Metadata-Version: 2.1
Name: qubicon
Version: 3.5.14
Summary: Python SDK for interacting with the Qubicon platform through the library or CLI
Home-page: 
Author: Olivier Guillet
Author-email: olivier.guillet@qubicon.io
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: attrs==25.1.0
Requires-Dist: httpx==0.28.1
Requires-Dist: pandas==2.2.3
Requires-Dist: rapidfuzz==3.9.6
Requires-Dist: rich==13.9.4
Requires-Dist: setuptools==68.2.2
Requires-Dist: tabulate==0.9.0
Requires-Dist: requests==2.32.3
Requires-Dist: openpyxl==3.1.5

# Qubicon SDK

## Overview

The **Qubicon SDK** is a Python client library designed for interacting with the Qubicon API. It provides methods for authentication, process management, model creation, data extraction, and more.

This SDK wraps the **OpenAPI-generated client** and adds custom functionalities to streamline interactions with the Qubicon platform.

## Usage Modes

The Qubicon SDK can be used in two ways:

1. **As a Python Library** – Import and use the SDK programmatically in your Python applications.
2. **As an Interactive CLI** – Run an interactive command-line interface to execute commands without writing code.

To start the interactive menu, run:

```sh
qubicon-client --interactive
```

All function outputs are returned in **JSON format**, making it easy to parse and integrate with other tools.

## Features

- **Authentication & Token Management**
- **Process Management** (Create, List, Delete Processes & Groups)
- **Model Management** (Create, Fetch, Export Computable Models)
- **Physical Quantities Handling**
- **Process Data Extraction & Export**
- **File Upload & Advanced Model Management**
- **Event Streaming**

## Installation

Install the SDK using pip:

```sh
pip install qubicon
```

Alternatively, install from a local package:

```sh
pip install /path/to/qubicon_package
```

## Quick Start

### 1. **Initialize the SDK**

```python
from qubicon.core import QubiconCore, AuthenticatedClient

# Define base URL (e.g., production or staging server)
BASE_URL = "https://qubicon-hostname"

# Create a client instance
client = AuthenticatedClient(base_url=BASE_URL, token=None)

# Initialize QubiconCore with the authenticated client
qubicon = QubiconCore(client)
```

### 2. **Login to Qubicon**

```python
username = "your_username"
password = "your_password"
token = qubicon.login_user(username, password)
print("Token:", token)
```

### 3. **List Processes**

```python
processes = qubicon.list_processes()
print(processes)
```

### 4. **Create a Process**

```python
new_process = qubicon.create_process(
    name="Test Process",
    recipe_id=1822,
    description="Automated process creation"
)
print(new_process)
```

### 5. **Delete a Process**

```python
response = qubicon.delete_process(process_id=1234)
print(response)
```

---

## API Reference

### **Authentication**

```python
def login_user(username: str, password: str) -> Optional[str]
```

- Logs in a user and retrieves an authentication token.

```python
def refresh_token(refresh_token: str) -> Optional[str]
```

- Refreshes an expired authentication token.

---

### **Process Management**

```python
def list_processes()
```

- Lists all processes with optional filters.

```python
def create_process(name: str, recipe_id: int, description: str = "") -> Optional[Dict[str, Any]]
```

- Creates a new process using a specified recipe.

```python
def start_process(process_id: int) -> bool
```

- Start a process by ID.

```python
def delete_process(process_id: int) -> Optional[Dict[str, Any]]
```

- Deletes a specific process by ID.

```python
def delete_multiple_processes(process_ids: List[int]) -> Dict[int, Optional[Dict[str, Any]]]
```

- Deletes multiple processes in a batch operation.

```python
def create_process_group(name: str) -> Optional[Dict[str, Any]]
```

- Creates a new process group.

```python
def add_processes_to_group(group_id: int, process_ids: List[int]) -> Optional[Dict[str, Any]]
```

- Adds multiple processes to an existing group.

```python
def start_processgroup(group_id: int) -> bool
```

- Start a process group.

```python
def stop_processgroup(group_id: int) -> bool
```

- Stop a process group.

```python
def get_process_state(process_id: int) -> Dict[str, Any]
```

- Fetch the current state for a specific process ID.

```python
def get_active_processes_list_state(
        statuses: List[str] = ["READY", "RUNNING", "WARMING_UP"],
    ) -> List[Dict[str, Any]]
```

- Fetch status data for processes.

---

### **Computable Models**

```python
def list_computable_models()
```

- Lists all available computable models.

```python
def fetch_model_details(model_id: int)
```

- Fetches detailed information about a computable model.

```python
def create_computable_model(model_data: dict) -> Optional[Dict[str, Any]]
```

- Creates a new computable model with the given specifications.

```python
def export_model_to_json(model_id: int, filename: str)
```

- Exports a computable model into an importable JSON format.

---

### **Physical Quantities**

```python
def list_physical_quantities()
```

- Retrieves all available physical quantities.

```python
def create_physical_quantity(pq_dict: Dict[str, Any]) -> Optional[Dict[str, Any]]
```

- Creates a new physical quantity in the system.

```python
def check_existing_physical_quantity(pq_name: str) -> Optional[dict]
```

- Checks if a physical quantity already exists.

---

### **Process Data & Channels**

```python
def extract_channels(process_id: int)
```

- Extracts available channels for a given process.

```python
def extract_process_data(process_id: int, output_format: str = "csv", output_file: str = "process_data.csv")
```

- Extracts and exports process data in a file.

```python
def extract_offline_channels(process_id: int)
```

- Extracts available offline channels for a given process.

```python
def extract_offline_process_data(process_id: int, selected_channels: List[Dict[str, Any]], start_date: [int], end_date: [int])
```

- Extracts and exports offline process data for selected channels and a given period.

```python
def get_process_samplings(self, process_id: int) -> List[Dict[str, Any]]
```

- Fetch detailed sampling data for a given process ID.

```python
def discard_sampling_data(self, external_sampling_id: str, process_id: int) -> bool
```

- Discard a specific external sampling for a given process.

```python
def get_offline_equipment_data(equipment_id: int, process_id: int,)
```

- Get the list of offline data for an offline equipment and a process.

```python
def get_process_tag_values(process_id: int) -> List[Dict[str, Any]]
```

- Fetches process tag values and extracts TagDto with corresponding values.

```python
def set_tag_value(self, process_id: int, tag_value_id: int, new_value: Any) -> Optional[Dict[str, Any]]:
```

- Updates a tag value for a specific process and tag value ID.

---

### **File Upload & Advanced Models**

```python
def upload_file(file_path: str) -> Optional[Dict[str, Any]]
```

- Uploads an external file (e.g., ZIP archive) to Qubicon.

```python
def create_advanced_model(model_data: dict, file_path: str) -> Optional[Dict[str, Any]]
```

- Creates an advanced model that references an external file.

---

### **Sampling**

```python
def generate_and_upload_sampling_plan(process_group_id: int, number_of_samples: int, sample_prefix: str = "Day")
```

- Generates and uploads a sampling plan to the specified process group ID.

```python
def generate_and_upload_sampling_plan_single_process(process_id: int, number_of_samples: int, sample_prefix: str = "Day")
```

- Generates and uploads a sampling plan to the specified process ID.

---

### **Event Streaming**

```python
def stream_events(event_types: List[str], nonce: str)
```

- Streams real-time events from the API.

---
