Metadata-Version: 2.1
Name: ebdtable2graph
Version: 0.1.17
Summary: Converts (already scraped) Entscheidungsbaumdiagramm tables to real graphs
Home-page: https://github.com/Hochfrequenz/ebd_table_to_graph
Author: Hochfrequenz Unternehmensberatung GmbH
Author-email: info@hochfrequenz.de
License: mit
Project-URL: Documentation, https://github.com/Hochfrequenz/ebd_table_to_graph
Project-URL: Code, https://github.com/Hochfrequenz/ebd_table_to_graph
Project-URL: Bug tracker, https://github.com/Hochfrequenz/ebd_table_to_graph/issues
Platform: any
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.11
Classifier: Operating System :: OS Independent
Requires-Python: >=3.11
Description-Content-Type: text/markdown; charset=UTF-8
License-File: LICENSE
Requires-Dist: attrs
Requires-Dist: cattrs
Requires-Dist: lxml
Requires-Dist: networkx
Requires-Dist: requests
Requires-Dist: svgutils

# ebdtable2graph

![Unittests status badge](https://github.com/Hochfrequenz/ebd_table_to_graph/workflows/Unittests/badge.svg)
![Coverage status badge](https://github.com/Hochfrequenz/ebd_table_to_graph/workflows/Coverage/badge.svg)
![Linting status badge](https://github.com/Hochfrequenz/ebd_table_to_graph/workflows/Linting/badge.svg)
![Black status badge](https://github.com/Hochfrequenz/ebd_table_to_graph/workflows/Black/badge.svg)
![PyPi Status Badge](https://img.shields.io/pypi/v/ebdtable2graph)

🇩🇪 Dieses Repository enthält ein Python-Paket namens [`ebdtable2graph`](https://pypi.org/project/ebdtable2graph), 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 [`ebdtable2graph`](https://pypi.org/project/ebdtable2graph).

## 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 [`ebddocx2table`](https://github.com/Hochfrequenz/ebddocx2table).)
Also assume, that the result of your scraping is a [`ebdtable2graph.models.EbdTable`](src/ebdtable2graph/models/ebd_table.py).

The package `ebdtable2graph` contains logic to convert your scraped data into a graph.
This graph can then be exported e.g. as SVG and/or UML.

## How to use `ebdtable2graph`?

Install the package from pypi:

```bash
pip install ebdtable2graph
```

### 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.

```python
from ebdtable2graph.graph_conversion import convert_table_to_graph
from ebdtable2graph.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="7.39 AD: Bestellung der Aggregationsebene der Bilanzkreissummenzeitreihe auf Ebene der Regelzone",
        sub_chapter="7.39.1 E_0003_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

```python
from ebdtable2graph 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:

```puml
@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 as SVG

You can also export the graph as SVG

```python
from ebdtable2graph import convert_plantuml_to_svg_kroki

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

![](mwe_e0003.svg)

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

Please follow the instructions in
our [Python Template Repository](https://github.com/Hochfrequenz/python_template_repository#how-to-use-this-repository-on-your-machine)
. And for further information, see the [Tox Repository](https://github.com/tox-dev/tox).

## 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](https://github.com/Hochfrequenz/digital_market_communication/).


