airwer

v0.2.1 safe
4.0
Medium Risk

Word Error Rate for Air Traffic Control

🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate and serves its intended purpose without any direct malicious activities. However, the metadata contains some red flags, such as an incomplete author profile and a potentially inactive account.

  • No network calls or shell executions detected.
  • Author lacks a complete profile and the account might be new or inactive.
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package's functionality requires external API interactions.
  • Shell: No shell executions detected, indicating the package does not execute system commands, which is generally safe.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The package shows some red flags such as an author with a missing name and a new or inactive account, but there are no clear signs of typosquatting or malicious intent.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 4 test file(s) found

  • 4 test file(s) detected (e.g. test_metrics.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (1118 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 29 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 21 commits in twangodev/airwer
  • 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: twango.dev>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 airwer 
Develop a Python-based mini-application called 'AirTrafficAssistant' that leverages the 'airwer' package to enhance communication accuracy in simulated air traffic control scenarios. Your task is to create a tool that can compare the original spoken instructions from an air traffic controller with the received message by the pilot, calculating the word error rate (WER) to assess the clarity and accuracy of the communication. This tool will help identify potential miscommunications and improve training protocols for both controllers and pilots.

Steps to develop the application:
1. Set up a basic Python environment with all necessary packages installed, including 'airwer'.
2. Create a function that takes two strings as input: one representing the original spoken message and another representing the received message.
3. Utilize the 'airwer' package to calculate the WER between these two messages and output a score indicating the similarity or difference.
4. Design a simple user interface where users can input the original and received messages, and see the calculated WER along with a brief analysis of any discrepancies.
5. Implement a feature that logs all comparisons made, storing them for future reference or analysis.
6. Enhance the application by adding a feature that suggests possible corrections for commonly confused words or phrases based on previous inputs and their corresponding WER scores.
7. Ensure your application is well-documented and easy to use, providing clear instructions for installation and operation.