Metadata-Version: 2.1
Name: frequenz-client-reporting
Version: 0.7.0
Summary: Reporting API client for Python
Author-email: Frequenz Energy-as-a-Service GmbH <floss@frequenz.com>
License: MIT
Project-URL: Documentation, https://frequenz-floss.github.io/frequenz-client-reporting-python/
Project-URL: Changelog, https://github.com/frequenz-floss/frequenz-client-reporting-python/releases
Project-URL: Issues, https://github.com/frequenz-floss/frequenz-client-reporting-python/issues
Project-URL: Repository, https://github.com/frequenz-floss/frequenz-client-reporting-python
Project-URL: Support, https://github.com/frequenz-floss/frequenz-client-reporting-python/discussions/categories/support
Keywords: frequenz,python,lib,library,client-reporting,client,reporting,api
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Software Development :: Libraries
Classifier: Typing :: Typed
Requires-Python: <4,>=3.11
Description-Content-Type: text/markdown
Provides-Extra: dev-flake8
Provides-Extra: dev-formatting
Provides-Extra: dev-mkdocs
Provides-Extra: dev-mypy
Provides-Extra: dev-noxfile
Provides-Extra: dev-pylint
Provides-Extra: dev-pytest
Provides-Extra: dev
Provides-Extra: examples
License-File: LICENSE

# 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=0.6.0
pip install frequenz-client-reporting==$VERSION
```


### Initialize the client

```python
from datetime import datetime

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

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

Besides the microgrid_id, component_ids, and metrics, start, and end time,
you can also set the sampling period for resampling using the `resolution` parameter.
For example, to resample data every 15 minutes, use a `resolution` of 900 seconds. The default is 1 second.

### 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"),
        resolution=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"),
        resolution=1,
    )
]
```

### 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=$(<api_key.txt)
    --mid 42 \
    --cid 23 \
    --metrics AC_ACTIVE_POWER AC_REACTIVE_POWER \
    --start 2024-05-01T00:00:00 \
    --end 2024-05-02T00:00:00 \
    --format csv
```
In addition to the default CSV format the data can be output as individual samples or in `dict` format.
