Python from Beginner to Mastery - Chapter 17 Project Practice
This chapter introduces Python project practice, including project planning and design, involving requirements analysis (functional and non-functional requirements), system design (such as MVC architecture), and technology selection (such as Flask); Project 1 is a personal blog system, implemented with Flask and other tools to achieve functions like user management and article management, as well as RESTful APIs; Project 2 is a data analysis platform, covering data processing, visualization, etc. It summarizes the improvement of technical skills and project management experience, provides optimization suggestions, and outlines the next learning directions.
Read MorePython from Beginner to Master — Chapter 16 Testing and Debugging
This chapter mainly introduces Python testing and debugging. It covers testing fundamentals, including test types (unit, integration, etc.) and TDD processes; frameworks like unittest and pytest, such as unittest assertions, pytest Fixtures, and parameterization; Mock technology for simulating dependencies; test coverage tools; debugging methods (print, logging, pdb, etc.); performance analysis tools (time, cProfile, etc.); examples of integration and end-to-end testing; and proposes testing best practices like the FIRST principle and test pyramid to ensure code quality and reliability.
Read MorePython from Beginner to Mastery - Chapter 15: Concurrent Programming
This chapter introduces Python concurrent programming, covering basic concepts (differences between concurrency and parallelism, GIL, task types), multithreading (threading module, daemon threads, synchronous communication), multiprocessing (multiprocessing module, process pools), asynchronous programming (asyncio module), as well as the concurrent.futures module and synchronization primitives. The appropriate concurrency method should be selected based on task types: multiprocessing for CPU-bound tasks, multithreading/asynchronous for I/O-bound tasks, and reasonable selection and optimization should be applied to enhance program performance.
Read MorePython from Beginner to Master - Chapter 14: Web Scraping and Automation
This chapter mainly introduces knowledge related to web crawling and automation, including the basics of web crawlers (definition, purposes, working principles, classification, laws and ethics), HTTP protocol basics (request and response, Cookie/Session), web page structure analysis (HTML, CSS, JS, encoding), crawler development environment (tools, proxy, user agent, debugging), network requests using the Requests library (basics, GET/POST, parameters and headers, response handling, etc.), and web page parsing with BeautifulSoup (basics, HTML/CSS parsing, data extraction, advanced operations, encoding handling).
Read MorePython from Beginner to Mastery — Chapter 13 Web Development
This chapter focuses on Python Web development, covering basic concepts such as web architecture, HTTP protocol, and the ecosystem. It compares frameworks like Flask (lightweight), Django (full-stack), and FastAPI (modern). The content includes Flask installation, basic application development, and deployment, as well as database operations (SQLite, SQLAlchemy), integration of frontend AJAX, design of RESTful APIs. Additionally, it addresses production deployment (Gunicorn, Nginx, Docker) and performance optimization (query optimization, caching, asynchronous processing, monitoring), helping readers master the entire web development process.
Read MorePython from Beginner to Mastery — Chapter 12: Data Science and Analysis
This chapter focuses on Python data science, covering the basics of data science, NumPy numerical computation, Pandas data processing, data visualization, statistical analysis, machine learning introduction, and project practice. It systematically learns core data science technologies, including data processing, visualization, statistical analysis, machine learning model construction and evaluation, to help master the full - process skills of data science.
Read MorePython from Beginner to Pro - Chapter 11 Network Programming
This chapter introduces Python network programming, covering the basics of network protocols (TCP/IP four - layer model, common protocols), Socket programming (implementation of TCP/UDP servers and clients), HTTP clients (usage of urllib/requests libraries), Web server development (http.server module), network data processing (serialization, compression, encryption), asynchronous network programming (asyncio), and network security (common threats and protections). It helps in building efficient and secure network applications.
