bump again for readme

Author: soodoku

CHANGELOG.md

@@ -5,6 +5,18 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.3.1] - 2025-09-01
+
+### Documentation
+- **README Overhaul**: Complete rewrite with modern, quickstart-focused approach
+  - 3-line quickstart example for immediate use
+  - Clear migration guide from old API to new DomainClassifier
+  - Prominent examples for all classification methods (text, images, combined)
+  - Archive.org historical analysis prominently featured
+  - Batch processing examples and performance guidelines
+  - Moved legacy API documentation to LEGACY_API.rst for reference
+- **User Experience**: Much clearer onboarding and usage examples
+
 ## [0.3.0] - 2025-09-01
 
 ### 🚀 Major API Overhaul - Modern, Intuitive Interface

README.rst

@@ -12,7 +12,7 @@ piedomains: AI-powered domain content classification
 **piedomains** predicts website content categories using AI analysis of domain names, text content, and homepage screenshots. Classify domains as news, shopping, adult content, education, etc. with high accuracy.
 
 🚀 **Quickstart**
------------------
+-------------------
 
 Install and classify domains in 3 lines:
 
@@ -34,7 +34,7 @@ Install and classify domains in 3 lines:
     # 2 wikipedia.org   education   0.891234
 
 📊 **Key Features**
-------------------
+--------------------
 
 - **High Accuracy**: Combines text analysis + visual screenshots for 90%+ accuracy
 - **Historical Analysis**: Classify websites from any point in time using archive.org
@@ -43,7 +43,7 @@ Install and classify domains in 3 lines:
 - **41 Categories**: From news/finance to adult/gambling content
 
 ⚡ **Usage Examples**
--------------------
+---------------------
 
 **Basic Classification**
 
@@ -87,20 +87,20 @@ Install and classify domains in 3 lines:
     )
 
 🏷️ **Supported Categories**
---------------------------
+------------------------------
 
 News, Finance, Shopping, Education, Government, Adult Content, Gambling, Social Networks, Search Engines, and 32 more categories based on the Shallalist taxonomy.
 
 📈 **Performance**
------------------
+-------------------
 
 - **Speed**: ~10-50 domains/minute (depends on method and network)
 - **Accuracy**: 85-95% depending on content type and method
 - **Memory**: <500MB for batch processing
 - **Caching**: Automatic content caching for faster re-runs
 
 🔧 **Installation**
-------------------
+--------------------
 
 **Requirements**: Python 3.9+
 
@@ -115,7 +115,7 @@ News, Finance, Shopping, Education, Government, Adult Content, Gambling, Social
     pip install -e .
 
 🔄 **Migration from v0.2.x**
----------------------------
+-----------------------------
 
 **Old API** (still supported):
 
@@ -133,14 +133,14 @@ News, Finance, Shopping, Education, Government, Adult Content, Gambling, Social
     result = classifier.classify_by_text(["example.com"])
 
 📖 **Documentation**
--------------------
+---------------------
 
 - **API Reference**: https://piedomains.readthedocs.io
 - **Examples**: `/examples` directory
 - **Notebooks**: `/piedomains/notebooks` (training & analysis)
 
 🤝 **Contributing**
-------------------
+--------------------
 
 .. code-block:: bash
 
@@ -156,12 +156,12 @@ News, Finance, Shopping, Education, Government, Adult Content, Gambling, Social
     flake8 piedomains/
 
 📄 **License**
--------------
+---------------
 
 MIT License - see LICENSE file.
 
 📚 **Citation**
---------------
+----------------
 
 If you use piedomains in research, please cite:
 

docs/source/conf.py

@@ -14,7 +14,7 @@
 project = 'piedomains'
 copyright = '2023, rajashekar chintalapati and gaurav sood'
 author = 'rajashekar chintalapati and gaurav sood'
-release = '0.3.0'
+release = '0.3.1'
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "piedomains"
-version = "0.3.0"
+version = "0.3.1"
 description = "Predict categories based on domain names and their content"
 readme = "README.rst"
 license = {text = "MIT License"}