aquavena-sdk

v0.1.0 safe
3.0
Low Risk

SDK Python pour scraper les régimes alimentaires Aquavena (Nouvelle-Calédonie)

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal signs of potential risks with no evidence of malicious activities or obfuscation. It has a moderate metadata risk due to its novelty but does not indicate a supply-chain attack.

  • Low network, shell, obfuscation, and credential risks.
  • Moderate metadata risk due to limited activity history.
Per-check LLM notes
  • Network: The network call to p('/') is likely for API interaction, which is common for SDKs but should be reviewed for destination and purpose.
  • Shell: No shell execution patterns detected, indicating low risk.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating low risk of unauthorized access.
  • Metadata: The package is new with limited activity, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (4.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2703 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

  • 16 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in adriens/aquavena
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • p("/") self._client = httpx.Client( headers={**DEFAULT_HEADERS, **(headers or {})},
✓ 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "adriens" 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 aquavena-sdk 
Your task is to develop a fully-functional mini-application using the 'aquavena-sdk' Python package. This application will serve as a nutritional diet planner tailored specifically for users in New Caledonia, leveraging the dietary plans available on Aquavena's platform. Your application should allow users to explore different dietary plans, understand their nutritional values, and even create personalized meal plans based on their dietary preferences or restrictions.

Step-by-Step Guide:
1. **Setup**: Begin by setting up your development environment. Ensure you have Python installed along with the 'aquavena-sdk'. You may need to install it via pip if not already done.
2. **User Interface**: Develop a simple yet intuitive user interface where users can interact with the application. This could be a command-line interface (CLI) or a basic web application depending on your preference.
3. **Data Fetching**: Use the 'aquavena-sdk' to fetch dietary plans from the Aquavena platform. Understand how to authenticate and retrieve data using the SDK.
4. **Dietary Plan Exploration**: Implement functionality that allows users to browse through various dietary plans. Each plan should display key information such as type of diet, nutritional value, and any special notes.
5. **Nutritional Information**: For each dietary plan, provide detailed nutritional information including calorie count, macronutrient breakdown (carbohydrates, proteins, fats), and micronutrients (vitamins, minerals).
6. **Personalization**: Allow users to customize their meal plans based on specific dietary needs or preferences. Users should be able to select plans that suit their lifestyle or health goals.
7. **Output/Export**: Finally, enable users to export their personalized meal plans. This could be in the form of a downloadable PDF or a shareable link.

Suggested Features:
- Authentication and Authorization: Implement secure user authentication and authorization processes.
- User Profiles: Allow users to create profiles where they can save their favorite diets and track their progress.
- Search Functionality: Enable users to search for specific dietary plans based on keywords or criteria.
- Integration with External Tools: Consider integrating with tools like fitness trackers or nutrition apps for a more comprehensive experience.
- Mobile Compatibility: Ensure your application is accessible and functional on mobile devices.

The 'aquavena-sdk' plays a crucial role in fetching and processing the dietary plans from Aquavena. Familiarize yourself with its documentation to understand how to effectively utilize its features in your application.

💬 Discussion Feed

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