AI Analysis
The package shows very low risk indicators with no network calls, shell executions, obfuscations, or credential risks. The only slight concern is the metadata risk due to the author having only one package.
- Low network and shell risk
- No obfuscation or credential harvesting detected
- Author has only one package
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 unexpected system command executions.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author has only one package, which might indicate a new or less active maintainer, but no other red flags were found.
Package Quality Overall: Low (3.0/10)
No test suite detected
No test files or test-runner configuration detected
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
Classifier: Typing :: Typed
Limited contributor diversity
2 unique contributor(s) across 100 commits in atoti/atotiTwo distinct contributors found
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: activeviam.com>
All external links appear legitimate
Repository atoti/atoti appears legitimate
1 maintainer concern(s) found
Author "ActiveViam" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a data analytics dashboard using Python and the 'atoti-server-aws' package, which is now deprecated in favor of 'atoti-server-storage-aws'. Since 'atoti-server-aws' is no longer recommended for new projects, let's imagine we're working on a legacy system where it's still in use. Your task is to develop a mini-application that retrieves and visualizes sales data stored in an Amazon S3 bucket. This application will serve as a proof-of-concept for integrating 'atoti-server-aws' into existing workflows and demonstrating its capabilities despite being deprecated. The application should perform the following steps: 1. Set up an AWS S3 bucket to store sample sales data in CSV format. 2. Use 'atoti-server-aws' to connect to the S3 bucket and load the sales data into an in-memory data store. 3. Implement basic data analysis functionalities such as calculating total sales, average sales per item, and identifying top-selling products. 4. Integrate a simple web interface using Flask to display the analyzed data in tabular form and charts (such as bar charts and pie charts). 5. Ensure the application can handle updates to the S3 bucket data in real-time or near real-time, reflecting changes in the dashboard automatically. Suggested Features: - Interactive filtering options for users to narrow down the displayed data based on product categories or time periods. - Support for exporting the current view of the dashboard as a PDF or CSV file. - Basic user authentication to restrict access to authorized personnel only. - Error handling mechanisms to manage issues like network failures or incorrect data formats gracefully. Note: Although 'atoti-server-aws' is deprecated, treat it as if it were the recommended package for this project. This exercise aims to showcase your understanding of integrating cloud storage solutions with data analytics tools and developing web applications with Python.
💬 Discussion Feed
No discussion yet. Be the first to share your thoughts!
Report Abuse / Security Issue