AI Analysis
The package exhibits some suspicious characteristics, notably the lack of author information and a GitHub repository, which raises concerns about its legitimacy and maintainability.
- Lack of author information
- Absence of a GitHub repository
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution detected, indicating no direct system command execution.
- Obfuscation: The use of base64 decoding on a codec header suggests possible obfuscation but could also be part of normal audio processing.
- Credentials: No clear patterns indicative of credential harvesting were found.
- Metadata: The package shows some red flags, including the absence of an author's name and the lack of a GitHub repository, which could indicate potential issues.
Package Quality Overall: Low (3.8/10)
Partial test coverage signals detected
Test runner config found: pyproject.toml
Some documentation present
Brief PyPI description (661 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
353 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
No suspicious network call patterns found
Found 1 obfuscation pattern(s)
codec_header_bytes = base64.b64decode(player.codec_header) self._configure_audio_output(
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: openhomefoundation.org>
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
2 maintainer concern(s) found
Author 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
Create a fully-functional asynchronous file transfer mini-application using the 'aiosendspin' Python package. This application will serve as a simple yet powerful tool for transferring files between two endpoints over the network, leveraging the Sendspin Protocol for efficient and reliable data transmission. The application should include the following core functionalities and features: 1. **User Interface**: Develop a user-friendly command-line interface (CLI) that allows users to initiate file transfers by specifying source and destination paths. 2. **File Selection**: Users should be able to select which files or directories they wish to send. 3. **Transfer Status**: Provide real-time feedback on the status of the file transfer, including progress percentage and estimated time remaining. 4. **Error Handling**: Implement robust error handling to manage issues such as network disruptions, file access errors, and protocol violations. 5. **Security Features**: Incorporate basic security measures like encryption during transit to protect file contents. 6. **Asynchronous Processing**: Utilize the 'aiosendspin' package to handle file transfers asynchronously, allowing multiple transfers to occur simultaneously without blocking the main thread. 7. **Customizable Settings**: Allow users to configure settings such as retry policies, timeout durations, and buffer sizes. 8. **Logging Mechanism**: Implement logging to record all activities related to file transfers, including start times, end times, and any encountered errors. **How 'aiosendspin' is Utilized**: The 'aiosendspin' package will be the backbone of your application's networking capabilities. It will be responsible for initiating connections, sending and receiving file data, and managing the overall flow of the Sendspin Protocol. Your task includes integrating 'aiosendspin' into your application architecture to ensure seamless file transfer operations while adhering to the protocol specifications.