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5000 articles · Page 27 of 50
Test Development Learning Exchange
Test Development Learning Exchange
Feb 19, 2024 · Backend Development

Using Python's json Module for Serialization, Deserialization, and API Testing

This article explains how to use Python's built‑in json module for serializing and deserializing data, demonstrates sending JSON payloads with the requests library, and covers advanced techniques such as data‑driven testing, JsonPath/JMESPath extraction, JSON Schema validation, and dynamic request body construction for API automation.

API-testingPythondeserialization
0 likes · 9 min read
Using Python's json Module for Serialization, Deserialization, and API Testing
Python Programming Learning Circle
Python Programming Learning Circle
Feb 18, 2024 · Fundamentals

Hello World Examples in 12 Popular Programming Languages

This article showcases the correct "Hello World" syntax for twelve widely used programming languages, providing clear code snippets and brief explanations to help beginners understand the fundamental first program across Java, C, Python, C++, C#, Visual Basic .NET, JavaScript, PHP, Objective‑C, SQL, Ruby, and MATLAB.

C++JavaPython
0 likes · 4 min read
Hello World Examples in 12 Popular Programming Languages
Python Programming Learning Circle
Python Programming Learning Circle
Feb 18, 2024 · Backend Development

Introduction, Installation, and Usage of PyMuPDF (Python Bindings for MuPDF)

This article provides a comprehensive overview of PyMuPDF, covering its purpose as Python bindings for the lightweight MuPDF viewer, detailed installation instructions, essential dependencies, naming conventions, and extensive usage examples for opening documents, accessing pages, extracting text and images, manipulating PDFs, and saving changes.

Document ProcessingLibraryMuPDF
0 likes · 12 min read
Introduction, Installation, and Usage of PyMuPDF (Python Bindings for MuPDF)
Test Development Learning Exchange
Test Development Learning Exchange
Feb 18, 2024 · Backend Development

Dynamic Environment Switching in Test Frameworks Using Python Decorators

The article explains the importance of dynamic environment switching in testing frameworks for multi‑environment validation, resource isolation, debugging, and CI/CD, and provides Python unittest decorator examples along with best‑practice considerations such as scope, thread safety, resource management, and execution order.

CI/CDDecoratorPython
0 likes · 9 min read
Dynamic Environment Switching in Test Frameworks Using Python Decorators
Model Perspective
Model Perspective
Feb 13, 2024 · Big Data

Mastering Noisy Data: From Cleaning to Visualization and NLP with Python

This article reviews the key concepts from the Bad Data Handbook, covering noise identification, data validation, human readability, web data restructuring, special domain challenges, and data quality analysis, while also presenting practical data visualization techniques, popular analysis tools, Python web‑scraping libraries, and a basic NLP workflow with code examples.

Data VisualizationNLPPython
0 likes · 20 min read
Mastering Noisy Data: From Cleaning to Visualization and NLP with Python
Test Development Learning Exchange
Test Development Learning Exchange
Feb 10, 2024 · Frontend Development

Integrating Playwright with Test Frameworks, CI/CD, and an End‑to‑End Playwright + pytest E‑commerce Example

This article explains how Playwright can be integrated with testing frameworks, CI/CD pipelines, monitoring, logging, build tools, API testing, reporting, and distributed testing, and provides a complete Playwright‑pytest Python example that automates user registration, login, product browsing, ordering and post‑order processes for an e‑commerce site.

Frontend TestingPlaywrightPython
0 likes · 8 min read
Integrating Playwright with Test Frameworks, CI/CD, and an End‑to‑End Playwright + pytest E‑commerce Example
Top Architecture Tech Stack
Top Architecture Tech Stack
Feb 8, 2024 · Backend Development

Guide to Using the 12306 Ticket‑Grabbing Python Project

This article introduces the popular 12306 ticket‑grabbing assistant, explains its history and features, provides step‑by‑step installation and configuration instructions—including required dependencies, proxy settings, and email notifications—and shows how to run the script to automatically secure train tickets during the Spring Festival travel rush.

