A Python library that analyzes code for ecological impact
Project description
Eco-Code Analyzer
Eco-Code Analyzer is a Python library that analyzes code for its ecological impact and provides a score based on various factors such as energy efficiency, resource usage, and code optimizations.
Installation
You can install Eco-Code Analyzer using pip:
pip install eco-code-analyzer
For development, you can install additional dependencies:
pip install eco-code-analyzer[dev]
Features
- Analyzes Python code for ecological impact
- Provides an overall eco-score
- Breaks down the analysis into categories:
- Energy Efficiency
- Resource Usage
- Code Optimizations
- Custom Rules
- Analyzes entire projects or directories
- Generates detailed reports
- Integrates with Git to analyze code history
- Supports custom configuration
- Extensible rule system for adding new ecological impact checks
Usage
As a library
from eco_code_analyzer import analyze_code, get_eco_score, get_improvement_suggestions
code = """
def example_function():
result = []
for i in range(100):
result.append(i * 2)
return result
"""
analysis_result = analyze_code(code)
eco_score = get_eco_score(analysis_result)
suggestions = get_improvement_suggestions(analysis_result)
print(f"Eco-Score: {eco_score}")
print("Improvement Suggestions:")
for suggestion in suggestions:
print(f"- {suggestion}")
As a command-line tool
Analyze a single file:
eco-code-analyzer path/to/your/python_file.py
Analyze a project directory:
eco-code-analyzer path/to/your/project/directory -v
Generate a detailed report:
eco-code-analyzer path/to/your/project/directory -o report.json
Analyze Git history:
eco-code-analyzer path/to/your/project/directory -g -n 10
Use a custom configuration:
eco-code-analyzer path/to/your/project/directory -c config.json
Configuration
You can customize the behavior of the Eco-Code Analyzer by providing a JSON configuration file. Here's an example:
{
"weights": {
"energy_efficiency": 0.4,
"resource_usage": 0.3,
"code_optimizations": 0.2,
"custom_rules": 0.1
},
"thresholds": {
"eco_score": 0.7,
"category_score": 0.6
}
}
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License.
Project details
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