🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks associated with it, showing no signs of malicious activities or supply-chain attacks. However, its low activity and incomplete metadata suggest that it may not be well-maintained.

No network or shell risks detected
Incomplete metadata and low package activity

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution detected, indicating no direct system command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows low activity and lacks proper metadata, indicating potential low quality or maintenance efforts.

🔬 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

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author "Pooja" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with Topsis-Pooja-102303845

Create a decision-making support system using the Python package 'Topsis-Pooja-102303845'. This system will help users evaluate multiple alternatives based on several criteria using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. Here's a step-by-step guide to building your application:

1. **Project Setup**: Start by setting up a new Python environment. Install necessary packages including 'pandas' for data manipulation and 'Topsis-Pooja-102303845' for TOPSIS calculations.

2. **User Input Interface**: Develop a simple user interface where users can input their dataset. The dataset should include various alternatives (options) and criteria (factors) with associated weights for each criterion. Ensure the data is structured in a tabular format, typically a CSV file.

3. **Data Preprocessing**: Implement functions to preprocess the data. This includes normalizing the dataset and handling any missing values or inconsistencies in the data.

4. **TOPSIS Calculation**: Utilize the 'Topsis-Pooja-102303845' package to calculate the TOPSIS score for each alternative. Remember to define whether each criterion is a benefit or a cost type, as this affects how the scores are calculated.

5. **Ranking Alternatives**: Based on the TOPSIS scores, rank the alternatives from best to worst. Display these rankings back to the user in a clear and understandable format.

6. **Visualization**: To make the results more accessible, implement visualization tools such as bar charts or pie charts to visually represent the ranking of alternatives.

7. **Report Generation**: Finally, allow users to generate a report summarizing the analysis performed, including the raw data, preprocessed data, calculated TOPSIS scores, and the final ranking. This report should be exportable as a PDF or a Word document.

**Additional Features**:
- Include an option for users to customize the weight of each criterion.
- Provide real-time feedback during data entry to ensure data integrity.
- Implement a feature that suggests optimal solutions based on the highest TOPSIS score.
- Offer tutorials or guides on how to effectively use the tool and interpret the results.