AutomationBackendConfiguration
0 likes · 10 min read
Guide to Using the 12306 Ticket‑Grabbing Python Project
Python Crawling & Data Mining
Python Crawling & Data Mining
Feb 8, 2024 · Backend Development

How to Fix Flask Image Loading Issues with Relative Paths

This article walks through a Flask image loading issue, explains why the picture fails to appear, and provides two concrete solutions—using a direct static file path and leveraging Flask's url_for helper—along with full HTML code examples and best‑practice tips for template organization.

FlaskPythonRelative Path
0 likes · 4 min read
How to Fix Flask Image Loading Issues with Relative Paths
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Feb 7, 2024 · Artificial Intelligence

Step-by-Step Guide to Building Multi‑Agent Applications with LangChain LangGraph in Google Colab

This tutorial walks through installing LangChain, LangGraph and related packages in Google Colab, configuring environment variables, defining search and Twitter‑writer tools, constructing a StateGraph workflow with supervisor logic, and executing a multi‑agent LLM pipeline using LangChain’s new multi‑agent capabilities.

AIGoogle ColabLLM
0 likes · 11 min read
Step-by-Step Guide to Building Multi‑Agent Applications with LangChain LangGraph in Google Colab
Test Development Learning Exchange
Test Development Learning Exchange
Feb 6, 2024 · Frontend Development

Using Playwright for Browser Automation: Form Submission, File Upload, Screenshots, Navigation, and Page Title Manipulation in Python

This article demonstrates how to use the Playwright Python library to automate browser actions such as submitting forms with file uploads, capturing screenshots, navigating between pages, and retrieving or setting the page title, providing complete code examples for each task.

PlaywrightPythonbrowser automation
0 likes · 7 min read
Using Playwright for Browser Automation: Form Submission, File Upload, Screenshots, Navigation, and Page Title Manipulation in Python
Baidu Geek Talk
Baidu Geek Talk
Feb 5, 2024 · Artificial Intelligence

Why Static Graphs Outperform Dynamic Graphs in AutoDiff: A Deep Dive

This article explains the fundamental differences between static and dynamic computation graphs, compares their memory and performance characteristics, shows how automatic differentiation works in each paradigm, and provides a step‑by‑step implementation of a toy static‑graph AutoDiff engine with Python code examples.

AutoDiffDynamic GraphPyTorch
0 likes · 18 min read
Why Static Graphs Outperform Dynamic Graphs in AutoDiff: A Deep Dive
Top Architecture Tech Stack
Top Architecture Tech Stack
Feb 5, 2024 · Fundamentals

Simple Techniques to Speed Up Python For Loops by 1.3× to 970×

This article presents a collection of straightforward Python techniques—such as list comprehensions, external length calculation, set usage, early‑exit loops, inlining functions, pre‑computations, generators, map(), memoization, NumPy vectorization, filterfalse, and join()—that can accelerate for‑loops anywhere from 1.3‑fold up to nearly a thousand‑fold, with explanations and benchmark results.

Loop OptimizationNumPyPerformance
0 likes · 18 min read
Simple Techniques to Speed Up Python For Loops by 1.3× to 970×
Test Development Learning Exchange
Test Development Learning Exchange
Feb 4, 2024 · Frontend Development

Using Playwright for Web Interaction: Installation, Element Selection, Click Handling, and Assertions

This guide explains how to install Playwright, write Python scripts to launch a Chromium browser, locate and interact with page elements, ensure element presence using various waiting methods, and verify actions with assertions, providing practical code examples for web automation.

Click EventsPlaywrightPython
0 likes · 5 min read
Using Playwright for Web Interaction: Installation, Element Selection, Click Handling, and Assertions
Python Programming Learning Circle
Python Programming Learning Circle
Feb 4, 2024 · Fundamentals

Using FuzzyWuzzy for Fuzzy String Matching in Python

This article introduces the FuzzyWuzzy Python library, explains its Levenshtein‑based matching functions (Ratio, Partial Ratio, Token Sort Ratio, Token Set Ratio) and the process module, and demonstrates practical applications for fuzzy matching of company and province names with complete code examples.

