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140 articles · Page 2 of 2
Python Programming Learning Circle
Python Programming Learning Circle
Apr 2, 2021 · Fundamentals

Effective Python Parallelism with Thread Pools and the map() Function

This article critiques traditional Python threading tutorials and demonstrates how to replace verbose thread‑pool code with concise map‑based parallelism using multiprocessing and multiprocessing.dummy, providing practical examples, performance measurements, and guidelines for choosing pool sizes for I/O‑ and CPU‑bound tasks.

Multiprocessingconcurrencymap
0 likes · 11 min read
Effective Python Parallelism with Thread Pools and the map() Function
Amap Tech
Amap Tech
Feb 1, 2021 · Frontend Development

Realistic Lighting Rendering for 3D Building Elements in AMap JSAPI 2.0

The article explains how AMap JSAPI 2.0 achieves realistic 3‑D building lighting by applying the Blinn‑Phong model with ambient, diffuse and specular components, employing directional, point and spot lights together with a classic three‑point lighting setup—including a high‑altitude point light over the Oriental Pearl Tower—to produce depth‑rich, non‑flat visualizations.

3D renderingBlinn-PhongWebGL
0 likes · 11 min read
Realistic Lighting Rendering for 3D Building Elements in AMap JSAPI 2.0
MaGe Linux Operations
MaGe Linux Operations
Aug 17, 2020 · Fundamentals

Boost Python Performance: Simple Parallelism with map and ThreadPool

This article explains why traditional Python threading tutorials are often over‑engineered, introduces the concise map‑based parallelism using multiprocessing and multiprocessing.dummy, and demonstrates how a few lines of code can dramatically speed up I/O‑bound and CPU‑bound tasks.

MultiprocessingThreadPoolconcurrency
0 likes · 11 min read
Boost Python Performance: Simple Parallelism with map and ThreadPool
Python Programming Learning Circle
Python Programming Learning Circle
Jun 19, 2020 · Fundamentals

Python List Operations: Filtering, Mapping, Zipping, and More

This tutorial demonstrates various Python list techniques—including filter(), list comprehensions, map(), zip(), slicing for reversal, membership testing, finding the most common element, flattening nested lists, and checking uniqueness—providing clear examples and explanations for each operation.

FundamentalsListlist-comprehension
0 likes · 8 min read
Python List Operations: Filtering, Mapping, Zipping, and More
Python Programming Learning Circle
Python Programming Learning Circle
May 12, 2020 · Fundamentals

Understanding Functional Programming in Python: Map, Filter, Reduce, Lambda, and Partial Application

This article introduces the functional programming paradigm, contrasts it with imperative programming, and demonstrates core Python functional tools such as map, filter, reduce, lambda expressions, and partial application, including code examples and explanations of side‑effects and higher‑order functions.

filtermappartial application
0 likes · 9 min read
Understanding Functional Programming in Python: Map, Filter, Reduce, Lambda, and Partial Application
Java Captain
Java Captain
Apr 29, 2020 · Fundamentals

Comprehensive Overview of the Java Collection Framework: Interfaces, Implementations, and Usage

This article provides a detailed introduction to Java's collection framework, covering the core interfaces (Collection and Map), concrete implementations such as List, Set, and Map, iterator mechanisms, differences among classes like ArrayList, LinkedList, HashSet, TreeSet, and practical code examples illustrating their behavior.

CollectionsIteratorJava
0 likes · 33 min read
Comprehensive Overview of the Java Collection Framework: Interfaces, Implementations, and Usage
Programmer DD
Programmer DD
Nov 30, 2019 · Backend Development

Master Java 8 Stream: When to Use map vs flatMap

This tutorial explains how Java 8's Stream API's map and flatMap operations work, showing practical examples of extracting student ages from collections and demonstrating why flatMap is needed to flatten nested lists, with clear code snippets and diagrams.

