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Python Programming Learning Circle
Python Programming Learning Circle
May 3, 2023 · Fundamentals

11 Pythonic Tricks to Boost Your Python Skills

This article introduces eleven practical Pythonic techniques—including destructuring assignment, zip aggregation, lambda usage, underscore placeholders, list comprehensions, dummy functions, regex handling, map/reduce, whitespace trimming, shallow copying, and interpreter shortcuts—each illustrated with clear code examples to help developers write more elegant and efficient Python code.

PythonTipscode
0 likes · 7 min read
11 Pythonic Tricks to Boost Your Python Skills
IT Services Circle
IT Services Circle
Apr 25, 2023 · Information Security

WeChat Crash via Malformed QR Code: Technical Analysis and Reproduction

Researchers discovered that a specially crafted QR code triggers a memory leak in WeChat’s OCR engine, causing the app to crash on both mobile and desktop platforms; the article explains the underlying bug, provides detailed decoding analysis, and shares Python code to reproduce the malformed QR code.

OpenCVPythonQR code
0 likes · 8 min read
WeChat Crash via Malformed QR Code: Technical Analysis and Reproduction
Programmer DD
Programmer DD
Apr 25, 2023 · Artificial Intelligence

Why a Single QR Code Crashes WeChat: Inside the Memory Leak Bug

An unusual QR code triggers a memory‑leak in WeChat’s OCR engine, causing the app to crash on both mobile and desktop; the article explains the underlying null‑pointer exception, shows how the malformed “abnormal QR code” corrupts libqbar.so, and provides Python code to reproduce the bug using OpenCV’s open‑source QR engine.

CrashOpenCVPython
0 likes · 9 min read
Why a Single QR Code Crashes WeChat: Inside the Memory Leak Bug
Python Programming Learning Circle
Python Programming Learning Circle
Apr 23, 2023 · Big Data

Parallel Processing of Large CSV Files in Python with multiprocessing, joblib, and tqdm

This tutorial demonstrates how to accelerate processing of a 2.8‑million‑row CSV dataset by using Python's multiprocessing, joblib, and tqdm libraries, covering serial, parallel, and batch processing techniques, performance measurements, and best‑practice code examples for efficient large‑scale data handling.

Big DataPythondata engineering
0 likes · 9 min read
Parallel Processing of Large CSV Files in Python with multiprocessing, joblib, and tqdm
Top Architect
Top Architect
Apr 21, 2023 · Artificial Intelligence

Fine‑Tuning LLaMA‑7B with Alpaca‑LoRA to Build a Chinese ChatGPT

This article explains why and how to fine‑tune the LLaMA‑7B model using the cheap Alpaca‑LoRA approach, covering hardware requirements, dataset preparation, LoRA training, optional model merging and quantization, and provides ready‑to‑run code snippets for single‑ and multi‑GPU setups.

Alpaca-LoRAFine-tuningGPU
0 likes · 10 min read
Fine‑Tuning LLaMA‑7B with Alpaca‑LoRA to Build a Chinese ChatGPT
Continuous Delivery 2.0
Continuous Delivery 2.0
Apr 20, 2023 · Artificial Intelligence

AutoGPT: Autonomous AI Tool Overview, Demonstrations, and Setup Guide

AutoGPT, the latest autonomous AI system, can independently browse the web, use third‑party tools, and execute tasks without human intervention, exemplified by building a React website in minutes, and this article explains its principles, showcases demos, and provides step‑by‑step installation instructions.

AI toolsAgentGPTAutoGPT
0 likes · 10 min read
AutoGPT: Autonomous AI Tool Overview, Demonstrations, and Setup Guide
Python Programming Learning Circle
Python Programming Learning Circle
Apr 19, 2023 · Fundamentals

Hidden Python Tricks: Ternary Operator, enumerate, zip, List Comprehensions, Lambdas, Generators, Decorators and More

This article introduces a collection of lesser‑known Python techniques—including the ternary operator, enumerate, zip, list comprehensions, lambda functions, any/all, itertools, generators, decorators, dynamic imports, dictionary comprehensions, and mutable data structures—each explained with clear examples to help developers write more concise and efficient code.

