v0.4.1: Fix Version Inconsistency

Critical Bugfix Release

This release fixes a critical version inconsistency bug that was breaking downstream packages.

Bugfix

• Fix version mismatch: __init__.py now imports __version__ dynamically from __version__.py
• Remove hardcoded version: Removed incorrect __version__ = '0.2.0' from __init__.py
• Bump version: Updated to 0.4.1 in both pyproject.toml and __version__.py

Impact

Before this fix:

• python -c "import excel_to_sql; print(excel_to_sql.__version__)" → 0.2.0 ❌
• pip show excel-to-sql → 0.4.0 ✅

After this fix:

• python -c "import excel_to_sql; print(excel_to_sql.__version__)" → 0.4.1 ✅
• pip show excel-to-sql → 0.4.1 ✅

Fixes

• Fixes #47: Version Inconsistency Bug
• Unblocks wareflow-analysis releases
• Enables correct version checks in downstream packages

Installation

pip install excel-to-sql==0.4.1

Verification

python -c "import excel_to_sql; assert excel_to_sql.__version__ >= '0.3.0'"

v0.3.0 - Auto-Pilot Mode

🎉 Version 0.3.0 - Auto-Pilot Mode

This major release introduces Auto-Pilot Mode, a zero-configuration intelligent import system that automatically detects patterns, scores data quality, and guides you through the setup process.

✨ What's New

🤖 Auto-Pilot Mode

Automatic Pattern Detection:

• Primary keys - Automatically identifies unique columns
• Foreign keys - Detects relationships between tables
• Value mappings - Finds code columns (e.g., "1"/"0" → "Active"/"Inactive")
• Split fields - Identifies redundant status columns to combine with COALESCE
• Data types - Infers SQL types from data

Quality Analysis:

• Quality score (0-100) with letter grades (A-D)
• Issue detection (null values, duplicates, type mismatches)
• Statistical analysis (value distributions, outliers)
• Data profiling (column types, null percentages)

Smart Recommendations:

• Prioritized suggestions (HIGH/MEDIUM/LOW)
• Auto-fixable issues with one-click corrections
• Default value suggestions
• French code detection (ENTRÉE→inbound, SORTIE→outbound, etc.)

🎯 Interactive Wizard

Step-by-step guided configuration for complex datasets:

• Welcome screen with instructions
• File-by-file processing workflow
• Analysis display (rows, columns, PK, quality score, transformations)
• Transformation review (value mappings, calculated columns)
• User choice menu [1/3/4/5/h/q]
• Sample data viewer (first 10 rows)
• Statistics viewer (column types, null percentages)
• Help system and final summary

🛠️ Auto-Fix Capabilities

Automatic correction of common data quality issues:

• Null value fixing - Fills nulls with smart defaults ("0", "CURRENT_TIMESTAMP", "Other")
• French code translation - 11 common mappings (ENTRÉE→inbound, SORTIE→outbound, ACTIF→active, INACTIF→inactive, etc.)
• Split field combination - Combines redundant status columns using COALESCE
• Backup system - Automatic backups before modifications with rotation (max 5)

🚀 Usage

# Automatic mode - analyze and generate configuration
excel-to-sql magic --data ./excels

# Interactive mode - guided step-by-step setup
excel-to-sql magic --data ./excels --interactive

# Dry run - analyze without generating configuration
excel-to-sql magic --data ./excels --dry-run

📊 Components

PatternDetector (97% coverage)

Analyzes Excel files and detects patterns with confidence scores.

QualityScorer (99% coverage)

Generates comprehensive quality reports with multi-dimensional analysis.

RecommendationEngine (92% coverage)

Provides prioritized, actionable recommendations based on quality analysis.

AutoFixer (88% coverage)

Automatically fixes data quality issues with backup system for safe modifications.

InteractiveWizard (54% coverage)

Rich terminal UI for guided configuration workflow.

🧪 Testing

• 143+ tests for Auto-Pilot components
• Integration tests with real Excel fixtures
• >85% coverage for core Auto-Pilot modules
• 200+ total tests across all features

📝 Documentation

Completely rewritten README with:

• Auto-Pilot quick start guide
• Component API documentation
• Usage examples and best practices
• Interactive workflow examples

🔧 Under the Hood

• New excel_to_sql/auto_pilot/ module with pattern detection, quality scoring, recommendations, and auto-fix
• New excel_to_sql/ui/ module with InteractiveWizard
• Enhanced magic CLI command with --interactive flag
• Improved Rich terminal output with better formatting

📦 Installation

pip install excel-to-sql==0.3.0

# Or with uv
uv pip install excel-to-sql==0.3.0

🔄 Migration from 0.2.x

No breaking changes. The Auto-Pilot features are completely optional and additive:

• Existing workflows continue to work unchanged
• New magic command for zero-configuration setup
• Interactive mode for guided configuration

🐛 Bug Fixes

• Fixed Windows compatibility issues with tempfile handling
• Fixed Unicode character encoding issues (cp1252 console support)
• Improved error handling throughout Auto-Pilot components

🙏 Acknowledgments

This release completes the Auto-Pilot Mode EPIC, implementing 8 major issues:

• Pattern Detection (#14)
• Quality Scoring (#15)
• Config Generation (#16)
• CLI Magic Command (#17)
• Rich Terminal Output (#18)
• Dry-Run Mode (#19)
• Recommendations Engine (#20)
• Auto-Fix Capabilities (#22)
• Interactive Mode (#21)
• Documentation & Production Readiness (#10)

📖 Full Changelog

See CHANGELOG.md for complete details.

