Angry liver for half a month! Python learning route + summary of resources

Python learning route by fish skin.

Original is not easy, please do not plagiarize, offenders must be investigated!

is the same as the previous suggestion The following video understands a few questions:

• Why is Python so popular?
• Why are all talking about learning Python and can’t find a job? Is Python really fragrant?
• Do I want to learn Python?
• How to learn quickly?

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There are many reasons,List a few points:

1. has simple syntax is easy to learn , other languages ​​can only be achieved with 5 lines of code, python can be done in one line! You can write a lot of code less, so many students use Python to brush algorithm questions (but pay attention to understand the algorithm itself).
2. class library is rich in ecology, basically there are ready-made codes for any function you want, just use it directly, it is extremely convenient!
3. is free and open source. Interested and capable students can study the source code by themselves.
4. Other features, such as cross-platform, extensible, etc.
5. , as the preferred language of data science and artificial intelligence, has stepped on the wind of the times.

Since then, Python was promoted to the altar, and even in the programming language in October 2021, Python was ranked first!

TIOBE programming language ranking list

, but that’s the "eternal god"But on the Internet, there is a rhetoric: I can’t find a job if I learn Python!

Hey, why?

Why is Python not suitable for job hunting?

On the one hand, most companies do not use Python to develop applications.

Because the running speed of Python is too slow, let alone compare with the underlying C++, Java can get rid of it a few blocks! And this is related to the design and implementation of the language itself, so even if you develop any technology to optimize its performance, there will be a bottleneck after all, the world's best language PHP is the same.

For enterprises, performance will directly affect user experience and machine cost, especially in this era of information explosion and everyone is pursuing performance. Python is in the application development era. The status is very embarrassing, and the development post happens to be a very high proportion of programmers.

On the other hand, although Python has many application scenarios and many related positions, what is the mainstream language of AI and data science? The future is very bright. However, the difficulty of these cutting-edge technologies is not the Python language code itself, but the algorithms and ideas. Python is just a tool for tuning packages and expressing your thoughts. Therefore, the threshold for these cutting-edge positions is much higher than when you get started with Python or when you listen to training institutions to draw cakes.Algorithm jobs and product jobs at major factories are really fairy fights, and most of them are graduate students.

learning objectives

In this case, should I learn Python?

I think: must learn!

However, you must first think about your learning goals. Different goals have different attitudes towards Python and the time invested.

If you want to find a job in a development position, as mentioned above, it is not recommended to use Python as your main language, but as your secondary weapon. Just simply learn the basics of Python, you can write Python scripts to automate office, improve work efficiency, and make some small tools, which is very cost-effective.

If programming language is a tool, then Python is the perfect interpretation of this sentence. will use one more artifact, who doesn’t love it?

If you want to find jobs in other positions, such as operation and maintenance, testing, data analysis, product manager, big data, crawlers, artificial intelligence, image processing, multimedia processing, algorithm research, of course, you can.It's just that if you target these positions, in addition to laying a good foundation in Python, it is more important to understand the ideas, methods, and practices of the corresponding field, rather than just referencing the library.

If you are a beginner programming or learning programming out of curiosity, I also recommend that you learn Python. It is fun, can learn, and cultivate interest. These are very important for beginners. After you become interested, you should learn more. The language will be like a fish in water.

Learning Suggestions

For beginners and non-Python practitioners, use Python as a tool to learn, understand the basic syntax and common libraries, and use search engines and documents when you need to write Python scripts Just write (or copy) the code. As long as you have learned other programming languages, it is really easy to get started with Python, and you can learn it in 3-7 days.

It is recommended to write more small examples when learning, such as Python processing tables, Python processing PDF, etc., feel the power of the Python library and it’s done~

span part of the study route

Fish Skin-Python learning route _span_

h1 learning route h174 h175h1

• Python mounted
• expression operators and tools PyCharm SublimeVS Code
• variable naming rules define the variable keyword conversion type basic data types Formula
• flow control conditional branch loop
• basic data structure string list tuple set dictionary _span_li2span function definition function domain commonly used function definition lib_span_li2span 33 span5span _ li38li
• ⭐ Three major features of object-oriented programming classes and objects encapsulate self attribute method class method instance method static method access control inherit single inheritance multiple inheritance polymorphic method override operator overload decorator reflection
• module import module common module file processing date and time
• package import package generation package
• exception handling capture exception try ... else ... finally5 structure span _span _span _span _span _38
• file operation file opening and closing file read and write

advanced

• function advanced closure anonymous function generator function decorator high-order function _li2li5 span _li2li5
• database programming database basic SQL writing query aggregation group association sort transaction database design database tuning
• concurrent programming synchronous and asynchronous blocking and non-blocking multi-threaded multi-process library _ coroutine span5span
• network programming network foundation (seven-layer model, IP) network protocols (TCP, UDP, HTTP, HTTPS, FTP, DNS) WebSocket

