astro-pipeline

v1.0.0 suspicious
4.0
Medium Risk

CLI tool and library for CSV import pipelines

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in terms of network calls, shell execution, and obfuscation. However, the metadata risk score is moderately high due to the package being newly created with limited activity and only one published package from the author.

  • Metadata risk due to new package with limited activity
  • Single package from the author increases suspicion
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no immediate risk of command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package is newly created with limited activity and a single package from the author, which raises some suspicion but not enough to conclusively label it as malicious.

📦 Package Quality Overall: Medium (7.0/10)

✦ High Test Suite 9.0

Test suite present — 7 test file(s) found

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

Well-documented package

  • Documentation URL: "Documentation" -> https://astro-pipeline.readthedocs.io
  • 1 documentation file(s) (e.g. conf.py)
  • Detailed PyPI description (2031 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
  • 242 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 29 commits in starlincs/astro
  • Two distinct contributors found

🔬 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository starlincs/astro appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "Tom" 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 astro-pipeline 
Create a fully-functional mini-app called 'AstroDataAnalyzer' using the Python package 'astro-pipeline'. This app will allow astronomers to process and analyze astronomical data from CSV files efficiently. Here’s a step-by-step guide on what the application should do:

1. **Setup**: Initialize the project structure and install 'astro-pipeline' as a dependency.
2. **CSV Import**: Implement a feature to import CSV files containing astronomical data (e.g., star positions, galaxy distances). Use 'astro-pipeline' to streamline the import process, handling any potential errors or inconsistencies in the data.
3. **Data Processing**: Develop functions within 'astro-pipeline' to perform basic data cleaning tasks such as removing null values, correcting units, and normalizing data ranges.
4. **Analysis Tools**: Integrate analysis tools into 'astro-pipeline' that can calculate various statistical measures (mean, median, mode) and create visualizations (charts, graphs) of the imported data.
5. **Output Export**: Allow users to export processed and analyzed data back into CSV format or generate PDF reports summarizing key findings.
6. **User Interface**: Design a simple command-line interface (CLI) for interacting with 'AstroDataAnalyzer', making it easy for users to import data, view analysis results, and export outputs.
7. **Documentation**: Provide comprehensive documentation detailing how to use 'AstroDataAnalyzer', including examples of input CSV formats and expected output types.

Suggested Features:
- Support for multiple CSV file imports at once.
- Customizable data processing rules based on user input.
- Integration with common astronomical databases for real-time data validation.
- Advanced plotting options allowing users to customize charts and graphs.
- Error logging and recovery mechanisms to handle unexpected issues during data processing.

How 'astro-pipeline' is Utilized:
- As a CLI tool for importing CSV data directly into the application.
- As a library for performing data cleaning, normalization, and statistical analysis.
- For generating visualizations and exporting data back out in a usable format.

💬 Discussion Feed

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