# Pyfingridapi
`pyfingridapi` is a Python client library for interacting with the Fingrid API. It provides convenient methods for accessing time-series data, dataset information, notifications, and the health status of the Fingrid API.
## Features
- Fetch real-time and historical time-series data.
- Retrieve detailed dataset metadata.
- Access active notifications and alerts.
- Check the health status of the Fingrid API services.
- Built using `httpx` for robust HTTP interactions and `pydantic` for data validation.
## Installation
Install the library using pip:
```bash
pip install pyfingriaApi
```
## Usage
### Initialization
Create an instance of the `FingridApi` client:
```python
import httpx
from pyfingridapi import FingridApi
# Initialize the API client
with httpx.Client() as client
api_client = FingridApi(client=client, x_api_key="your_api_key")
```
### Fetching the Latest Data by Dataset
```python
latest_data = api_client.get_last_data_by_dataset(datasetId=12345)
print(latest_data)
```
### Fetching Multiple Time Series Data
```python
time_series_data = api_client.get_multiple_timeseries_data(
datasetId=[123, 456],
startTime="2024-01-01T00:00:00Z",
endTime="2024-01-31T23:59:59Z"
)
print(time_series_data)
```
### Retrieving Dataset Information
```python
dataset_info = api_client.get_dataset(datasetId=12345)
print(dataset_info)
```
### Fetching Active Notifications
```python
notifications = api_client.get_active_notifications()
print(notifications)
```
### Checking API Health Status
```python
health_status = api_client.get_health_status()
print(health_status)
```
## Models
The library uses `pydantic` models to structure and validate the data retrieved from the API. Key models include:
- `DataRecord`: Represents a single data point in a time series.
- `TimeSeriesDataResponse`: Encapsulates time-series data and pagination information.
- `DataSet`: Contains detailed metadata about a dataset.
- `ActiveNotifications`: Represents active notifications from Fingrid.
- `HealthStatus`: Describes the health status of the Fingrid API.
## Logging
`pyfingridapi` uses Python's `logging` module to log errors and debug information. To configure logging:
```python
import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger("fingridapi")
```
## TODO
- Add support for API endpoints such as `GetDatasetFile`, `GetDatasetFileData`, and `GetDatasetShorts`.
- test this as module
- push this to pypi_test
- push this to pypi
- create documentation site
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Contributing
Contributions are welcome! Feel free to submit issues or pull requests to enhance the library.
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"description": "\n# Pyfingridapi\n\n`pyfingridapi` is a Python client library for interacting with the Fingrid API. It provides convenient methods for accessing time-series data, dataset information, notifications, and the health status of the Fingrid API.\n\n## Features\n\n- Fetch real-time and historical time-series data.\n- Retrieve detailed dataset metadata.\n- Access active notifications and alerts.\n- Check the health status of the Fingrid API services.\n- Built using `httpx` for robust HTTP interactions and `pydantic` for data validation.\n\n## Installation\n\nInstall the library using pip:\n\n```bash\npip install pyfingriaApi\n```\n\n## Usage\n\n### Initialization\n\nCreate an instance of the `FingridApi` client:\n\n```python\nimport httpx\nfrom pyfingridapi import FingridApi\n\n# Initialize the API client\nwith httpx.Client() as client\n api_client = FingridApi(client=client, x_api_key=\"your_api_key\")\n```\n\n### Fetching the Latest Data by Dataset\n\n```python\nlatest_data = api_client.get_last_data_by_dataset(datasetId=12345)\nprint(latest_data)\n```\n\n### Fetching Multiple Time Series Data\n\n```python\ntime_series_data = api_client.get_multiple_timeseries_data(\n datasetId=[123, 456],\n startTime=\"2024-01-01T00:00:00Z\",\n endTime=\"2024-01-31T23:59:59Z\"\n)\nprint(time_series_data)\n```\n\n### Retrieving Dataset Information\n\n```python\ndataset_info = api_client.get_dataset(datasetId=12345)\nprint(dataset_info)\n```\n\n### Fetching Active Notifications\n\n```python\nnotifications = api_client.get_active_notifications()\nprint(notifications)\n```\n\n### Checking API Health Status\n\n```python\nhealth_status = api_client.get_health_status()\nprint(health_status)\n```\n\n## Models\n\nThe library uses `pydantic` models to structure and validate the data retrieved from the API. Key models include:\n\n- `DataRecord`: Represents a single data point in a time series.\n- `TimeSeriesDataResponse`: Encapsulates time-series data and pagination information.\n- `DataSet`: Contains detailed metadata about a dataset.\n- `ActiveNotifications`: Represents active notifications from Fingrid.\n- `HealthStatus`: Describes the health status of the Fingrid API.\n\n## Logging\n\n`pyfingridapi` uses Python's `logging` module to log errors and debug information. To configure logging:\n\n```python\nimport logging\n\nlogging.basicConfig(level=logging.INFO)\nlogger = logging.getLogger(\"fingridapi\")\n```\n\n## TODO\n\n- Add support for API endpoints such as `GetDatasetFile`, `GetDatasetFileData`, and `GetDatasetShorts`.\n- test this as module\n- push this to pypi_test\n- push this to pypi\n- create documentation site\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n\n## Contributing\n\nContributions are welcome! Feel free to submit issues or pull requests to enhance the library.\n\n\n",
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