alpharaw

v0.6.0 suspicious
4.0
Medium Risk

An open-source Python package to unify raw MS data access and storage.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal risk in terms of network and shell usage, but the incomplete maintainer information and potential inactivity raise concerns about its legitimacy.

  • Incomplete maintainer's author information
  • Potential inactivity of the 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.
  • Metadata: The maintainer's author information is incomplete and they appear to be new or inactive, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (3.4/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (11895 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in MannLabs/alpharaw
  • 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository MannLabs/alpharaw appears legitimate

⚠ 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 alpharaw 
Create a mini-application called 'MSDataExplorer' that leverages the 'alpharaw' package to facilitate the exploration, analysis, and visualization of raw Mass Spectrometry (MS) data. This tool should allow users to upload their raw MS data files, view basic information about the data, perform simple analyses, and visualize the results. Here are the steps and features you need to implement:

1. **Setup**: Ensure that the user has installed the necessary packages including 'alpharaw'. Provide instructions on how to install 'alpharaw' if it's not already installed.
2. **Data Upload**: Allow users to upload one or multiple raw MS data files. Use 'alpharaw' to load these files into your application efficiently.
3. **Data Overview**: Display basic metadata about the uploaded files such as file name, size, acquisition date, and experiment type. Use 'alpharaw' functionalities to extract this information.
4. **Basic Analysis**: Implement functions to perform basic analysis on the MS data, such as peak detection, retention time calculation, and intensity normalization. Again, utilize 'alpharaw' for its robust data handling capabilities.
5. **Visualization**: Develop a feature where users can visualize the MS data through customizable plots like total ion chromatograms (TIC), extracted ion chromatograms (EIC), and mass spectra. Ensure that users can interact with these plots to explore different aspects of the data.
6. **Export Options**: Provide options for users to export the analyzed data and visualizations in common formats such as CSV, PNG, or PDF.
7. **User Interface**: Design a clean and intuitive graphical user interface (GUI) using a Python library like PyQt or Tkinter. Make sure the UI reflects the functionality of each step clearly.
8. **Documentation**: Write comprehensive documentation explaining how to use 'MSDataExplorer', including installation instructions, usage examples, and explanations of the output.

By completing this project, you will create a powerful yet accessible tool for researchers and analysts working with MS data, demonstrating the versatility and efficiency of the 'alpharaw' package.

💬 Discussion Feed

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