AI Analysis
Final verdict: SAFE
The package is deemed safe with minimal risks identified. The metadata risk due to non-HTTPS links is noted but lacks evidence of malicious activity.
- No network or shell execution risks detected
- Low metadata risk with non-HTTPS links but no signs of malintent
Per-check LLM notes
- Network: No network call patterns detected, which is normal for a package that does not require external API interactions.
- Shell: No shell execution patterns detected, which is expected for a standard library or utility package.
- Metadata: The presence of non-HTTPS links might indicate a potential risk, but there's no clear evidence of malicious intent or typosquatting.
Package Quality Overall: Low (3.8/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (29336 chars)
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low
Type Annotations
1.0
No type annotations detected
No type annotations, py.typed marker, or stub files detected
✦ High
Multiple Contributors
10.0
Active multi-contributor project
13 unique contributor(s) across 100 commits in Maillol/aiohttp-pydanticActive community — 5 or more distinct contributors
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: gmail.com>
Suspicious Page Links
score 8.0
Found 4 suspicious link(s) on the package page
Non-HTTPS external link: http://127.0.0.1:8080/article?with_comments=aNon-HTTPS external link: http://127.0.0.1:8080/article?with_comments=yesNon-HTTPS external link: http://127.0.0.1:8080/articleNon-HTTPS external link: http://127.0.0.1:8080/oas
Git Repository History
Repository Maillol/aiohttp-pydantic appears legitimate
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 aiohttp-pydantic
Develop a mini-application named 'Task Manager' using Python, which leverages the 'aiohttp-pydantic' package to handle and validate HTTP requests efficiently. This application will allow users to manage their tasks through a simple API interface, supporting operations such as adding new tasks, marking tasks as completed, and listing all tasks. The goal is to demonstrate how aiohttp-pydantic can simplify the process of validating request data against Pydantic models while handling asynchronous HTTP requests. ### Application Features: - **Add Task:** Users can add new tasks via a POST request, providing task details like title, description, and due date. - **Mark Task as Completed:** Users can mark a specific task as completed by sending a PUT request to the task's unique identifier. - **List Tasks:** Users can retrieve a list of all tasks via a GET request, optionally filtering by completion status. - **Delete Task:** Users can delete a task by sending a DELETE request to the task's unique identifier. ### Utilizing aiohttp-pydantic: 1. **Setup Project Structure:** Begin by setting up your project structure including necessary imports from aiohttp, aiohttp_pydantic, and pydantic. 2. **Define Models:** Use Pydantic to define models for the task data that will be validated during incoming requests. 3. **Create Handlers:** Implement handlers for each API endpoint using aiohttp_pydantic decorators to automatically validate incoming request bodies and query parameters against the defined Pydantic models. 4. **Run the Server:** Finally, run the aiohttp server and test the functionality using tools like curl or Postman. This project aims to showcase the ease and efficiency of using aiohttp-pydantic for building robust, type-safe, and easy-to-maintain APIs in Python.