pgsfile 0.7.5

PgsFile is an all-in-one Python toolkit for web scraping, file management, AI-powered text analysis, and data visualization, helping students and researchers collect, process, and analyze data with minimal code.

Purpose: This module is designed to make complex tasks accessible and convenient, even for beginners. By providing a unified set of tools, it simplifies the workflow for data collection, processing, and analysis. Whether you're scraping data from the web, cleaning text, or performing LLM-based NLP tasks, this module ensures you can focus on your research without getting bogged down by technical challenges.

Key Features:

1. Web Scraping: Easily scrape data from websites and download multimedia content.
2. Package Management: Install, uninstall, and manage Python packages with simple commands.
3. Data Retrieval: Extract data from various file formats like text, JSON, CSV, TSV, XLSX, XML, TMX, and HTML (both online and offline).
4. Data Storage: Write and append data to text files, Excel, JSON, TMX, and JSON lines.
5. File and Folder Processing: Manage file paths, create directories, move or copy files, convert CSV to JSON, and search for files with specific keywords.
6. Data Cleaning: Clean text, handle punctuation, remove stopwords, detect noisy text, convert Markdown strings into Python objects, and prepare data for analysis, utilizing valuable corpora and dictionaries such as CET-4/6 and TEM-8 vocabulary, BE21 and BNC-COCA word lists.
7. NLP: Perform OCR, word tokenization, lemmatization, idiom extraction, POS tagging, NER, dependency parsing, ATE, MDD, WSD, LIWC, MIP analysis, text classification, and Chinese-English sentence alignment using prepared LLM prompts.
8. Math Operations: Format numbers, convert decimals to percentages, and validate data.
9. Visualization: Process images (e.g., make white pixels transparent, resize images) and manage fonts for rendering text.

Author: Dr. Guisheng Pan (潘贵生) is an instructor at the School of Foreign Studies, Shanghai University of Finance and Economics (SUFE). Email: [e-mail] Homepage: https://sfs.sufe.edu.cn/bf/ef/c4221a245743/page.htm