cpp26-equality-linter 2025.12.20185334

A new package that automates equality checks in C++ code by leveraging the upcoming reflection capabilities in C++26. This tool will allow developers to input C++ code snippets or class definitions, a

C++26 Equality Linter

A new package that automates equality checks in C++ code by leveraging the upcoming reflection capabilities in C++26. This tool allows developers to input C++ code snippets or class definitions, and the package will use llmatch-messages to parse and analyze the code, ensuring that equality operators (like ==, !=) are correctly implemented and consistent with the class's structure.

Features

• Automated equality checks for C++ code
• Leverages C++26 reflection capabilities
• Provides structured feedback on potential issues
• Suggests corrections and verifies best practices
• Easy integration with existing C++ codebases

Installation

pip install cpp26-equality-linter

Usage

Basic Usage

from cpp26-equality-linter import cpp26_equality_linter

response = cpp26_equality_linter(user_input="your C++ code here")
print(response)

Using a Custom LLM

from langchain_openai import ChatOpenAI
from cpp26-equality-linter import cpp26_equality_linter

llm = ChatOpenAI()
response = cpp26_equality_linter(user_input="your C++ code here", llm=llm)
print(response)

Using LLM7 with API Key

from cpp26-equality-linter import cpp26_equality_linter

response = cpp26_equality_linter(user_input="your C++ code here", api_key="your_api_key")
print(response)

Parameters

• user_input (str): The user input text to process
• llm (Optional[BaseChatModel]): The langchain llm instance to use, if not provided the default ChatLLM7 will be used.
• api_key (Optional[str]): The api key for llm7, if not provided

Default LLM

The package uses ChatLLM7 from langchain_llm7 by default. You can safely pass your own llm instance if you want to use another LLM.

Example with OpenAI

from langchain_openai import ChatOpenAI
from cpp26-equality-linter import cpp26_equality_linter

llm = ChatOpenAI()
response = cpp26_equality_linter(user_input="your C++ code here", llm=llm)
print(response)

Example with Anthropic

from langchain_anthropic import ChatAnthropic
from cpp26-equality-linter import cpp26_equality_linter

llm = ChatAnthropic()
response = cpp26_equality_linter(user_input="your C++ code here", llm=llm)
print(response)

Example with Google

from langchain_google_genai import ChatGoogleGenerativeAI
from cpp26-equality-linter import cpp26_equality_linter

llm = ChatGoogleGenerativeAI()
response = cpp26_equality_linter(user_input="your C++ code here", llm=llm)
print(response)

Rate Limits

The default rate limits for LLM7 free tier are sufficient for most use cases of this package. If you want higher rate limits for LLM7, you can pass your own api_key via environment variable LLM7_API_KEY or via passing it directly like:

from cpp26-equality-linter import cpp26_equality_linter

response = cpp26_equality_linter(user_input="your C++ code here", api_key="your_api_key")
print(response)

You can get a free api key by registering at LLM7.

Issues

If you encounter any issues or have suggestions, please open an issue on GitHub.

Author

Eugene Evstafev

• Email: [e-mail]
• GitHub: chigwell
• LinkedIn: Eugene Evstafev

License

This project is licensed under the MIT License - see the LICENSE file for details.