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.
Project description
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:
- Web Scraping: Easily scrape data from websites and download multimedia content.
- Package Management: Install, uninstall, and manage Python packages with simple commands.
- Data Retrieval: Extract data from various file formats like text, JSON, CSV, TSV, XLSX, XML, TMX, and HTML (both online and offline).
- Data Storage: Write and append data to text files, Excel, JSON, TMX, and JSON lines.
- File and Folder Processing: Manage file paths, create directories, move or copy files, convert CSV to JSON, and search for files with specific keywords.
- 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 vocabulary, BE21 and BNC-COCA word lists.
- 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.
- Math Operations: Format numbers, convert decimals to percentages, and validate data.
- 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: panguisheng@sufe.edu.cn Homepage: https://sfs.sufe.edu.cn/bf/ef/c4221a245743/page.htm
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file pgsfile-0.6.6.tar.gz.
File metadata
- Download URL: pgsfile-0.6.6.tar.gz
- Upload date:
- Size: 42.4 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
be317443f8be006fd6b47ea46c2845850acc698eca5320a6ac51992d795dadb6
|
|
| MD5 |
c7e087646cf0680d1b30af094ce73b9b
|
|
| BLAKE2b-256 |
1bf245a1e8334207134898476200605fa0c7263c1bd1bfdb7237e930f6390192
|
File details
Details for the file pgsfile-0.6.6-py3-none-any.whl.
File metadata
- Download URL: pgsfile-0.6.6-py3-none-any.whl
- Upload date:
- Size: 44.1 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
43fa7e5c44602d0af737d1ddcf46bcd6d4f2da3f03d5edccceef9a6f31ca6d7e
|
|
| MD5 |
6cecca1f131765431aec3abbae567083
|
|
| BLAKE2b-256 |
94589eede62e21b876adf3fed1e9130403bdc5a70f9995dd5b649736eb56d052
|