atoti-jupyterlab

v0.9.15 safe
3.0
Low Risk

Extension to create interactive Atoti widgets in JupyterLab

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity, with low risks across all categories checked. The metadata risk is slightly elevated due to the author having only one package, but this alone does not suggest a supply-chain attack.

  • No network or shell risks detected
  • Low metadata risk despite single-author status
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 injection or local privilege escalation.
  • 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 may indicate a new or less active account, but no other red flags are present.

📦 Package Quality Overall: Low (4.2/10)

○ Low Test Suite 1.0

No test suite detected

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

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.activeviam.com/products/atoti/python-sdk/0.9.15
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in atoti/atoti
  • 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

Email domain looks legitimate: activeviam.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository atoti/atoti appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "ActiveViam" 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 atoti-jupyterlab 
Create a financial data analysis dashboard using the 'atoti-jupyterlab' package in JupyterLab. This application should allow users to interactively explore stock market data over time, focusing on key metrics such as opening price, closing price, volume traded, and percentage change. The goal is to provide a user-friendly interface where analysts can quickly visualize trends, compare different stocks, and identify potential investment opportunities.

### Features:
- **Data Import**: Allow users to upload CSV files containing historical stock data.
- **Interactive Widgets**: Utilize 'atoti-jupyterlab' to create interactive widgets that enable users to filter and analyze data based on date ranges, specific stocks, and other relevant parameters.
- **Visualization Tools**: Implement visualizations like line charts for price trends, bar charts for volume, and candlestick charts for more detailed price movements.
- **Summary Statistics**: Display summary statistics such as average daily change, total volume traded, and peak-to-trough changes for selected periods.
- **Comparison Tool**: Enable side-by-side comparisons of up to three different stocks to help users identify relative performance and trends.
- **Alert System**: Integrate an alert system that notifies users when certain conditions are met, such as significant price drops or spikes.

### Steps:
1. Set up your JupyterLab environment and install the necessary packages including 'pandas', 'matplotlib', 'plotly', and 'atoti-jupyterlab'.
2. Design the user interface using 'atoti-jupyterlab' widgets to facilitate easy data input and manipulation.
3. Develop functions to load and preprocess stock data from uploaded CSV files.
4. Create dynamic visualizations linked to user interactions through the 'atoti-jupyterlab' widgets.
5. Implement the comparison tool allowing users to select multiple stocks and view comparative analysis.
6. Add a summary statistics section that updates based on user-selected filters.
7. Finally, integrate the alert system to notify users of significant market movements based on predefined criteria.

This project will not only demonstrate the power of 'atoti-jupyterlab' in creating interactive dashboards but also serve as a practical tool for financial analysts.

💬 Discussion Feed

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