Share 7 Python development engineer interview questions
do you know? In fact, Python was born as early as the early 1990s, but it has not been popular for a long time. As far as the editor is concerned, I only learned about it in the past few years. According to statistics, the current salary of Python developers is more than 10K. It is difficult to refuse such a temptation, so many people have learned Python in recent years.
Python is an interpreted scripting language that focuses on readability and efficiency, especially compared to languages like Java, PHP and C. These two advantages make it very popular among developers, and it is also widely used in automated operation and maintenance scenarios in the field of operation and maintenance. Today, Python is used in a wide range of fields, including artificial intelligence, graphics processing, database programming, network programming, Web programming, multimedia applications, etc. By the way, why are so many companies recruiting Python developers now? The main reason is that the various advantages of Python have led major companies to start using Python development, which has caused a shortage of Python development talents, and the corresponding salaries of Python developers have also increased. Let me share with you a wave of related interview questions:
Recommended related articles: "2020 python interview questions summary (latest)"
NO.1 What are the built-in data types of Python?
Integer--int Boolean--bool
String--str List--list
Tuple--tuple Dictionary--dict
NO.2What is the difference between range(100) in Python2 and Python3?
python2 returns a list, python3 returns an iterator, saving memory
NO.3 Briefly describe the difference between __new__ and __init__ in object-oriented?
__init__ is the initialization method. After the object is created, it is called by default immediately and can receive parameters.
1. __new__ must have at least one parameter cls, representing the current class. This parameter is automatically recognized by the Python interpreter during instantiation
2. __new__ must have a return value and return the instantiated instance. Pay special attention to this when implementing __new__ yourself. You can return An instance from __new__ of the parent class (through super (current class name, cls)), or an instance directly from __new__ of object
3. __init__ has a parameter self, which is this __new__ The returned instance, __init__ can complete some other initialization actions based on __new__, __init__ does not need to return a value
4. If __new__ creates an instance of the current class, it will be called automatically __init__ function, the first parameter of the __new__ function called in the return statement is cls to ensure that it is the current class instance. If it is the class name of another class, then the actual creation and return are instances of other classes. In fact The __init__ function of the current class will not be called, nor will the __init__ function of other classes be called.
NO.4 Please tell me how to generate random integers, random decimals, and decimals between 0--1 in python?
Random integers: random.randint(a,b), generate integers in the interval
Random decimals: used to use numpy library, generated using np.random.randn(5) 5 random decimals
0-1 Random decimal: random.random(), no parameters are passed in brackets
##NO.5 Avoid transfer Which letter should be added to the string to represent the original string?
r means that the original string is required and special characters are not escapedExamples of assertion methods in pythonassert() method, if the assertion is successful, the program will continue to execute. If the assertion fails, the program will report an errorNO.6 Explain in one sentence what kind of language can use decorators?
Languages where functions can be passed as parameters, decorators can be usedNO.7 Briefly explain what the with method does to open the processing file for us?
Open Some abnormal situations may occur when the file is read and written. If we follow the conventional f.open writing method, we need to try, except, and finally to make exception judgments, and no matter what situation the file encounters in the end, We must execute finally f.close() to close the file. The with method helps us realize f.close in finallyThe above is the interview questions compiled by the editor today. Do you all understand it? Friends who don’t know should study it carefully, work hard and practice more to make your Python programming skills even better. In this way, no matter how difficult the interviewer asks, it will be a piece of cake for you. Let’s pick it up. Keep your sleeves up! [Recommended courses:Python related courses, Python3 related courses]
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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.

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Is 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.

Key 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 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.


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