skillfed

proces

text preprocess.

proces v0.1.7 284.1K downloads/30d#8,069 on PyPI5
Permissive license MIT License DORMANT released

What it is and what it does

Proces is a text preprocessing library focused on cleaning and normalizing text, particularly for Chinese language content. It provides a pipeline-based approach where you can apply transformations in sequence—such as removing whitespace, converting uppercase to lowercase, converting traditional Chinese characters to simplified, and converting full-width punctuation to half-width—or select individual transformations as needed. The library also includes utilities for masking sensitive information like phone numbers and addresses.

The package has no external runtime dependencies, making installation lightweight. However, it has been dormant since 2023-09-09, with no recent commits or active maintenance. It supports Python 3.6 through 3.9 and is positioned as a utility for developers working with Chinese text or building preprocessing pipelines that require basic text normalization steps.

Use it for:

  • Normalize mixed-case, mixed-width Chinese text before feeding it into NLP models or search systems.
  • Remove or mask personally identifiable information like phone numbers and addresses from user-generated text.
  • Clean whitespace and standardize punctuation in Chinese documents as a preprocessing step for text analysis.
  • Convert traditional Chinese characters to simplified form in bulk text processing workflows.
  • Build a text cleaning pipeline by composing individual transformation functions for domain-specific preprocessing.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Proces provides text preprocessing functions for cleaning and normalizing text, including whitespace handling, case conversion, traditional-to-simplified Chinese conversion, full-width to half-width character conversion, and sensitive information masking.

Yes, if you need lightweight Chinese text preprocessing with no external dependencies and can tolerate dormant maintenance. The library is small, permissively licensed, and handles common normalization tasks. No, if you require active maintenance, bug fixes, or support for edge cases—the last update was 2023-09-09. Consider it a stable utility for straightforward preprocessing rather than a foundation for production systems.

Install

proces on PyPI

pip

pip install proces

uv

uv add proces

poetry

poetry add proces

Installing proces

Before you install

Installation is straightforward with no runtime dependencies. The package is dormant—last updated 2023-09-09, over a year ago—so expect no active maintenance or bug fixes going forward.

License in practice

MIT License permits free use, modification, and distribution with minimal restrictions, making it safe to adopt from a licensing standpoint.

Quickstart

pip install proces

from proces import preprocess
result = preprocess("Today, 你 幹 什 麼 !")
# result: today,你干什么!

Requires Python 3.6 or later.

Verify before relying

  • Whether the package handles edge cases in Chinese character conversion reliably, given dormant maintenance status.
  • Performance characteristics on large text corpora or streaming input.
  • Completeness of the sensitive information masking (phone, address) against real-world formats.

Package facts

License MIT License (permissive)
Python support supports the current Python release (>=3.6)
Install friction low — pure-Python wheel
Runtime dependencies none
Maintenance dormant — 1,070 days since the last release
Last repo commit
First released
Downloads 284,077/month — #8,069 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: proces-0.1.7-py3-none-any.whl

License :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9

Tags

text preprocessingchinese text normalizationwhitespace handlingcharacter conversionsensitive data maskingtext cleaningunicode normalization
chinese-texttext-normalization

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