Text Normalizer

😫 The Pain Point

Your data has inconsistent text: ” JOHN SMITH ” vs “john smith” vs “John Smith”. Before processing, you need everything standardized.

🚀 Agentic Solution

A Text Cleaner that applies consistent formatting rules.

Key Features:

• Whitespace Cleanup: Remove extra spaces, trim edges.
• Case Normalization: UPPER, lower, Title Case.
• Unicode Normalization: NFC/NFD forms for Vietnamese.

⚔️ Phase 1: Commander (Quick Fix)

For quick normalization.

Prompt:

“I have an Excel data.xlsx with text columns. Write a Python script to:

1. Trim: Remove leading/trailing whitespace.
2. Collapse: Multiple spaces to single space.
3. Unicode: Normalize to NFC form.
4. Case: Apply Title Case to ‘Name’ column.
5. Output: Save as data_normalized.xlsx.

Print sample before/after.”

Result: Clean, consistent text data.

🏗️ Phase 2: Architect (Permanent Tool)

Engineering Prompt:

**Role:** Python Tool Developer
**Task:** Create a "Text Normalizer".

**Requirements:**
1.  **GUI:**
    *   Select Excel file.
    *   Column selector (apply to which columns).
    *   Rule checkboxes: Trim, Collapse spaces, Case (dropdown).
    *   Unicode form dropdown (NFC, NFD).
    *   Preview changes.

2.  **Logic:**
    *   String manipulation with regex.
    *   unicodedata.normalize().
    *   Handle None/NaN values.

3.  **Deliverables:**
    *   `text_normalizer.py`
    *   `run.bat`, `run.sh`
    *   `requirements.txt`

🧠 Prompt Decoding

• Unicode Normalization: Vietnamese characters can be composed differently. NFC is preferred for web.

🛠️ Instructions

1. Copy Prompt → Run.