What do you need to learn for python backend development?-Python Tutorial-php.cn

Home

Backend Development

Python Tutorial

What do you need to learn for python backend development?

下次还敢

Apr 20, 2024 pm 09:27 PM

mysqllinuxpythonredisgitdockermongodb

Basic skills for Python backend development include: Python programming language Data structures and algorithms Relational and non-relational databases Web frameworks (Django or Flask) RESTful API development Operating system knowledge Version control Debugging and error handling Data validation and security

What do you need to learn for python backend development?

Skills required for Python backend development

Basic skills

Python Programming Language: Proficient in Python's syntax, data types, control flow, and object-oriented programming concepts.
Data structures and algorithms: Master common data structures (such as lists, dictionaries, sets) and algorithms (such as sorting, search).

Database

Relational database: Be familiar with SQL queries and understand common database management systems (such as MySQL, PostgreSQL).
Non-relational databases: Understand NoSQL databases (such as MongoDB, Redis) and their advantages.

Web Framework

Django or Flask:Proficient in at least one Python Web framework and understand its MVC architecture and URL configuration and view handling.
RESTful API Development: Understand the principles and design patterns of RESTful APIs and be able to build and test APIs using Python.

Others

Operating system knowledge: Familiar with Unix/Linux operating system, understanding of file system and process management.
Version Control: Understand version control systems such as Git and be able to manage code libraries.
Debugging and error handling: Ability to use debugging tools (such as pdb) and error handling mechanisms to troubleshoot problems.
Data Validation and Security: Learn best practices for data validation and web application security.

Extended skills

Cloud computing: Understand cloud platforms such as AWS or Azure, and be able to deploy and manage back-end services .
Microservice Architecture: Understand the principles and implementation of microservice architecture and be able to design and build scalable back-end systems.
Containerization: Understand containerization technologies such as Docker and be able to use containers to deploy and manage back-end applications.

The above is the detailed content of What do you need to learn for python backend development?. For more information, please follow other related articles on the PHP Chinese website!

Statement

The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

What are the alternatives to concatenate two lists in Python?May 09, 2025 am 12:16 AM

There are many methods to connect two lists in Python: 1. Use operators, which are simple but inefficient in large lists; 2. Use extend method, which is efficient but will modify the original list; 3. Use the = operator, which is both efficient and readable; 4. Use itertools.chain function, which is memory efficient but requires additional import; 5. Use list parsing, which is elegant but may be too complex. The selection method should be based on the code context and requirements.

Python: Efficient Ways to Merge Two ListsMay 09, 2025 am 12:15 AM

There are many ways to merge Python lists: 1. Use operators, which are simple but not memory efficient for large lists; 2. Use extend method, which is efficient but will modify the original list; 3. Use itertools.chain, which is suitable for large data sets; 4. Use * operator, merge small to medium-sized lists in one line of code; 5. Use numpy.concatenate, which is suitable for large data sets and scenarios with high performance requirements; 6. Use append method, which is suitable for small lists but is inefficient. When selecting a method, you need to consider the list size and application scenarios.

Compiled vs Interpreted Languages: pros and consMay 09, 2025 am 12:06 AM

Compiledlanguagesofferspeedandsecurity,whileinterpretedlanguagesprovideeaseofuseandportability.1)CompiledlanguageslikeC arefasterandsecurebuthavelongerdevelopmentcyclesandplatformdependency.2)InterpretedlanguageslikePythonareeasiertouseandmoreportab

Python: For and While Loops, the most complete guideMay 09, 2025 am 12:05 AM

In Python, a for loop is used to traverse iterable objects, and a while loop is used to perform operations repeatedly when the condition is satisfied. 1) For loop example: traverse the list and print the elements. 2) While loop example: guess the number game until you guess it right. Mastering cycle principles and optimization techniques can improve code efficiency and reliability.

Python concatenate lists into a stringMay 09, 2025 am 12:02 AM

To concatenate a list into a string, using the join() method in Python is the best choice. 1) Use the join() method to concatenate the list elements into a string, such as ''.join(my_list). 2) For a list containing numbers, convert map(str, numbers) into a string before concatenating. 3) You can use generator expressions for complex formatting, such as ','.join(f'({fruit})'forfruitinfruits). 4) When processing mixed data types, use map(str, mixed_list) to ensure that all elements can be converted into strings. 5) For large lists, use ''.join(large_li

Python's Hybrid Approach: Compilation and Interpretation CombinedMay 08, 2025 am 12:16 AM

Pythonusesahybridapproach,combiningcompilationtobytecodeandinterpretation.1)Codeiscompiledtoplatform-independentbytecode.2)BytecodeisinterpretedbythePythonVirtualMachine,enhancingefficiencyandportability.

Learn the Differences Between Python's 'for' and 'while' LoopsMay 08, 2025 am 12:11 AM

ThekeydifferencesbetweenPython's"for"and"while"loopsare:1)"For"loopsareidealforiteratingoversequencesorknowniterations,while2)"while"loopsarebetterforcontinuinguntilaconditionismetwithoutpredefinediterations.Un

Python concatenate lists with duplicatesMay 08, 2025 am 12:09 AM

In Python, you can connect lists and manage duplicate elements through a variety of methods: 1) Use operators or extend() to retain all duplicate elements; 2) Convert to sets and then return to lists to remove all duplicate elements, but the original order will be lost; 3) Use loops or list comprehensions to combine sets to remove duplicate elements and maintain the original order.

See all articles