Power BI Connector for Python In this article you will learn how to integrate Power BI data in Python (live / bi-directional connection to Power BI). Connect to your Power BI account and retrieve data, refresh datasets, etc.. Using Power BI Connector you will be able to connect, read, and write data from within Python. Follow the steps below to see how we would accomplish that. Download Documentation The driver mentioned above is part of ODBC PowerPack which is a collection of high-performance Drivers for various API data source (i.e. REST API, JSON, XML, CSV, Amazon S3 and many more). Using familiar SQL query language you can make live connections and read/write data from API sources or JSON / XML / CSV Files inside SQL Server (T-SQL) or your favorite Reporting (i.e. Power BI, Tableau, Qlik, SSRS, MicroStrategy, Excel, MS Access), ETL Tools (i.e. Informatica, Talend, Pentaho, SSIS). You can also call our drivers from programming languages such as JAVA, C#, Python, PowerShell etc. If you are new to ODBC and ZappySys ODBC PowerPack then check the following links to get started. ODBC PowerPack - System Requirements and Installation Getting Started - Using ODBC PowerPack ODBC API Driver Help File

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Create ODBC Data Source (DSN) based on ZappySys API Driver

Step-by-step instructions

To get data from Power BI using Python we first need to create a DSN (Data Source) which will access data from Power BI. We will later be able to read data using Python. Perform these steps:

1. Install ZappySys ODBC PowerPack.

2. Open ODBC Data Sources (x64):
   

3. Create a User Data Source (User DSN) based on ZappySys API Driver

   ZappySys API Driver

   
   You should create a System DSN (instead of a User DSN) if the client application is launched under a Windows System Account, e.g. as a Windows Service. If the client application is 32-bit (x86) running with a System DSN, use ODBC Data Sources (32-bit) instead of the 64-bit version.

4. When the Configuration window appears give your data source a name if you haven't done that already, then select "Power BI" from the list of Popular Connectors. If "Power BI" is not present in the list, then click "Search Online" and download it. Then set the path to the location where you downloaded it. Finally, click Continue >> to proceed with configuring the DSN:

   PowerBiDSN

   Power BI

   

5. Now it's time to configure the Connection Manager. Select Authentication Type, e.g. Token Authentication. Then select API Base URL (in most cases, the default one is the right one). More info is available in the Authentication section.

    User Credentials [OAuth]

   OAuth App must be created in Microsoft Azure AD. These settings typically found here https://docs.microsoft.com/en-us/graph/auth-register-app-v2. [API Help..]

   Steps to get Power BI Credentials : User Credentials [OAuth]
   

   Firstly, login into Azure Portal and there create an OAuth application:

   1. Go to Azure Portal and login there.
   2. Then go to Azure Active Directory.
   3. On the left side click menu item App registrations
   4. Then proceed with clicking New registration.
   5. Enter a name for your application.
   6. Select the account types to support with the Supported account types option.
   7. In Redirect URI, select Web.
   8. In the textbox enter https://zappysys.com/oauth as the Redirect URI or another valid redirect URL.
   9. Use this same Redirect URI in the Redirect URI (must match App Redirect URL) grid row.
   10. Copy Client ID and paste it into the API Connection Manager configuration grid in the Client ID row.
   11. Click on the Endpoints link and copy the OAuth 2.0 authorization endpoint (v2) URL to the Authorization URL grid row. Usually it looks similar to this:
       • https://login.microsoftonline.com/daed1250-xxxx-xxxx-xxxx-ef0a982d3d1e/oauth2/v2.0/authorize
   12. Copy the OAuth 2.0 token endpoint (v2) URL to the Token URL grid row. Usually it looks similar to this:
       • https://login.microsoftonline.com/daed1250-xxxx-xxxx-xxxx-ef0a982d3d1e/oauth2/v2.0/token
   13. Close "Endpoints" popup and create a Client Secret in the Certificates & secrets tab.
   14. Proceed by clicking New client secret and setting expiration period. Copy the client secret and paste it into configuration grid in Client Secret row.
   15. Now lets setup permissions for the app. Click on API Permissions and on the page click Plus Sign Add Permission
   16. Click on Microsoft Graph API and then choose Delegated Permissions
   17. on Permission list page search or choose permissions as needed. We need to enable following Permissions from 2 Sections: Microsoft Graph API and Power BI Service.
   18. Make sure you have checked below permissions (If you do not need Write feature then you can skip Write scopes)

       offline_access
       Dataset.ReadWrite.All
       

   19. Click Generate Token to generate tokens.
   20. That's it!

   Fill in all required parameters and set optional parameters if needed:

   PowerBiDSN

   Power BI

   User Credentials [OAuth]

   https://api.powerbi.com/v1.0/myorg

   Required Parameters
   Authorization URL	Fill in the parameter...
   Token URL	Fill in the parameter...
   Client ID	Fill in the parameter...
   Scope	Fill in the parameter...
   Default Dataset (select after generating tokens)	Fill in the parameter...
   Optional Parameters
   Client Secret	Fill in the parameter...
   Redirect URI (must match App Redirect URI)	Fill in the parameter...
   Default Workspace (Keep Empty for My Workspace - select after generating tokens)	Fill in the parameter...
   RetryMode	Fill in the parameter...
   RetryStatusCodeList	Fill in the parameter...
   RetryCountMax	Fill in the parameter...
   RetryWaitTimeMs	Fill in the parameter...
   RetryMultiplyWaitTime	Fill in the parameter...
   Login options	Fill in the parameter...

   

6. Once the data source has been configured, you can preview data. Select the Preview tab and use settings similar to the following to preview data:
   

7. Click OK to finish creating the data source.

Video instructions

Read data in Python

Using ODBC DSN

1. Python code to get the data:
   

   PowerBiDSN')

   

2. When you run the code it will make the API call and read the data:
   

3. Here is Python program's code in text format:

   
       import pyodbc
       conn = pyodbc.connect('DSN=PowerBiDSN')
   
       cursor = conn.cursor()
   
       #execute query to fetch data from API service
       cursor.execute("SELECT id,title FROM products")
   
       row = cursor.fetchone()
       while row:
           print(row)
           row = cursor.fetchone()
   
       ##For loop example
       #for row in cursor:
       #    print(row)
   

Using a full ODBC connection string

If you want to avoid being dependent on a DSN and creating multiple DSNs for each platform (x86, x64), then you can use a fully qualified connection string. Simply go to your DSN and copy the Connection String:

1. Open ODBC data source configuration and click Copy settings:
   

   ZappySys API Driver - Power BI

   Connect to your Power BI account and retrieve data, refresh datasets, etc.

   PowerBiDSN

   
2. The window opens, telling us the connection string was successfully copied to the clipboard:

3. Then in your Python code use Connection String when initializing OdbcConnection object, for example:

   conn = pyodbc.connect('DRIVER={ZappySys API Driver};ServiceUrl=https://yourservices.provider.com/api/xxxx....;AuthName=Http;')

How to install `pyodbc` in the Python?

Advanced topics

Create Custom Stored Procedure in ZappySys Driver

You can create procedures to encapsulate custom logic and then only pass handful parameters rather than long SQL to execute your API call.

Steps to create Custom Stored Procedure in ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here

1. Go to Custom Objects Tab and Click on Add button and Select Add Procedure:
   

2. Enter the desired Procedure name and click on OK:
   

3. Select the created Stored Procedure and write the your desired stored procedure and Save it and it will create the custom stored procedure in the ZappySys Driver:
   Here is an example stored procedure for ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here
   

   CREATE PROCEDURE [usp_get_orders]
       @fromdate = '<<yyyy-MM-dd,FUN_TODAY>>'
    AS
       SELECT * FROM Orders where OrderDate >= '<@fromdate>';
   

   
   

4. That's it now go to Preview Tab and Execute your Stored Procedure using Exec Command. In this example it will extract the orders from the date 1996-01-01:
   

   Exec usp_get_orders '1996-01-01';

   
   

5. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC usp_get_orders @fromdate=''1996-07-30''')

   
   

6. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Create Custom Virtual Table in ZappySys Driver

ZappySys API Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

If you're dealing with Microsoft Access and need to import data from an SQL query, it's important to note that Access doesn't allow direct import of SQL queries. Instead, you can create custom objects (Virtual Tables) to handle the import process.

Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 URLs with slight variations you can create virtual tables with just URL as Parameter setting.

1. Go to Custom Objects Tab and Click on Add button and Select Add Table:
   

2. Enter the desired Table name and click on OK:
   

3. And it will open the New Query Window Click on Cancel to close that window and go to Custom Objects Tab.

4. Select the created table, Select Text Type AS SQL and write the your desired SQL Query and Save it and it will create the custom table in the ZappySys Driver:
   Here is an example SQL query for ZappySys Driver. You can insert Placeholders also. Read more about placeholders here
   

   SELECT
     "ShipCountry",
     "OrderID",
     "CustomerID",
     "EmployeeID",
     "OrderDate",
     "RequiredDate",
     "ShippedDate",
     "ShipVia",
     "Freight",
     "ShipName",
     "ShipAddress",
     "ShipCity",
     "ShipRegion",
     "ShipPostalCode"
   FROM "Orders"
   Where "ShipCountry"='USA'

   
   

5. That's it now go to Preview Tab and Execute your custom virtual table query. In this example it will extract the orders for the USA Shipping Country only:
   

   SELECT * FROM "vt__usa_orders_only"

   
   

6. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC [usp_get_orders] ''1996-01-01''')

   
   

7. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Actions supported by Power BI Connector

Power BI Connector Examples for Python Connection

This page offers a collection of SQL examples designed for seamless integration with the ZappySys API ODBC Driver under ODBC Data Source (36/64) or ZappySys Data Gateway, enhancing your ability to connect and interact with Prebuilt Connectors effectively.