Levenshtein distancePythondata cleaning
0 likes · 10 min read
Using FuzzyWuzzy for Fuzzy String Matching in Python
Top Architecture Tech Stack
Top Architecture Tech Stack
Feb 4, 2024 · Fundamentals

Comprehensive Overview of Python Built‑in Types and Common Methods

This article provides a detailed guide to Python's fundamental built‑in classes such as int, float, str, list, dict, set, and tuple, explaining their typical uses and presenting extensive examples of string operations, collection methods, built‑in functions, iterator utilities, type conversions, and file handling techniques.

Built-in TypesProgramming FundamentalsPython
0 likes · 20 min read
Comprehensive Overview of Python Built‑in Types and Common Methods
Test Development Learning Exchange
Test Development Learning Exchange
Feb 2, 2024 · Frontend Development

Playwright Overview: Features, Installation, Basic Concepts, and Sample Tests

This article introduces Playwright, a powerful cross‑browser automation tool, outlines its key features and advantages, provides step‑by‑step installation instructions for Python, explains core concepts, demonstrates locating invisible elements, and offers practical code examples for common web operations and testing best practices.

JavaScriptPlaywrightPython
0 likes · 7 min read
Playwright Overview: Features, Installation, Basic Concepts, and Sample Tests
Python Programming Learning Circle
Python Programming Learning Circle
Feb 2, 2024 · Operations

17 Essential Python Scripts for Automating Everyday Tasks

This article presents 17 practical Python scripts covering file management, web scraping, email handling, Excel processing, database interaction, system tasks, image editing, and more, each with code examples and explanations, enabling developers and analysts to automate repetitive workflows and boost productivity across diverse domains.

AutomationData ProcessingPython
0 likes · 26 min read
17 Essential Python Scripts for Automating Everyday Tasks
Python Programming Learning Circle
Python Programming Learning Circle
Feb 2, 2024 · Fundamentals

Annual Expense Report Generation Using Python Pandas

The article explains how to use Python's pandas library to import daily expense data from Excel, convert dates to yearly periods, group and sum expenditures by year and category, and display an annual financial summary, providing complete code snippets for each step.

DataFrameExpense TrackingPython
0 likes · 3 min read
Annual Expense Report Generation Using Python Pandas
Python Programming Learning Circle
Python Programming Learning Circle
Feb 1, 2024 · Big Data

Analyzing the Distribution and Competition Between Starbucks and Luckin Coffee Using Python Data Visualization

Using Python and the Shapely library, this article visualizes and compares the nationwide store distribution of Starbucks and Luckin Coffee, revealing that Starbucks concentrates in coastal first‑tier cities while Luckin is more dispersed, with an average of 0.6 Luckin stores within 500 m of each Starbucks location.

Luckin CoffeePythonShapely
0 likes · 10 min read
Analyzing the Distribution and Competition Between Starbucks and Luckin Coffee Using Python Data Visualization
Python Programming Learning Circle
Python Programming Learning Circle
Jan 31, 2024 · Fundamentals

10 Common Ways to Call Functions in Python

This article introduces ten frequently used Python function‑calling techniques—including built‑ins like filter, eval, exec and utilities from functools and operator—explaining their purpose, typical use cases, and providing clear code examples for each method.

OperatorPythonbuiltin
0 likes · 6 min read
10 Common Ways to Call Functions in Python
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jan 31, 2024 · Artificial Intelligence

Advanced RAG with Semi‑Structured Data Using LangChain, Unstructured, and ChromaDB

This tutorial demonstrates how to build an advanced Retrieval‑Augmented Generation (RAG) system for semi‑structured PDF data by leveraging LangChain, the unstructured library, ChromaDB vector store, and OpenAI models, covering installation, PDF partitioning, element classification, summarization, and query execution.

