template-processing

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# Template Processing: Placeholders and Conditionals

## Overview
When filling document templates, you often need to:
1. Replace placeholders like `{{PLACEHOLDER}}` with actual data
2. Handle conditional sections (show/hide content based on data)
3. Clean up formatting markers

This skill covers patterns for template processing in both text and document contexts.

## Placeholder Patterns

### Basic Placeholders
```
{{CANDIDATE_FULL_NAME}}
{{POSITION}}
{{START_DATE}}
{{BASE_SALARY}}
```

### Parsing from JSON
```python
import json

with open('employee_data.json', 'r') as f:
    data = json.load(f)

# Access placeholder values
name = data['CANDIDATE_FULL_NAME']
position = data['POSITION']
```

## Conditional Section Pattern

### Template Format
```
{{IF_CONDITION_NAME}}
  Content to show if CONDITION_NAME is "Yes"
{{END_IF_CONDITION_NAME}}
```

### Processing Conditionals

```python
def process_conditional_section(text, condition_key, condition_value):
    """Remove conditional markers based on condition value"""
    start_marker = f'{{{{IF_{condition_key}}}}}'
    end_marker = f'{{{{END_IF_{condition_key}}}}}'

    # Find section
    start_idx = text.find(start_marker)
    end_idx = text.find(end_marker)

    if start_idx == -1 or end_idx == -1:
        return text  # No conditional section found

    # Extract the content between markers
    before = text[:start_idx]
    content = text[start_idx + len(start_marker):end_idx]
    after = text[end_idx + len(end_marker):]

    if condition_value.lower() == 'yes':
        # Keep content, remove markers
        return before + content + after
    else:
        # Remove entire section
        return before + after
```

## Workflow for Template Processing

### Step 1: Load Data
```python
import json
from docx import Document

with open('employee_data.json', 'r') as f:
    data = json.load(f)

doc = Document('template.docx')
```

### Step 2: Replace Basic Placeholders
```python
def replace_placeholders(doc, data):
    """Replace all {{PLACEHOLDER}} with data values"""

    # Replace in paragraphs
    for para in doc.paragraphs:
        para_text = para.text
        for key, value in data.items():
            placeholder = f'{{{{{key}}}}}'
            para_text = para_text.replace(placeholder, str(value))

        # Update paragraph (handle text fragmentation)
        if para_text != para.text:
            for run in para.runs:
                run.text = ''
            para.text = para_text

    # Replace in tables
    for table in doc.tables:
        for row in table.rows:
            for cell in row.cells:
                cell_text = cell.text
                for key, value in data.items():
                    placeholder = f'{{{{{key}}}}}'
                    cell_text = cell_text.replace(placeholder, str(value))

                if cell_text != cell.text:
                    for para in cell.paragraphs:
                        for run in para.runs:
                            run.text = ''
                        para.text = cell_text
                    cell_text = cell.text  # Reset after first cell
```

### Step 3: Handle Conditionals
```python

From cxcscmu/SkillLearnBench, MIT.

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