C++ Standard Library And Qt, Python, etc. Implementation in C – Reviving the Spirit of C For Enhanced Development

This project aims to reimplement the C++ standard library functionality using the C programming language.

It provides C developers with tools and libraries commonly available in C++, enabling better data structure management, algorithm implementation, and feature usage while staying within the C language’s ecosystem.

A Personal Note From Me

I undertake this project out of a deep affection for the C programming language.

It is my belief that C remains an essential tool for any computer engineer or programmer, providing the foundation necessary to build efficient and robust software.

My love for C drives this endeavor, aiming to enrich the language with the familiar conveniences found in C++.

Project Structure

The project is organized into several subdirectories, each representing a different module of the standard library:

• Array: Implements a dynamic array similar to std::array in C++.
• ForwardList: Implements a singly-linked list analogous to std::forward_list in C++.
• List: Implements a doubly-linked list similar to std::list in C++.
• Queue: Implements a queue based on std::queue in C++.
• Stack: Implements a stack akin to std::stack in C++.
• String: Implements a basic string class that mimics std::string in C++.
• Vector: Implements a dynamic array similar to std::vector in C++.
• PriorityQueue: Implements a priority queue based on std::priority_queue in C++.
• Deque: Implements a deque based on std::deque in C++.
• CsvFile, CsvRow: For read, write, and other operations on CSV files.
• ConfigFile: Provides a flexible solution for handling configuration files in C.
• Map: A generic implementation of a map, or associative array.
• Span: Implements a span container for working with contiguous memory.
• Algorithm: Provides a wide range of generic functionalities similar to std::algorithm in C++.
• Encoding: A versatile tool for encoding and decoding operations.
• Numbers: Provides constants for common mathematical values, similar to C++20’s <numbers>.
• Numeric: Implements various numerical operations and algorithms, including those for basic arithmetic, interpolation, and mathematical calculations. This module aims to bring the functionality of the C++ <numeric> header to C, offering features like GCD, LCM, and midpoint calculations, among others.
• Crypto: Provides tools for cryptographic operations. This module might include functions for encryption and decryption, hashing, and secure random number generation. It’s intended to offer C developers basic cryptographic utilities, similar to what might be found in a more comprehensive C++ cryptographic library.
• Time: The Time library in C is a comprehensive tool designed for handling time-related operations. Inspired by the functionality of more advanced languages, this library provides a robust set of functions for manipulating and comparing time values in C programs.
• Date: The Date library in C offers a robust solution for handling and manipulating dates in both Gregorian and Persian calendars. This library is particularly useful for applications requiring operations on dates, such as calculations, conversions, and comparisons. Its comprehensive set of functions simplifies complex date-related tasks in C programming.
• Dir: Dir is used to manipulate path names, access information regarding paths and files, and manipulate the underlying file system.
• Tuple: implement tuple similar to std::tuple in c++.
• FileWriter: The FileWriter library is a versatile tool designed for file writing operations in C. It provides functionalities similar to higher-level languages, offering various modes for writing text and binary files, including support for Unicode (UTF-8 and UTF-16).
• FileReader: The FileReader library is a versatile tool designed for file writing operations in C.
• fmt: The fmt library is a comprehensive formatting and I/O library for C, inspired by fmt package in golang. It offers a wide range of formatting options and is designed to work seamlessly with multilingual and Unicode text.
• Json : The Json library is a comprehensive and efficient tool designed for parsing, generating, and manipulating JSON data in C. It aims to provide a robust and user-friendly interface for handling JSON objects and arrays, enabling seamless integration of JSON functionality into C projects.

Each module in the project comes with a .c source file, a .h header file, and a README.md file.

These README files offer detailed explanations of each module’s functionality, usage examples, and any other relevant information, ensuring that developers can easily understand and utilize the components of the library.

Compilation And Execution

Certainly! Based on your description and the provided Python script, it seems you prefer a more streamlined compilation process using a custom Python script (compile.py) rather than traditional makefiles.

I’ll update the compilation section of your README to reflect this preference.

Here’s the revised compilation and execution section of your README:

Compilation And Execution

This project utilizes a Python script (compile.py) for easy compilation of modules, making the build process straightforward and efficient.

Requirements

• Python 3.10 or higher
• GCC compiler (ensure it’s added to your system’s PATH)

Using The Compile.py Script

To compile the entire project, simply run the compile.py script with the b argument:

python compile.py b

This command compiles all source files and produces an executable in the ./build directory.

Running The Compiled Program

To compile and immediately run the compiled program, use the r argument:

python compile.py r

Adding New Modules

If you add new modules or directories containing .c files, simply include their paths in the source_directories list within the compile.py script.

The script automatically finds and compiles all .c files in the specified directories.

Streamlined Build Process

The use of compile.py eliminates the need for traditional makefiles or manual compilation commands, providing a simple and unified build process.

The script handles dependencies, includes, and linking, ensuring a hassle-free compilation experience.

Manual Compilation Using GCC

For developers who prefer manual compilation or need to integrate the project into other build systems, the source files can be compiled using the GCC command line.

While the compile.py script is recommended for its convenience and automated handling of file dependencies, manual compilation offers flexibility for advanced use cases.

Requirements For Manual Compilation

• GCC compiler (ensure it’s added to your system’s PATH)
• C17 standard support in GCC

Compiling With GCC

To manually compile a specific module or your entire project, you can use the GCC command with the -std=c17 flag to ensure compliance with the C17 standard. Here’s an example command to compile a program with the vector module:

gcc -std=c17 -O3 -march=native -flto -funroll-loops -Wall -Wextra -pedantic -s -o your_program your_program.c vector.c

In this command:

• -std=c17 specifies the use of the C17 standard.
• -O3, -march=native, -flto, and -funroll-loops are optimization flags.
• -Wall, -Wextra, and -pedantic enable additional warnings for better code quality.
• -s strips the binary for a smaller executable size.
• your_program.c is your main C source file.
• vector.c is the source file for the vector module (include other .c files as needed).
• your_program is the output executable file.

Customizing The Compilation

You can modify the GCC command to suit your specific requirements, such as including additional modules, linking libraries, or adjusting optimization levels.

This approach offers full control over the compilation process, allowing you to tailor it to your project’s needs.

Individual READMEs For Libraries

Each library module comes with its own README.md file, providing detailed instructions, sample code, function descriptions, and other relevant usage information.