SELECT * 
FROM Workspaces

SELECT * 
FROM Workspaces
WHERE Id='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'

SELECT * 
FROM Datasets

SELECT * 
FROM Datasets
WITH (WorkspaceId = 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')

SELECT * 
FROM Datasets
WHERE Id='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'

SELECT * 
FROM create_push_dataset
WITH (Definition='{
  "name": "My Push Dataset Name",
  "defaultMode": "Push",
  "tables": [
	{
      "name": "Products",
      "columns": [
        {
          "name": "Id",
          "dataType": "Int64"
        },
        {
          "name": "Name",
          "dataType": "string"
        },
        {
          "name": "Category",
          "dataType": "string"
        },
        {
          "name": "IsComplete",
          "dataType": "bool"
        },
        {
          "name": "ManufacturedOn",
          "dataType": "DateTime"
        },
        {
          "name": "Sales",
          "dataType": "Int64",
          "formatString": "Currency"
        },        
        {
          "name": "Price",
          "dataType": "Double",
          "formatString": "Currency"
        }
      ]
    }
  ]
}'
)

-- More info on creating a Push Dataset:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/push-datasets/datasets-post-dataset

SELECT * 
FROM create_push_dataset
WITH (Definition='{
  "name": "My Push Dataset Name",
  "defaultMode": "Push",
  "tables": [
     {
      "name": "Customers",
      "columns": [
        {
          "name": "Id",
          "dataType": "Int64"
        },
        {
          "name": "Name",
          "dataType": "string"
        }
      ]
    },
	{
      "name": "Products",
      "columns": [
        {
          "name": "Id",
          "dataType": "Int64"
        },
        {
          "name": "Name",
          "dataType": "string"
        },
        {
          "name": "Category",
          "dataType": "string"
        },
        {
          "name": "IsComplete",
          "dataType": "bool"
        },
        {
          "name": "ManufacturedOn",
          "dataType": "DateTime"
        },
        {
          "name": "Sales",
          "dataType": "Int64",
          "formatString": "Currency"
        },        
        {
          "name": "Price",
          "dataType": "Double",
          "formatString": "Currency"
        }
      ]
    }
  ]
}'
)

-- More info on creating a Push Dataset:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/push-datasets/datasets-post-dataset

SELECT *
FROM delete_dataset
WHERE Id = 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'

-- More info on deleting a Dataset:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/datasets/delete-dataset

SELECT *
FROM refresh_dataset
WHERE Id = 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'
                
-- More info on refreshing a Dataset:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/datasets/refresh-dataset

SELECT * 
FROM get_tables

SELECT * 
FROM get_tables
WITH (DatasetId='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')

SELECT * 
FROM get_table_columns
WITH (TableName='MyTable')

SELECT * 
FROM get_table_columns
WITH (TableName='MyTable',
      DatasetId='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')

SELECT * 
FROM MyTable

SELECT *
FROM get_table_rows
WITH(
	  "TableName"='Products'
	, "DatasetId"='11b6c287-51d3-4061-bed8-811a4e5f6ce9'
	, "WorkspaceId"='848353e2-f3b1-4fb4-89d7-44e84b8bdf9f'
)

INSERT INTO Products 
SOURCE(
  'MSSQL',
  'Data Source=localhost\developer;Initial Catalog=Northwind;Integrated Security=true',
  '  SELECT T.* FROM (       SELECT  TOP 50                
      ProductName AS [Name]              
      ,C.CategoryName AS Category              
      ,Discontinued AS IsComplete              
      ,GETDATE() AS ManufacturedOn              
      ,CAST(UnitPrice * ReOrderLevel * 100 AS BIGINT) AS Sales              
      ,CAST(UnitPrice AS DECIMAL) AS Price       
      FROM Northwind.dbo.Products AS P       
      JOIN Northwind.dbo.Categories C ON P.CategoryId = P.CategoryId       
      ) AS T              
      CROSS JOIN GENERATE_SERIES(1, 2000)             
      -- COMMENT:  50 x 2000 = 100 000 rows  
   '
) 
CONNECTION(
  Parameters = '[{ Name: "TokenUrl",Value:"https://login.microsoftonline.com/organizations/oauth2/v2.0/token"}                         
  ,{ Name: "DatasetId",Value: "6a0e04da-a6e4-4533-abe4-30fcabd0e2a5"},                      
  { Name: "WorkspaceId",Value: "848353e2-f3b1-4fb4-89d7-44e84b8bdf9f"}]'
)