Read MorePython from Beginner to Pro - Chapter 10: Advanced Python Features
This chapter delves into advanced Python features, including: list, dictionary, and set comprehensions, which are concise and efficient for quickly creating data structures; generators with lazy evaluation that save memory and support infinite sequences and pipeline processing; iterators providing a unified traversal interface; decorators for extending function functionality and achieving cross-cutting concern separation; closures enabling functional programming and state retention; and context managers ensuring proper resource management. These features embody Python's "Readability counts" philosophy and help in writing concise and efficient code.
Read MorePython from Beginner to Pro - Chapter 9: Modules and Packages
This chapter introduces Python's module and package system. A module is a file containing code, which can be categorized into types such as built-in and standard. It can be imported through various methods, with search paths and caching mechanisms in place. A package is a container for modules, including an __init__.py file, and can be structured hierarchically. There are both relative and absolute import methods. Third-party modules are managed using pip, and dependencies can be isolated through virtual environments. Commonly used third-party libraries like requests and numpy are also introduced, forming the foundation for building Python projects.
Read MorePython from Beginner to Pro - Chapter 8 Exception Handling
This chapter introduces Python exception handling, covering concepts such as exceptions (runtime errors in programs, divided into syntax errors and exceptions), hierarchy (based on BaseException), and common built-in exceptions. It focuses on explaining the try-except statement (basic syntax, catching specific/multiple/all exceptions), the finally clause (executed regardless of exceptions), and the else clause (executed when there are no exceptions). raise can be used to actively throw exceptions and create exception chains, and custom exception classes can be defined. It also adheres to best practices like EAFP, such as prioritizing specific exceptions, logging, and avoiding anti-patterns, to help write robust programs.
Read MorePython from Beginner to Mastery — Chapter 7: Object-Oriented Programming
This chapter introduces Python object-oriented programming, covering concepts such as classes and objects. A class is defined using the `class` keyword and can be instantiated. Attributes are divided into instance attributes and class attributes, while methods include instance methods, class methods, and static methods. The constructor `__init__` initializes objects, and the destructor `__del__` cleans up resources. Inheritance enables code reuse, and polymorphism reflects different implementations of the same interface. Encapsulation is achieved through access control and the `@property` decorator. Special methods customize object behavior, along with advanced features like class decorators and descriptors, which help in building efficient code.
Read MorePython from Beginner to Master — Chapter 6 File Operations
This chapter introduces Python file operations, including: file opening and closing using the `open()` function with different modes, emphasizing the automatic resource management via the `with` statement; file reading methods such as `read`, with chunked reading for large files; file writing methods such as `write`, with attention to the differences between modes; file pointer positioning using `tell` and `seek`; directory operations implemented through the `os` module and `pathlib`, involving path manipulation and traversal. Best practices such as following specified encodings and using the `with` statement are also covered.
Read MorePython from Beginner to Master — Chapter 5 Functions
This chapter provides an in - depth explanation of Python functions, covering function definition and invocation, such as defining functions with `def` and using docstrings for description. For parameter passing, it includes positional, keyword, and default parameters, as well as variable parameters `*args` and `**kwargs`. Regarding return values and scopes, it discusses single/multiple return values, local and global scopes, and the use of the `global` and `nonlocal` keywords. Recursive functions require understanding both the base and recursive cases. Lambda expressions are introduced for concisely defining anonymous functions. Additionally, built - in functions such as mathematical operations and type conversion are covered. Functions are a core part of programming, and mastering their usage is conducive to writing high - quality code.
Read MorePython from Beginner to Mastery — Chapter 4: Data Structures
This chapter introduces 5 built-in data structures in Python. Strings can be defined using multi - quotes and have a rich set of operation methods. Lists are ordered and mutable, supporting operations such as adding, deleting, modifying, querying, sorting, and reversing. Tuples are immutable and ordered, and can be used as keys in dictionaries. Dictionaries are key - value pair mappings, unordered and mutable. Sets store unique elements and support mathematical operations. When choosing a data structure, factors such as data properties, operations, and performance should be considered to write efficient and elegant code.