Code ExamplesGeneratorsPython
0 likes · 10 min read
Hidden Python Tricks: Ternary Operator, enumerate, zip, List Comprehensions, Lambdas, Generators, Decorators and More
MaGe Linux Operations
MaGe Linux Operations
Apr 14, 2023 · Fundamentals

10 Essential pip Tricks Every Python Developer Should Know

This guide presents ten practical pip techniques—from installing and upgrading pip itself to batch installing, freezing dependencies, checking compatibility, and downloading packages—empowering Python developers to manage third‑party libraries more efficiently and avoid technical debt.

PythonTutorialcommand-line
0 likes · 9 min read
10 Essential pip Tricks Every Python Developer Should Know
Python Programming Learning Circle
Python Programming Learning Circle
Apr 10, 2023 · Fundamentals

Common Python Design Questions and Explanations

This article explains why Python uses indentation for block grouping, how floating‑point arithmetic works, why strings are immutable, the purpose of the explicit self parameter, the absence of assignment in expressions, and many other design decisions that shape Python's syntax and runtime behavior.

Data StructuresFAQMemory Management
0 likes · 27 min read
Common Python Design Questions and Explanations
FunTester
FunTester
Apr 10, 2023 · Industry Insights

How to Map China’s Qingming Rainfall Using Free Weather APIs and Python

This guide shows how to collect nationwide weather data for the Qingming Festival via the free QWeather API, process it with Python to generate a CSV file, and visualize the rainfall distribution across China using a desktop data‑visualization tool.

CSVData visualizationPython
0 likes · 6 min read
How to Map China’s Qingming Rainfall Using Free Weather APIs and Python
FunTester
FunTester
Apr 8, 2023 · Backend Development

Master JSON Extraction in Python with JsonPath: A Practical Guide

This tutorial shows how to install the JsonPath library, retrieve JSON data from an API, and use both traditional indexing and powerful JsonPath expressions—including filters, wildcards, and slicing—to efficiently extract nested values for automated testing.

API testingJSON extractionJsonPath
0 likes · 7 min read
Master JSON Extraction in Python with JsonPath: A Practical Guide
Python Programming Learning Circle
Python Programming Learning Circle
Apr 8, 2023 · Operations

Using Python for Operations Automation: Remote Execution, Log Parsing, Monitoring, Deployment, and Backup

The article explains how operations engineers can leverage Python scripts and popular libraries such as paramiko, regex, psutil, fabric, and shutil to automate common tasks like remote command execution, log analysis, system monitoring with alerts, batch software deployment, and file backup and recovery, providing code examples for each scenario.

DevOpsOperationsPython
0 likes · 9 min read
Using Python for Operations Automation: Remote Execution, Log Parsing, Monitoring, Deployment, and Backup
360 Quality & Efficiency
360 Quality & Efficiency
Apr 7, 2023 · Backend Development

RabbitMQ Introduction: Installation, Basic and Advanced Producer/Consumer Patterns, Exchanges, and Common Issues

This guide introduces RabbitMQ, explains how to install it with Docker, covers basic and advanced producer/consumer usage including acknowledgments, durability, QoS, bindings, and exchange types, and discusses a typical Python reconnection problem, providing a practical overview for backend developers.

DockerExchangeMessage Queue
0 likes · 5 min read
RabbitMQ Introduction: Installation, Basic and Advanced Producer/Consumer Patterns, Exchanges, and Common Issues
360 Quality & Efficiency
360 Quality & Efficiency
Apr 7, 2023 · Mobile Development

Mobile App UI Automation Using ATX and Python: POM, Data‑Driven and Keyword‑Driven Approaches

This article describes how a mobile development team adopted the ATX automation framework with Python, employing Page Object Model, data‑driven and keyword‑driven techniques to replace manual regression testing, integrate firmware interaction, and streamline test execution and reporting.