web development

• Django framework installation and DemoMVT hierarchical model database basic ORM single table query multi-table query aggregation query view template syntax static resource routing Django Admin management tool test session authentication file upload middle Advanced features paging cache local cache Redis distributed cache serialization signal celery task scheduling Restful API development concept data serialization Django Rest Framework deployment project actual combat
• front-end basic HTMLCSS JavaScript li2span span33 Flask framework

crawler

• concept
• _span2 li38li
• li3 Request type response response header response parameter requests module urllib module simulates landing static/dynamic website crawling headless browser seleniumpuppeteer
• data analysis commonly used tags BeautifulSoup regular expression xpath _li33 xcelCSV database MongoDBMySQL middleware Redis
• Scrapy framework of the core concepts of command-line tools SpidersSelectorsItemsItem Loaders pipeline Scrapy ShellLink Extractors scheduler distributed crawler deployment
• concurrent asynchronous reptile aioHttpasyncio
• advanced IP Proxy verification code identification APP crawling incremental crawler
• project actual combat
• anti-crawler request header restriction verification code black and white list blocking IP data encryption data confusion behavior analysis _ul174 automated operation and maintenance
  • Linux environment
  • Shell scripting
  • script Manager
  • script released
  • Python library operation and maintenance
  • common operation and maintenance tools _spa n5span

  data analysis (Data Science)

  • environment to build AnacondaCondaMinicondaJupyter Notebook
  • common data structures
  • common library NumPy slice array index multidimensional array indexing function Pandas SeriesDataFrame Alignment function statistics
  • data processing data cleaning hierarchical index data connection data merge grouping aggregation axial rotation
  • 175 block liborn5pyspan _span quot _span _span _span _span _span _span _span57 Yuskin doesn’t have much exposure to artificial intelligence,It is compiled based on the information of many great gods on the Internet, and it also has certain reference significance.
    • Mathematical foundations advanced mathematics linear algebra probability theory statistical analysis
    • model supervised model training and classification machine learning regression model with common regression model supervised model learning Supervised) Linear regression decision tree integration algorithm classification (supervised) Logistic regression decision tree support vector machine integration algorithm Bayesian algorithm clustering (unsupervised) k-meansdbscan dimensionality reduction principal component analysis linear discriminant analysis advanced GBDT lifting algorithm lightgbmEM algorithm Hidden Markov model multi-factor model commonly used library Scikit-learn quantitative trading strategy
    • deep learning data preprocessing algorithm neural network convolutional neural network recurrent neural network confrontation generation network sequence network model common algorithm framework and platform Tenserflow2PytorchKerasCaffe
    • natural language processing
    • image processing
    • computer vision

    common

    Python library that can be widely used,To a large extent, it is because of its rich class library, which is the code written and encapsulated by others in advance. Basically, you can find the corresponding class library for whatever you want. Just look at the documentation and use it, which greatly improves development efficiency!

    open source project awesome-python-cn (address: https://github.com/jobbole/awesome-python-cn) and -python (address: https://github.com/jobbole/awesome-python-cn) .com/vinta/awesome-python) has compiled a large number of Python libraries in various directions. On this basis, Fishskin selected some relatively high-quality libraries and shared them with everyone.

    General

    date processing

    • delorean: date processing library
    • li38li span_span li_span li_span_span _span _span _span _span_span33 span5span

    terminal optimization

    • IPython : a feature-rich interactive Python parser _span5_span li_span _span li33_span li33_span li33_span _span _span li33_span _span _span _span _span33_span_span _span5 Prettytable: Generate beautiful ASCII format tables
    • Colorama: Let the terminal have colors
    • li38li bashplotlib_span5 lioji_span5 in the terminal to support basic drawing in the terminal li Python terminal output emoticons
    • Ipyvolume: Visualize 3d volume and glyphs in Jupyter notebook _ li38li

    text processing

    • FlashText: Efficient search and replace text library
    • furl: url processing library
    • pypinyin: Pinyin conversion tools
    • simplejson: JSON encoder/decoder
    • JMESPath: JSON query syntax library

