atoti-client-directquery-clickhouse

v0.9.15 safe
2.0
Low Risk

Code to use DirectQuery on ClickHouse

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks across all categories with no signs of malicious behavior. The only elevated concern is the metadata risk due to the maintainer having just one package.

  • No network calls detected
  • Single package from maintainer
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution detected, indicating no direct system command execution within the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package, suggesting a potentially new or less active account, but no other red flags are present.

📦 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-directquery-clickhouse 
Your task is to create a real-time data analysis tool using the 'atoti-client-directquery-clickhouse' package in Python. This tool will allow users to interactively query large datasets stored in ClickHouse databases, providing immediate insights and visualizations. Here’s a step-by-step guide to building this mini-application:

1. **Setup Environment**: Ensure you have Python installed and set up a virtual environment. Install necessary packages including 'atoti-client-directquery-clickhouse', pandas, and any visualization libraries like matplotlib or seaborn.
2. **Database Connection**: Use 'atoti-client-directquery-clickhouse' to establish a connection to your ClickHouse database. Configure it to handle direct queries efficiently without loading all data into memory.
3. **Data Exploration**: Design a simple GUI (using libraries such as tkinter or PyQt) where users can input SQL-like queries directly. Implement a feature to preview the first few rows of the dataset they intend to analyze.
4. **Query Execution & Visualization**: When a user submits a query, execute it using 'atoti-client-directquery-clickhouse'. Display the results in a tabular format and provide options to visualize the data through graphs and charts.
5. **Advanced Features**: Consider adding advanced features such as saving frequently used queries, exporting results to CSV, and allowing users to compare different datasets or time periods.
6. **Testing & Documentation**: Thoroughly test the application to ensure it handles various types of queries and data sizes effectively. Document the setup process and how to use each feature.

This project will showcase your ability to work with big data tools and libraries while providing a practical solution for real-time data exploration.

💬 Discussion Feed

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