astrodb-utils

v1.3.1 safe
2.0
Low Risk

astrodb_utils: scripts for interacting with the astrodb database

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal signs of malicious activity, with only slight concerns regarding network calls which may be necessary for its functionality.

  • Low network risk, possibly due to legitimate database interactions
  • No shell execution, obfuscation, or credential risks detected
Per-check LLM notes
  • Network: The observed network calls appear to be for checking URLs and fetching resources, which could be legitimate if the package is intended to interact with remote astronomical databases.
  • 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 author has only one package, suggesting a new or less active account, but no other suspicious elements were found.

📦 Package Quality Overall: Medium (7.0/10)

✦ High Test Suite 9.0

Test suite present — 10 test file(s) found

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

Well-documented package

  • Documentation URL: "Documentation" -> https://astrodb-utils.readthedocs.io/en/latest/
  • 1 documentation file(s) (e.g. conf.py)
  • Detailed PyPI description (883 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

  • 20 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 8 unique contributor(s) across 100 commits in astrodbtoolkit/astrodb_utils
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • _name}" try: r = requests.get(url) except requests.exceptions.ConnectTimeout as e:
  • t: request_response = requests.head(spectrum) status_code = request_response.status_code
  • """ request_response = requests.head(url, timeout=60) status_code = request_response.status_c
✓ 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: umd.edu>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository astrodbtoolkit/astrodb_utils appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Kelle Cruz, David Rodriguez" 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 astrodb-utils 
Your task is to develop a Python-based mini-application called 'AstroQuery' which will serve as a user-friendly interface to interact with astronomical databases using the 'astrodb-utils' package. This application will allow users to query specific astronomical objects, retrieve relevant data, and visualize the results in a comprehensible format. Here's a detailed breakdown of the steps and features you'll need to implement:

1. **Setup**: Begin by installing the 'astrodb-utils' package and any other necessary Python libraries such as pandas for data manipulation and matplotlib for visualization.
2. **User Interface**: Design a simple command-line interface (CLI) where users can input queries about astronomical objects. Ensure the CLI provides clear instructions and accepts inputs like object name, type of data requested (e.g., spectral information, position, etc.), and desired output format (text, graph).
3. **Data Retrieval**: Utilize the 'astrodb-utils' package to connect to the astrodb database and retrieve the requested data based on user inputs. Implement error handling to manage cases where the queried object does not exist in the database.
4. **Data Processing**: Use pandas to clean and process the retrieved data, ensuring it's in a suitable format for analysis and visualization. This might include filtering out irrelevant columns, converting units, or calculating derived quantities.
5. **Visualization**: Develop functions within your application to visualize the processed data. For instance, if the user requests spectral data, generate a plot showing the spectrum. If positional data is requested, create a sky map showing the location of the object.
6. **Output**: Allow users to choose how they want the output presented - either directly through the CLI or saved to a file (CSV, PNG). If saving to a file, ensure the filename includes key information about the query (e.g., object name, date).
7. **Documentation & Testing**: Write comprehensive documentation detailing how to use the application, including examples of valid inputs and expected outputs. Additionally, write unit tests to verify that each component of the application works as intended.

By completing these steps, you'll have created a powerful tool for astronomers and astronomy enthusiasts alike, enabling them to easily access and understand complex astronomical data.

💬 Discussion Feed

Leave a comment

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