atoti-client-jdbc

v0.9.15 safe
3.0
Low Risk

Code to interact with databases through JDBC

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity and poses minimal risk. However, the maintainer's limited presence on PyPI is slightly concerning.

  • No network, shell, obfuscation, or credential risks detected.
  • Maintainer has only one package on PyPI.
Per-check LLM notes
  • Network: No network calls detected, which is normal for a JDBC client library.
  • Shell: No shell execution patterns detected, consistent with a benign library.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package, which could indicate a new or less active account.

📦 Package Quality Overall: Low (4.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.activeviam.com/products/atoti/python-sdk/0.9.15
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in atoti/atoti
  • Two distinct contributors found

🔬 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: activeviam.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository atoti/atoti appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "ActiveViam" 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 atoti-client-jdbc 
Create a data analysis tool called 'DBQueryMaster' using Python and the 'atoti-client-jdbc' package. This tool will allow users to connect to various databases via JDBC, execute SQL queries, and visualize the results in real-time. Here’s a detailed breakdown of the project steps and features:

1. **Project Setup**: Initialize your Python environment and install the necessary packages including 'atoti-client-jdbc'. Ensure you have the appropriate JDBC drivers for the databases you plan to connect to.

2. **Database Connection**: Implement a feature where users can input connection details such as database URL, username, and password. Use 'atoti-client-jdbc' to establish a connection to the specified database.

3. **Query Execution**: Allow users to write SQL queries directly into the application. Utilize 'atoti-client-jdbc' to execute these queries against the connected database and retrieve the results.

4. **Result Visualization**: Display the query results in a user-friendly format. Consider using libraries like Matplotlib or Plotly for visualizations.

5. **Interactive Features**: Add interactive elements such as sliders, dropdowns, or checkboxes that modify the SQL query dynamically based on user input. For example, users could select different date ranges or categories to filter the data.

6. **Error Handling**: Implement robust error handling to manage issues such as invalid queries, connection failures, or data type mismatches. Provide meaningful feedback to users when errors occur.

7. **Saving and Exporting**: Enable users to save their queries and export the results in formats like CSV, Excel, or PDF.

8. **User Interface**: Design a clean and intuitive UI using frameworks like PyQt or Streamlit. The interface should guide users through each step of connecting to a database, executing queries, and viewing results.

9. **Documentation**: Write comprehensive documentation explaining how to use DBQueryMaster, including setup instructions, API documentation, and examples.

By completing this project, you will create a powerful tool for anyone needing to analyze data stored in relational databases. The 'atoti-client-jdbc' package plays a crucial role in facilitating the interaction between Python and databases through JDBC connections.

💬 Discussion Feed

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