AIChromaDBLangChain
0 likes · 11 min read
Advanced RAG with Semi‑Structured Data Using LangChain, Unstructured, and ChromaDB
DeWu Technology
DeWu Technology
Jan 29, 2024 · Backend Development

Design and Implementation of a Full-Platform Automated Test Execution Engine

The article describes a full‑platform automated test execution engine that replaces legacy offline‑script/Jenkins setups with a lightweight, visual, component‑based solution supporting low‑/zero‑code case creation, parallel execution, protected environment variables, dynamic placeholders, system‑method libraries, and extensible script and case workers for scalable, efficient testing.

AutomationPythonplaceholder
0 likes · 27 min read
Design and Implementation of a Full-Platform Automated Test Execution Engine
Open Source Tech Hub
Open Source Tech Hub
Jan 26, 2024 · Fundamentals

How Smaz2 Compresses LoRa Messages on Tiny Devices

This article explains the motivation, dictionary design, bigram table, encoding rules, and real‑world compression results of the Smaz2 library, a space‑optimized C/Python compressor for short LoRa messages on microcontrollers with less than 2 KB RAM.

C++LoRAPython
0 likes · 8 min read
How Smaz2 Compresses LoRa Messages on Tiny Devices
Test Development Learning Exchange
Test Development Learning Exchange
Jan 26, 2024 · Artificial Intelligence

Data Mining Techniques for Marketing: Customer Segmentation, Purchase Prediction, Recommendation, and More with Python

This article introduces ten data‑mining applications for marketing—including customer segmentation, purchase forecasting, market‑basket analysis, churn prediction, sentiment analysis, response modeling, recommendation systems, brand reputation, competitive analysis, and public‑opinion monitoring—each illustrated with concise Python code examples.

Customer SegmentationPythondata mining
0 likes · 11 min read
Data Mining Techniques for Marketing: Customer Segmentation, Purchase Prediction, Recommendation, and More with Python
Python Programming Learning Circle
Python Programming Learning Circle
Jan 25, 2024 · Fundamentals

Python Memory Optimization Techniques: __slots__, Generators, mmap, Data Types, and String Interning

This article explains practical Python memory‑saving methods—including inspecting memory usage, using __slots__, generators, memory‑mapped files, choosing efficient data structures, and string interning—providing code examples and performance comparisons to help developers write more memory‑efficient programs.

Data StructuresMemory OptimizationPython
0 likes · 11 min read
Python Memory Optimization Techniques: __slots__, Generators, mmap, Data Types, and String Interning
Python Programming Learning Circle
Python Programming Learning Circle
Jan 24, 2024 · Backend Development

Running Scrapy Crawlers: Command‑Line, CrawlerProcess, and CrawlerRunner Approaches

This tutorial demonstrates how to execute Scrapy spiders from the command line, run them within Python files using cmdline, and manage single or multiple spiders with CrawlerProcess and CrawlerRunner, highlighting configuration steps, limitations, and best‑practice recommendations.

Backend DevelopmentCrawlerProcessCrawlerRunner
0 likes · 3 min read
Running Scrapy Crawlers: Command‑Line, CrawlerProcess, and CrawlerRunner Approaches
Test Development Learning Exchange
Test Development Learning Exchange
Jan 23, 2024 · Fundamentals

Common Data Preprocessing Techniques with Python Code Examples

This article presents ten essential data preprocessing methods—including handling missing values, type conversion, standardization, encoding, smoothing, outlier treatment, text cleaning, word frequency counting, sentiment analysis, and topic modeling—each explained with clear Python code snippets.

Pythondata cleaningdata preprocessing
0 likes · 9 min read
Common Data Preprocessing Techniques with Python Code Examples
Python Programming Learning Circle
Python Programming Learning Circle
Jan 23, 2024 · Fundamentals

Python Essentials: 60 Frequently Used Built-in Functions and Techniques

This article presents a comprehensive collection of 60 frequently used Python built-in functions and techniques, covering numeric operations, string handling, data structures, function definitions, class utilities, and useful tools, each illustrated with clear code examples and explanations for practical programming.

