async-geotiff

v0.5.1 safe
3.0
Low Risk

Async GeoTIFF reader for Python

🤖 AI Analysis

Final verdict: SAFE

The package async-geotiff v0.5.1 presents minimal risks across all assessed categories, with no indications of malicious activity or supply-chain attacks.

  • Low risk scores in all categories.
  • No network calls, shell executions, or credential harvesting attempts detected.
Per-check LLM notes
  • Network: No network calls detected, which is normal for a package focused on handling GeoTIFF files asynchronously.
  • Shell: No shell execution patterns detected, aligning with the expected behavior of a library designed for file processing.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, suggesting the package is not attempting to steal secrets.
  • Metadata: The maintainer has only one package, which might indicate a new or less active user, but no other red flags are present.

📦 Package Quality Overall: Medium (5.4/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://developmentseed.github.io/async-geotiff/
  • Detailed PyPI description (5383 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 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 46 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 6 unique contributor(s) across 100 commits in developmentseed/async-geotiff
  • Active community — 5 or more distinct 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: developmentseed.org>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository developmentseed/async-geotiff appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Kyle Barron" 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 async-geotiff 
Create a geospatial data analysis tool using Python that leverages the 'async-geotiff' library for handling large GeoTIFF files asynchronously. This tool will enable users to upload a GeoTIFF file, select specific geographic areas of interest, and perform basic statistical analyses on the data within those regions. Additionally, it should support exporting the results into a CSV file for further processing or reporting purposes.

### Steps:
1. **Setup**: Initialize your Python environment with necessary libraries including 'async-geotiff', 'pandas', and 'matplotlib'.
2. **User Interface**: Develop a simple command-line interface where users can interact with the tool.
3. **File Upload**: Implement functionality allowing users to upload GeoTIFF files. Ensure the tool can handle multiple files at once.
4. **Geographic Selection**: Allow users to specify geographic boundaries for their analysis. This could involve selecting coordinates or uploading shapefiles.
5. **Data Extraction**: Use 'async-geotiff' to asynchronously read and extract relevant data from the specified geographic areas in the uploaded GeoTIFF files.
6. **Statistical Analysis**: Perform basic statistical operations such as mean, median, mode, and standard deviation on the extracted data.
7. **Visualization**: Provide options to visualize the data using plots or maps. Users should be able to choose between different types of visualizations like heatmaps, contour plots, etc.
8. **Export Results**: Enable users to export the analyzed data and any visualizations into a CSV file format.
9. **Documentation**: Write comprehensive documentation explaining how to use the tool, including setup instructions and examples.

### Features:
- Asynchronous reading of large GeoTIFF files to improve performance.
- Support for multiple file formats and geographic selections.
- Basic statistical analysis tools integrated into the application.
- Visualization capabilities with user-selectable output formats.
- Export functionalities to allow for further analysis or reporting.

### Utilizing 'async-geotiff':
- Use 'async-geotiff' to efficiently read GeoTIFF files without blocking the main thread, thus enabling the application to handle large datasets more effectively.
- Leverage the library's ability to work with geographic information systems (GIS) data directly, streamlining the process of extracting and analyzing spatial data.

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