 17, 2025 am 12:14 AMPython's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.
Python: The Power of Versatile ProgrammingApr 17, 2025 am 12:09 AMPython is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.
Learning Python in 2 Hours a Day: A Practical GuideApr 17, 2025 am 12:05 AMYes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.
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