ppms.customizer.module_reader | PLANTA Online-Hilfe

This page documents the ppms.customizer.module_reader package for consuming module data and converting that to JSON.

Classes

ModuleReader

The ModuleReader class reads a module’s visible data and can return either concrete JSON data or a structural JSON Schema. It respects customizing (visibility, headings, datafield configs) and filters special dataitems.

Reads top-level dataareas and recursively includes child dataareas (including self for recursive relations).
Filters out Background and Button dataitems in both data and schema outputs.
Supports two output formats: JSON (content) and JSON Schema (Draft 2020-12).

Methods

Function	Parameters	Return Value	Description
ModuleReader.__init__`(self, module, query_parameters=None, skip_hidden_fields=True)`	module: PPMS module instance query_parameters: `dict` or `None` skip_hidden_fields: `bool` (default `True`)	`ModuleReader` instance	Initialize a reader for a specific module. `query_parameters` are not relevant when using the `ModuleReader` directly Hidden datafields are skipped when `skip_hidden_fields=True`.
ModuleReader.read_module_data_as_dictionary`(self)`		`dict` with the key `data` containing the module content	Produces data JSON: each top-level DA (by Python ID) maps to an array of records; each record contains visible datafields and nested arrays for child DAs (including self for recursive DAs).
ModuleReader.get_json_schema_definition`(self)`		`dict` (JSON Schema Draft 2020-12)	Produces a schema for the data JSON above.

Function

Parameters

Return Value

Description

ModuleReader.__init__(self, module, query_parameters=None, skip_hidden_fields=True)

module: PPMS module instance

query_parameters: dict or None

skip_hidden_fields: bool (default True)

ModuleReader instance

Initialize a reader for a specific module.

query_parameters are not relevant when using the ModuleReader directly
Hidden datafields are skipped when skip_hidden_fields=True.

ModuleReader.read_module_data_as_dictionary(self)

dict with the key data containing the module content

Produces data JSON: each top-level DA (by Python ID) maps to an array of records; each record contains visible datafields and nested arrays for child DAs (including self for recursive DAs).

ModuleReader.get_json_schema_definition(self)

dict (JSON Schema Draft 2020-12)

Produces a schema for the data JSON above.

Note: All keys are based on the python IDs of the DA / DF. If your top level DA has no python id no data will be returned.

Configuring Field Keys and Values (DatafieldConfig)

Two per-field options influence how keys and values are emitted (applies to data JSON and to type inference in JSON Schema).

To use them set the relevant "Option" in the datafield configuration of the field you want to be exported differently

Option	Meaning	Affects Key	Affects Value	Notes
`use-df-heading`	Use datafield heading instead of Python ID	✅ key = `dfc.get_heading()`	—	If not set, key = customizing name (Python ID).
`get-tech-value`	Use technical/raw value instead of text	—	✅ value = `datafield.get_raw_value()`	If not set, value = `datafield.get_text_value()` (string). In Schema, enables type inference. Without `get-tech-value` all values will be of type `string`

Option

Meaning

Affects Key

Affects Value

Notes

use-df-heading

Use datafield heading instead of Python ID

✅ key = dfc.get_heading()

—

If not set, key = customizing name (Python ID).

get-tech-value

Use technical/raw value instead of text

—

✅ value = datafield.get_raw_value()

If not set, value = datafield.get_text_value() (string).

In Schema, enables type inference.

Without get-tech-value all values will be of type string

Examples

Read schema and data

Python

from ppms import ppms
from ppms.customizer.module_reader import ModuleReader

macro = ppms.get_macro_module()
with macro.open_module('002858') as replanning_module:
    reader = ModuleReader(module=replanning_module)

    schema = reader.get_json_schema_definition()
    data = reader.read_module_data_as_dictionary()

ppms.ui_message_box('schema', schema)
ppms.ui_message_box('data', data)

Example Schema (abridged)

JSON

{
  '$schema': 'https://json-schema.org/draft/2020-12/schema',
  'type': 'object',
  'properties': {
    'data': {
      'type': 'object',
      'properties': {
        'projects': {'type': 'array', 'items': {'$ref': '#/definitions/projects'}}
      }
    }
  },
  'definitions': {
    'projects': {
      'type': 'object',
      'items': {
        'type': 'array',
        'properties': {
          'pr_functional': {'type': 'string'},
          'project_name': {'type': 'string'},
          'pr_prio': {'type': 'string'},
          'pr_type_incarnation': {'type': 'string'},
          'pr_type': {'type': 'string'},
          'planning_type_incarnation': {'type': 'string'},
          'planning_type': {'type': 'string'},
          'pr_code_incarnation': {'type': 'string'},
          'calc_end': {'type': 'string'},
          'requested_end': {'type': 'string'},
          'loaded': {'type': 'string'},
          'last_sched_date': {'type': 'string'},
          'no_of_tasks_real': {'type': 'string'},
          'no_of_links': {'type': 'string'}
        }
      }
    }
  }
}

Example Data (abridged)

JSON

{
  'data': {
    'projects': [
      {
        'pr_functional': 'S+W 20XX',
        'project_name': 'Systempflege und Wartung',
        'pr_prio': '100',
        'pr_type_incarnation': 'Projekt',
        'pr_type': '0',
        'planning_type_incarnation': 'Termintreu',
        'planning_type': '0',
        'pr_code_incarnation': 'A-Projekte',
        'calc_end': '28.11.25',
        'requested_end': '30.11.25',
        'loaded': 'J',
        'last_sched_date': '28.01.25',
        'no_of_tasks_real': '7',
        'no_of_links': ''
      }
    ]
  }
}