Data StructuresPythonprogramming basics
0 likes · 22 min read
Python Essentials: 60 Frequently Used Built-in Functions and Techniques
Python Programming Learning Circle
Python Programming Learning Circle
Jan 23, 2024 · Backend Development

Comprehensive Guide to Python Libraries for Web Crawling, Web Development, and Asynchronous Programming

This article provides an extensive overview of Python libraries and frameworks for web crawling, data extraction, asynchronous networking, browser automation, and popular web development frameworks, helping developers choose the right tools for backend projects and avoid common misconceptions when selecting a framework.

Async ProgrammingLibrariesPython
0 likes · 9 min read
Comprehensive Guide to Python Libraries for Web Crawling, Web Development, and Asynchronous Programming
Test Development Learning Exchange
Test Development Learning Exchange
Jan 22, 2024 · Fundamentals

10 Essential Python Debugging Tools and Techniques Every Developer Should Know

This article introduces ten practical Python debugging tools and techniques—including breakpoints, print statements, logging, assertions, pdb, traceback, cProfile, timeit, memory_profiler, and pdbpp—providing code examples and explanations to help developers diagnose, trace, and optimize their code effectively.

PerformanceProfilingPython
0 likes · 5 min read
10 Essential Python Debugging Tools and Techniques Every Developer Should Know
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jan 22, 2024 · Artificial Intelligence

Prompt Engineering and CAMEL: Role‑Playing AI Agents for Automated Prompt Generation

This article explains how Prompt Engineering combined with the CAMEL framework enables role‑playing AI agents to automatically generate and manage prompts, illustrates the concept with a stock‑trading example, and provides Python code using LangChain to build a marketing‑automation agent for a small business.

AI agentsCAMELInception Prompting
0 likes · 11 min read
Prompt Engineering and CAMEL: Role‑Playing AI Agents for Automated Prompt Generation
Test Development Learning Exchange
Test Development Learning Exchange
Jan 21, 2024 · Fundamentals

How to Extract MP3 Files from a PDF Using Python

This guide explains step‑by‑step how to install required Python libraries, extract text and images from a PDF, perform OCR on the images, locate embedded MP3 data in the combined text, and save the audio file, providing complete sample code for each stage.

MP3 extractionOCRPython
0 likes · 4 min read
How to Extract MP3 Files from a PDF Using Python
Test Development Learning Exchange
Test Development Learning Exchange
Jan 20, 2024 · Big Data

Practical Data Analysis Code Samples for Business Decision Making

This article presents ten practical Python code examples that demonstrate common data analysis techniques—such as handling missing values, sorting, pivot tables, visualization, association rules, outlier detection, time‑series forecasting, clustering, feature selection, and cross‑validation—to help improve business decision effectiveness.

Business IntelligencePythonbig data
0 likes · 4 min read
Practical Data Analysis Code Samples for Business Decision Making
Open Source Tech Hub
Open Source Tech Hub
Jan 20, 2024 · Artificial Intelligence

How to Set Up ModelScope with Anaconda and Run OCR Inference via PHP

This guide walks through installing Anaconda, creating a Python 3.10 conda environment, adding PyTorch and ModelScope libraries, installing domain-specific dependencies, verifying NLP pipelines, and using PHPY to call ModelScope's OCR model from PHP, complete with code snippets and troubleshooting tips.

AI inferenceAnacondaModelScope
0 likes · 10 min read
How to Set Up ModelScope with Anaconda and Run OCR Inference via PHP
AntTech
AntTech
Jan 19, 2024 · Backend Development

Fury: A High‑Performance Multi‑Language Serialization Framework and Its Path to the Apache Incubator

Fury is a JIT‑compiled, zero‑copy, multi‑language serialization framework that delivers up to 170× speed improvements over traditional serializers, supports Java, Python, C++, Go, JavaScript, Scala and Rust, and has recently been donated to the Apache Software Foundation after a successful open‑source journey.

ApacheFuryJava
0 likes · 17 min read
Fury: A High‑Performance Multi‑Language Serialization Framework and Its Path to the Apache Incubator
Python Programming Learning Circle
Python Programming Learning Circle
Jan 18, 2024 · Fundamentals

Python Quirks and Tricky Behaviors: 10 Quiz Questions with Explanations

This article presents ten Python quiz questions that reveal surprising language behaviors—such as banker's rounding, attribute lookup order, handling of -0.0, lazy evaluation of all/any, negative string multiplication, object‑type relationships, sum() defaults, name binding in functions, handling of NaN/Infinity, and floating‑point precision limits—along with detailed explanations for each.

