frequenz-client-reporting 0.6.0

Reporting API client for Python

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 to install
VERSION=0.5.0
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
SERVICE_ADDRESS = "localhost:4711"
API_KEY = open('api_key.txt').read().strip()
client = ReportingApiClient(service_address=SERVICE_ADDRESS, key=API_KEY)

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"),
        page_size=10000,
        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"),
        page_size=10000,
        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.