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feat(i18n): update translations (#1437)
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apps/docs/content/docs/de/sdks/python.mdx
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apps/docs/content/docs/de/sdks/python.mdx
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---
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title: Python SDK
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---
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import { Callout } from 'fumadocs-ui/components/callout'
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import { Card, Cards } from 'fumadocs-ui/components/card'
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import { Step, Steps } from 'fumadocs-ui/components/steps'
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import { Tab, Tabs } from 'fumadocs-ui/components/tabs'
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Das offizielle Python SDK für Sim ermöglicht es Ihnen, Workflows programmatisch aus Ihren Python-Anwendungen mithilfe des offiziellen Python SDKs auszuführen.
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<Callout type="info">
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Das Python SDK unterstützt Python 3.8+ und bietet synchrone Workflow-Ausführung. Alle Workflow-Ausführungen sind derzeit synchron.
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</Callout>
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## Installation
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Installieren Sie das SDK mit pip:
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```bash
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pip install simstudio-sdk
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```
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## Schnellstart
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Hier ist ein einfaches Beispiel für den Einstieg:
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```python
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from simstudio import SimStudioClient
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# Initialize the client
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client = SimStudioClient(
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api_key="your-api-key-here",
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base_url="https://sim.ai" # optional, defaults to https://sim.ai
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)
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# Execute a workflow
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try:
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result = client.execute_workflow("workflow-id")
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print("Workflow executed successfully:", result)
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except Exception as error:
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print("Workflow execution failed:", error)
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```
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## API-Referenz
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### SimStudioClient
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#### Konstruktor
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```python
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SimStudioClient(api_key: str, base_url: str = "https://sim.ai")
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```
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**Parameter:**
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- `api_key` (str): Ihr Sim API-Schlüssel
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- `base_url` (str, optional): Basis-URL für die Sim API
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#### Methoden
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##### execute_workflow()
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Führt einen Workflow mit optionalen Eingabedaten aus.
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```python
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result = client.execute_workflow(
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"workflow-id",
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input_data={"message": "Hello, world!"},
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timeout=30.0 # 30 seconds
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)
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```
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**Parameter:**
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- `workflow_id` (str): Die ID des auszuführenden Workflows
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- `input_data` (dict, optional): Eingabedaten, die an den Workflow übergeben werden
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- `timeout` (float, optional): Timeout in Sekunden (Standard: 30.0)
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**Rückgabewert:** `WorkflowExecutionResult`
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##### get_workflow_status()
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Ruft den Status eines Workflows ab (Deployment-Status usw.).
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```python
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status = client.get_workflow_status("workflow-id")
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print("Is deployed:", status.is_deployed)
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```
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**Parameter:**
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- `workflow_id` (str): Die ID des Workflows
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**Rückgabe:** `WorkflowStatus`
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##### validate_workflow()
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Überprüft, ob ein Workflow für die Ausführung bereit ist.
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```python
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is_ready = client.validate_workflow("workflow-id")
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if is_ready:
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# Workflow is deployed and ready
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pass
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```
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**Parameter:**
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- `workflow_id` (str): Die ID des Workflows
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**Rückgabe:** `bool`
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##### execute_workflow_sync()
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<Callout type="info">
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Derzeit ist diese Methode identisch mit `execute_workflow()`, da alle Ausführungen synchron sind. Diese Methode wird für zukünftige Kompatibilität bereitgestellt, wenn asynchrone Ausführung hinzugefügt wird.
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</Callout>
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Führt einen Workflow aus (derzeit synchron, identisch mit `execute_workflow()`).
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```python
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result = client.execute_workflow_sync(
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"workflow-id",
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input_data={"data": "some input"},
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timeout=60.0
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)
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```
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**Parameter:**
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- `workflow_id` (str): Die ID des auszuführenden Workflows
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- `input_data` (dict, optional): Eingabedaten, die an den Workflow übergeben werden
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- `timeout` (float): Timeout für die initiale Anfrage in Sekunden
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**Rückgabe:** `WorkflowExecutionResult`
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##### set_api_key()
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Aktualisiert den API-Schlüssel.