PythonQuizprogramming
0 likes · 8 min read
Python Quirks and Tricky Behaviors: 10 Quiz Questions with Explanations
MaGe Linux Operations
MaGe Linux Operations
Jan 17, 2024 · Fundamentals

Master Python’s Built‑In Functions: From range to zip

This article introduces Python’s most useful built‑in functions—including range, mathematical utilities, base‑conversion, string methods, and iterable helpers—explaining their parameters, showing practical examples, and demonstrating how they simplify common programming tasks.

Pythonbuilt-in functionsfundamentals
0 likes · 9 min read
Master Python’s Built‑In Functions: From range to zip
Python Programming Learning Circle
Python Programming Learning Circle
Jan 17, 2024 · Fundamentals

Eight Practical Python CLI -m Tricks Without Writing Code

This article demonstrates eight useful Python command‑line one‑liners that leverage the built‑in -m option to perform tasks such as port testing, launching a web server, formatting JSON, creating a simple editor, building executable packages, encoding/decoding data, retrieving system metadata, and compressing files, all without writing any source code.

AutomationCLINo-code
0 likes · 11 min read
Eight Practical Python CLI -m Tricks Without Writing Code
Test Development Learning Exchange
Test Development Learning Exchange
Jan 16, 2024 · Artificial Intelligence

Python Code Samples for Data Scraping and Analysis Across Various Business Scenarios

This article presents a collection of Python code examples demonstrating how to scrape, process, visualize, and analyze data from news sites, social media, stock markets, e‑commerce, web traffic, text, images, and more, covering tasks such as clustering, time‑series forecasting, and sentiment analysis.

Data AnalysisPythonWeb Scraping
0 likes · 12 min read
Python Code Samples for Data Scraping and Analysis Across Various Business Scenarios
Beijing SF i-TECH City Technology Team
Beijing SF i-TECH City Technology Team
Jan 16, 2024 · Big Data

Big Data Testing: Methods, Tool Selection, and Practical Implementation with Datacompy

This article introduces big data testing concepts, outlines common testing methods, evaluates the Python library Datacompy against alternatives, and details a practical implementation for large-scale data migration and validation, including configuration, volume comparison, content verification, and performance optimizations such as sorting and multithreading.

Pythondata migrationdata testing
0 likes · 10 min read
Big Data Testing: Methods, Tool Selection, and Practical Implementation with Datacompy
Python Programming Learning Circle
Python Programming Learning Circle
Jan 16, 2024 · Fundamentals

Interactive DataFrame Visualization in Jupyter Notebook with Pivottablejs, PyGWalker, Qgrid, and Itables

This article introduces four Python packages—Pivottablejs, PyGWalker, Qgrid, and Itables—that transform Pandas DataFrames into interactive tables and visualizations within Jupyter Notebook, providing code examples, usage tips, and comparisons to help users choose the right tool for data exploration.

Interactive TablesJupyter NotebookPyGWalker
0 likes · 4 min read
Interactive DataFrame Visualization in Jupyter Notebook with Pivottablejs, PyGWalker, Qgrid, and Itables
Test Development Learning Exchange
Test Development Learning Exchange
Jan 16, 2024 · Fundamentals

Functional Programming in Python: Concepts and Code Examples

This article introduces functional programming concepts in Python, explaining pure functions, higher‑order functions, and function composition, and demonstrates ten practical examples—including map, filter, reduce, list comprehensions, generators, partial application, operator usage, compose, zip, and recursion—to illustrate how to write concise, maintainable code.

Pythonhigher-order functions
0 likes · 5 min read
Functional Programming in Python: Concepts and Code Examples
21CTO
21CTO
Jan 14, 2024 · Frontend Development

Run Python Directly in the Browser with PyScript: A Step‑by‑Step Guide

Learn how to embed and execute Python code within HTML using PyScript, covering its background, core features, basic visualization, and a complete Hello World example that displays the host’s IP address, while showcasing code snippets and practical use cases for web development.