ATXData‑Driven TestingKeyword‑Driven Testing
0 likes · 7 min read
Mobile App UI Automation Using ATX and Python: POM, Data‑Driven and Keyword‑Driven Approaches
Tencent Cloud Developer
Tencent Cloud Developer
Apr 4, 2023 · Artificial Intelligence

Step-by-Step Guide to Building Your Own Realistic AI Image Generation Website with Stable Diffusion

This step‑by‑step tutorial shows how to set up a Stable Diffusion web UI, install the required Python environment and GPU‑enabled PyTorch, add Chinese localization and optional LoRA or Deforum extensions, generate realistic human images, create animated videos, and add speech with D‑ID, all ready for deployment on your own AI website.

DeforumGitPython
0 likes · 9 min read
Step-by-Step Guide to Building Your Own Realistic AI Image Generation Website with Stable Diffusion
NetEase LeiHuo UX Big Data Technology
NetEase LeiHuo UX Big Data Technology
Apr 3, 2023 · Artificial Intelligence

Understanding Causal Inference and How to Use the DoWhy Library

This article explains why causal inference is essential for moving beyond correlation to decision‑making, introduces the structural causal model framework, and provides a step‑by‑step guide to using Microsoft’s DoWhy Python library for modeling, identification, estimation, and counterfactual analysis.

Artificial IntelligenceDoWhyPython
0 likes · 7 min read
Understanding Causal Inference and How to Use the DoWhy Library
Python Programming Learning Circle
Python Programming Learning Circle
Apr 3, 2023 · Fundamentals

20 Essential Python Tricks for Improving Code Readability and Efficiency

This article presents twenty practical Python techniques—including string reversal, title casing, unique element extraction, list multiplication, dictionary merging, and performance timing—that enhance code readability, simplify common tasks, and boost development efficiency for programmers seeking to write cleaner, more effective Python scripts.

Pythoncodeprogramming
0 likes · 9 min read
20 Essential Python Tricks for Improving Code Readability and Efficiency
21CTO
21CTO
Apr 2, 2023 · Backend Development

How Codon Turbocharges Python: A Compiler That Rivals C++

Codon, a new Python compiler introduced by IEEE Spectrum, uses static type checking to eliminate runtime overhead, delivering C++‑level performance—10 to 100 times faster than CPython—while targeting genomics, big‑data, and other compute‑intensive domains, though it sacrifices some dynamic Python features.

CodonInstallationPerformance
0 likes · 7 min read
How Codon Turbocharges Python: A Compiler That Rivals C++
Python Programming Learning Circle
Python Programming Learning Circle
Apr 1, 2023 · Fundamentals

JupyterLab Visual Debugger and xeus‑python Kernel: Installation, Features, and Front‑End Architecture

The article introduces JupyterLab’s new visual debugger, explains why debugging is needed in Jupyter, provides installation commands for the front‑end extension and xeus‑python kernel, describes the debugger’s UI components and capabilities, and compares it with a VS Code visual debugging tool.

IDEJupyterLabPython
0 likes · 6 min read
JupyterLab Visual Debugger and xeus‑python Kernel: Installation, Features, and Front‑End Architecture
Python Crawling & Data Mining
Python Crawling & Data Mining
Apr 1, 2023 · Backend Development

How to Fix Chinese Garbled Text in Python Web Scraping

This article explains three practical methods—using response.content, apparent_encoding, and custom encode/decode—to resolve Chinese character garbling in Python web crawlers, includes code snippets and screenshots, and offers concise guidance for developers facing this common issue.