Functional ProgrammingJavaJava 8
0 likes · 4 min read
Master Java 8 Stream: When to Use map vs flatMap
DataFunTalk
DataFunTalk
Nov 14, 2019 · Artificial Intelligence

Sample Imbalance and Importance in Object Detection: IoU‑Balanced Sampling and Prime Sample Attention

The talk analyzes sample imbalance and importance in object detection, proposes IoU‑balanced negative sampling and instance‑balanced positive sampling, introduces the Prime Sample concept with Hierarchical Local Rank, and presents Importance‑based Sample Reweighting and Classification‑Aware Regression Loss, achieving consistent mAP gains without extra overhead.

IoU-balanced samplingcomputer visionhard mining
0 likes · 22 min read
Sample Imbalance and Importance in Object Detection: IoU‑Balanced Sampling and Prime Sample Attention
HomeTech
HomeTech
Aug 7, 2019 · Artificial Intelligence

Near-Duplicate Video Retrieval: Framework, Feature Extraction, Metric Learning, and Model Optimization

This article presents a comprehensive study of near‑duplicate video retrieval, covering the definition of near‑duplicate videos, motivations for deduplication, challenges, a two‑stage offline/online processing framework, keyframe and VGG16‑based feature extraction, metric‑learning loss functions, training procedures, dataset preparation, evaluation metrics, and model enhancements using LSTM and attention mechanisms.

LSTMVGG16attention
0 likes · 12 min read
Near-Duplicate Video Retrieval: Framework, Feature Extraction, Metric Learning, and Model Optimization
NetEase Game Operations Platform
NetEase Game Operations Platform
Apr 27, 2019 · Frontend Development

Functional Programming in JavaScript: Refactoring User List Processing

This article demonstrates how to apply functional programming concepts in JavaScript by refactoring an example that reads user data from an API, filters active SREs, and formats output, illustrating the benefits of pure functions, higher‑order utilities like map, filter, reduce, and improved code readability and maintainability.

Functional ProgrammingHigher-Order FunctionsPure Functions
0 likes · 22 min read
Functional Programming in JavaScript: Refactoring User List Processing
MaGe Linux Operations
MaGe Linux Operations
Apr 1, 2019 · Backend Development

Boost Python Performance: Parallelize Tasks with ThreadPool and map

This article critiques traditional Python multithreading tutorials and demonstrates how the built‑in map function together with multiprocessing.dummy's ThreadPool can dramatically speed up I/O‑bound and CPU‑bound tasks, offering concise code examples, performance benchmarks, and a real‑world thumbnail generation case study.

MultiprocessingThreadPoolmap
0 likes · 11 min read
Boost Python Performance: Parallelize Tasks with ThreadPool and map
UC Tech Team
UC Tech Team
Nov 13, 2018 · Fundamentals

Understanding Higher-Order Functions in JavaScript

This article explains what higher‑order functions are, why JavaScript supports functional programming, demonstrates built‑in methods like map, filter and reduce with code examples, and shows how to create your own higher‑order function for clearer, more concise code.

Functional ProgrammingHigher-Order FunctionsJavaScript
0 likes · 8 min read
Understanding Higher-Order Functions in JavaScript
Node Underground
Node Underground
Oct 12, 2018 · Frontend Development

Why map and filter Beat forEach in JavaScript: Cleaner, Testable Code

Using map and filter instead of forEach when creating new arrays in JavaScript offers semantic separation, easier testing, better readability, and async compatibility, making code more functional and maintainable while avoiding side‑effects and unnecessary complexity.

Functional Programmingarray methodsfilter
0 likes · 6 min read
Why map and filter Beat forEach in JavaScript: Cleaner, Testable Code
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Jul 16, 2018 · Fundamentals

Overview of the Java Collections Framework and Its Core Data Structures

This article provides a comprehensive overview of the Java Collections Framework, detailing its core interfaces, common implementations such as List, Set, Queue, and Map, their underlying data structures, performance characteristics, and usage examples including legacy classes and specialized collections like PriorityQueue and LinkedHashMap.

ArrayListCollectionsData Structures
0 likes · 8 min read
Overview of the Java Collections Framework and Its Core Data Structures
MaGe Linux Operations
MaGe Linux Operations
Jun 1, 2018 · Fundamentals

Master Python Functions: Definitions, Calls, Parameters, and Advanced Techniques

This article provides a comprehensive guide to Python functions, covering their definition syntax, calling conventions, parameter handling (including default, *args, **kwargs), return values, variable scope, anonymous lambda functions, and higher‑order utilities such as map, reduce, filter, and sorted, with clear code examples.