PyScriptPythonWebAssembly
0 likes · 8 min read
Run Python Directly in the Browser with PyScript: A Step‑by‑Step Guide
Python Programming Learning Circle
Python Programming Learning Circle
Jan 13, 2024 · Fundamentals

Comprehensive Guide to Python Time Handling Modules (time, datetime, pytz, dateutil, Arrow, ISO 8601)

This article provides a thorough overview of Python's time‑related libraries—including the built‑in time and datetime modules, third‑party pytz, dateutil, and Arrow—explaining core concepts such as timestamps, time zones, daylight‑saving time, and ISO 8601 parsing with clear code examples and usage patterns.

ArrowDateUtilPython
0 likes · 27 min read
Comprehensive Guide to Python Time Handling Modules (time, datetime, pytz, dateutil, Arrow, ISO 8601)
Python Programming Learning Circle
Python Programming Learning Circle
Jan 13, 2024 · Operations

17 Essential Python Scripts for Automating Everyday Tasks

Explore 17 practical Python scripts that automate tasks ranging from file management and web scraping to email handling, database interaction, system monitoring, and cloud services, enabling developers and analysts to boost productivity, reduce errors, and streamline workflows across diverse domains.

AutomationPythonSystem
0 likes · 28 min read
17 Essential Python Scripts for Automating Everyday Tasks
21CTO
21CTO
Jan 12, 2024 · Fundamentals

How CPython’s New JIT Will Boost Python 3.13 Performance

The upcoming CPython 3.13 release will optionally include a JIT compiler built on LLVM, offering modest speed gains of 2%‑9% today and promising larger improvements in future versions through advanced optimization techniques.

CPythonJITLLVM
0 likes · 6 min read
How CPython’s New JIT Will Boost Python 3.13 Performance
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jan 12, 2024 · Artificial Intelligence

Understanding Vector Databases, ANN Algorithms, and Their Integration with Large Language Models

This article explains the fundamentals of vector databases, how high‑dimensional vector data is generated and stored, reviews common ANN search algorithms such as Flat, k‑means and LSH, discusses benchmarking and product selection, and demonstrates practical integration of vector stores with LLMs using LangChain and Python code.

ANNLLM IntegrationPython
0 likes · 17 min read
Understanding Vector Databases, ANN Algorithms, and Their Integration with Large Language Models
Test Development Learning Exchange
Test Development Learning Exchange
Jan 10, 2024 · Fundamentals

Understanding Python Decorators: Theory and 10 Practical Use Cases

This article explains the concept and implementation of Python decorators as higher‑order functions and provides ten practical code examples—including timer, debugger, parameterized, class‑based, caching, permission, logging, exception handling, authentication, and chained decorators—to illustrate their versatile applications.

Pythonmetaprogrammingprogramming
0 likes · 7 min read
Understanding Python Decorators: Theory and 10 Practical Use Cases
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jan 10, 2024 · Artificial Intelligence

Understanding Backpropagation: From Simple to Advanced Neural Network Implementations in Python

This article explains the back‑propagation algorithm in neural networks, starting with a simple single‑neuron example using ReLU, Sigmoid and MSE, then extending to multi‑layer matrix‑based networks, providing detailed Python code, gradient calculations, and comparisons with TensorFlow implementations.

BackpropagationPythongradient descent
0 likes · 21 min read
Understanding Backpropagation: From Simple to Advanced Neural Network Implementations in Python
Python Crawling & Data Mining
Python Crawling & Data Mining
Jan 10, 2024 · Fundamentals

Batch Insert Images into Excel Cells with Python and openpyxl

This article demonstrates how to use Python's openpyxl library to automatically insert named images into specific Excel cells in bulk, explaining the problem, providing a complete script, and offering practical tips for handling large files and sharing the solution with the community.

