bioprocess-intelligence 0.2.0

A Python client for interacting with the Bioprocess Intelligence platform

Bioprocess Intelligence Python Client

This is the official Python client for interacting with Bioprocess Intelligence – a comprehensive platform for digital bioprocess development and operation.

The client provides programmatic access to the Bioprocess Intelligence API, enabling users to integrate, manage, and analyze bioprocess data. It supports common operations such as managing teams, collections, and processes, and importing structured data from various formats.

As the platform evolves, the client will be extended to cover additional capabilities including real-time data integration, statistical analysis, mechanistic modeling, and more.

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Features

• Authenticate using environment variables.
• List teams and collections.
• Create, retrieve, update, and delete processes.
• Import process data from YAML and JSON content.
• Monitor background tasks.

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Installation

pip install bioprocess-intelligence

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Getting Started

Authentication Methods

The client supports multiple authentication methods:

1. Username/Password Authentication

1. Create a .env file in your project root:

BPI_API_URL=https://your-api-url
BPI_USERNAME=your_username
BPI_PASSWORD=your_password

2. Initialize the client:

from bioprocess_intelligence.client import BioprocessIntelligenceClient
import os
from dotenv import load_dotenv
from pathlib import Path

load_dotenv(Path(__file__).parent / ".env")

client = BioprocessIntelligenceClient(
    api_url=os.getenv("BPI_API_URL"),
    username=os.getenv("BPI_USERNAME"),
    password=os.getenv("BPI_PASSWORD")
)

2. Microsoft Azure Active Directory (AAD) Authentication

For applications using Microsoft authentication, you can authenticate using either a Microsoft ID token or access token:

# Using Microsoft ID token (OAuth2/OIDC flow)
client = BioprocessIntelligenceClient(
    api_url="https://your-api-url",
    microsoft_id_token="eyJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiIs..."
)

# Using Microsoft access token (API access flow)
client = BioprocessIntelligenceClient(
    api_url="https://your-api-url",
    microsoft_access_token="eyJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiIs..."
)

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Example Usage

List Teams

teams = client.list_teams()
print("Teams:", teams)

Get Collections in a Team

collections = client.list_collections(team_id=5)

Get or Create a Process

try:
    process = client.get_process(name="New process", collection_id=123)
except:
    process = client.create_process(
        name="New process",
        collection_id=123
    )

Update a Process

process = client.update_process(
    process_id=process['id'],
    name="Updated name",
    description="Updated description",
    start_time="2024-01-01T10:00:00+01:00",
    end_time="2024-01-07T15:00:00+01:00"
)

Delete a Process

client.delete_process(process['id'])

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Importing Process Data

From YAML Content

from pathlib import Path

script_dir = Path(__file__).parent
yaml_file = script_dir / "files/process_import_template_v1.yaml"

try:
    content = yaml_file.read_text(encoding="utf-8")
    result = client.import_process_from_yaml(
        collection_id=123,
        content=content,
        timezone="UTC"
    )
    print("Import result:", result)
    client.monitor_background_task(result["backgroundTaskId"])
except Exception as e:
    print(f"Error importing process from YAML: {e}")

From JSON Content

import json

# Sample JSON data for import
json_data = {
    "process": {
        "MetaData": [
            {"name": "ProcessName", "value": "P_20250101_JSON"},
            {"name": "ProcessDescription", "value": "Process imported from JSON"},
            {"name": "Timezone", "value": "UTC"},
            {"name": "StartTime", "value": "01.01.2025-10:00:00"}
        ],
        "Parameters": [
            {"name": "Temperature", "value": 37.0, "units": "°C", "description": "Incubation temperature"},
            {"name": "Agitation", "value": 150, "units": "rpm"}
        ],
        "Variable_Group_1": [{
            "Timestamp": ["01.01.2025-10:00:00", "01.01.2025-11:00:00", "01.01.2025-12:00:00"],
            "Variables": [
                {
                    "name": "OD600",
                    "units": "AU",
                    "data": [0.1, 0.2, 0.35],
                    "description": "Optical density at 600nm"
                }
            ]
        }]
    }
}

try:
    # Convert to JSON string
    json_string = json.dumps(json_data)

    # Import JSON data (with async mode)
    result = client.import_process_from_json(
        json_data=json_string,
        collection_id=123,
        timezone="UTC",
        async_mode=True
    )
    print("JSON Import result:", result)

    if 'backgroundTaskId' in result:
        # Monitor the background task
        client.monitor_background_task(result["backgroundTaskId"])
    elif 'processId' in result:
        print(f"Process created synchronously with ID: {result['processId']}")

except Exception as e:
    print(f"Error importing process from JSON: {e}")

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Background Task Monitoring

Many operations like data imports run as background tasks. You can monitor their progress:

# Import data (returns background task info)
result = client.import_process_from_yaml(
    collection_id=123,
    content=yaml_content,
    timezone="UTC"
)

# Or import JSON data
result = client.import_process_from_json(
    json_data=json_string,
    collection_id=123,
    timezone="UTC",
    async_mode=True
)

# Monitor the background task until completion
task_id = result["backgroundTaskId"]
status_info = client.monitor_background_task(task_id)
print("Task completed:", status_info)

Process Retrieval

Get Process by ID

process = client.get_process(process_id="456")

Get Process by Name and Collection

# Retrieve a process by its name within a specific collection
process = client.get_process(
    name="P_20250101_A02", 
    collection_id=123
)
print("Found process:", process['id'])

This is particularly useful after importing YAML data when you know the process name but need to retrieve the generated process ID for further operations.

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Error Handling

Make sure to wrap API calls in try-except blocks to handle errors gracefully, especially when importing data or querying resources.

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License

This client is proprietary software distributed in binary form.

• Free for academic and non-commercial research use
• A commercial license is required for any commercial or for-profit use

To request a commercial license, please contact us at [e-mail].