AI Analysis
Final verdict: SAFE
The package DSLExamples v0.1.1 is considered safe as it does not exhibit any signs of obfuscation or credential harvesting, and its structure aligns well with similar packages in other languages.
- No obfuscation detected
- No credential harvesting detected
Per-check LLM notes
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
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
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 6.0
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with DSLExamples
Create a command-line utility named 'DSLTranslator' using Python that leverages the 'DSLExamples' package to translate domain-specific language (DSL) commands into executable scripts. This utility will serve as a powerful tool for developers working with complex systems where different components communicate through specific DSLs. Your task includes the following steps: 1. **Setup**: Initialize your Python environment with all necessary packages, including 'DSLExamples'. Ensure you have a virtual environment set up for this project. 2. **Design**: Sketch out the architecture of your utility. Consider how users will input their DSL commands, how these commands will be parsed, and what kind of output formats (e.g., shell scripts, Python scripts) the utility will generate. 3. **Implementation**: - **Command Parsing**: Implement a robust parser that can interpret various DSL commands based on predefined rules from the 'DSLExamples' package. - **Translation Logic**: Utilize the 'DSLExamples' package to map these parsed commands into executable code snippets. This involves understanding the workflows provided by 'DSLExamples' and applying them to create coherent scripts. - **Output Generation**: Develop functionalities to output the translated scripts in different formats (as mentioned above). Also, include options for users to customize the output format. 4. **Testing**: Thoroughly test your utility with a variety of DSL commands to ensure accuracy and reliability. Include both positive tests (valid inputs) and negative tests (invalid or unexpected inputs). 5. **Documentation**: Write comprehensive documentation explaining how to install, use, and extend 'DSLTranslator'. Highlight the importance of the 'DSLExamples' package and how it enhances the utility's functionality. 6. **Deployment**: Prepare 'DSLTranslator' for deployment. Package it as a distributable Python package and upload it to PyPI or another suitable repository. 7. **User Interface**: Since this is a CLI tool, focus on making the interface user-friendly. Provide clear help messages and examples for common usage scenarios. Suggested Features: - Support for multiple DSLs by allowing users to select or define the DSL they are working with. - Customizable output templates to allow users to tailor the script generation process. - Integration with version control systems like Git to automatically commit changes to the generated scripts. - A logging mechanism to track translations and any errors encountered during the process. Remember to leverage the 'DSLExamples' package throughout your development process to ensure that your utility is not only functional but also adheres to best practices in DSL command translation and workflow management.