audl

v0.0.19 safe
3.0
Low Risk

Unofficial audl api

🤖 AI Analysis

Final verdict: SAFE

The package audl v0.0.19 presents a low risk profile with no indications of malicious activities such as shell execution, obfuscation, or credential harvesting. The network calls appear to be benign, fetching JSON data.

  • Low risk scores across all categories except metadata
  • No signs of malicious intent or behavior
Per-check LLM notes
  • Network: The observed network calls are typical for fetching JSON data from URLs, likely part of the package's intended functionality.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting the package is not involved in secret or credential theft.
  • Metadata: The maintainer has only one package, indicating a new or less active account which could be suspicious but not necessarily malicious.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 8 test file(s) found

  • 8 test file(s) detected (e.g. test_alltimeplayerstats.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://htmlpreview.github.io/?https://github.com/yukikongju
  • Detailed PyPI description (4843 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 5 type-annotated function signatures (partial)
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in yukikongju/audl
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • elf._get_url() return requests.get(url).json() def get_game_metadata(self): """
  • t_url() results = requests.get(url).json() df = pd.DataFrame(results["stats"])
  • {year}" results = requests.get(url).json() df = pd.DataFrame(results["stats"])
  • try: response = requests.get(url) except Exception as e: raise Connec
  • (page_num) page = requests.get(url) results = page.json() players =
  • try: page = requests.get(url) except BaseException: print
✓ 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: outlook.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository yukikongju/audl appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "yukikongju" 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 audl 
Your task is to develop a fully functional command-line tool using Python that leverages the 'audl' package to provide users with detailed information about American Ultimate Disc League (AUDL) teams, players, and game statistics. This tool will allow users to interactively explore various aspects of AUDL data, making it easier for fans and analysts to access and understand the league's rich dataset.

Step-by-Step Guide:
1. Set up your development environment with Python and install the 'audl' package.
2. Create a main menu that allows users to choose between different functionalities such as viewing team details, player profiles, and game stats.
3. Implement a feature that fetches and displays detailed information about a specific team, including its roster, win-loss record, and recent games.
4. Develop a function that retrieves player statistics based on user input (e.g., name or team), showing metrics like points scored, assists, and turnovers.
5. Add functionality to show game results, including scores, attendance, and key plays from past matches.
6. Enhance the tool by allowing users to filter data based on seasons, specific dates, or types of games played.
7. Ensure the application handles errors gracefully, providing clear feedback to users when inputs are invalid or data cannot be fetched.
8. Finally, polish the user interface to make it intuitive and user-friendly, guiding users through each step of their interaction with the tool.

Suggested Features:
- User-friendly command-line interface with clear prompts and instructions.
- Ability to save frequently accessed data to a local file for quick reference.
- Integration of real-time updates for live game scores and highlights.
- Export options to share collected data in CSV or JSON formats.

How 'audl' Package is Utilized:
The 'audl' package provides the necessary API endpoints and functions to fetch all required data efficiently. Use its methods to query team rosters, player stats, and game outcomes directly from the AUDL database. Ensure that you handle the response objects correctly, parsing them into meaningful data structures that can be easily displayed or manipulated within your application.

💬 Discussion Feed

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