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Description:

frequenzclientreporting 0.8.0

Frequenz Reporting API Client

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.
Usage
Please also refer to examples for more detailed usage.
Installation
# Choose the version you want to install
VERSION=0.7.0
pip install frequenz-client-reporting==$VERSION

Initialize the client
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:
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
# 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
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.
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.