🤖 AI Analysis

Final verdict: SAFE

The package is assessed as safe with a moderate metadata risk due to the lack of maintainer information and a single package on PyPI.

No network calls detected
No shell execution patterns
No obfuscation patterns
No credential harvesting patterns
Moderate metadata risk

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires internet access to function properly.
Shell: No shell execution patterns detected, indicating the package does not execute external commands.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
Credentials: No credential harvesting patterns detected, indicating low risk of credential theft.
Metadata: The package shows some red flags, particularly the lack of maintainer information and a single package on PyPI, which may indicate a new or less active account.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 14 test file(s) found

14 test file(s) detected (e.g. create_benzene_test.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (3677 chars)

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

◈ Medium Type Annotations 5.0

Partial type annotation coverage

59 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: example.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with ahuora-compounds

Create a chemistry-focused educational tool called 'Compound Explorer' using the Python package 'ahuora-compounds'. This application will allow users to input chemical compound names or formulas and retrieve detailed information about them, such as molecular weight, boiling point, melting point, and other physical properties. Additionally, users should be able to compare two different compounds side by side and see a visual representation of their structures. Here’s a detailed breakdown of the project requirements:

1. **User Interface**: Develop a simple yet intuitive web interface using Flask or Django for the front-end. Ensure it includes fields for entering compound names/formulas and buttons for submitting queries.
2. **Data Retrieval**: Utilize the 'ahuora-compounds' package to fetch compound data based on user inputs. Ensure you handle errors gracefully if invalid entries are made.
3. **Property Display**: Once a valid compound is entered, display its key properties (molecular weight, boiling point, melting point, etc.) clearly on the page. Use charts or graphs where applicable to visualize these properties.
4. **Comparison Feature**: Implement a feature that allows users to enter a second compound and compare it with the first one. Highlight differences and similarities in properties visually.
5. **Structure Visualization**: Integrate a functionality that shows the structural formula of each compound. Consider using SVG or other vector graphics formats for clarity.
6. **Educational Content**: For each compound, provide a brief educational snippet explaining its common uses, hazards, and any interesting facts. This content can be static initially but should be easily updatable.
7. **Testing and Validation**: Ensure all functionalities work as expected by thoroughly testing your application with various compound entries. Pay special attention to edge cases and error handling.
8. **Documentation**: Write clear documentation detailing how to use the application, including setup instructions and examples of valid inputs.

This project aims to not only utilize the 'ahuora-compounds' package effectively but also create an engaging educational tool for students and enthusiasts alike.