| Name | hurricane-net JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | None |
| Summary | A small example package |
| upload_time | 2025-07-21 01:27:21 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | None |
| keywords |
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| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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No coveralls.
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# Hurricane Net
`hurricane_net` is a Python package designed to facilitate the analysis and exploration of hurricane and tropical storm data from the International Best Track Archive for Climate Stewardship (IBTrACS). The package leverages the power of Pandas to filter and manipulate data, making it easier to perform analyses on specific storm regions or types, such as Atlantic hurricanes.
## Features
- **Data Loading**: Easily load IBTrACS data directly from a provided URL.
- **Filtering**: Filter data by storm basin or type (e.g., hurricanes) using intuitive methods.
- **Logging**: Comprehensive logging for debugging and tracking the data loading and filtering processes.
- **Prompt Templates**: Use predefined prompt templates for generating daily reports or other structured outputs.
## Installation
To install `hurricane_net`, you can use pip to install it from a local source or directly from a repository if available. If you are building a wheel, follow the instructions in the setup documentation.
```bash
pip install hurricane_net
```
## Usage
Below are examples demonstrating how to use `hurricane_net` to load, filter, and generate reports on storm data.
### Importing the Package
```python
import hurricane_net as hn
```
### Loading and Filtering Data
1. **Initialize the Data Loader**
Load the IBTrACS data from a specified URL. The default URL points to the IBTrACS database.
```python
data_loader = hn.data()
```
2. **Filter Data**
Filter the data based on different criteria. For example, to get all storms, Atlantic storms, or hurricanes:
```python
# Load all available storms
data_loader.filter('all')
all_storms = data_loader.storms
# Load storms from the North Atlantic basin
data_loader.filter('NA')
atlantic_storms = data_loader.storms
# Load hurricanes (NA basin with USA_STATUS 'HU' or 'HR')
data_loader.filter('hurricanes')
hurricanes = data_loader.storms
```
3. **Logging**
The package logs all major actions, such as data loading and filtering, to help trace operations.
### Generating Reports
The `Prompt` class provides functionality to generate reports using predefined templates.
## References
- [IBTrACS Data Access](https://www.ncei.noaa.gov/data/international-best-track-archive-for-climate-stewardship-ibtracs/v04r01/access/csv/)
- [IBTrACS Documentation](https://www.ncei.noaa.gov/products/international-best-track-archive)
- [IBTrACS v04r01 Column Documentation](https://www.ncei.noaa.gov/sites/g/files/anmtlf171/files/2025-04/IBTrACS_v04r01_column_documentation.pdf)
## Troubleshooting
- [Python Package](https://github.com/hammad93/hurricane-net/issues/19)
## License
This package is open source. Please see the LICENSE file for more information.
## Contributing
Contributions are welcome! Please feel free to open issues or submit pull requests.
## Acknowledgments
This package uses data from the International Best Track Archive for Climate Stewardship (IBTrACS) maintained by NOAA's National Centers for Environmental Information (NCEI).
Raw data
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"description": "# Hurricane Net\n\n`hurricane_net` is a Python package designed to facilitate the analysis and exploration of hurricane and tropical storm data from the International Best Track Archive for Climate Stewardship (IBTrACS). The package leverages the power of Pandas to filter and manipulate data, making it easier to perform analyses on specific storm regions or types, such as Atlantic hurricanes.\n\n## Features\n\n- **Data Loading**: Easily load IBTrACS data directly from a provided URL.\n- **Filtering**: Filter data by storm basin or type (e.g., hurricanes) using intuitive methods.\n- **Logging**: Comprehensive logging for debugging and tracking the data loading and filtering processes.\n- **Prompt Templates**: Use predefined prompt templates for generating daily reports or other structured outputs.\n\n## Installation\n\nTo install `hurricane_net`, you can use pip to install it from a local source or directly from a repository if available. If you are building a wheel, follow the instructions in the setup documentation.\n\n```bash\npip install hurricane_net\n```\n\n## Usage\n\nBelow are examples demonstrating how to use `hurricane_net` to load, filter, and generate reports on storm data.\n\n### Importing the Package\n\n```python\nimport hurricane_net as hn\n```\n\n### Loading and Filtering Data\n\n1. **Initialize the Data Loader**\n\n Load the IBTrACS data from a specified URL. The default URL points to the IBTrACS database.\n\n ```python\n data_loader = hn.data()\n ```\n\n2. **Filter Data**\n\n Filter the data based on different criteria. For example, to get all storms, Atlantic storms, or hurricanes:\n\n ```python\n # Load all available storms\n data_loader.filter('all')\n all_storms = data_loader.storms\n\n # Load storms from the North Atlantic basin\n data_loader.filter('NA')\n atlantic_storms = data_loader.storms\n\n # Load hurricanes (NA basin with USA_STATUS 'HU' or 'HR')\n data_loader.filter('hurricanes')\n hurricanes = data_loader.storms\n ```\n\n3. **Logging**\n\n The package logs all major actions, such as data loading and filtering, to help trace operations.\n\n### Generating Reports\n\nThe `Prompt` class provides functionality to generate reports using predefined templates.\n\n\n## References\n\n- [IBTrACS Data Access](https://www.ncei.noaa.gov/data/international-best-track-archive-for-climate-stewardship-ibtracs/v04r01/access/csv/)\n- [IBTrACS Documentation](https://www.ncei.noaa.gov/products/international-best-track-archive)\n- [IBTrACS v04r01 Column Documentation](https://www.ncei.noaa.gov/sites/g/files/anmtlf171/files/2025-04/IBTrACS_v04r01_column_documentation.pdf)\n\n## Troubleshooting\n\n- [Python Package](https://github.com/hammad93/hurricane-net/issues/19)\n\n## License\n\nThis package is open source. Please see the LICENSE file for more information.\n\n## Contributing\n\nContributions are welcome! Please feel free to open issues or submit pull requests.\n\n## Acknowledgments\n\nThis package uses data from the International Best Track Archive for Climate Stewardship (IBTrACS) maintained by NOAA's National Centers for Environmental Information (NCEI).\n",
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