Python Client

Our official Python client library brings Gender-API.com's powerful gender detection to your data science workflows, machine learning pipelines, and automation scripts. With 99.5% accuracy across 150+ countries, our API outperforms generic AI models by 9-34% while being 10x-90x faster. Perfect for pandas DataFrames, batch processing, and scientific computing. The Pythonic API design makes integration intuitive with clean, readable code. Process over 9 million names with intelligent fallback and smart normalization that handles typos and spelling variants. Ideal for customer analytics, demographic research, and data cleaning. Start free with 100 API calls per month. GDPR compliant and production-ready.

First install our library with composer:

See full client documentation here:

https://github.com/markus-perl/gender-api-client

First install our library with npm:

See full client documentation here:

https://github.com/markus-perl/gender-api-client-npm

First install our library with npm:

See full client documentation here:

https://github.com/markus-perl/gender-api-client-npm

First install our library with pip:

# Install: pip install gender-api-client
from gender_api import Client

client = Client(api_key="insert your server key here")

# Simple gender lookup
result = client.get_by_first_name("kevin")

if result.result_found:
    print(f"Gender: {result.gender}")  #Gender: male
    print(f"Accuracy: {result.accuracy}%")  #Accuracy: 99%
Python Simple (Without Client Library): 
Python 3.*
import json

from urllib.request import urlopen

myKey = "insert your server key here"
url = "https://gender-api.com/get?key=" + myKey + "&name=kevin"
response = urlopen(url)
decoded = response.read().decode('utf-8')
data = json.loads(decoded)
print( "Gender: " + data["gender"]); #Gender: male

See full client documentation here:

https://github.com/markus-perl/gender-api-client-python
https://pypi.org/project/gender-api-client/

Advanced Gender Detection for Python Data Science

Gender-API.com's official Python client library brings state-of-the-art gender detection to your data science workflows, machine learning pipelines, and automation scripts. Designed with data scientists and Python developers in mind, our library integrates seamlessly with pandas, NumPy, and the entire Python scientific computing ecosystem.

Why Gender-API Outperforms Generic AI Models

Generic AI solutions like ChatGPT, Claude, or other LLMs are general-purpose tools that weren't designed specifically for gender detection. Gender-API.com is purpose-built for this exact task:

  • Lightning-Fast Processing : Process names in under 100ms vs. 1-10 seconds for generic AI
  • Superior Accuracy : 99.5% accuracy with 9-34% better performance than LLMs on gender detection tasks
  • Massive Database : 37% more names than typical AI training datasets, with continuous daily updates
  • Batch Processing : Process entire DataFrames efficiently - something generic AI APIs struggle with
  • Predictable Costs : Clear per-request pricing vs. unpredictable token-based costs of AI services
  • Specialized Intelligence : Understands cultural nuances, regional variations, and handles ambiguous names correctly

Powerful Features for Data Scientists

  • Pandas Integration : Apply gender detection directly to DataFrame columns with vectorized operations
  • Batch API Support : Process up to 1,000 names per request for maximum efficiency
  • Smart Normalization : Automatically handles typos, spelling variants, and special characters
  • Country-Specific Lookups : Get accurate results for names that vary by region (e.g., "Andrea" in Italy vs. Germany)
  • Confidence Scores : Receive probability scores to filter results based on your accuracy requirements
  • Async Support : Use async/await for non-blocking operations in modern Python applications
  • Type Hints : Full type annotation support for better IDE integration and code quality

Ideal Use Cases

  • Customer Analytics : Analyze customer demographics from name data in your CRM or database
  • Survey Analysis : Enrich survey responses with gender data for demographic breakdowns
  • Machine Learning : Add gender as a feature in your ML models for better predictions
  • Data Cleaning : Validate and complete customer records in large datasets
  • Academic Research : Process research data for demographic studies and social science analysis
  • Marketing Segmentation : Create targeted campaigns based on gender demographics

Global Coverage with Cultural Intelligence

Our database covers over 9 million names across 150+ countries with specialized handling for different cultures and regions. We understand that "Kim" is typically male in Korea but female in English-speaking countries. Our intelligent fallback system ensures maximum coverage while maintaining high accuracy.

Production-Ready & Scalable

Used by data teams at Fortune 500 companies and research institutions worldwide, our Python client is battle-tested for production workloads. Process millions of names with confidence, backed by our 99.9% uptime SLA and GDPR-compliant infrastructure.

Get Started in Minutes

Install with pip, grab your free API key, and start processing names immediately. Begin with 100 free API calls per month and scale as your needs grow. No credit card required to start.

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