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This article is about how to systematically self-learn Python programming, the editor thinks it is very practical, so I share it with you. I hope you can get something after reading this article.

The purpose of the vast majority of people who change careers with zero foundation is to find a job with high salary and development prospects, and the better the employment prospect of which programming language is, the better it is to learn. It is a good choice for students with zero foundation to learn Python.

The most confused thing for beginners with zero foundation is that they don't know how to start learning. It is recommended to use video + books to learn. Watching video learning can quickly master the basic syntax of programming, while watching the video while typing the code can quickly get started proficient in grammar. Reading and learning is not to read the whole book, you can put the book at hand when you do not understand the place can be used as a reference book. Today, the editor shares the learning route of Python:

Systematic self-study of Python is divided into the following five stages:

I. the basic stage of Python

Master python script, python interface programming ability, database, basic crawler, multi-thread and multi-process development ability, can be competent for the basic python development work. Knowledge points:

1. Data storage: Python overview, binary and binary conversion, original code, inverse code, complement, the first Python program, terminal reading and printing, etc.

two。 Operators and expressions: keywords and identifiers, arithmetic operators, python data types, assignment operators, operators, compound operators, conditional control statements (if..else...), logical operators, and so on.

3. Loops: while of looping statements, for of looping statements, break and continue statements, etc.

4. Basic data structures: Number and mathematical function operations, String (find, replace, subscript index, list (common), tuple, dictionary (common), set collection, iterator and generator (common), function overview, etc.

5. Function: function call, definition of simple function, return value of function, pass parameter, keyword parameter, default parameter, indefinite length parameter, anonymous function, decorator, partial function, callback function, scope of variable, recursive function, directory traversal, recursive traversal directory, stack simulation recursive traversal directory (depth traversal), queue simulation recursive traversal directory (breadth traversal), etc.

6. Module Overview using modules in the standard library use the overview of the custom module name property pack to install third-party module virtualenv and time-related modules.

7. Object-oriented programming: object-oriented ideas, classes and objects, methods and properties of classes, constructors and destructors, use of self, rewriting _ _ repr__ and _ _ str__ functions, access restrictions, etc.

8. Inheritance, encapsulation, polymorphism: implementation of single inheritance, implementation of multi-inheritance, function rewriting, small cases of human shooting bullets, polymorphism, object and class properties, class methods and static methods, etc.

9. Object-oriented high-level: dynamic add attribute method, property, operator overloading, email and SMS and so on.

10. File operation and exception handling: StringIO and BytesIO, file management operation, file read and write (csv, txt) operation, exception handling, etc.

11. Higher-order functions and testing: debugging (print, assertion, logging, pdb)

twelve。 Permutations and combinations and regular expressions: cracking codes (permutations, combinations, permutations and combinations), regular expressions, etc.

13. Network programming: TCP/IP introduction, TCP programming, UDP programming, etc.

II. Linux and database phase

Mastering Linux operating system management technology, you can build almost all Linux environment servers. Knowledge points:

1.Linux operating system: common operating system, operating system development history, system use, Linux version, Linux application field, virtual machine and Vmware installation, Linux version and Ubuntu 16.04, configuration of own Linux system, programming IDE installation, apt-get installation package.

two。 File system and user management: directory access, file and directory management, file permissions, user management.

3. Text operation command: text command, text editor Vi/Vim.

4. Network commands, process management and service configuration: network management commands, system directories, important system files, setup boot and login startup, IP configuration, service startup and stop, firewall configuration.

5.Shell programming and bash, source file compilation: basic IO operations, process control, definition variables and environment variables, script parameters, timing tasks, timing system operations.

6. Version control: installation and configuration of Git, registration and use of GitHub, Clone and Fork, common Git commands, tags, branches and sources, multi-person collaborative development.

Basic use of 7.MySQL: installation of MySQL, introduction to MySQL, basic command scripts for MySQL, interaction between MySQL and Python.

Basic use of 8.MongoDB: MongoDB installation, basic operation of MongoDB.

The basic use of 9.Redis: Redis installation, basic operation of Redis, data type of Redis, backup and recovery of Redis.

III. Python web development

Master Python backend framework, solve front and back end Web development problems, knowledge points:

1. HelloDjangoviso BSAccording CS MagneMVC, Django request flow, Admin management.

2.Models:ORM, model field properties, CRUD, aggregate function, Fmai Q object.

3.Models&Templates: model correspondence, template loading, static resources, template syntax.

4.Views: routing rules, reverse parsing, request and response, session technology cookie,token,ses-sion, file upload.

5.Advanced: CAPTCHA, pager, class view, middleware, log, cache, signal, Cerlery, user rights, user roles.

6.RESTful:REST concepts, HelloREST, data serialization, request and response, views, converters, relationships, hyperlinks, authentication, and permissions.

IV. Python crawler stage

Master distributed multi-thread large crawler technology, can develop enterprise crawler program.

1. Multithreading principle: synchronous and asynchronous, concatenation and concurrency, thread, opening up a thread, thread safety and thread lock, multithread queue.

two。 Collaborative process: the limitation of thread, the definition and principle of cooperative program, and the realization of cooperative program.

3. The concept of crawler and related tools: the concept and function of crawler, the principle of HTTP protocol, the installation and use of tools.

The use of 4.Python http libs:urllib, the use of the sample requests library, the use of the bs4 library, xpath syntax.

5. Crawler practice: use requests to write a simple crawler, transform requests crawler into multi-threaded version, use redis to transform multithreaded crawler to distributed.

6.scrapy framework: scrapy installation, project creation, spider file creation Write parse methods, scrapy subcommands, run scrapy crawler, pass parameters on the command line, further parse secondary pages, pass parameters before parse method, export json, Csv format data, state preservation of scrapy crawler, definition of item, use of item, use of pipeline, use of pipeline to store items to MySQ, Lscrapy overall architecture, downloadermiddleware, use downloadermiddleware to achieve IP proxy pool, spidermiddleware, scrapy plug-in, scrapy-redis.

7. Quantitative trading: automated trading theory, Python quantitative trading framework.

5. Python machine learning stage

Master Python data mining analysis, introduction to artificial intelligence. Knowledge points:

Introduction to 1.jupyter: installation of jupyter software, introduction to jupyter, numpy learning.

Introduction to 2.pandas:pandas, pandas-Series, pandas data loss, pandas indexing, pandas data processing, face recognition technology based on Pandas.

3.scipy:scipy learning

4.matpoltlib: the concept of data visualization, the drawing of visual charts, animation and interactive rendering, data merging and grouping.

5.KNN: proximity algorithm, preprocessing, KNN correlation function.

6. Linear regression and logistic regression: linear regression, logistic regression.

7. Decision tree and Bayesian: Bayesian learning, decision tree learning.

8.SVM and K-means clustering: SVC Learning

9.Kmeans: Kmeans learning

10. Machine learning framework TensorFlow: machine learning, weight distribution and optimization scheme, deep learning, automatic neural network, AI network description.

11. Natural language processing and social network processing: text data processing, natural language processing and NLTK, topic model, LDA, introduction to graph theory, network operation and data visualization.

The utilization rate of Python abroad is very high, but in China, Python has just become popular in recent years. Python is in a period of rapid growth. The demand for Python development talents in the market is increasing rapidly, and the prospect of learning Python is good.

The above is how to systematically self-teach Python programming, the editor believes that there are some knowledge points that we may see or use in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.

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