audformat

v1.4.2 safe
2.0
Low Risk

Python implementation of audformat

🤖 AI Analysis

Final verdict: SAFE

The package audformat v1.4.2 presents minimal risks across all evaluated categories, indicating a low likelihood of malicious activity. The only slightly elevated risk is in metadata, due to the maintainer having only one package.

  • No network calls detected
  • No shell executions
  • No obfuscation patterns
  • Low credential risk
  • Single package from maintainer
Per-check LLM notes
  • Network: No network calls detected, which is normal for most utility packages that do not require internet access.
  • Shell: No shell executions detected, indicating the package does not perform any system-level operations.
  • 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 may indicate a new or less active account but does not necessarily imply malicious intent.

📦 Package Quality Overall: Medium (7.0/10)

✦ High Test Suite 9.0

Test suite present — 14 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 14 test file(s) detected (e.g. conftest.py)
✦ High Documentation 9.0

Well-documented package

  • Documentation URL: "documentation" -> https://audeering.github.io/audformat/
  • 2 documentation file(s) (e.g. conf.py)
  • Detailed PyPI description (1925 chars)
○ 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

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

Active multi-contributor project

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

🔬 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: audeering.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository audeering/audformat appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Johannes Wagner, BahaEddine Abrougui" 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 audformat 
Create a mini-application named 'AudioMetadataManager' that leverages the 'audformat' Python package to manage and analyze audio metadata efficiently. This application will serve as a tool for researchers and developers who need to handle large datasets of audio files, providing them with an easy-to-use interface for extracting, viewing, and manipulating metadata information.

**Step 1: Setup Environment**
- Ensure you have Python installed on your system.
- Install necessary packages including 'audformat', 'pandas', and 'numpy'.

**Step 2: Define Core Features**
- **Data Import**: Allow users to import multiple audio files from a specified directory. Use 'audformat' to read and store metadata associated with these files.
- **Metadata Extraction**: Implement functionality to extract specific types of metadata (e.g., file duration, bit rate, sampling frequency) using 'audformat'.
- **Search Functionality**: Enable searching for audio files based on metadata criteria such as file format, duration range, or sampling frequency.
- **Data Visualization**: Provide visual representations of metadata statistics (e.g., histogram of file durations).
- **Export Options**: Offer the ability to export extracted metadata into different formats like CSV or Excel for further analysis.

**Step 3: Utilizing 'audformat' Package**
- Use 'audformat.Table' to store and manipulate metadata efficiently.
- Leverage 'audformat.FileSet' for managing collections of audio files and their associated metadata.
- Implement 'audformat.Table.read()' and 'audformat.Table.write()' methods for importing/exporting metadata.

**Step 4: User Interface Design**
- Develop a simple yet effective GUI using PyQt5 or Tkinter, allowing users to interact with the application through a graphical interface.
- Ensure the GUI is intuitive, with clear labels and buttons for each feature.

**Step 5: Testing & Documentation**
- Test the application thoroughly to ensure all features work as expected.
- Document the code and provide a user manual explaining how to use each feature effectively.

This project not only showcases the capabilities of 'audformat' but also provides a practical tool for anyone dealing with large volumes of audio data.

💬 Discussion Feed

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