🇩🇪 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.
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.
Install the package from pypi:
pip install rebdhuhnEbdTable 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="ÃœNB",
),
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)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
@endumlTo 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)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)")Please follow the instructions in our Python Template Repository . And for further information, see the Tox Repository.
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.
You are very welcome to contribute to this template repository by opening a pull request against the main branch.
This repository is part of the Hochfrequenz Libraries and Tools for a truly digitized market communication.