axes-client

v0.1.0 suspicious
4.0
Medium Risk

Python client for the Axes data API

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits signs of low maintenance and questionable authorship, raising concerns about its reliability and potential for misuse.

  • Metadata risk is elevated due to low maintenance and suspicious author details.
  • No immediate malicious activities were detected, but the package warrants further scrutiny.
Per-check LLM notes
  • Network: The detected network call patterns suggest normal HTTP/HTTPS client operations, possibly for making API requests or communicating with a server.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of low maintenance and suspicious author details, but lacks clear indicators of malicious intent.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 4 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 4 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2870 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

  • 53 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • f socket_path: return httpx.Client( base_url=_UNIX_SOCKET_BASE_URL, hea
  • imeout, ) return httpx.Client( base_url=endpoint.rstrip("/"), # type: ignore[unio
✓ 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: axes.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 8.0

4 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with axes-client 
Create a mini-application named 'DataExplorer' that leverages the Axes data API through the Python package 'axes-client'. This application should serve as a user-friendly tool for exploring and visualizing datasets hosted on the Axes platform. Your task is to design and implement a feature-rich application that not only fetches data from the Axes API but also provides various methods for data manipulation and visualization. Here’s a detailed breakdown of the requirements:

1. **User Authentication**: Implement a login system where users can authenticate themselves using their Axes account credentials. Ensure that the authentication process securely handles user data.
2. **Dataset Exploration**: Allow users to browse available datasets hosted on the Axes platform. Provide filters to refine search results based on dataset categories, popularity, or date of publication.
3. **Data Visualization**: Integrate a simple yet effective visualization module that can generate basic plots such as line charts, bar graphs, and pie charts directly from the fetched data. Users should be able to select which columns to plot and customize chart colors and labels.
4. **Data Manipulation**: Offer functionalities like sorting, filtering, and aggregating data. For example, allow users to filter data based on specific conditions, sort data by column values, and calculate summary statistics.
5. **Export Functionality**: Enable users to export the processed data into common formats such as CSV, Excel, or JSON.
6. **Interactive Interface**: Design an intuitive and interactive user interface using a library like Streamlit or Dash. The interface should be responsive and user-friendly.
7. **Error Handling and Documentation**: Ensure your application gracefully handles errors and includes comprehensive documentation explaining how to install, configure, and use the application.

The 'axes-client' package will primarily be used for authenticating users, fetching datasets, and handling API requests to the Axes data API. Make sure to explore the full capabilities of 'axes-client' and integrate them effectively into your application to provide a seamless experience for data exploration and analysis.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!