PgsFile

v0.7.3 safe
2.0
Low Risk

This module streamlines Python package management, script execution, file handling, web scraping, and multimedia downloads. It supports LLM-based NLP tasks like OCR, tokenization, lemmatization, idiom extraction, POS tagging, NER, ATE, dependency parsing, MDD, WSD, LIWC, MIP analysis, text classification, and Chinese-English sentence alignment. Additionally, it generates word lists and data visualizations, making it a practical tool for data scraping and analysis—ideal for literary students and researchers.

⚠ Tarball exceeded 25 MB — source code analysis was limited to package metadata only.

🤖 AI Analysis

Final verdict: SAFE

The package shows very low risks across all checked categories. The only slight concern is the metadata risk due to the maintainer's apparent newness or inactivity, but this alone does not indicate malicious intent.

  • No network or shell risks detected
  • Low metadata risk
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 from command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has a verifiable academic affiliation but appears to be new or inactive on PyPI.

🔬 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: sufe.edu.cn

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository Petercusin/PgsFile appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Dr. Guisheng Pan is an instructor at Shanghai University of Finance and Economics (SUFE)." 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 PgsFile 
Create a comprehensive mini-app called 'LiteraryAnalyzer' that leverages the PgsFile Python package to analyze and visualize data from literary texts. The app should allow users to upload a text file or URL of a literary work, perform various natural language processing tasks, and generate insightful visualizations. Here’s a step-by-step guide on how to build this application:

1. **Setup**: Begin by installing the necessary packages including PgsFile. Ensure you have the latest version of Python installed.
2. **User Interface**: Design a simple yet effective user interface using a framework like Tkinter or Streamlit. The UI should allow users to upload a text file or enter a URL of a literary work.
3. **Text Processing**: Utilize PgsFile's capabilities to preprocess the uploaded text. This includes removing stop words, performing tokenization, and applying lemmatization to normalize the text.
4. **NLP Tasks**: Implement core NLP functionalities such as part-of-speech tagging, named entity recognition, sentiment analysis, and dependency parsing. Use these analyses to understand the structure and themes within the text.
5. **Visualization**: Generate visual representations of the text analysis results. For instance, create word clouds, frequency distributions of parts of speech, and graphs showing character interactions (if applicable).
6. **Advanced Analysis**: Incorporate more advanced features such as identifying idiomatic expressions, extracting key phrases, and performing machine learning-based text classification to categorize the text into predefined genres or styles.
7. **Export Options**: Allow users to export the analysis results and visualizations in formats like PDF, Excel, or as images.
8. **Testing and Deployment**: Test the application thoroughly to ensure all functionalities work as expected. Consider deploying the app online for wider accessibility.

Throughout the development process, make sure to leverage PgsFile's extensive suite of tools for efficient and accurate data processing and analysis. This will help in building a robust and insightful literary analysis tool.