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The SEO Machine Python API provides powerful analysis modules for SEO content optimization, SERP analysis, and content scoring. These modules are located in data_sources/modules/ and can be imported and used in your Python scripts.

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Module Categories

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Analysis Modules

Core analysis modules for content optimization:

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Data Integration Modules

Modules for connecting to external data sources:
  • DataForSEO - SERP positions and keyword metrics
  • Google Analytics - Traffic and engagement data
  • Google Search Console - Rankings and impressions
  • WordPress Publisher - Publish content with Yoast SEO metadata

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Installation

Install required dependencies: 
pip install -r data_sources/requirements.txt
Required packages:
  • requests - HTTP requests
  • beautifulsoup4 - HTML parsing
  • scikit-learn - Machine learning for clustering
  • textstat - Readability metrics
  • numpy - Numerical operations

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Basic Usage

All analysis modules follow a consistent pattern: 
from data_sources.modules.keyword_analyzer import analyze_keywords

# Using convenience function
result = analyze_keywords(
    content="Your article content here",
    primary_keyword="your target keyword",
    secondary_keywords=["related keyword 1", "related keyword 2"]
)

print(f"Keyword density: {result['primary_keyword']['density']}%")
print(f"Recommendations: {result['recommendations']}")
Or using the class directly: 
from data_sources.modules.keyword_analyzer import KeywordAnalyzer

analyzer = KeywordAnalyzer()
result = analyzer.analyze(
    content="Your article content here",
    primary_keyword="your target keyword"
)

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Common Patterns

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Chaining Multiple Analyses

Combine multiple modules for comprehensive content analysis: 
from data_sources.modules.search_intent_analyzer import analyze_intent
from data_sources.modules.keyword_analyzer import analyze_keywords
from data_sources.modules.readability_scorer import score_readability
from data_sources.modules.seo_quality_rater import rate_seo_quality

# Step 1: Analyze search intent
intent = analyze_intent(
    keyword="how to start a podcast",
    serp_features=["featured_snippet", "people_also_ask"]
)

# Step 2: Analyze keywords
keywords = analyze_keywords(
    content=article_content,
    primary_keyword="how to start a podcast",
    secondary_keywords=["podcast hosting", "podcast equipment"]
)

# Step 3: Check readability
readability = score_readability(article_content)

# Step 4: Get overall SEO quality score
quality = rate_seo_quality(
    content=article_content,
    primary_keyword="how to start a podcast",
    keyword_density=keywords['primary_keyword']['density'],
    meta_title="How to Start a Podcast: Complete Guide",
    meta_description="Learn how to start a podcast from scratch..."
)

print(f"Intent: {intent['primary_intent']}")
print(f"SEO Score: {quality['overall_score']}/100")
print(f"Readability Grade: {readability['reading_level']}")

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Working with SERP Data

Many modules accept SERP data from DataForSEO: 
from data_sources.modules.dataforseo import DataForSEO
from data_sources.modules.search_intent_analyzer import analyze_intent
from data_sources.modules.content_length_comparator import compare_content_length

# Get SERP data
dfs = DataForSEO()
serp_data = dfs.get_serp_data("your keyword")

# Analyze intent with SERP features
intent = analyze_intent(
    keyword="your keyword",
    serp_features=serp_data['features'],
    top_results=serp_data['organic_results'][:10]
)

# Compare content length
length_comparison = compare_content_length(
    keyword="your keyword",
    your_word_count=2500,
    serp_results=serp_data['organic_results']
)

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Output Format

All modules return dictionaries with consistent structure:
  • Metrics: Numerical scores and measurements
  • Analysis: Detailed breakdowns and insights
  • Recommendations: Actionable suggestions for improvement
  • Status/Grade: Quick assessment of quality level
{
    'overall_score': 85.2,
    'grade': 'B (Good)',
    'metrics': { ... },
    'analysis': { ... },
    'recommendations': [
        'Add 500 more words to match competitors',
        'Increase keyword density to 1.5%'
    ],
    'publishing_ready': True
}

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Error Handling

All modules include error handling: 
result = analyze_keywords(
    content="",
    primary_keyword="test"
)

if 'error' in result:
    print(f"Error: {result['error']}")
else:
    print(f"Density: {result['primary_keyword']['density']}%")

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Configuration

API credentials are configured in data_sources/config/.env: 
# DataForSEO API
DATAFORSEO_LOGIN=your_login
DATAFORSEO_PASSWORD=your_password

# Google Analytics
GA4_PROPERTY_ID=your_property_id

# WordPress
WORDPRESS_URL=https://your-site.com
WORDPRESS_USERNAME=your_username
WORDPRESS_APP_PASSWORD=your_app_password

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Next Steps

Explore the individual analysis modules:

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