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```python
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client.set_api_key("new-api-key")
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```
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##### set_base_url()
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Aktualisiert die Basis-URL.
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```python
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client.set_base_url("https://my-custom-domain.com")
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```
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##### close()
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Schließt die zugrunde liegende HTTP-Sitzung.
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```python
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client.close()
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```
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## Datenklassen
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### WorkflowExecutionResult
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```python
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@dataclass
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class WorkflowExecutionResult:
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success: bool
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output: Optional[Any] = None
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error: Optional[str] = None
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logs: Optional[List[Any]] = None
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metadata: Optional[Dict[str, Any]] = None
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trace_spans: Optional[List[Any]] = None
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total_duration: Optional[float] = None
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```
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### WorkflowStatus
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```python
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@dataclass
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class WorkflowStatus:
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is_deployed: bool
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deployed_at: Optional[str] = None
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is_published: bool = False
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needs_redeployment: bool = False
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```
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### SimStudioError
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```python
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class SimStudioError(Exception):
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def __init__(self, message: str, code: Optional[str] = None, status: Optional[int] = None):
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super().__init__(message)
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self.code = code
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self.status = status
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```
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## Beispiele
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### Grundlegende Workflow-Ausführung
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<Steps>
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<Step title="Client initialisieren">
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Richten Sie den SimStudioClient mit Ihrem API-Schlüssel ein.
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</Step>
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<Step title="Workflow validieren">
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Prüfen Sie, ob der Workflow bereitgestellt und für die Ausführung bereit ist.
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</Step>
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<Step title="Workflow ausführen">
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Führen Sie den Workflow mit Ihren Eingabedaten aus.
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</Step>
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<Step title="Ergebnis verarbeiten">
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Verarbeiten Sie das Ausführungsergebnis und behandeln Sie eventuelle Fehler.
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</Step>
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</Steps>
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```python
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import os
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from simstudio import SimStudioClient
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client = SimStudioClient(api_key=os.getenv("SIMSTUDIO_API_KEY"))
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def run_workflow():
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try:
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# Check if workflow is ready
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is_ready = client.validate_workflow("my-workflow-id")
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if not is_ready:
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raise Exception("Workflow is not deployed or ready")
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# Execute the workflow
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result = client.execute_workflow(
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"my-workflow-id",
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input_data={
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"message": "Process this data",
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"user_id": "12345"
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}
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)
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if result.success:
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print("Output:", result.output)
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print("Duration:", result.metadata.get("duration") if result.metadata else None)
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else:
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print("Workflow failed:", result.error)
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except Exception as error:
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print("Error:", error)
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run_workflow()
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```
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### Fehlerbehandlung
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Behandeln Sie verschiedene Fehlertypen, die während der Workflow-Ausführung auftreten können:
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```python
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from simstudio import SimStudioClient, SimStudioError
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import os
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client = SimStudioClient(api_key=os.getenv("SIMSTUDIO_API_KEY"))
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def execute_with_error_handling():
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try:
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result = client.execute_workflow("workflow-id")
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return result
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except SimStudioError as error:
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if error.code == "UNAUTHORIZED":
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print("Invalid API key")
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elif error.code == "TIMEOUT":
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print("Workflow execution timed out")
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elif error.code == "USAGE_LIMIT_EXCEEDED":
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print("Usage limit exceeded")
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elif error.code == "INVALID_JSON":
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print("Invalid JSON in request body")
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else:
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print(f"Workflow error: {error}")
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raise
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except Exception as error:
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print(f"Unexpected error: {error}")
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raise
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```
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### Verwendung des Kontextmanagers
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Verwenden Sie den Client als Kontextmanager, um die Ressourcenbereinigung automatisch zu handhaben:
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```python
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from simstudio import SimStudioClient
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import os
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# Using context manager to automatically close the session
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with SimStudioClient(api_key=os.getenv("SIMSTUDIO_API_KEY")) as client:
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result = client.execute_workflow("workflow-id")
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print("Result:", result)
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# Session is automatically closed here
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```
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### Batch-Workflow-Ausführung
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Führen Sie mehrere Workflows effizient aus:
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```python
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from simstudio import SimStudioClient
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import os
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client = SimStudioClient(api_key=os.getenv("SIMSTUDIO_API_KEY"))
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def execute_workflows_batch(workflow_data_pairs):
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"""Execute multiple workflows with different input data."""
