AI Analysis
Final verdict: SAFE
The package Assertical is considered safe as it shows no signs of engaging in risky behaviors such as making network calls or executing shell commands. The metadata risk score is moderately high due to the maintainer's limited history and non-secure links.
- No network risk detected
- No shell execution risk detected
- Maintainer has only one package and includes non-secure links
Per-check LLM notes
- Network: No network calls suggest the package does not engage in external communications, which is typical for many utility packages.
- Shell: No shell execution detected indicates the package is not executing system commands, reducing the risk of it being used for malicious activities.
- Metadata: The maintainer has only one package, which could indicate a new or less active account. The presence of non-secure links may pose some risk.
Package Quality Overall: Medium (7.0/10)
✦ High
Test Suite
9.0
Test suite present — 1 test file(s) found
Test runner config found: pyproject.toml1 test file(s) detected (e.g. test_snapshot.py)
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (13148 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
◈ Medium
Type Annotations
7.0
Partial type annotation coverage
Type checker (mypy / pyright / pytype) referenced in project58 type-annotated function signatures detected in source
✦ High
Multiple Contributors
10.0
Active multi-contributor project
5 unique contributor(s) across 54 commits in bsgip/asserticalActive 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
No author email provided
Suspicious Page Links
score 6.0
Found 3 suspicious link(s) on the package page
Non-HTTPS external link: http://first.example.com/Non-HTTPS external link: http://second.example.com/Non-HTTPS external link: http://127.0.0.1:12345
Git Repository History
Repository bsgip/assertical appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Battery Storage and Grid Integration Program" 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 assertical
Create a small project that demonstrates the use of the 'assertical' library for writing unit and integration tests for a FastAPI application backed by SQLAlchemy and PostgreSQL. This project will serve as a practical example of how 'assertical' can simplify testing processes for developers working on such applications. The project should include the following components: 1. A simple FastAPI application that interacts with a PostgreSQL database through SQLAlchemy ORM. This application should have endpoints for creating, reading, updating, and deleting items from a 'tasks' table. 2. Integration of 'assertical' into your test suite. Utilize 'assertical' to write asynchronous tests that cover CRUD operations on the 'tasks' table. 3. Ensure that your tests verify the correct behavior of the API endpoints under various conditions, including edge cases like attempting to delete a non-existent task. 4. Implement additional features such as: - Logging of test results and any exceptions encountered during test execution. - Use of fixtures provided by 'assertical' to set up and tear down test environments efficiently. - Writing comprehensive documentation explaining how each test works and why it is necessary. 5. Showcase how 'assertical' can help manage different types of assertions and error handling within the context of testing FastAPI applications. By completing this project, you will gain hands-on experience with 'assertical', understand its benefits over traditional testing frameworks, and learn best practices for testing FastAPI applications.
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