Batch ProcessingExcel AutomationPython
0 likes · 5 min read
Batch Insert Images into Excel Cells with Python and openpyxl
Python Programming Learning Circle
Python Programming Learning Circle
Jan 9, 2024 · Fundamentals

Comprehensive List of Python Libraries and Tools

This article presents an extensive, categorized catalog of Python libraries and tools covering environments, package management, web frameworks, data processing, machine learning, testing, and many other domains, providing developers with a valuable reference to discover and select appropriate modules for their projects.

Pythonreferencetools
0 likes · 48 min read
Comprehensive List of Python Libraries and Tools
Python Programming Learning Circle
Python Programming Learning Circle
Jan 9, 2024 · Artificial Intelligence

Overview of Common Python Libraries for Artificial Intelligence with Code Examples

This article provides a comprehensive introduction to popular Python libraries used in artificial intelligence, such as NumPy, OpenCV, scikit-image, Pillow, SimpleCV, Mahotas, Ilastik, Scikit-learn, SciPy, NLTK, spaCy, LibROSA, Pandas, Matplotlib, Seaborn, Orange, PyBrain, Theano, Keras, Caffe, MXNet, PaddlePaddle, CNTK, and more, including code snippets and usage examples.

AIData ScienceLibraries
0 likes · 34 min read
Overview of Common Python Libraries for Artificial Intelligence with Code Examples
Python Programming Learning Circle
Python Programming Learning Circle
Jan 8, 2024 · Fundamentals

Comprehensive Guide to Python Built-in Functions

This article presents a detailed overview of Python's 68 built-in functions up to version 3.6.2, categorizing them into twelve groups such as numeric operations, data structures, scope, iterators, I/O, memory, file handling, modules, and more, with code examples illustrating each function's usage.

Data TypesProgramming FundamentalsPython
0 likes · 13 min read
Comprehensive Guide to Python Built-in Functions
Test Development Learning Exchange
Test Development Learning Exchange
Jan 7, 2024 · Big Data

Association Rule Mining Applications Across Various Business Scenarios with Python Code

This article demonstrates how to apply the Apriori algorithm and association rule mining using Python's mlxtend library across ten real‑world business scenarios, providing step‑by‑step code examples for retail, e‑commerce, marketing, healthcare, security, CRM, social networks, travel, market basket, and online advertising.

AprioriPythonassociation rule mining
0 likes · 9 min read
Association Rule Mining Applications Across Various Business Scenarios with Python Code
Python Programming Learning Circle
Python Programming Learning Circle
Jan 6, 2024 · Fundamentals

10 Practical pip Tips for Managing Python Packages

This article introduces ten essential pip techniques—including installation, upgrading, version-specific installs, uninstalling, checking dependencies, using domestic mirrors, downloading without installing, and batch installing from requirements files—to help Python developers efficiently manage their packages.

InstallationPythonmirrors
0 likes · 6 min read
10 Practical pip Tips for Managing Python Packages
Python Programming Learning Circle
Python Programming Learning Circle
Jan 4, 2024 · Fundamentals

Simple Methods to Speed Up Python For Loops (1.3× to 970×)

This article presents a series of practical techniques—such as list comprehensions, pre‑computing lengths, using sets, skipping irrelevant iterations, inlining functions, generators, map, memoization, vectorization, and efficient string joining—that can accelerate Python for‑loops anywhere from 1.3‑fold up to 970‑fold, with concrete benchmark results and code examples.

Loop OptimizationPythonmemoization
0 likes · 15 min read
Simple Methods to Speed Up Python For Loops (1.3× to 970×)
DataFunTalk
DataFunTalk
Jan 4, 2024 · Artificial Intelligence

Using OpenLLM to Quickly Build and Deploy Large Language Model Applications

This presentation explains how OpenLLM, an open‑source LLM framework, together with BentoML, addresses the challenges of deploying large language models by offering model switching, memory optimizations, multi‑GPU support, observability, and easy containerized deployment for production AI applications.

BentoMLLLM deploymentOpenLLM
0 likes · 18 min read
Using OpenLLM to Quickly Build and Deploy Large Language Model Applications