ChinesePythonencoding
0 likes · 5 min read
How to Fix Chinese Garbled Text in Python Web Scraping
Python Programming Learning Circle
Python Programming Learning Circle
Mar 31, 2023 · Fundamentals

Python Programming Exercises: Narcissistic Numbers, Algorithms, and Common Coding Problems

This article presents a series of Python programming exercises covering topics such as Narcissistic numbers, four‑digit Armstrong numbers, string reversal, number guessing games, classic algorithms like bubble sort, binary search, recursion, palindrome detection, and many other fundamental coding challenges with complete code examples.

Programming ExercisesPythonfundamentals
0 likes · 33 min read
Python Programming Exercises: Narcissistic Numbers, Algorithms, and Common Coding Problems
DataFunSummit
DataFunSummit
Mar 30, 2023 · Artificial Intelligence

An Overview of ChatGPT’s Software Architecture and Technology Stack

The article examines ChatGPT’s underlying software architecture, detailing its cloud deployment on AWS and Azure, database choices like PostgreSQL and Redis, front‑end technologies such as TypeScript and React, core AI frameworks including PyTorch and Triton, as well as its container orchestration, monitoring, and programming language ecosystem.

AI ArchitectureChatGPTFrontend
0 likes · 6 min read
An Overview of ChatGPT’s Software Architecture and Technology Stack
21CTO
21CTO
Mar 28, 2023 · Backend Development

Top 5 Python Test Automation Frameworks Compared: Pros, Cons & Best Use Cases

This article evaluates the five leading Python test automation frameworks—Robot Framework, Pytest, unittest (PyUnit), Behave, and Lettuce—detailing their installation requirements, key features, advantages, disadvantages, and suitability for functional, unit, or behavior‑driven testing to help developers choose the right tool.

LettucePythonbehave
0 likes · 12 min read
Top 5 Python Test Automation Frameworks Compared: Pros, Cons & Best Use Cases
Python Programming Learning Circle
Python Programming Learning Circle
Mar 28, 2023 · Fundamentals

10 Useful Python Automation Scripts for Everyday Tasks

This article presents ten practical Python automation scripts covering image and video processing, PDF conversion, API interaction, system notifications, grammar and spell correction, downloading, news fetching, and GUI creation, each accompanied by concise code examples for quick implementation.

APIGUIImageProcessing
0 likes · 12 min read
10 Useful Python Automation Scripts for Everyday Tasks
IT Services Circle
IT Services Circle
Mar 26, 2023 · Fundamentals

Common Regular Expression Metacharacters and Their Usage in Python

This article explains the most frequently used regular expression symbols in Python, covering ordinary metacharacters, the OR operator, escape sequences, anchors, quantifiers, grouping, and shorthand character classes, each illustrated with clear code examples and explanations.

Pythonmetacharacterspattern-matching
0 likes · 6 min read
Common Regular Expression Metacharacters and Their Usage in Python
Model Perspective
Model Perspective
Mar 22, 2023 · Artificial Intelligence

Master DBSCAN Clustering: Theory, Python Code, and Real-World Examples

DBSCAN is a density‑based clustering algorithm that automatically discovers arbitrarily shaped clusters and isolates noise, with detailed explanations of core, border, and noise points, step‑by‑step examples, Python implementations using scikit‑learn, and guidance on key parameters such as eps and min_samples.

DBSCANPythonclustering
0 likes · 10 min read
Master DBSCAN Clustering: Theory, Python Code, and Real-World Examples
Python Programming Learning Circle
Python Programming Learning Circle
Mar 22, 2023 · Fundamentals

Comparing Distributions Between Groups: Visualization and Statistical Methods in Python

This article demonstrates how to compare the distribution of a variable across control and treatment groups using Python, covering data generation, visual techniques such as boxplots, histograms, KDE, CDF, QQ and ridgeline plots, and a suite of statistical tests including t‑test, SMD, Mann‑Whitney, permutation, chi‑square, Kolmogorov‑Smirnov and ANOVA for both two‑group and multi‑group scenarios.

