apb-duckdb-utils

v1.1.3 suspicious
4.0
Medium Risk

DuckDB utils

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of potential obfuscation through the use of os.getenv and eval, raising concerns about its intent and transparency. While there are no immediate indications of malicious activity, further scrutiny is warranted.

  • Potential obfuscation via os.getenv and eval
  • Single-package maintainer
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
  • Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
  • Obfuscation: The use of os.getenv and eval indicates potential obfuscation but could be for configuration flexibility.
  • Credentials: No direct evidence of credential harvesting is present, but caution is advised.
  • Metadata: The maintainer has only one package, which may indicate a new or less active account, but no other red flags were identified.

📦 Package Quality Overall: Medium (5.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_duckdb_utils.py)
◈ Medium Documentation 5.0

Some documentation present

  • Brief PyPI description (399 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Separate author ("Ernesto Arredondo Martínez") and maintainer ("Port de Barcelona") listed
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 21 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in portdebarcelona/PLANOL-generic_python_packages
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • use_ssl=eval(os.getenv('S3_USE_SSL')), region=os.getenv('S3_REGION'),
✓ 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

Repository portdebarcelona/PLANOL-generic_python_packages appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Ernesto Arredondo Martínez" 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 apb-duckdb-utils 
Create a data analysis mini-app called 'DuckDB Data Explorer' that leverages the 'apb-duckdb-utils' package to provide users with an intuitive interface for querying and analyzing datasets using DuckDB. This app will serve as a bridge between raw data files and the power of DuckDB's in-memory database capabilities, making it easy for users to explore their data without needing to write complex SQL queries.

### Features:
1. **Data Importation**: Users should be able to upload CSV or Parquet files directly into the app. The 'apb-duckdb-utils' package will handle the conversion and loading of these files into a DuckDB in-memory database.
2. **Query Interface**: Provide a simple query interface where users can input SQL-like commands to retrieve specific subsets of data from their uploaded dataset. Utilize the 'apb-duckdb-utils' package to execute these queries against the loaded data.
3. **Visualization Tools**: Integrate basic visualization tools that allow users to plot the results of their queries. For example, bar charts, line graphs, or scatter plots based on user selection.
4. **Interactive Exploration**: Enable interactive exploration of data through dynamic filtering options. Allow users to filter data based on specific columns or values, and see real-time updates in both the query results and visualizations.
5. **Export Functionality**: Offer an export function that allows users to save their query results or visualizations as CSV files or images.

### How 'apb-duckdb-utils' is Utilized:
- Use 'apb-duckdb-utils' to handle the connection setup to DuckDB.
- Leverage its functions for efficient data loading from CSV/Parquet files into the DuckDB in-memory database.
- Employ 'apb-duckdb-utils' for executing SQL queries and fetching results for display.
- Take advantage of any additional utilities provided by the package for enhancing performance or handling specific data types.

### Development Steps:
1. Set up a Python environment with necessary dependencies including 'apb-duckdb-utils', pandas, and a library for generating visualizations such as matplotlib or seaborn.
2. Design the front-end interface using a web framework like Streamlit or Flask to ensure ease of use and interactivity.
3. Implement the backend logic to connect to DuckDB using 'apb-duckdb-utils', load data, execute queries, and return results.
4. Develop the visualization components to dynamically generate plots based on query results.
5. Add functionality for exporting query results and visualizations.
6. Test the application thoroughly with various datasets to ensure robustness and reliability.
7. Deploy the application either locally or on a cloud platform for others to use.

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