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https://github.com/frequenz-floss/frequenz-client-reporting-python

A python client for the Frequenz Reporting API
https://github.com/frequenz-floss/frequenz-client-reporting-python

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A python client for the Frequenz Reporting API

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# Frequenz Reporting API Client

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[![PyPI Package](https://img.shields.io/pypi/v/frequenz-client-reporting)](https://pypi.org/project/frequenz-client-reporting/)
[![Docs](https://img.shields.io/badge/docs-latest-informational)](https://frequenz-floss.github.io/frequenz-client-reporting-python/)

## Introduction

Reporting API client for Python

## Supported Platforms

The following platforms are officially supported (tested):

- **Python:** 3.11
- **Operating System:** Ubuntu Linux 20.04
- **Architectures:** amd64, arm64

## Contributing

If you want to know how to build this project and contribute to it, please
check out the [Contributing Guide](CONTRIBUTING.md).

## Usage

Please also refer to [examples](https://github.com/frequenz-floss/frequenz-client-reporting-python/tree/HEAD/examples) for more detailed usage.

### Installation

```bash
# Choose the version you want to install
VERSION=0.12.0
pip install frequenz-client-reporting==$VERSION
```

### Initialize the client

```python
from datetime import datetime, timedelta

from frequenz.client.common.metric import Metric
from frequenz.client.reporting import ReportingApiClient

# Change server address if needed
SERVER_URL = "grpc://reporting.api.frequenz.com:443"
API_KEY = open('api_key.txt').read().strip()
client = ReportingApiClient(server_url=SERVER_URL, key=API_KEY)
```

Besides the `microgrid_id`, `component_id`s, `metrics`, start, and end time,
you can also set the sampling period for resampling using the `resampling_period`
parameter. For example, to resample data every 15 minutes, use
`resampling_period=timedelta(minutes=15)`.

### Query metrics for a single microgrid and component:

```python
data = [
sample async for sample in
client.list_single_component_data(
microgrid_id=1,
component_id=100,
metrics=[Metric.AC_ACTIVE_POWER, Metric.AC_REACTIVE_POWER],
start_dt=datetime.fromisoformat("2024-05-01T00:00:00"),
end_dt=datetime.fromisoformat("2024-05-02T00:00:00"),
resampling_period=timedelta(seconds=1),
)
]
```

### Query metrics for multiple microgrids and components

```python
# Set the microgrid ID and the component IDs that belong to the microgrid
# Multiple microgrids and components can be queried at once
microgrid_id1 = 1
component_ids1 = [100, 101, 102]
microgrid_id2 = 2
component_ids2 = [200, 201, 202]
microgrid_components = [
(microgrid_id1, component_ids1),
(microgrid_id2, component_ids2),
]

data = [
sample async for sample in
client.list_microgrid_components_data(
microgrid_components=microgrid_components,
metrics=[Metric.AC_ACTIVE_POWER, Metric.AC_REACTIVE_POWER],
start_dt=datetime.fromisoformat("2024-05-01T00:00:00"),
end_dt=datetime.fromisoformat("2024-05-02T00:00:00"),
resampling_period=timedelta(seconds=1),
include_states=False, # Set to True to include state data
include_bounds=False, # Set to True to include metric bounds data
)
]
```

### Optionally convert the data to a pandas DataFrame

```python
import pandas as pd
df = pd.DataFrame(data)
print(df)
```

## Command line client tool

The package contains a command-line tool that can be used to request data from the reporting API.
```bash
reporting-cli \
--url localhost:4711 \
--key=$(