Metadata-Version: 2.4
Name: mango-calendar
Version: 0.1.0a3
Summary: Library with a collection of useful classes and methods to DRY
Author-email: baobab soluciones <mango@baobabsoluciones.es>
License: Apache Software License
Project-URL: repository, https://github.com/baobabsoluciones/mango
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: holidays>=0.76
Requires-Dist: numpy>=2.2.4
Requires-Dist: pandas>=2.3.1
Requires-Dist: polars>=1.31.0
Requires-Dist: pyarrow>=20.0.0
Requires-Dist: pycountry>=24.6.1
Requires-Dist: unidecode>=1.4.0
Provides-Extra: dev
Requires-Dist: coverage[toml]>=7.0; extra == "dev"
Dynamic: license-file

# Mango Calendar 🥭📅

A Python library for working with calendar data, holidays, and date-related features with a focus on Spanish holidays and autonomous communities.

## Features ✨

- 🇪🇸 **Spanish Holiday Support**: Comprehensive support for Spanish national and autonomous community holidays
- 🌍 **Multi-Country Support**: Built on the `holidays` library for international calendar support
- 📊 **Flexible Data Formats**: Support for both pandas and polars DataFrames
- 🏋️ **Weighted Communities**: Assign weights to different autonomous communities
- 📏 **Distance Calculations**: Calculate distances to holidays for time-series analysis
- 🛍️ **Calendar Events**: Support for commercial events like Black Friday
- 🦠 **COVID Lockdown Data**: Built-in COVID-19 lockdown period data
- 🔄 **Pivot Functionality**: Transform calendar data into pivot tables
- 🏗️ **Type Hints**: Full type annotation support for better IDE integration

## Installation 📦

```bash
# Using pip
pip install mango-calendar

# Using uv (recommended)
uv add mango-calendar
```

## Quick Start 🚀

```python
from mango_calendar import get_calendar

# Get Spanish holidays for 2024
holidays_df = get_calendar(country="ES", start_year=2024, end_year=2025)
print(holidays_df.head())
```

## Usage Examples 📚

### Basic Holiday Calendar

```python
from mango_calendar import get_calendar

# Get basic Spanish holidays
holidays = get_calendar(
    country="ES",
    start_year=2024,
    end_year=2025
)
print(holidays[['date', 'name']].head())
```

### Advanced Features

```python
# Get holidays with autonomous communities and weights
holidays_with_communities = get_calendar(
    country="ES",
    start_year=2024,
    end_year=2025,
    communities=True,
    return_weights=True,
    calendar_events=True  # Include Black Friday
)

# Calculate distances to holidays
holidays_with_distances = get_calendar(
    country="ES",
    start_year=2024,
    end_year=2025,
    communities=True,
    return_distances=True,
    distances_config={
        "steps_back": 7,
        "steps_forward": 7
    }
)
```

### Date Utilities

```python
from mango_calendar.date_utils import get_holidays_df, get_covid_lockdowns

# Get holidays in a specific format with window bounds
holidays_polars = get_holidays_df(
    steps_back=3,
    steps_forward=7,
    start_year=2024,
    country="ES",
    output_format="polars"
)

# Get COVID lockdown periods
covid_data = get_covid_lockdowns()
```

### Pivot Calendar Data

```python
# Create a pivot table of holidays
pivot_calendar = get_calendar(
    country="ES",
    start_year=2024,
    end_year=2025,
    communities=True,
    return_weights=True,
    pivot=True,
    pivot_keep_communities=True
)
```

## API Reference 📖

### `get_calendar()`

Main function to retrieve calendar data.

**Parameters:**
- `country` (str): Country code (default: "ES")
- `start_year` (int): Start year for the calendar (default: 2010)
- `end_year` (int): End year for the calendar (default: current year + 2)
- `communities` (bool): Include autonomous community holidays (default: False)
- `weight_communities` (dict): Custom weights for communities
- `calendar_events` (bool): Include events like Black Friday (default: False)
- `return_weights` (bool): Return community weights (default: None)
- `return_distances` (bool): Return distance calculations (default: False)
- `distances_config` (dict): Configuration for distance calculations
- `name_transformations` (bool): Apply name transformations (default: True)
- `pivot` (bool): Return data in pivot format (default: False)
- `pivot_keep_communities` (bool): Keep communities when pivoting (default: False)

**Returns:**
- `pd.DataFrame`: Calendar data with requested features

### `get_holidays_df()`

Get holidays dataframe with window bounds.

**Parameters:**
- `steps_back` (int): Days to go back from holiday
- `steps_forward` (int): Days to go forward from holiday
- `start_year` (int): Start year (default: 2014)
- `country` (str): Country code (default: "ES")
- `output_format` (str): "polars" or "pandas" (default: "polars")

## Development Setup 🔧

### Prerequisites

- Python 3.12+
- uv (recommended) or pip

### Setup

```bash
# Clone the repository
git clone <repository-url>
cd mango_calendar

# Install dependencies
uv sync

# Run tests
python run_tests.py
```

### Project Structure

```
mango_calendar/
├── src/
│   └── mango_calendar/
│       ├── __init__.py
│       ├── calendar_features.py
│       └── date_utils.py
├── tests/
│   ├── test_calendar_features.py
│   ├── test_date_utils.py
│   └── test_init.py
├── pyproject.toml
└── README.md
```

### Dependencies

- `holidays>=0.76`: Holiday data
- `numpy>=2.3.1`: Numerical operations
- `pandas>=2.3.1`: Data manipulation
- `polars>=1.31.0`: Fast DataFrame operations
- `pyarrow>=20.0.0`: Columnar data format
- `pycountry>=24.6.1`: Country information
- `unidecode>=1.4.0`: Unicode text processing

## Code Quality 🎯

This project uses:
- **Ruff**: For linting and code formatting
- **Type hints**: Full type annotation support
- **pytest**: For testing
- **PEP 8**: Code style compliance
- **Docstring conventions**: PEP 257 compliance

## Contributing 🤝

1. Fork the repository
2. Create a feature branch (`git checkout -b feature/awesome-feature`)
3. Commit your changes (`git commit -m 'Add awesome feature'`)
4. Push to the branch (`git push origin feature/awesome-feature`)
5. Open a Pull Request

### Development Guidelines

- Follow PEP 8 style guidelines
- Add type hints to all functions
- Write comprehensive docstrings
- Include tests for new features
- Run `uv run coverage run -m unittest discover -s tests -p "test_*.py" -v` before submitting 

## License 📄

This project is developed by **baobab soluciones** (mango@baobabsoluciones.es).

## Support 💬

For questions, issues, or contributions, please contact:
- Email: mango@baobabsoluciones.es
- Create an issue on the repository

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Made with ❤️ by [baobab soluciones](mailto:mango@baobabsoluciones.es)