Read MorePython from Beginner to Mastery — Chapter 3 Control Flow
This chapter mainly introduces Python control flow, including conditional statements and loop statements. Conditional statements include single, double, and multi-branch structures, which can be combined with boolean, comparison, and logical operations, and have usage scenarios such as nesting and the ternary operator (e.g., leap year judgment). For loop statements, there are while and for loops: while loops have an else clause, and for loops can iterate over sequences (often combined with range). break is used to exit a loop, continue skips the current iteration, and pass is used for placeholder purposes. Additionally, the chapter covers applications such as nested loop pattern printing and data processing, while emphasizing performance optimization and the effective use of built-in functions to enhance efficiency.
Read MorePython from Beginner to Mastery - Chapter 2: Python Basic Syntax
This chapter introduces Python basic syntax, including: variable-related aspects such as naming rules (identifier composition, PEP 8 specifications, etc.), assignment references, and scopes; data types are divided into basic types (numbers, strings, etc.) and composite types (lists, tuples, etc.), supporting dynamic typing and type conversion; operators include arithmetic, comparison, logical, etc.; input/output functions include the usage and formatting of print and input; comments include single-line, multi-line, and docstrings, following PEP 8 code specifications, which form the foundation for subsequent learning.
Read MorePython from Beginner to Pro - Chapter 1: Python Environment Setup
This chapter mainly introduces Python environment setup and basic usage. First, it explains the Python installation and configuration methods for different operating systems (Windows, macOS, Linux); then it covers the writing of the first Python program (e.g., "Hello World"), running methods, and structure analysis; next, it introduces the Python interactive environment (including IPython and Jupyter Notebook); finally, it elaborates on the use of the pip package management tool, including installing, uninstalling, and upgrading packages, using requirements.txt files, configuring domestic mirror sources, and virtual environments.
Read MoreA Tool Website Developed with Python
This article introduces a feature-rich tool website developed using Python. It includes various tools such as document tools, PDF tools, image tools, audio tools, video tools, voice tools, and programming tools, which are commonly used in work or study.
Read MoreSpeaker Log Implementation Based on PyTorch (Speaker Separation)
This article introduces the speaker diarization feature of the VoiceprintRecognition_Pytorch framework implemented based on PyTorch, which supports various advanced models and data preprocessing methods. By executing the `infer_speaker_diarization.py` script or using the GUI interface program, audio can be speaker-separated and results displayed. The output includes the start and end times of each speaker and their identity information (registration is required first). Additionally, the article provides solutions for Chinese names in the Ubuntu system... （注：原文末尾“解决中文名”表述不完整，已保留原文未尽部分的省略格式，完整内容需参考原文后续章节）
Read MoreIntroduction and Usage of YeAudio Audio Tool
These classes define various audio data augmentation techniques. Each class is responsible for a specific data augmentation operation and can control the degree and type of augmentation by setting different parameters. The following is a detailed description of each class: ### 1. **SpecAugmentor** - **Function**: Frequency domain masking and time domain masking - **Main Parameters**: - `prob`: Probability of data augmentation. - `freq_mask_ratio`: Ratio of frequency domain masking (e.g., 0.15 means randomly selecting
Read MoreVoiceprint Recognition System Implemented Based on PyTorch
This project provides an implementation of voice recognition based on PaddlePaddle, mainly using the EcapaTDNN model, and integrates functions of speech recognition and voiceprint recognition. Below, I will summarize the project structure, functions, and how to use these functions. ## Project Structure ### Directory Structure ``` VoiceprintRecognition-PaddlePaddle/ ├── docs/ # Documentation │ └── README.md # Project description document ```
Read MoreSegmenting Long Speech into Multiple Short Segments Using Voice Activity Detection (VAD)
This paper introduces YeAudio, a voice activity detection (VAD) tool implemented based on deep learning. The installation command for the library is `python -m pip install yeaudio -i https://pypi.tuna.tsinghua.edu.cn/simple -U`, and the following code snippet can be used for speech segmentation: ```python from yeaaudio.audio import AudioSegment audio_seg ``` (Note: The original code snippet appears incomplete in the user's input; the translation preserves the partial code as provided.)
