C++ Standard Library and Qt, Python etc Implementation in C

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 the fmt package in Go. 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.

• Log: The Log library offers a flexible and powerful logging system for C projects, enabling detailed message logging across various levels (DEBUG, INFO, WARN, ERROR, FATAL). It supports multiple output destinations (console, file, or both), timestamp inclusion, log level configuration, and keyword filtering to refine log output. Integrated with file I/O operations and customizable settings, it enhances diagnostic and monitoring capabilities in development and production environments.

• Cli: The CLI library provides a comprehensive solution for parsing command-line arguments in C projects, supporting options, commands, and subcommands with both short and long names. It features advanced functionalities like custom error handling, option grouping, interactive mode, and pipelining support, making it versatile for both simple and complex CLI applications. This library simplifies command-line parsing, validation, and execution, offering a robust foundation for building user-friendly command-line interfaces.

• Network: The Network library provides support for TCP and UDP protocols, enabling the development of networked applications. It includes functions for creating sockets, binding, listening, connecting, sending, and receiving data over both TCP and UDP connections.

• Database: The Database library offers tools for interacting with PostgreSQL databases. It includes functions for connecting to databases, executing queries, retrieving results, and handling transactions. This library aims to simplify database operations in C by providing a high-level API.

• Matrix: The Matrix library provides tools for matrix operations, including creation, manipulation, and mathematical computations on matrices. It is designed to support a wide range of matrix operations needed in scientific computing and data analysis.

• Random: This random library provides functionality like python random module for working with probablity and randomly numbers and elements.

• Statistics: This Statistics library in C provides a set of functions for calculating mathematical statistics of numeric data. exactly like python statistics module .

• SysInfo: This SysInfo library in C provides a set of functions for gathering lots of information about system also operating system. and work fine in (windows and linux) not Mac :))

• Turtle: The Turtle Graphics library in C provides functions for drawing shapes and lines using a "turtle" that moves around the screen. Inspired by the Python turtle module, this library allows C developers to easily create graphics and animations.

• HttpRequest and HttpResponse :The Http library provides functionality for creating and handling HTTP servers and clients. It includes support for routing, request parsing, response generation, and handling various HTTP methods (GET, POST, etc.). This library simplifies the development of web-based applications in C, enabling easy integration of HTTP 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

CMake Support

This project now supports building with CMake, a powerful cross-platform build system that simplifies the process of compiling and linking code.

Building with CMake

To build the project using CMake, follow these steps:

1. Install CMake:

   • Ensure that CMake is installed on your system. You can download it from the official website or use a package manager like apt, brew, or choco depending on your operating system.

2. Create a Build Directory:

   • Navigate to the root directory of the project and create a build directory:

     mkdir build
     cd build

3. Generate Build Files:

   • Run CMake to generate the build files for your system:

     cmake ..

4. Compile the Project:

   • Once the build files are generated, compile the project using make (or another build tool depending on your system):

     make

5. Run the Compiled Program:

   • After compilation, the executable and shared libraries will be located in the build directory. You can run the executable directly:

     ./main

   • On Linux, ensure to set the LD_LIBRARY_PATH if you're using shared libraries:

     export LD_LIBRARY_PATH=./build:$LD_LIBRARY_PATH
     ./build/main

Adding Modules with CMake

If you add new modules, you need to update the CMakeLists.txt file to include them. This file is used by CMake to configure the build process. Here's how to add a new module:

1. Edit CMakeLists.txt:

   • Add the new module's source files to the add_library or add_executable commands in the CMakeLists.txt file.

2. Re-run CMake:

   • After editing CMakeLists.txt, re-run CMake in the build directory:

     cmake ..

3. Compile Again:

   • Use make or another build tool to compile the updated project.

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)
• Linux Users: Make sure to install the necessary development libraries:

  sudo apt-get install libssl-dev libpq-dev

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

On Linux, make sure to set the LD_LIBRARY_PATH before running the program:

export LD_LIBRARY_PATH=./build:$LD_LIBRARY_PATH
./build/main

Compiling to Shared Libraries Only

To compile only the shared libraries (DLLs or .so files) for each module, use the l argument:

python compile.py l

This command compiles all source files into shared libraries in the ./build directory without producing an executable.

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.

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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.

Contribution

Contributions are welcome. Whether it's extending existing libraries, improving performance, or fixing bugs, your help is appreciated. Fork the repository, make your changes, and submit a pull request.

License

This project is open-source and available under ISC License.