athena-core

v1.0.0 safe
4.0
Medium Risk

Athena Core

🤖 AI Analysis

Final verdict: SAFE

The package athena-core v1.0.0 is assessed as having low risks for obfuscation and credential harvesting. While there are some signs of low activity, it does not strongly indicate malicious intent.

  • No obfuscation or credential harvesting patterns detected.
  • Low activity and effort observed in metadata.
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
  • Metadata: The package shows some signs of low activity and effort, but there are no clear indicators of malicious intent.

📦 Package Quality Overall: Low (2.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 11 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 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: gmail.com>

✓ 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

  • Only one version has ever been released — brand new package
  • Author "wangmu" 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 athena-core 
Create a Python-based mini-application named 'AthenaQueryTool' that leverages the 'athena-core' package to facilitate querying and data analysis on Amazon Athena datasets. This tool will enable users to connect to their Athena databases, execute SQL queries, visualize query results, and export data into various formats like CSV or JSON.

### Project Overview:
- **Name:** AthenaQueryTool
- **Objective:** Develop a user-friendly interface for querying Amazon Athena datasets.
- **Features:**
  - Connect to AWS Athena databases using credentials provided by the user.
  - Execute complex SQL queries directly from the app.
  - Display query results in a tabular format with pagination support.
  - Provide basic data visualization options (e.g., bar charts, line graphs).
  - Export query results to CSV or JSON files.
  - Save frequently used queries for future use.
- **Target Audience:** Data analysts, researchers, and developers working with large datasets stored in Amazon S3 and queried via Athena.

### Utilization of 'athena-core':
- Use 'athena-core' to establish a connection to the Athena database.
- Leverage the package's query execution capabilities to run user-defined SQL queries.
- Implement error handling and logging functionalities provided by 'athena-core'.
- Integrate 'athena-core' features to enhance data retrieval and manipulation processes within the application.

### Step-by-Step Guide:
1. **Setup Environment:** Install Python and necessary packages including 'athena-core'.
2. **Project Structure:** Organize the project into modules such as 'connection', 'query', 'visualization', and 'export'.
3. **Connection Module:** Implement functionality to securely connect to Athena using AWS credentials.
4. **Query Module:** Design an input form where users can write and submit SQL queries. Ensure proper validation and sanitization of inputs.
5. **Visualization Module:** Integrate a library (such as matplotlib or seaborn) for visualizing query results. Offer different types of plots based on the nature of the data.
6. **Export Module:** Allow users to export query results in CSV or JSON format. Provide options to customize file names and directories.
7. **User Interface:** Develop a simple GUI using Tkinter or a web interface with Flask/Django. Ensure the UI is intuitive and easy to navigate.
8. **Testing & Documentation:** Thoroughly test all features and document the project setup, usage instructions, and API documentation.

This project aims to streamline the process of querying and analyzing large datasets stored in Amazon Athena, making it accessible and efficient for a wide range of users.

💬 Discussion Feed

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