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results = []
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for workflow_id, input_data in workflow_data_pairs:
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try:
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# Validate workflow before execution
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if not client.validate_workflow(workflow_id):
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print(f"Skipping {workflow_id}: not deployed")
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continue
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result = client.execute_workflow(workflow_id, input_data)
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results.append({
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"workflow_id": workflow_id,
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"success": result.success,
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"output": result.output,
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"error": result.error
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})
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except Exception as error:
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results.append({
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"workflow_id": workflow_id,
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"success": False,
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"error": str(error)
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})
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return results
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# Example usage
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workflows = [
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("workflow-1", {"type": "analysis", "data": "sample1"}),
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("workflow-2", {"type": "processing", "data": "sample2"}),
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]
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results = execute_workflows_batch(workflows)
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for result in results:
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print(f"Workflow {result['workflow_id']}: {'Success' if result['success'] else 'Failed'}")
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```
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### Umgebungskonfiguration
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Konfigurieren Sie den Client mit Umgebungsvariablen:
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<Tabs items={['Development', 'Production']}>
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<Tab value="Development">
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```python
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import os
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from simstudio import SimStudioClient
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# Development configuration
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client = SimStudioClient(
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api_key=os.getenv("SIMSTUDIO_API_KEY"),
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base_url=os.getenv("SIMSTUDIO_BASE_URL", "https://sim.ai")
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)
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```
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</Tab>
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<Tab value="Production">
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```python
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import os
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from simstudio import SimStudioClient
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# Production configuration with error handling
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api_key = os.getenv("SIMSTUDIO_API_KEY")
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if not api_key:
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raise ValueError("SIMSTUDIO_API_KEY environment variable is required")
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client = SimStudioClient(
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api_key=api_key,
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base_url=os.getenv("SIMSTUDIO_BASE_URL", "https://sim.ai")
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)
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```
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</Tab>
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</Tabs>
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## API-Schlüssel erhalten
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<Steps>
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<Step title="Bei Sim anmelden">
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Navigieren Sie zu [Sim](https://sim.ai) und melden Sie sich bei Ihrem Konto an.
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</Step>
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<Step title="Ihren Workflow öffnen">
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Navigieren Sie zu dem Workflow, den Sie programmatisch ausführen möchten.
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</Step>
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<Step title="Ihren Workflow bereitstellen">
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Klicken Sie auf "Deploy", um Ihren Workflow bereitzustellen, falls dies noch nicht geschehen ist.
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</Step>
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<Step title="API-Schlüssel erstellen oder auswählen">
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Wählen Sie während des Bereitstellungsprozesses einen API-Schlüssel aus oder erstellen Sie einen neuen.
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</Step>
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<Step title="API-Schlüssel kopieren">
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Kopieren Sie den API-Schlüssel zur Verwendung in Ihrer Python-Anwendung.
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</Step>
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</Steps>
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<Callout type="warning">
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Halte deinen API-Schlüssel sicher und committe ihn niemals in die Versionskontrolle. Verwende Umgebungsvariablen oder sicheres Konfigurationsmanagement.
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</Callout>
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## Anforderungen
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- Python 3.8+
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- requests >= 2.25.0
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## Lizenz
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Apache-2.0
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