Pypowerbi. 

Python library for PowerBI. Loosely modelled after the C# PowerBI library to keep things somehow consistent.  

Installation (Pypowerbi) 

Pypowerbi  can be installed using pip.In the Command Prompt, type pip install pypowerbi to install your Python package 

Adal 

The ADAL for Python library makes it easy for python application to authenticate to Azure Active Directory (ADD) in order to access AAD protected web resources. 

Requests 

The requests module allows you to send HTTP requests using Python. The HTTP request returns a Response Object with all the response data. 

Client_ID 

The client ID is the unique application (client) ID assigned to you application by Azure AD when the app was registered. 

Access Token. 

Access tokens are used in token-based authentication to allow an application to access an API.  

Python Script  

First step is to import all libraries. 

Import adal 
Import requests
From pypowerbi.dataset import Column, Table, Dataset 
From pypowerbi.client import PowerBIClient 

authority_url = ‘https://login.microsoftonline.com/common/’ 
resource_url = ‘https://analysis.windows.net/powerbi/api‘ 
api_url = ‘https://login.live.com/oauth20_desktop.srf’ 

 Change these to your credentials 

client_id = ‘YOUR CLIENT ID’ 
username = YOUR USERNAME’
password = ‘YOUR PASSWORD!’  

 First you need to authenticate using adal 

context = adal.AuthenticationContext(authority=authority_url, 
                                     validate_authority=True, 
                                     api_version=None)  

Get your authentication token 

token = context.acquire_token_with_username_password(resource=resource_url, 
                                                     client_id=client_id, 
                                                     username=username, 
                                                     password=password)  

Create your powerbi api client 

client = PowerBIClient(api_url, token) 
print(client.token) 

Create your columns 

columns = [] 

columns.append(Column(name=’id’, data_type=’Int64′)) 
columns.append(Column(name=’name’, data_type=’string’)) 
columns.append(Column(name=’is_interesting‘, data_type=’boolean‘)) 
columns.append(Column(name=’cost_usd‘, data_type=’double’)) 
columns.append(Column(name=’purchase_date‘, data_type=’datetime‘)) 

Create your tables 

tables = [] 
tables.append(Table(name=’AnExampleTableName‘, columns=columns)) 

Create your dataset 

dataset = Dataset(name=’AnExampleDatasetName‘, tables=tables)