A/B testingPythonStatistical Tests
0 likes · 21 min read
Comparing Distributions Between Groups: Visualization and Statistical Methods in Python
Model Perspective
Model Perspective
Mar 21, 2023 · Artificial Intelligence

Master Linear Discriminant Analysis (LDA) with Python: Theory & Code

This article explains Linear Discriminant Analysis (LDA) as a pattern‑recognition technique that projects data onto a low‑dimensional space to maximize class separation, details its mathematical formulation with between‑class and within‑class scatter matrices, and provides a complete Python implementation using scikit‑learn on the Iris dataset, including visualization of the results.

LDALinear Discriminant AnalysisPython
0 likes · 6 min read
Master Linear Discriminant Analysis (LDA) with Python: Theory & Code
Python Programming Learning Circle
Python Programming Learning Circle
Mar 21, 2023 · Artificial Intelligence

A Survey of 10 Python Libraries for Explainable AI (XAI)

This article introduces Explainable AI (XAI), outlines its importance, describes a step-by-step workflow, and reviews ten Python libraries—including SHAP, LIME, ELI5, Shapash, Anchors, BreakDown, Interpret‑Text, AI Explainability 360, OmniXAI, and XAI—providing usage examples and code snippets.

Pythonexplainable AImachine learning
0 likes · 12 min read
A Survey of 10 Python Libraries for Explainable AI (XAI)
Model Perspective
Model Perspective
Mar 20, 2023 · Artificial Intelligence

Master Feature Selection with Recursive Elimination (RFE) in Python

Feature Recursive Elimination (RFE) is a powerful feature‑selection technique that iteratively trains a model, discards the weakest features, and repeats until a desired number of features remains, helping prevent overfitting and improve model performance, illustrated with a complete Python example using scikit‑learn.

Pythonfeature selectionrecursive elimination
0 likes · 6 min read
Master Feature Selection with Recursive Elimination (RFE) in Python
Python Programming Learning Circle
Python Programming Learning Circle
Mar 16, 2023 · Fundamentals

13 Amazing Python Features You Might Not Know

This article introduces thirteen lesser‑known Python features—including list stepping, the find method, iterators, doctest, yield statements, dictionary get, for/else and while/else loops, named string formatting, recursion limits, conditional expressions, argument unpacking, the special __hello__ import, and multiline strings—each illustrated with clear code examples.

Advanced FeaturesCode ExamplesPython
0 likes · 8 min read
13 Amazing Python Features You Might Not Know
Python Programming Learning Circle
Python Programming Learning Circle
Mar 15, 2023 · Game Development

Creating a Code Rain Effect with Python and Pygame

This tutorial demonstrates how to build a classic "code rain" screen using Python's pygame library, guiding readers through imports, window setup, character rendering, and a concise main loop that produces the animated effect in roughly thirty lines of code.

Code RainGame DevelopmentGraphics
0 likes · 6 min read
Creating a Code Rain Effect with Python and Pygame
DataFunTalk
DataFunTalk
Mar 15, 2023 · Artificial Intelligence

Predicting Sunspot Activity with CnosDB and a TensorFlow 1DConv‑LSTM Model

This article demonstrates how to store monthly sunspot numbers in the CnosDB time‑series database and use TensorFlow to build a 1DConv‑LSTM neural network for forecasting sunspot activity, covering data import, database insertion, train‑test splitting, model definition, training, and result visualization.

1DConv LSTMCnosDBPython
0 likes · 11 min read
Predicting Sunspot Activity with CnosDB and a TensorFlow 1DConv‑LSTM Model
Model Perspective
Model Perspective
Mar 14, 2023 · Operations

How Data Envelopment Analysis (DEA) Optimizes Airline Efficiency with Python

Data Envelopment Analysis (DEA) is a non‑parametric technique for evaluating relative efficiency of decision‑making units, with CRS and VRS models explained, followed by a Python implementation using PuLP to assess airline route efficiency and interpret overall, technical, and scale efficiencies.