Higher-Order FunctionsLambdafilter
0 likes · 10 min read
Master Python Functions: Definitions, Calls, Parameters, and Advanced Techniques
Liulishuo Tech Team
Liulishuo Tech Team
Apr 11, 2018 · Mobile Development

Understanding map, flatMap, and compactMap in Swift

This article explains the differences between map, flatMap, and compactMap in Swift, covering the three overloads of flatMap, their behavior with sequences and optionals, the rationale behind renaming one overload to compactMap, and when to prefer optional chaining versus optional mapping.

Functional ProgrammingOptionalSwift
0 likes · 8 min read
Understanding map, flatMap, and compactMap in Swift
21CTO
21CTO
Jul 29, 2017 · Backend Development

Why JavaBeans Fall Short: Embracing Maps for Cleaner Backend Design

The article explores a programmer’s view of software as code and data, distinguishes persistent and transient data, critiques JavaBean‑centric MVC architecture, and proposes key‑value Maps as a more flexible, decoupled alternative for backend development.

JavaMVCdata modeling
0 likes · 8 min read
Why JavaBeans Fall Short: Embracing Maps for Cleaner Backend Design
Architecture Digest
Architecture Digest
Jul 28, 2017 · Backend Development

Understanding Programs, JavaEE MVC, and Why Maps Can Replace JavaBeans

The article reflects on the nature of programs as code and data, distinguishes persistent and transient data, explains JavaEE MVC and multi‑layer architecture, critiques the overuse of JavaBeans, and advocates using key‑value Maps as a simpler, more flexible data‑transfer model.

JavaMVCdata modeling
0 likes · 10 min read
Understanding Programs, JavaEE MVC, and Why Maps Can Replace JavaBeans
Java Captain
Java Captain
Jul 11, 2017 · Fundamentals

Understanding Java Collection Framework: Interfaces, Implementations, and Usage

This article provides a comprehensive overview of Java's collection framework, covering the core Collection interface, List, Set, and Map interfaces, their common implementations such as ArrayList, LinkedList, Vector, Stack, Hashtable, and HashMap, and demonstrates traversal using the Iterator pattern with code examples.

Data StructuresIteratorList
0 likes · 12 min read
Understanding Java Collection Framework: Interfaces, Implementations, and Usage
Aotu Lab
Aotu Lab
Apr 29, 2016 · Frontend Development

Mastering JavaScript’s reduce(): From Basics to Advanced Use Cases

This article explains the ES5 Array.prototype.reduce() method, compares it with forEach and map, details its syntax and parameters, provides step‑by‑step code examples—including handling of initial values and object arrays—and notes browser compatibility and library alternatives.

ArrayJavaScriptforeach
0 likes · 7 min read
Mastering JavaScript’s reduce(): From Basics to Advanced Use Cases
21CTO
21CTO
Feb 9, 2016 · Frontend Development

Why Using map Beats for Loops: Cleaner, Declarative JavaScript

This article explains how replacing traditional for‑loops with JavaScript’s map method leads to more declarative, readable code, reduces boilerplate, improves maintainability, and offers comparable performance, while also discussing functional programming principles, browser support, and best practices for naming helper functions.

Declarative programmingFunctional ProgrammingJavaScript
0 likes · 7 min read
Why Using map Beats for Loops: Cleaner, Declarative JavaScript
ITPUB
ITPUB
Nov 12, 2015 · Fundamentals

Essential Differences and Usage Tips for Java Collections

This article explains why Map does not extend Collection, compares HashMap with Hashtable, clarifies Comparable versus Comparator, shows how to sort object lists, distinguishes fail‑fast from fail‑safe iterators, and outlines key differences among Set, List, ArrayList, Vector, and related Java collection classes.

ArrayListCollectionsHashMap
0 likes · 7 min read
Essential Differences and Usage Tips for Java Collections