datatang-customer-service 1.0.3
This SDK aims to provide customers with a range of features to simplify order management, dataset processing, and data acceptance.
Requires Python: >=3.6

#### Order Services

Our order management service offers a comprehensive set of APIs for querying orders and detailed information about the delivery batches under an order.

#### Dataset Services

Dataset services allow users to upload, download, and view datasets.

#### Data Acceptance Services

Data acceptance includes acceptance lists, details, and end-of-acceptance features, helping users ensure that their orders and datasets meet specific business standards and compliance requirements.

### Prerequisites

- Python 3.6+ (It is recommended to use Python 3.6 or higher)
- pip (Python's package manager)

### Installation

Install the customerService Python SDK using pip:

```
    pip install datatang-customer-service-x.x.x
```

### Configuration

Before using the SDK, some basic configurations are required, including obtaining AppKey and AppSecret, and binding callback links.

#### Obtain AppKey and AppSecret

1. Log in to the customer service system.
2. Go to Personal Center - Application Credentials.
3. Create a new key at "AppKey" and "AppSecret".

#### Configure the SDK

Configure the keys in the code:

  ``` 
  from customerService.auth import Auth
  auth = Auth(app_key='your-app-key', app_secret='your-app-secret')
  ```

### Quick Start

Here is an example of how to use the Customer Service Python SDK for basic operations.

#### Initialize the Client

  ```
  from customerService.auth import Auth
  auth = Auth(app_key='your-app-key', app_secret='your-app-secret')
  ```

#### Query Datasets

  ```
  from customerService.datasets import Datasets
  from customerService.page_params import PageParams
  
  dataset = Datasets(auth)
  page = PageParams()
  json = dataset.dataset_list(dataset_state='state', page=page)
  ```

#### Create a Dataset

  ```
  from customerService.datasets import Datasets
  
  dataset = Datasets(auth)
  dataset.create_dataset(dataset_name='name', order_ids='orderId', storage_area='area')
  ```

#### Get a Dataset

  ```
  from customerService.datasets import Datasets
  
  dataset = Datasets(auth)
  json = dataset.dataset_info(dataset_id='dataset_id')
  ```

#### Update a Dataset

  ```
  from customerService.datasets import Datasets
  
  dataset = Datasets(auth)
  json = dataset.update_dataset(dataset_id='dataset_id', dataset_name='dataset_name', 
  add_order_ids='add_order_ids', remove_order_ids='remove_order_ids')
  ```

#### Delete a Dataset

  ```
  from customerService.datasets import Datasets
  
  dataset = Datasets(auth)
  json = dataset.delete_dataset(dataset_id='dataset_id')
  ```

#### Pagination Handling

  ```
  from customerService.datasets import Datasets
  from customerService.page_params import PageParams
  
  dataset = Datasets(auth)
  page = PageParams()
  page.page_size = 10
  page.page = 1
  json = dataset.dataset_list(dataset_state='dataset_state', page=page)
  ```

#### DataSet Upload

  ```
  from customerService.auth import Auth
  from customerService.datasets import DatasetBatchs, Datasets
  from customerService.upload import Upload
  
  dataset = Datasets(auth)
  dataset_id = dataset.create_dataset(dataset_name='upload_name' + 'dataset_name', 
  order_ids='order_id', storage_area='storage_area')['responseObject']
  batchs = DatasetBatchs(auth)
  batch_id = batchs.create_dataset_batch(dataset_id=dataset_id, batch_name=batch_name, comment='')['responseList'][0]['batchId']
  upload = Upload(auth=auth, dataset_id=dataset_id, batch_id=batch_id, file_path='your_file_path' ,region='your_storage_area')
  upload.execute()
  ```