    other

    ul Pipenul li33span li33span li33 li33 li33 li33 li li33 li li33 li li33 li li 33 official new-generation management package threading: built-in threading library
  • multiprocessing: built-in multi-threading library
  • lispan _span5 logging span33_span5 chardet: _span5 _span5 chardet: span33_span5 logging character encoding detector
  • PySnooper: Python debugging tool
  • s pan2span sphinx: Python document generator
  • pyttsx3: text-to-speech library
  • short
  • _span li
  • more-itertools: support iterative operation object
  • cryptography: cryptography toolkit _span5 _li5174h_hul57 requests lispans33 _span2 _spans33 request analysis
  • aiohttp: Asynchronous HTTP web library
  • scrapy: Distributed web collection framework
  • _span_span
  • _A powerful spanlispan
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  • _a powerful crawler system for
  • _span_span_span38 or a library for extracting data from XML files
  • you-ge t: Web video downloader
  • wget: Web file download
  • musicdl: Python music downloader _ul33 _span 175 _span 5span _ul span _ul57 and means for switching operation of the CSV
  • XlsxWriter:: library
  • tablib: the data processing form
  • CSV kit operation Excel
  • python-docx: manipulating office word documents
  • PyPDF2: manipulating PDF documents
  • pdfminer: a tool for extracting information from HTML documents _span li2 li33 pdf _span li33 pdf
  • WeasyPrint: visualize web pages,And support exporting to PDF
  • html2text: Convert HTML to Markdown document
  • _span5 _span5 xmltodict: _span5 moviespan _span5 _span _span5 _span _span5 _span _span5
  • eyeD3: A tool for manipulating audio files span5span
  • pyAudioAnalysis: Audio feature extraction and analysis 32 _spanspan32
  • Turtle: interactive painting Gallery
  • pyglet: cross-platform interface and multimedia framework
  • wxPython : Python user interface development tools
  • Pygame : A set of Python modules used to develop games
  li33 li Manim: Python math animation engine
  • progressbar: a scroll bar function library
  • progress: fast expandable progress 33, li2span progress bar output _span5, progress can be expanded 33, Article

  test

  • nose: testing framework
  • faker: generating false data
  • PyAutoGUI: cross-platform GUI automated test module
  • coverage: code coverage measurement
  • sqlmap: automatic SQL injection and penetration testing tool

  web development

  ul32span li33 Django span5 the most popular framework in the world
• Django REST framework: a framework for developing web api
• s pan2span FastAPI: Quickly build web applications
• flask: Python micro-framework
• Twisted: an event-driven web engine 1175 hul ul : Cross-platform process and system tool module
• supervisor: Process control management system
• sh: Let Python support shell script _li2span li2span li2span 33
• scapy: packet processing library
• pexpect: control the interactive program in pseudo terminal
• paramiko: remote connection service
• Ansible : IT automation platform
• SaltStack: Infrastructure automation and management system _span5 span
• watchdog: API and shell tool for managing file system events

image processing & computer vision

• Pillow5: image processing library Pillow5 Pillow5: computer vision library Pillow5
• Opencv: Open-source computer vision library
• Mahotas: Computer vision and image processing library _span_li33 _span5 _span li33 _li38 _li38 _li38 _li38 Data Analysis & Data Science
  • NumPy: Numerical calculation toolkit
  • Pandas : mainstream data analysis tool _span _span li span _span 38 _span 5span _span li _span _span _span 38 span5span
  • Dash: Quickly build web data visualization applications
  • matplotlib: Python 2D drawing library
  • Seaborn: Use Matplotlib for statistical data visualization
  • python-recsys: a library that implements a high-speed recommendation system 5span33 33
  • SciPy: algorithms and mathematical tools library
  • blaze: big data and Pandas NumPy interface
  • statsmodels: statistical modeling and econometrics

  artificial intelligence

  • Tensorflow: Google open source the most popular deep learning framework
  • keras: deep learning packaging library,Get started quickly with neural networks
  • Pytorch: A deep learning framework with tensors and dynamic neural networks, and powerful GPU acceleration capabilities
  • Caffe2: a lightweight, scalable, and scalable Deep learning framework
  • scikit-learn: A machine learning Python module built on SciPy
  • PyMC: Markov chain Monte Carlo 33 33 Learning object detection toolbox
  • imbalanced-learn: Unbalanced learning toolkit
  • XGBoost: Distributed gradient enhancement library _li2span li2span33 Span _li2span _li2span 33

  natural language processing

  • NLTK: Natural Language Processing Toolkit
  • Patternspanspanspan5_Genspan3
  • Patternspan5 Span_Genspan5 Natural Language Processing Libraries _sp an5span
  • fuzzywuzzy: used for string fuzzy matching, token matching, etc.
  • TextBlob: Provide consistent API for common natural language processing tasks 2 li33 _li38
  • jieba: Chinese word segmentation tool

  outline

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  h175h1 join.qq.com/post.html?keyword=python _spanspan

• post salary query: OfferShow applet
• 2span5span lispan lispan33 lispan _spanspan _span _span _spanspan33
• test engineer
• data analyst li38li
• product manager
• algorithm engineer machine learning computer vision NLP multimedia processing _li38span li2span li2span li2span li33span li2span li2span li2span li2span li2span large data mining big data engineer
• technical researcher

resources

video

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