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Pre-release

This release is a pre-release and may not be stable for production use.

Seven2one Questra Data

Python Client für die Questra Data Platform – Verwaltung von benutzerdefinierten Datenmodellen, Zeitreihen und Berechtigungen.

Features

  • Data Client: Vereinfachte Schnittstelle für häufige Operationen
  • Typsichere Dataclasses: IDE-Unterstützung mit Type Hints
  • Zeitreihen-Verwaltung: Effiziente Verwaltung von TimeSeries-Daten
  • CRUD-Operationen: Für benutzerdefinierte Datenmodelle
  • Optional: pandas Integration: DataFrames für Analyse-Workflows

Installation

# Basis-Installation
pip install seven2one-questra-data

# Mit pandas-Unterstützung (empfohlen für Data Science)
pip install seven2one-questra-data[pandas]

Siehe INSTALLATION.md für detaillierte Installations-Anleitungen.

Schnellstart

from seven2one.questra.authentication import QuestraAuthentication
from seven2one.questra.data import QuestraData
from datetime import datetime

# Authentifizierung
auth = QuestraAuthentication(
    url="https://auth.example.com",
    username="user",
    password="pass"
)

# Client initialisieren
client = QuestraData(
    graphql_url="https://api.example.com/data-service/graphql",
    auth_client=auth
)

# Inventory Items auflisten
items = client.list_items(
    inventory_name="Devices",
    namespace_name="IoT",
    properties=["_id", "name", "status"],
    first=10
)

# Zeitreihen-Werte laden
result = client.list_timeseries_values(
    inventory_name="Sensors",
    namespace_name="IoT",
    timeseries_properties="measurements",
    from_time=datetime(2025, 1, 1),
    to_time=datetime(2025, 1, 31)
)

# Optional: Als pandas DataFrame
df = result.to_df()

Inventory erstellen

from seven2one.questra.data import StringProperty, IntProperty

properties = [
    StringProperty(property_name="name", max_length=200, is_required=True),
    IntProperty(property_name="age")
]

client.create_inventory(name="Users", properties=properties)

pandas Integration

# Alle Result-Objekte haben .to_df() Methode
df = result.to_df()
df_items = items.to_df()

Weitere Informationen

Requirements

  • Python >= 3.10
  • gql >= 3.5.0
  • requests >= 2.31.0
  • questra-authentication >= 0.1.4

Optional

  • pandas >= 2.0.0 (für DataFrame-Unterstützung)

License

Proprietary - Seven2one Informationssysteme GmbH

Release files for seven2one-questra-data 3.3.0rc1

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