rebdhuhn 1.0.1

Converts (already scraped) Entscheidungsbaumdiagramm tables to real graphs

rebdhuhn

🇩🇪 Dieses Repository enthält ein Python-Paket namens rebdhuhn, das genutzt werden kann, um aus .docx-Dateien extrahierte maschinenlesbare Tabellen, die einen Entscheidungsbaum (EBD) modellieren, in echte Graphen zu konvertieren. Diese Entscheidungsbäume sind Teil eines regulatorischen Regelwerks für die deutsche Energiewirtschaft und kommen in der Eingangsprüfung der Marktkommunikation zum Einsatz.

🇬🇧 This repository contains the source code of the Python package rebdhuhn.

Rationale

Assume, that you scraped the Entscheidungsbaumdiagramm tables by EDI@Energy from their somewhat "digitized" PDF/DOCX files. (To do so, you can use the package ebdamame.) Also assume, that the result of your scraping is a rebdhuhn.models.EbdTable.

The package rebdhuhn contains logic to convert your scraped data into a graph. This graph can then be exported e.g. as SVG and/or UML. ebdamame and rebdhuhn combined are the core of our ebd_toolchain which scrapes EBD.docx files from the edi_energy_mirror and pushes them to machine_readable-entscheidungsbaumdiagramme.

How to use rebdhuhn?

Install the package from pypi:

pip install rebdhuhn

Create an Instance of EbdTable

EbdTable contains the raw data by BDEW in a machine-readable format. Creating instances of EbdTable is out of scope for this package. Ask Hochfrequenz for support on this topic. In the following example we hard code the information.

from rebdhuhn.graph_conversion import convert_table_to_graph
from rebdhuhn.models import EbdCheckResult, EbdTable, EbdTableMetaData, EbdTableRow, EbdTableSubRow, EbdGraph

ebd_table: EbdTable  # this is the result of scraping the docx file
ebd_table = EbdTable(  # this data shouldn't be handwritten
    metadata=EbdTableMetaData(
        ebd_code="E_0003",
        chapter="MaBiS",
        section="7.39 AD: Bestellung der Aggregationsebene der Bilanzkreissummenzeitreihe auf Ebene der Regelzone",
        ebd_name="Bestellung der Aggregationsebene RZ prüfen",
        role="ÜNB",
    ),
    rows=[
        EbdTableRow(
            step_number="1",
            description="Erfolgt der Eingang der Bestellung fristgerecht?",
            sub_rows=[
                EbdTableSubRow(
                    check_result=EbdCheckResult(result=False, subsequent_step_number=None),
                    result_code="A01",
                    note="Fristüberschreitung",
                ),
                EbdTableSubRow(
                    check_result=EbdCheckResult(result=True, subsequent_step_number="2"),
                    result_code=None,
                    note=None,
                ),
            ],
        ),
        EbdTableRow(
            step_number="2",
            description="Erfolgt die Bestellung zum Monatsersten 00:00 Uhr?",
            sub_rows=[
                EbdTableSubRow(
                    check_result=EbdCheckResult(result=False, subsequent_step_number=None),
                    result_code="A02",
                    note="Gewählter Zeitpunkt nicht zulässig",
                ),
                EbdTableSubRow(
                    check_result=EbdCheckResult(result=True, subsequent_step_number="Ende"),
                    result_code=None,
                    note=None,
                ),
            ],
        ),
    ],
)
assert isinstance(ebd_table, EbdTable)

ebd_graph = convert_table_to_graph(ebd_table)
assert isinstance(ebd_graph, EbdGraph)

Export as PlantUML

from rebdhuhn import convert_graph_to_plantuml

plantuml_code = convert_graph_to_plantuml(ebd_graph)
with open("e_0003.puml", "w+", encoding="utf-8") as uml_file:
    uml_file.write(plantuml_code)

The file e_0003.puml now looks like this:

@startuml
...
if (<b>1: </b> Erfolgt der Eingang der Bestellung fristgerecht?) then (ja)
else (nein)
    :A01;
    note left
        Fristüberschreitung
    endnote
    kill;
endif
if (<b>2: </b> Erfolgt die Bestellung zum Monatsersten 00:00 Uhr?) then (ja)
    end
else (nein)
    :A02;
    note left
        Gewählter Zeitpunkt nicht zulässig
    endnote
    kill;
endif
@enduml

Export the graph as SVG

To export the graph as SVG, you need a Kroki instance. You can either:

• Use the public instance at https://kroki.io
• Run a local instance via Docker: docker run -p 8125:8000 yuzutech/kroki:0.24.1

Then use

from rebdhuhn import convert_plantuml_to_svg_kroki
from rebdhuhn.kroki import Kroki

kroki_client = Kroki()
svg_code = convert_plantuml_to_svg_kroki(plantuml_code, kroki_client)
with open("e_0003.svg", "w+", encoding="utf-8") as svg_file:
    svg_file.write(svg_code)

Error Handling

rebdhuhn provides three base exception classes to help you distinguish between errors in different pipeline stages:

Exception	Pipeline Stage	Description
GraphConversionError	table → graph	Errors during table-to-graph conversion. Affects both SVG and PlantUML.
PlantumlConversionError	graph → puml	Errors specific to PlantUML generation.
SvgConversionError	graph → dot → svg	Errors specific to SVG/DOT generation via Kroki.

This allows you to handle PlantUML failures gracefully while still generating SVG output:

from rebdhuhn import (
    convert_table_to_graph,
    convert_graph_to_plantuml,
    convert_graph_to_dot,
    convert_dot_to_svg_kroki,
    GraphConversionError,
    PlantumlConversionError,
    SvgConversionError,
)
from rebdhuhn.kroki import Kroki

# ebd_table is an instance of EbdTable (see above for how to create one)
kroki_client = Kroki()  # requires a running Kroki instance

try:
    graph = convert_table_to_graph(ebd_table)
except GraphConversionError:
    # Table-to-graph conversion failed - neither SVG nor PlantUML will work
    raise

# SVG generation (primary)
try:
    dot_code = convert_graph_to_dot(graph)
    svg = convert_dot_to_svg_kroki(dot_code, kroki_client)
except SvgConversionError:
    print("SVG generation failed")

# PlantUML generation (secondary)
try:
    puml_code = convert_graph_to_plantuml(graph)
except PlantumlConversionError:
    print("PlantUML generation failed (non-critical)")

How to use this Repository on Your Machine (for development)

Please follow the instructions in our Python Template Repository . And for further information, see the Tox Repository.

Running Tests

Tests use testcontainers to automatically start a Kroki instance when needed. Make sure Docker is installed and running. Tests that require Kroki will be skipped if Docker is not available.

Contribute

You are very welcome to contribute to this template repository by opening a pull request against the main branch.

Related Tools and Context

This repository is part of the Hochfrequenz Libraries and Tools for a truly digitized market communication.