AI Analysis
The package has no evident signs of obfuscation or credential harvesting, but its recent creation and lack of activity raise suspicion about potential malicious intent.
- Low obfuscation risk
- Low credential risk
- High metadata risk due to newness and minimal activity
Per-check LLM notes
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows signs of being newly created with minimal activity, raising concerns about potential malicious intent.
Package Quality Overall: Low (3.0/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (827 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Limited contributor diversity
2 unique contributor(s) across 6 commits in HeshamMoawad/asas-pyTwo distinct contributors found
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com>
All external links appear legitimate
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forksAll 6 commits happened within 24 hours
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Your task is to develop a fully-functional mini-application using the 'asas-py' Python package. This application will serve as a simple but robust client for interacting with a hypothetical online service that provides weather data. The app should allow users to query current weather conditions based on location and display the results in an easy-to-read format. Here are the steps and features you need to implement: 1. Set up a virtual environment and install 'asas-py'. Use 'asas-py' to define the API schema for your weather service client. Include endpoints for fetching current weather data by city name or coordinates. 2. Implement a function that takes user input for location (either city name or coordinates) and uses 'asas-py' to construct a request to the weather service. 3. Display the retrieved weather information in a human-readable format, including temperature, humidity, wind speed, and a brief description of the weather condition. 4. Add error handling to manage cases where the location provided does not return any data or if there's an issue connecting to the weather service. 5. Optionally, enhance the application by adding features such as caching responses to avoid redundant requests, displaying historical weather data, or allowing users to switch between Celsius and Fahrenheit for temperature readings. Use 'asas-py' throughout your development process to ensure your client is type-safe and elegantly structured. Explain how 'asas-py' simplifies the creation of the API client and enhances the reliability of your application.
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