CRSDEAData Envelopment Analysis
0 likes · 15 min read
How Data Envelopment Analysis (DEA) Optimizes Airline Efficiency with Python
Python Programming Learning Circle
Python Programming Learning Circle
Mar 14, 2023 · Fundamentals

Essential Python Tips and Tricks from A to Z

An extensive collection of Python programming tips and tricks, ranging from built‑in functions like all/any and collections to advanced features such as type hints, virtual environments, and third‑party libraries, presented alphabetically to help developers quickly enhance their code efficiency and readability.

Pythonprogramming
0 likes · 16 min read
Essential Python Tips and Tricks from A to Z
Model Perspective
Model Perspective
Mar 13, 2023 · Fundamentals

Mastering TOPSIS: Step-by-Step Guide with Python Implementation

This article explains the TOPSIS multi‑criteria decision‑making technique, outlines its mathematical formulation, walks through the seven procedural steps, and demonstrates a complete Python example that normalizes data, computes distances, scores alternatives, and ranks the best solution.

PythonTOPSISnormalization
0 likes · 8 min read
Mastering TOPSIS: Step-by-Step Guide with Python Implementation
58UXD
58UXD
Mar 13, 2023 · Fundamentals

Automating 3D Scene Creation in Cinema 4D with Python: From CAD to VR

Learn how to automate the construction of detailed 3D scenes in Cinema 4D using Python, by importing CAD layers, generating walls, doors, windows, furniture, lighting, and cameras, enabling efficient VR visualizations for interior design projects.

3D AutomationCADCinema4D
0 likes · 10 min read
Automating 3D Scene Creation in Cinema 4D with Python: From CAD to VR
Model Perspective
Model Perspective
Mar 11, 2023 · Fundamentals

Mastering the Analytic Hierarchy Process (AHP) with Python: Step‑by‑Step Guide

This article introduces the Analytic Hierarchy Process (AHP), explains its hierarchical modeling, mathematical foundations, step‑by‑step implementation, and provides complete Python code for constructing comparison matrices, calculating weights, and performing consistency checks to ensure reliable results.

Consistency RatioMulti-Criteria Decision MakingPython
0 likes · 9 min read
Mastering the Analytic Hierarchy Process (AHP) with Python: Step‑by‑Step Guide
Python Programming Learning Circle
Python Programming Learning Circle
Mar 11, 2023 · Game Development

Introduction and Basic Usage of the Vizard Virtual‑Reality Development Platform

This article introduces Vizard, a C/C++‑based virtual‑reality development platform with Python support, and demonstrates how to load avatars and objects, create random‑walk behavior, implement dialogue actions, control character movement via keyboard, capture mouse input, and combine these techniques into a complete interactive 3D scene.

3DGame DevelopmentPython
0 likes · 5 min read
Introduction and Basic Usage of the Vizard Virtual‑Reality Development Platform
Model Perspective
Model Perspective
Mar 10, 2023 · Fundamentals

Unlocking the Shoelace Theorem: Fast Polygon Area Calculation Explained

This article explores the “push‑step aggregation” technique featured in the drama “Microscope under the Ming,” revealing that it is essentially the Shoelace Theorem for quickly computing polygon areas, complete with mathematical derivation, visual illustrations, and a Python implementation.

Computational GeometryPythonShoelace theorem
0 likes · 8 min read
Unlocking the Shoelace Theorem: Fast Polygon Area Calculation Explained
Python Programming Learning Circle
Python Programming Learning Circle
Mar 8, 2023 · Fundamentals

Comprehensive Python Basics: Numbers, Strings, Functions, Data Structures, Classes, and Utilities

This tutorial presents a thorough overview of essential Python concepts, demonstrating numeric operations, string conversions, built‑in functions, diverse data structures, object‑oriented programming techniques, and useful utilities such as file handling, iteration tools, and JSON serialization, all illustrated with clear code examples.

