A modular Python toolkit designed to support notebook-based workflows. It provides reusable tools for data ingestion, transformations, visualisation, notifications, and microgrid metadata managers. These tools make the repository ideal for streamlining analytics workflows with minimal setup and building data pipelines, reporting workflows, and alert systems seamlessly in Jupyter or cloud notebooks.
The following platforms are officially supported (tested):
- Python: 3.11
- Operating System: Ubuntu Linux 20.04
- Architectures: amd64, arm64
If you want to know how to build this project and contribute to it, please check out the Contributing Guide.
Install the package, open the example notebooks, and explore the available modules.
# Choose the version you want to install
VERSION=0.9.2
pip install frequenz‑lib‑notebooks==$VERSION
Then open the prebuilt example notebooks using your preferred interface:
- Classic Notebook:
jupyter examples/
- JupyterLab:
jupyter-lab examples/
jupyter
or jupyterlab
by default. You will need to install it separately if you want to run notebooks:
pip install jupyterlab
This example shows how to:
- Transform a
pandas
DataFrame of alert records into a structured HTML email usinggenerate_alert_email
. - Use
AlertEmailConfig
to control layout (e.g., table row limits, sorting by severity). - Integrate microgrid-component alerts cleanly into operational workflows (e.g., for notifications or reporting tools).
import pandas as pd
from IPython.display import HTML
from frequenz.lib.notebooks.alerts.alert_email import (
AlertEmailConfig,
generate_alert_email,
)
from frequenz.lib.notebooks.notification_utils import format_email_preview
# Example alert records dataframe
alert_records = pd.DataFrame(
[
{
"microgrid_id": 1,
"component_id": 1,
"state_type": "error",
"state_value": "UNDERVOLTAGE",
"start_time": "2025-03-14 15:06:30",
"end_time": "2025-03-14 17:00:00",
},
{
"microgrid_id": 2,
"component_id": 1,
"state_type": "state",
"state_value": "DISCHARGING",
"start_time": "2025-03-14 15:06:30",
"end_time": None,
},
]
)
# Configuration for email generation
alert_email_config = AlertEmailConfig(
displayed_rows=10,
sort_by_severity=True,
)
# Generate the HTML body of the alert email
html_email = generate_alert_email(
alert_records=alert_records, config=alert_email_config
)
# Output the HTML # or send it via email as shown in the next example
print(html_email)
# or preview it in a nicer format
HTML(format_email_preview(subject="Alert Notification", body_html=html_email))
Continuing from Example 1, this snippet builds on the generated HTML email and demonstrates:
- Configuring SMTP credentials and recipients.
- Attaching both a CSV export of the alert data and optional visual plots.
- Sending the email once or scheduling it periodically. Note that the periodic scheduling would make sense when the data also refreshes so as to not send the same email over and over again!
import time
from datetime import datetime
from frequenz.lib.notebooks.alerts.alert_email import ExportOptions, plot_alerts
from frequenz.lib.notebooks.notification_service import (
EmailConfig,
EmailNotification,
SchedulerConfig,
)
# Configuration for email notification
email_config = EmailConfig(
subject="Critical Alert",
message=html_email, # Assuming that html_email already exists. See the code example above on how to generate this.
recipients=["[email protected]"],
smtp_server="smtp.example.com",
smtp_port=587,
smtp_user="[email protected]",
smtp_password="password",
from_email="[email protected]",
scheduler=SchedulerConfig(
send_immediately=True,
interval=60, # send every minute
duration=3600, # for one hour total
),
)
# The SMTP details and sender/recipient details need to be adjusted accordingly
# note that the library provides a convenient way to validate the settings via frequenz.lib.notebooks.notification_utils.validate_email_config
# Create a notification object
email_notification = EmailNotification(config=email_config)
# optionally add attachments (a list of files)
email_config.attachments = None
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
alert_file_name = f"alert_details_{timestamp}.csv"
alert_records.to_csv(alert_file_name, index=False)
email_config.attachments = [alert_file_name]
# Optionally create a visualisation of the alert records
img_path = plot_alerts(
records=alert_records,
plot_type="all",
export_options=ExportOptions(
format="png",
show=True,
),
)
email_config.attachments += img_path if img_path else []
# Send one-off notification
email_notification.send()
# Or start a periodic scheduler:
email_notification.start_scheduler()
time.sleep(300) # let it run for 5 minutes
email_notification.stop_scheduler()
- Solar Maintenance App: Interactive forecasting and visualisation tools tailored to solar installations.
- Notification Service: Flexible and configurable email dispatching.
- Alert Email Generation: Embed rich Plotly charts into alert emails, complete with context and summaries.
- Microgrid Configuration: Manage structured microgrid metadata—location, devices, etc. — consistently across notebooks.
For more details about each module/project, please refer to the overview Wiki
page which has links to dedicated project pages.
The full code documentation can be accessed here.