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Template libraries and generic libraries implement generic programming by allowing data type parameterization and providing predefined templates, improving code reusability and flexibility, including: Template library: providing a template declaration mechanism, creating A type or function parameterized based on a data type, such as a std::vector template container. Generic library: Provides predefined template functions and types that perform common tasks, such as the std::sort generic function for sorting elements.
The role of template libraries and generic libraries in C generic programming
Overview
Generic programming in C allows the development of code that works for a variety of data types, improving code reusability and flexibility. Template libraries and generic libraries are key components for implementing generic programming.
Template library
The template library provides a mechanism for declaring templates, allowing you to create parameterized types or functions based on data types. For example, std::vector
is a template container that accepts a type parameter to store elements.
Code sample:
#include <vector> // 定义存储整数的模板向量 template <typename T> using IntVector = std::vector<T>; // 创建一个存储整数的向量 IntVector<int> myVector; myVector.push_back(10);
Generic library
The generic library provides predefined template functions and types that are available for performing a variety of common tasks. For example, std::sort
is a generic function that accepts a comparison function to sort elements.
Code example:
#include <algorithm> // 比较函数 int compare(const int& a, const int& b) { return a > b; } // 对向量进行降序排序 std::sort(myVector.begin(), myVector.end(), compare);
Practical case
Consider the following matrix multiplication problem:
A = [[1, 2], [3, 4]] B = [[5, 6], [7, 8]] C = A * B = [[19, 22], [43, 50]]
Using generic programming, we can create a template function to perform matrix multiplication that will work for any element type.
#include <vector> // 矩阵相乘模板函数 template <typename T> std::vector<std::vector<T>> matrixMultiply(const std::vector<std::vector<T>>& a, const std::vector<std::vector<T>>& b) { int m = a.size(), n = a[0].size(), p = b[0].size(); std::vector<std::vector<T>> c(m, std::vector<T>(p, 0)); for (int i = 0; i < m; i++) { for (int j = 0; j < p; j++) { for (int k = 0; k < n; k++) { c[i][j] += a[i][k] * b[k][j]; } } } return c; } // 矩阵相乘实战 auto c = matrixMultiply(a, b);
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