nexdata-customer-system 1.0.4

This SDK aims to provide customers with a range of features to simplify order management, dataset processing, and data acceptance.

Overview

Welcome to the project description of the Customer Service Python SDK. This SDK aims to provide customers with a range of features to simplify order management, dataset processing, and data acceptance. Through our SDK, you can integrate the following services into your Python applications.

Customer Service

Our customer service system 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 supports customers to accept annotated data according to rules and requirements. We also support viewing the acceptance list, detailed information, and acceptance details in the data acceptance section to help users customers 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 nexdata-customer-system-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', block_size = 100)
upload.execute()