AI Analysis
Final verdict: SAFE
The package shows minimal risks across all categories analyzed, with no indications of malicious activities. The metadata risk is slightly elevated due to the author's single package history, but this alone is insufficient to warrant suspicion.
- No network or shell risks detected
- Low metadata risk
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communication.
- Shell: No shell execution detected, indicating the package does not execute system commands, which is typical for most packages.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
- Credentials: No credential harvesting patterns detected, indicating secure handling of secrets.
- Metadata: The author has only one package, which may indicate a new or less active account, but no other red flags are present.
Package Quality Overall: Medium (5.4/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
7.0
Some documentation present
Documentation URL: "Documentation" -> https://gravitino.apache.org/docs/overviewDetailed PyPI description (8117 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Separate author ("Apache Software Foundation") and maintainer ("Apache Gravitino Community") listed
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
146 type-annotated function signatures detected in source
✦ High
Multiple Contributors
10.0
Active multi-contributor project
26 unique contributor(s) across 100 commits in apache/gravitinoActive 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: gravitino.apache.org
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository apache/gravitino appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Apache Software Foundation" 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 apache-gravitino
Your task is to develop a small, fully-functional mini-application that leverages the 'apache-gravitino' Python package to interact with the Apache Gravitino service. This application will serve as a simple yet powerful tool for managing and querying data stored within the Gravitino system. Here’s a detailed breakdown of the project requirements and steps to achieve it:
1. **Project Overview**: Create a command-line utility named 'GravQuery' that allows users to easily query, insert, update, and delete data from the Apache Gravitino database.
2. **Core Features**:
- **Query Data**: Users should be able to execute SELECT queries to retrieve specific records from the database.
- **Insert Data**: Provide functionality to insert new records into the database.
- **Update Data**: Allow users to update existing records based on certain criteria.
- **Delete Data**: Implement a feature to delete records from the database.
3. **Application Flow**:
- Initialize the application by establishing a connection to the Gravitino server using the 'apache-gravitino' client library.
- Prompt the user to input their desired action (query, insert, update, delete).
- Based on the user's choice, collect necessary parameters such as table name, column names, and values.
- Execute the corresponding operation via the 'apache-gravitino' API and display the results back to the user.
4. **Using 'apache-gravitino'**:
- Utilize the 'connect' method provided by the 'apache-gravitino' package to connect to the Gravitino server.
- Use the 'execute_query', 'insert_data', 'update_data', and 'delete_data' methods (or similar) to perform CRUD operations on the database.
- Handle exceptions and errors gracefully, providing meaningful feedback to the user when something goes wrong.
5. **Additional Features (Optional)**:
- Implement a help command ('help') that lists all available commands and their usage.
- Add support for multiple databases or tables within a single Gravitino instance.
- Integrate logging to track operations performed by the application.
6. **Testing**:
- Ensure each feature works as expected by testing with various data sets.
- Validate error handling mechanisms thoroughly.
7. **Documentation**:
- Write clear and concise documentation explaining how to install the application, its usage, and any dependencies.
- Include examples demonstrating how to use the different functionalities of your application.
By following these guidelines, you'll create a useful and efficient tool for interacting with Apache Gravitino databases directly from the command line.
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