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Download from PyPI | View on GitHub

v0.2.0 - Major Feature Release

🎉 Version 0.2.0 - Major Feature Release

This release adds 12 major features with comprehensive testing and documentation.

✨ New Features

Data Transformations

• ✅ Value Mapping (#1) - Standardize data values (e.g., "NY" → "New York")
• ✅ Calculated Columns (#2) - Create derived columns using expressions
• ✅ Pre/Post Hooks (#10) - Execute custom code during import/export pipeline

Data Validation

• ✅ Custom Validators (#3) - Range, regex, unique, not-null, enum validators
• ✅ Reference Validation (#4) - Foreign key validation against lookup tables
• ✅ Validation Rules (#9) - Declarative rule-based validation system

Data Quality

• ✅ Data Profiling (#5) - Automatic quality analysis with detailed reports
• ✅ Quality Reports - Generate JSON/Markdown/HTML reports

Multi-Sheet Support

• ✅ Multi-Sheet Import (#6) - Import multiple sheets in one operation
• ✅ Multi-Sheet Export (#7) - Export multiple sheets with custom queries

Core Enhancements

• ✅ Incremental Import (#8) - Only process changed files using content hashing
• ✅ Python SDK (#11) - Full-featured programmatic API
• ✅ Metadata & Tags (#12) - Tag and categorize imports with rich metadata

📊 Statistics

• 68 tests added with comprehensive coverage
• 10 atomic commits for each major feature
• 4 new packages: transformations, validators, profiling, metadata, sdk
• 500+ lines of new functionality

🚀 Python SDK Example

from excel_to_sql import ExcelToSqlite

sdk = ExcelToSqlite()

# Import with transformations
result = sdk.import_excel(
    file_path="data.xlsx",
    type_name="products",
    tags=["q1-2024", "verified"]
)

# Profile data
profile = sdk.profile_table("products")
print(f"Quality: {profile['summary']['null_percentage']}% nulls")

📦 Installation

pip install excel-to-sql==0.2.0

🔗 Links

• Documentation
• Full Changelog

🙏 Credits

Built with ❤️ using Python, Pandas, SQLAlchemy, and Pydantic.

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Full Changelog: AliiiBenn/excel-to-sql@v0.1.1...v0.2.0

v0.1.1 - Excel to SQL CLI Tool

Excel to SQL CLI Tool - v0.1.1

The first public release of excel-to-sql, a CLI tool for importing Excel files into SQLite and exporting data back to Excel with formatting support.

What's New in v0.1.1

This release updates package metadata:

• Updated author to "Code with dave"
• Updated contact email to davidddpereiraaa6@gmail.com

Features

Excel to SQL Import

• Import Excel files (.xlsx, .xls) into SQLite database
• Automatic table creation based on column types
• UPSERT support (insert or update based on primary key)
• Composite primary key support
• Content-based change detection (SHA256 hashing)
• Skip unchanged files to avoid redundant operations
• Detailed import logging with statistics

SQL to Excel Export

• Export entire tables or custom SQL queries to Excel
• Rich Excel formatting:
  • Bold headers
  • Auto-adjusted column widths
  • Frozen header row
• Export history tracking
• Multiple output formats supported

Status & Monitoring

• View complete import history
• See file statistics (rows, columns, size)
• Track import dates and file hashes
• Detect file changes

Configuration Management

• Type-based mapping system
• Auto-detect column types from Excel files
• Add, list, show, remove, and validate mappings
• Composite primary key configuration
• Column type mapping (integer, float, string, boolean, date)

Installation

pip install excel-to-sql

Quick Start

# Initialize a new project
excel-to-sql init

# Add a type mapping
excel-to-sql config --add-type products --table products --pk id --file data/products.xlsx

# Import Excel data
excel-to-sql imports/products.xlsx --type products

# View import history
excel-to-sql status

# Export to Excel
excel-to-sql export output.xlsx --table products

# List configuration
excel-to-sql config --list

Documentation

• GitHub: https://github.com/AliiiBenn/excel-to-sql
• PyPI: https://pypi.org/project/excel-to-sql/

Requirements

• Python 3.10 or higher
• Dependencies automatically installed:
  • typer (CLI framework)
  • pandas (data manipulation)
  • openpyxl (Excel I/O)
  • sqlalchemy (database ORM)
  • rich (terminal formatting)

License

MIT License - see LICENSE file for details