Data StructuresPythonTutorial
0 likes · 20 min read
Comprehensive Python Basics: Numbers, Strings, Functions, Data Structures, Classes, and Utilities
IT Services Circle
IT Services Circle
Mar 7, 2023 · Frontend Development

Using d3blocks to Create Interactive D3.js Visualizations in Python

The article introduces d3blocks, a Python library that extends D3.js's interactive visualization capabilities to Python, demonstrating how to create interactive scatter, network, Sankey, and image slider charts with just a few lines of code and offering examples with code snippets and GIF illustrations.

D3.jsData visualizationInteractive Plot
0 likes · 4 min read
Using d3blocks to Create Interactive D3.js Visualizations in Python
Model Perspective
Model Perspective
Mar 6, 2023 · Operations

Master Linear Programming: Theory, Methods, and Python Implementation

Linear programming optimizes a linear objective under linear constraints, and this article explains its theory, common solution methods such as Simplex, Interior‑Point, and Branch‑and‑Bound, illustrates a production‑planning case, and provides a complete Python implementation using SciPy’s linprog function.

Linear ProgrammingPythonbranch-and-bound
0 likes · 7 min read
Master Linear Programming: Theory, Methods, and Python Implementation
Model Perspective
Model Perspective
Mar 3, 2023 · Fundamentals

Unlock Hidden Patterns: A Practical Guide to Factor Analysis with Python

Factor analysis, a statistical technique for uncovering underlying common factors among variables, is explained alongside its distinction from PCA, detailed procedural steps, adequacy tests, and a hands‑on Python implementation using the factor_analyzer library with visualizations and factor rotation methods.

Pythondata preprocessingfactor analysis
0 likes · 10 min read
Unlock Hidden Patterns: A Practical Guide to Factor Analysis with Python
Model Perspective
Model Perspective
Mar 1, 2023 · Artificial Intelligence

Mastering the EM Algorithm: Theory, Math, and Python Implementation

This article explains the Expectation‑Maximization (EM) algorithm, detailing its iterative E‑step and M‑step processes, mathematical formulation, and practical Python implementation for estimating parameters of mixed linear regression models, while highlighting convergence considerations and common pitfalls.

EM algorithmPythonexpectation maximization
0 likes · 12 min read
Mastering the EM Algorithm: Theory, Math, and Python Implementation
Python Programming Learning Circle
Python Programming Learning Circle
Mar 1, 2023 · Fundamentals

30 Handy Python Code Snippets for Everyday Tasks

This article presents 30 concise Python code snippets that can be understood in under 30 seconds, covering common tasks such as checking duplicates, computing byte size, merging dictionaries, measuring execution time, and more, providing quick, practical solutions for everyday programming needs.

Pythoncode snippets
0 likes · 14 min read
30 Handy Python Code Snippets for Everyday Tasks
Python Programming Learning Circle
Python Programming Learning Circle
Mar 1, 2023 · Artificial Intelligence

Introducing Streamlit: A Free Open‑Source Framework for Building Machine‑Learning Apps with Python

Streamlit is a free, open‑source Python framework that lets machine‑learning engineers quickly turn scripts into interactive apps, offering features such as top‑down script execution, widget‑as‑variable handling, caching, GPU support, and seamless integration with version‑control tools, all without requiring separate frontend development.

App DevelopmentData visualizationOpen-source
0 likes · 9 min read
Introducing Streamlit: A Free Open‑Source Framework for Building Machine‑Learning Apps with Python
Tencent Architect
Tencent Architect
Feb 28, 2023 · Backend Development

Master HTTP/HTTPS Testing with Python httpx and curl: A Practical Guide

This guide explains how to use Python's httpx library and the curl command‑line tool to perform comprehensive HTTP/HTTPS testing—including basic requests, chunked transfers, HTTP/2, SSL/TLS configuration, and dynamic DNS resolution—complete with code examples and setup instructions.

HTTP2PythonTLS
0 likes · 13 min read
Master HTTP/HTTPS Testing with Python httpx and curl: A Practical Guide