Read MoreECAPa-TDNN Speaker Recognition Model Implemented Based on PaddlePaddle
This project is a voiceprint recognition system based on PaddlePaddle. It covers application scenarios from data preprocessing, model training to voiceprint recognition and comparison, and is suitable for practical applications such as voiceprint login. Here is a detailed analysis of the project: ### 1. Environment Preparation and Dependency Installation First, ensure that PaddlePaddle and other dependent libraries such as `numpy`, `matplotlib`, etc., have been installed. They can be installed using the following command: ```bash pip install paddlepaddle ```
Read MoreAdding Punctuation Marks to Speech Recognition Text
This paper introduces a method for adding punctuation marks to speech recognition text according to grammar, mainly divided into four steps: downloading and decompressing the model, installing PaddleNLP and PPASR tools, importing the PunctuationPredictor class, and using this class to automatically add punctuation marks to the text. The specific steps are as follows: 1. Download the model and decompress it into the `models/` directory. 2. Install the relevant libraries of PaddleNLP and PPASR. 3. Instantiate the predictor using the `PunctuationPredictor` class and pass in the pre
Read MoreSound Classification Based on PyTorch
This code is mainly based on the PaddlePaddle framework and is used to implement a speech recognition system based on acoustic features. The project structure is clear, including functional modules such as training, evaluation, and prediction, and provides detailed command-line parameter configuration files. The following is a detailed analysis and usage instructions for the project: ### 1. Project Structure ``` . ├── configs # Configuration files directory │ └── bi_lstm.yml ├── infer.py # Acoustic model inference code ├── recor ``` (Note: The original Chinese text was cut off at "recor" in the last line, so the translation reflects the visible content.)
Read MoreImplementing Common Sorting Algorithms in Python
Thank you very much for sharing the implementations of these sorting algorithms. To provide a more comprehensive and understandable version, I will briefly explain each sorting algorithm and include complete code snippets. Additionally, I will add necessary import statements and comments within each function to enhance code readability. ### 1. Bubble Sort Bubble Sort is a simple sorting method that repeatedly traverses the list to be sorted, comparing two elements at a time and swapping them if their order is incorrect. After multiple traversals, the largest element "bubbles up" to the end. ```python def bubble_sort(arr): n = len(arr) for i in range(n): # Last i elements are already in place swapped = False for j in range(0, n-i-1): if arr[j] > arr[j+1]: arr[j], arr[j+1] = arr[j+1], arr[j] swapped = True # If no swaps occurred, the array is sorted if not swapped: break return arr ```
Read MoreDistance Measurement Using Binocular Cameras
This code demonstrates how to implement stereo vision depth estimation using the SGBM (Semiglobal Block Matching) algorithm in OpenCV, and then calculate 3D coordinates in the image. The following is a detailed explanation of the key steps and parameters in the code: ### 1. Preparation First, import the necessary libraries: ```python import cv2 import numpy as np ``` ### 2. Reading and Preprocessing Images Load the left and right eye images, and then (the original content was cut off here, so the translation stops at the beginning of the preprocessing step)
Read MoreImplementing a Simple Web Crawler with Python2
This project is a simple web crawler designed to scrape relevant content from CSDN blogs and save it as HTML files. It includes the basic process of a crawler: crawling, parsing, and storage. ### Crawling Process 1. **Scheduler (`spider_main.py`)**: - This is the entry point of the entire project. - It calls `HtmlOutputer` to output data, `Downloader` to download web page content, and `HtmlParser` to parse the downloaded content (parsing logic continues...).
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