langcompare
A Python package that helps developers quickly compare programming languages (Java, JavaScript, Python, Go) for a given task or context. It analyzes your requirements and provides structured comparisons highlighting key differences, strengths, and recommendations among the languages.
🚀 Features
- Compare multiple languages (Java, JavaScript, Python, Go) for any development scenario
- Get structured, actionable insights without manual research
- Customizable LLM integration (supports OpenAI, Anthropic, Google, etc.)
- Simple API with sensible defaults
📦 Installation
pip install langcompare
🔧 Usage
Basic Usage (uses default LLM7)
from langcompare import langcompare
response = langcompare(
user_input="I need to build a real-time chat application. What are the key differences between JavaScript and Python?"
)
print(response)
Custom LLM Integration
Using OpenAI
from langchain_openai import ChatOpenAI
from langcompare import langcompare
llm = ChatOpenAI()
response = langcompare(
user_input="Which language is better for microservices?",
llm=llm
)
Using Anthropic
from langchain_anthropic import ChatAnthropic
from langcompare import langcompare
llm = ChatAnthropic()
response = langcompare(
user_input="What are the performance characteristics of Go vs Python?",
llm=llm
)
Using Google Generative AI
from langchain_google_genai import ChatGoogleGenerativeAI
from langcompare import langcompare
llm = ChatGoogleGenerativeAI()
response = langcompare(
user_input="Which language has better concurrency support?",
llm=llm
)
🔑 API Key Configuration
The package uses LLM7 as the default LLM provider. You can configure it in two ways:
- Environment Variable (recommended for security):
export LLM7_API_KEY="your_api_key_here"
- Direct Parameter:
from langcompare import langcompare
response = langcompare(
user_input="Compare Python and Java for backend services",
api_key="your_api_key_here"
)
Get a free API key at LLM7 Token Generator.
📊 Response Format
The function returns a list of structured comparison points, typically including:
- Language-specific strengths
- Key differences for the given use case
- Recommendations based on requirements
- Performance considerations
- Ecosystem support
📜 Parameters
| Parameter | Type | Description | Default |
|---|---|---|---|
user_input |
str |
Your development scenario or requirement description | Required |
api_key |
Optional[str] |
Your LLM7 API key (if not using environment variable) | None (uses LLM7_API_KEY env var) |
llm |
Optional[BaseChatModel] |
Custom LLM instance (e.g., OpenAI, Anthropic) | None (uses default LLM7) |
🔄 Rate Limits
The default LLM7 free tier provides sufficient rate limits for most use cases. For higher limits, use your own API key or consider upgrading your LLM7 plan.
📝 Issues & Support
For issues or feature requests, please open a GitHub issue at: https://github.com/chigwell/langcompare/issues
👤 Author
- Eugene Evstafev (@chigwell)
- Email: hi@eugene.plus
📄 License
MIT License
Metadata
Release files for langcompare 2025.12.21132232
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