# DibsDataSourceCSV
## Overview
This repository contains a set of utilities `utils` and a Python file named `datasource_csv`. The primary purpose
of `datasource_csv` is to provide functionality for handling Excel and CSV files, performing
calculations on data and returning objects as results. `DataSourceCSV`implements the `DataSource` interface defined in
another module called `dibs_computing_core`.
## File Structure
- **utils/**: This directory contains several Python files, each housing methods that are utilized
within `datasource_csv`.
- **datasource_csv.py**: This Python file implements the `DataSource` interface, defined in `dibs_computing_core`, to
interact with Excel and CSV files, converting them into appropriate objects (performing
calculations on data and returning objects
as results.)
### Arguments:
- `path`: Path to the file containing building data type of `str`. (Required)
- `profile_from_norm`: type of `str`. (Optional)
- `gains_from_group_values`: type of `str`. (Optional)
- `usage_from_norm`: type of `str`. (Optional)
- `weather_period`: type of `str`. (Optional)
## Usage
To use the functionalities provided by this repository, follow these steps:
1. **Installation**: Use pip to install the module. This will automatically install the required dependencies
mentioned in `pyproject.toml`.
```bash
pip install dibs_datasource_csv
```
2. **Importing DatasourceCSV**: You can import and use the `DataSourceCSV` class directly from the terminal or any
Python
environment.
```bash
python
```
```python
from dibs_computing_core.iso_simulator.dibs.dibs import DIBS
from dibs_datasource_csv.datasource_csv import DataSourceCSV
import dibs_data
```
1. **Performing Simulation**: Use the methods provided in `dibs class` (`calculate_result_of_one_building`
or `multi`) to perform calculations on your data. The method `calculate_result_of_one_building` simulates one
building and `multi` simulates multiple building simultaneously for more performance.
```python
# Example usage
datasource_csv = DataSourceCSV(path="path_to_your_data", "din18599", "mid", "sia2024", "2007-2021") or
datasource_csv = DataSourceCSV(path="path_to_your_data", profile_from_norm="din18599", gains_from_group_values="mid", usage_from_norm="sia2024", weather_period="2007-2021")
dibs = DIBS(datasource_csv)
simulation_time, result_of_all_hours, summary_result = dibs.calculate_result_of_one_building()
# To see the hourly result of the simulated building
print(result_of_all_hours)
# To see the summary result of the simulated building
print(summary_result)
```
## Contributing
Contributions to this repository are welcome. If you find any bugs, have feature requests, or want to contribute
enhancements, feel free to open an issue or submit a pull request.
## License
This repository is licensed under the [MIT License](LICENSE). Feel free to use, modify, and distribute the code as per
the terms of this license.
## Acknowledgments
Special thanks to contributors and maintainers who have helped shape and improve this repository. Your efforts are
greatly appreciated.
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"keywords": "Building, Building-Stock, Non-Domestic, Non-Residential, Operational, Energy, Greenhouse Gas, Global Warming Potential, Simulation, Model, Germany, ISO 13790, 5R1C",
"author": "Simon Knoll, Michael H\u00f6rner",
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"description": "# DibsDataSourceCSV\n\n## Overview\n\nThis repository contains a set of utilities `utils` and a Python file named `datasource_csv`. The primary purpose\nof `datasource_csv` is to provide functionality for handling Excel and CSV files, performing\ncalculations on data and returning objects as results. `DataSourceCSV`implements the `DataSource` interface defined in\nanother module called `dibs_computing_core`.\n\n## File Structure\n\n- **utils/**: This directory contains several Python files, each housing methods that are utilized\n within `datasource_csv`.\n- **datasource_csv.py**: This Python file implements the `DataSource` interface, defined in `dibs_computing_core`, to\n interact with Excel and CSV files, converting them into appropriate objects (performing\n calculations on data and returning objects\n as results.)\n\n### Arguments:\n\n- `path`: Path to the file containing building data type of `str`. (Required)\n- `profile_from_norm`: type of `str`. (Optional)\n- `gains_from_group_values`: type of `str`. (Optional)\n- `usage_from_norm`: type of `str`. (Optional)\n- `weather_period`: type of `str`. (Optional)\n\n## Usage\n\nTo use the functionalities provided by this repository, follow these steps:\n\n1. **Installation**: Use pip to install the module. This will automatically install the required dependencies\n mentioned in `pyproject.toml`.\n\n ```bash\n pip install dibs_datasource_csv\n ```\n\n2. **Importing DatasourceCSV**: You can import and use the `DataSourceCSV` class directly from the terminal or any\n Python\n environment.\n\n ```bash\n python\n ```\n\n ```python\n from dibs_computing_core.iso_simulator.dibs.dibs import DIBS\n from dibs_datasource_csv.datasource_csv import DataSourceCSV\n import dibs_data\n ```\n\n\n1. **Performing Simulation**: Use the methods provided in `dibs class` (`calculate_result_of_one_building`\n or `multi`) to perform calculations on your data. The method `calculate_result_of_one_building` simulates one\n building and `multi` simulates multiple building simultaneously for more performance.\n\n ```python\n # Example usage\n datasource_csv = DataSourceCSV(path=\"path_to_your_data\", \"din18599\", \"mid\", \"sia2024\", \"2007-2021\") or \n datasource_csv = DataSourceCSV(path=\"path_to_your_data\", profile_from_norm=\"din18599\", gains_from_group_values=\"mid\", usage_from_norm=\"sia2024\", weather_period=\"2007-2021\")\n \n dibs = DIBS(datasource_csv)\n \n simulation_time, result_of_all_hours, summary_result = dibs.calculate_result_of_one_building()\n \n # To see the hourly result of the simulated building\n print(result_of_all_hours)\n \n # To see the summary result of the simulated building\n print(summary_result)\n ```\n\n## Contributing\n\nContributions to this repository are welcome. If you find any bugs, have feature requests, or want to contribute\nenhancements, feel free to open an issue or submit a pull request.\n\n## License\n\nThis repository is licensed under the [MIT License](LICENSE). Feel free to use, modify, and distribute the code as per\nthe terms of this license.\n\n## Acknowledgments\n\nSpecial thanks to contributors and maintainers who have helped shape and improve this repository. Your efforts are\ngreatly appreciated.\n\n",
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"summary": "This package translates CSV date files to DIBS input. DIBS---Dynamic-ISO-Building-Simulator is a simulation program for calculating the space heating, occupancy hot water, cooling and electricity demand of German non-residential buildings. Further the DIBS calculates the heating value based energy uses, the primary energy and the greenhouse gas emission. The underlying resistance-capacity-model is based on the simplified hourly method of ISO 13790:2008.",
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