atoti-server-directquery-clickhouse

v0.9.15 safe
3.0
Low Risk

Resources to use DirectQuery on ClickHouse

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks across all categories analyzed, with no indications of malicious behavior or supply-chain attacks.

  • No network calls detected.
  • Maintainer has only one package.
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 that the package does not execute system commands, which is typical unless command execution is part of its functionality.
  • 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 might indicate a new or less active account, but there are no other suspicious flags.

📦 Package Quality Overall: Low (3.4/10)

○ 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 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-server-directquery-clickhouse 
Create a real-time analytics dashboard that leverages the 'atoti-server-directquery-clickhouse' package to perform DirectQuery operations on a ClickHouse database. This dashboard will enable users to visualize and analyze large datasets stored in ClickHouse in near real-time, providing insights into data trends and patterns. Here are the steps and features you should include in your project:

1. **Setup**: Begin by setting up a ClickHouse database and populate it with sample data, such as financial transactions, IoT sensor readings, or web server logs.
2. **Integration**: Use the 'atoti-server-directquery-clickhouse' package to establish a connection between the ClickHouse database and your Python environment. Ensure that the setup allows for DirectQuery operations, which means that queries will be executed directly on the ClickHouse server without intermediate data transfer.
3. **Data Analysis**: Implement functions within your application to perform various types of data analysis, such as time-series analysis, trend detection, and anomaly detection. Leverage the power of ClickHouse for its high-performance query capabilities.
4. **Visualization**: Integrate a visualization library like Plotly or Matplotlib to create interactive charts and graphs that update in real-time based on user interactions and DirectQuery results from ClickHouse.
5. **User Interface**: Develop a simple but intuitive user interface using a framework like Streamlit or Flask. This UI should allow users to select different datasets, choose analysis types, and view the resulting visualizations.
6. **Custom Queries**: Provide an option for advanced users to input custom SQL queries directly into the application. These queries should also be executed through the 'atoti-server-directquery-clickhouse' package, ensuring that they run efficiently on ClickHouse.
7. **Real-Time Updates**: Ensure that the dashboard updates in real-time as new data is added to the ClickHouse database. This feature will showcase the efficiency of DirectQuery in handling streaming data.
8. **Documentation**: Include comprehensive documentation that explains how each part of the application works, especially focusing on how 'atoti-server-directquery-clickhouse' facilitates DirectQuery operations and enhances performance.

This project not only showcases the capabilities of the 'atoti-server-directquery-clickhouse' package but also demonstrates practical applications in real-time data analytics and visualization.

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