For those who don’t know what to do next after learning the basics, read this article to ease their confusion. Today’s lesson is about how to systematically teach yourself Python planning goals. Have a learning goal to act on. How do you act when you have a goal? It is recommended to learn by watching videos and reading books. Watching videos can help you quickly master the basic grammar of programming, and typing code while watching videos can help you quickly get familiar with the grammar.
Python Skill Comparison table:
There are five stages to systematically learning Python by yourself
1. Python Foundation stage
Master Python script, Python interface programming ability, database, basic crawler, multi-threaded and multi-process development ability, capable of basic Python development work.
1. Data storage
Overview of Python, base and base conversion, source code, inverse code, complement, first Python program, terminal reading and printing, etc.
2. Operators and expressions
Keywords and identifiers, arithmetic operators, Python data types, assignment operators, operators, compound operators, conditional control statements (if.. else…) , logical operators, etc.
3. The cycle
Loop statements such as while, for, break, and continue statements.
4. Basic data structure
Number and mathematical function operation, String(find, replace, subscript index, list (common), tuple, dictionary (common), set set, iterator and generator (common), function overview, etc.
5. The function
Function call, the definition of simple function, function return values, pass parameters, key parameters, the default parameters, variable length, anonymous functions, decorator, partial function, the callback function, the scope of the variable, recursive functions, directory traversal, recursive traversal recursive traversal, stack simulation directory traversal (depth), queue simulation recursive traversal directory (breadth traversal), etc.
Module 6.
Module Overview Using modules in the standard library Using an overview of the custom module Name property pack Install the third-party module Virtualenv time-dependent module.
7. Object-oriented programming
Object-oriented thinking, classes and objects, methods and properties of classes, constructors and destructors, use of self, overwriting __ repr__ and __str__ functions, access restrictions, etc.
8. Inheritance, encapsulation, polymorphism
The implementation of single inheritance, the implementation of multiple inheritance, function rewriting, people shooting bullets small case, polymorphism, object attributes and class attributes, class methods and static methods, etc.
9. Object-oriented high-level
Dynamically adding property methods, properties, operator overloading, sending emails and SMS messages, etc.
10. File operation and exception handling
StringIO and BytesIO, file management, file read and write (CSV, TXT) operations, exception handling, etc.
11. Higher order functions and tests
Debug (print, assert, logging, PDB)
12. Permutation, combination and regular expression
Crack passwords (permutation, combination, permutation combination), regular expression, etc.
13. Network programming
Introduction to TCP/IP, TCP programming, UDP programming, etc.
Ii. Linux and Database phase
Master the Linux operating system management technology, can set up almost all Linux environment servers. Knowledge:
1.Linux operating system
Common operating system, operating system development history, system usage, Linux version, Linux application domain, installation of virtual machine and Vmware, Linux version and Ubuntu 16.04, configuration of your own Linux system, installation of programming IDE, and apT-GET installation package.
2. File system and user management
Directory access, file and directory management, file permissions, user management.
3. Text operation commands
Text command and text editor Vi/Vim.
4. Network command, process management and service configuration
Network management commands, system directories, important system files, startup and login startup Settings, IP configuration, service start and stop, firewall configuration.
5.Shell programming and bash, source file compilation
Basic IO operations, process control, defined variables and environment variables, script parameters, scheduled tasks, scheduled system operations.
6. Version control
Git installation and configuration, GitHub registration and use, Clone and Fork, Git common commands, tags, branch and source, multi-person collaborative development.
7. Basic use of MySQL
MySQL installation, introduction to MySQL, basic commands and scripts of MySQL, and interaction between MySQL and Python.
8. Basic use of MongoDB
Install MongoDB and perform basic operations on MongoDB.
9. Basic use of Redis
Redis installation, Redis basic operation, Redis data type, Redis backup and restore.
3. Python Web development
Master Python backend framework, solve front and back end Web development problems, knowledge:
1.HelloDjango
BS/CS,MVC/MTV, Django request flow, Admin management.
2.Models
ORM, model field properties, CRUD, aggregate functions, F,Q objects.
3.Models&Templates
Model mapping, template loading, static resources, and template syntax.
4.Views
Routing rules, reverse resolution, request and response, session technology Cookie, Token, SES-SION, file upload.
5.Advanced
Verification code, 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.
4. Python crawler phase
Master distributed multi-threaded large crawler technology, can develop enterprise crawler program.
1. Multithreading principle
Synchronous vs. asynchronous, series vs. concurrency, threading, opening a thread, Thread safety vs. thread locking, multithreaded queues.
2. Coroutines
The limitation of thread, the definition and principle of coroutine, the implementation of coroutine.
3. Concept of crawler and related tools
Crawler concept and function, HTTP protocol principle, tool installation, use.
4.Python http libs
Use of urllib, use of the sample requests library, use of the BS4 library, xpath syntax.
5. Actual reptile combat
Write in Requests – a simple crawler, retrofit the requests crawler to multithreaded, retrofit the multithreaded crawler to distributed using Redis.
3. Scrapy framework
Scrapy install, create project, create spider file, Write a parse method, a scrapy subcommand, run a scrapy crawler, pass parameters on the command line, further parse secondary pages, pass parameters before parse, export JSON, Csv format data, preserve the state of a scrapy crawler, define an item, use an item, and pipeline Use, use pipeline to store items to MySQ, Lscrapy overall architecture, downloaderMiddleware, use Downloadermiddleware to implement IP proxy pool, Spidermiddleware, scrapy plugin, SCRA Py – redis.
7. Quantitative trading
Automated trading theory, Quantitative trading framework in Python.
5. Python machine learning phase
Master Python data mining analysis, introduction to artificial intelligence. Knowledge:
1. Introduction to jupyter
Jupyter software installation, Jupyter entry, NUMPY learning.
2.pandas
Introduction to Pandas, Pandas -Series, Pandas data loss, Pandas index, Pandas data processing, Face recognition technology based on Pandas.
3.matpoltlib
The concept of data visualization, visualization chart drawing, animation and interactive rendering, data merging and grouping.
4.KNN
Proximity algorithm, preprocessing, KNN correlation function.
5. Linear and logistic regression
Linear regression, logistic regression.
Decision trees and Bayes
Bayesian learning, decision tree learning.
7.SVM and K-means clustering
SVC learning
8.Kmeans
Kmeans learning
9. Machine learning framework TensorFlow
Description of machine learning, weight allocation and optimization scheme, deep learning, automatic neural network and AI network.
Natural language processing and social network processing
Text data processing, natural language processing and NLTK, subject model, LDA, introduction to Graph Theory, network operation and data visualization.
The use rate of Python in foreign countries is very high. In China, Python has been in a hot stage in recent years, and the market demand for Python development talents has increased sharply. The prospect of learning Python is good, so take action. Come to an end here, I am a small blogger that likes to share, have a problem can private message I + resources share, beg attention.