Python Code Samples - Module 2: Basic Search Operations

This directory contains focused Python examples for basic search operations in Azure AI Search. Each file demonstrates a specific aspect of search functionality with clear, beginner-friendly code.

📁 Files Overview

Core Search Operations (Files 01-05)

1. 01_simple_text_search.py - Basic text search and result handling
2. 02_phrase_search.py - Exact phrase matching with quotes
3. 03_boolean_search.py - Boolean operators (AND, OR, NOT)
4. 04_wildcard_search.py - Pattern matching with wildcards
5. 05_field_search.py - Field-specific and multi-field searches

Advanced Features (Files 06-08)

1. 06_result_processing.py - Processing and formatting search results
2. 07_error_handling.py - Comprehensive error handling and validation
3. 08_search_patterns.py - Advanced search patterns and strategies

🎯 Complete Coverage Matrix

Topic	Python	C#	JavaScript	REST	Description
Simple Text Search	✅	✅	✅	✅	Basic keyword searching
Phrase Search	✅	✅	✅	✅	Exact phrase matching
Boolean Search	✅	✅	✅	✅	AND, OR, NOT operators
Wildcard Search	✅	✅	✅	✅	Pattern matching with *
Field Search	✅	✅	✅	✅	Field-specific searches
Result Processing	✅	✅	✅	✅	Formatting and analysis
Error Handling	✅	✅	✅	✅	Robust error management
Search Patterns	✅	✅	✅	✅	Advanced strategies

🚀 Getting Started

⚠️ CRITICAL FIRST STEP: Prerequisites Setup

Before running ANY Python examples, you MUST run the prerequisites setup:

# Navigate to the parent directory
cd ../

# Run the prerequisites setup script
python setup_prerequisites.py

What this does: - 🔌 Tests your Azure AI Search connection - 🏗️ Creates the handbook-samples index with comprehensive schema - 📄 Uploads 10 sample documents with rich content - 🧪 Tests all search operations to ensure everything works - 📋 Provides a summary of what's ready

Time Required: 5-10 minutes

Prerequisites

# Install required packages
pip install azure-search-documents python-dotenv

# Set environment variables
export AZURE_SEARCH_SERVICE_ENDPOINT="https://your-service.search.windows.net"
export AZURE_SEARCH_API_KEY="your-api-key"
export AZURE_SEARCH_INDEX_NAME="handbook-samples"

Quick Start

# 1. FIRST: Run prerequisites setup (from parent directory)
cd ../
python setup_prerequisites.py

# 2. THEN: Run Python examples
cd python/
python 01_simple_text_search.py
python 02_phrase_search.py
python 03_boolean_search.py
# ... and so on

📚 Learning Path

Beginner Path (Recommended Order)

1. Start Here: 01_simple_text_search.py - Learn basic search concepts
2. Precision: 02_phrase_search.py - Understand exact matching
3. Logic: 03_boolean_search.py - Combine terms with operators
4. Flexibility: 04_wildcard_search.py - Pattern matching techniques
5. Targeting: 05_field_search.py - Search specific fields
6. Processing: 06_result_processing.py - Handle and format results
7. Safety: 07_error_handling.py - Robust error handling
8. Strategies: 08_search_patterns.py - Advanced search patterns

Quick Reference

• Need basic search? → 01_simple_text_search.py
• Want exact phrases? → 02_phrase_search.py
• Combining terms? → 03_boolean_search.py
• Partial matching? → 04_wildcard_search.py
• Specific fields? → 05_field_search.py
• Format results? → 06_result_processing.py
• Handle errors? → 07_error_handling.py
• Advanced patterns? → 08_search_patterns.py

💡 Key Concepts Covered

Search Types

• Simple Text Search: Basic keyword searching
• Phrase Search: Exact phrase matching with quotes
• Boolean Search: AND, OR, NOT operators
• Wildcard Search: Pattern matching with *
• Field Search: Targeting specific document fields

Result Handling

• Score Analysis: Understanding relevance scores
• Result Formatting: Display and export options
• Filtering: Score-based and custom filtering
• Sorting: By score, field, or custom criteria

Error Handling

• Input Validation: Query sanitization and validation
• HTTP Errors: Handling Azure Search API errors
• Fallback Strategies: Alternative queries when searches fail
• User-Friendly Messages: Converting technical errors

Search Patterns

• Progressive Search: From specific to broad strategies
• Fallback Search: Automatic strategy switching
• Multi-Field Search: Prioritized field searching
• Pattern Selection: Choosing the right approach

🔧 Code Structure

Each file follows a consistent structure:

"""
Module docstring explaining the concepts
"""

# Imports and setup
import os, sys, logging
from azure.search.documents import SearchClient

# Main class demonstrating the concept
class ConceptDemo:
    def __init__(self, search_client=None):
        # Initialize with search client

    def main_method(self, params):
        # Core functionality demonstration

    def helper_methods(self):
        # Supporting functionality

# Demonstration function
def demonstrate_concept():
    # Show the concept in action

# Best practices function  
def concept_best_practices():
    # Guidelines and tips

# Main execution
if __name__ == "__main__":
    demonstrate_concept()
    concept_best_practices()

🎯 Usage Examples

Basic Search

from azure.search.documents import SearchClient
from azure.core.credentials import AzureKeyCredential

# Initialize client
search_client = SearchClient(
    endpoint="https://your-service.search.windows.net",
    index_name="your-index",
    credential=AzureKeyCredential("your-api-key")
)

# Simple search
results = search_client.search(search_text="python programming")
for result in results:
    print(f"Title: {result.get('title')}")
    print(f"Score: {result['@search.score']}")

Using the Example Classes

# Import from any example file
from simple_text_search import SimpleTextSearch

# Initialize and use
search_ops = SimpleTextSearch()
results = search_ops.basic_search("machine learning", top=5)
search_ops.display_results(results)

🛡️ Error Handling

All examples include basic error handling:

try:
    results = search_client.search(search_text=query)
    # Process results
except HttpResponseError as e:
    print(f"Search error: {e.status_code}")
except Exception as e:
    print(f"Unexpected error: {str(e)}")

📊 Performance Tips

1. Limit Results: Use top parameter to limit result count
2. Select Fields: Use select to return only needed fields
3. Field Targeting: Use search_fields for specific field searches
4. Caching: Cache frequently used search results
5. Error Handling: Implement proper error handling and retries

🔗 Cross-Language Learning

These Python examples complement the other language implementations:

• C# Examples - .NET implementations with async/await patterns
• JavaScript Examples - Node.js and browser examples
• REST API Examples - Direct HTTP API calls for any language
• Interactive Notebooks - Jupyter examples for experimentation

🎯 Learning Approach:

• Sequential: Follow 01-08 in order for structured learning
• Cross-Language: Compare implementations across platforms
• Topic-Focused: Jump to specific search types as needed
• Interactive: Use notebooks for hands-on experimentation

🚀 Next Steps

After working through these examples:

1. ✅ Try modifying the queries and parameters
2. 🔧 Implement your own search functionality
3. 📚 Explore other language examples
4. 🎯 Check out the interactive notebooks
5. 📖 Move on to Module 3: Index Management

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Happy Coding! 🐍✨