INSERT INTO MyTable(MyColumn1, MyColumn2, MyColumn3, MyColumn4, MyColumn5)
VALUES (1001, 'Glass', true, '2001-02-03', 195.95)

INSERT INTO MyTable(MyColumn1, MyColumn2, MyColumn3, MyColumn4, MyColumn5)
VALUES (1001, 'Glass', true, '2001-02-03', 195.95)
WITH (DatasetId='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')

SELECT * 
FROM get_table_rows 
WITH (TableName='MyTable')

SELECT * 
FROM get_table_rows 
WITH (TableName='MyTable', DatasetId='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')

SELECT *
FROM truncate_push_dataset_table
WITH (TableName='MyTable')
                
-- More info on truncating a Push Dataset Table:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/push-datasets/datasets-delete-rows

SELECT *
FROM truncate_push_dataset_table
WITH (DatasetId='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee', TableName='MyTable')
                
-- More info on truncating a Push Dataset Table:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/push-datasets/datasets-delete-rows

SELECT * 
FROM execute_dax_query
WITH (Query='EVALUATE ''MyTable''')

-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/st/evaluate/
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/filter-functions-dax
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM execute_dax_query 
WITH (Query='EVALUATE FILTER(''MyTable'', [MyColumn] = "MyValue"')

-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/st/evaluate/
-- https://dax.guide/filter/
-- https://dax.guide/operators/
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM execute_dax_query 
WITH (Query='EVALUATE FILTER(''MyTable'', [MyColumn1] = "MyValue" && ([MyColumn2] > 0 || [MyColumn3] <= 1000))')

-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/operators/
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM execute_dax_query
WITH (Query='EVALUATE 
             SELECTCOLUMNS (
                ''MyTable'',
                "MyColumn1 alias", [MyColumn1],
                "MyColumn2 alias", [MyColumn2]
             )
             ORDER BY "MyColumn2 alias"'
    )
    
-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/st/evaluate/
-- https://dax.guide/selectcolumns/   
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM execute_dax_query
WITH (Query='EVALUATE 
             TOPN(1000, ''MyTable'', [MyColumnOrExpression], ASC)')

-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/st/evaluate/
-- https://dax.guide/topn/
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM execute_dax_query
WITH (Query='
DEFINE
    VAR MinimumAmount = 2000000
    VAR MaximumAmount = 8000000
EVALUATE
FILTER (
    ADDCOLUMNS (
        SUMMARIZE (Sales, Products[Category]),
        "CategoryAmount", [Sales Amount]
    ),
    AND (
        [CategoryAmount] <= MinimumAmount,
        [CategoryAmount] >= MaximumAmount
    )
)
ORDER BY [CategoryAmount]"')

-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/st/evaluate/
-- https://dax.guide/addcolumns/
-- https://dax.guide/summarize/
-- https://dax.guide/st/order-by/
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/filter-functions-dax
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM generic_request
WITH (Url='/groups',
Filter='$.value[*]')


/*
EXPLANATION:
- This configuration calls Power BI REST API "Get Groups" endpoint and gets the Workspaces back.
- This is achieved by "/groups" value in the "Url" parameter.
- The SQL query parameter "Filter" uses JsonPath "$.value[*]".
- This gets JSON objects from "value" array and transforms them into SQL rows.

MORE INFORMATION:
- About "Get Groups" REST API endpoint:
  https://learn.microsoft.com/en-us/rest/api/power-bi/groups/get-groups
- About JsonPath used in "Filter" parameter:
  https://zappysys.com/blog/jsonpath-examples-expression-cheetsheet  
*/

SELECT * 
FROM generic_request
WITH (Url='/groups?$filter=contains(name,''MyWorkspace'') or name eq ''My Blue Workspace''',
Filter='$.value[*]')


/*
EXPLANATION:
- This configuration calls Power BI REST API "Get Groups" endpoint and gets the Workspaces back.
- This is achieved by "/groups" value in the "Url" parameter.
- Workspaces are filtered on the Power BI REST API side by using the "$filter" URL parameter.
- Only those Workspaces are returned that:
  > contain a string value "MyWorkspace" or
  > if the Workspace name is "My Blue Workspace" (each single quote is escaped with two single quotes).
- The SQL query parameter "Filter" uses JsonPath "$.value[*]".
- This gets JSON objects from "value" array and transforms them into SQL rows.

MORE INFORMATION:
- About "Get Groups" REST API endpoint:
  https://learn.microsoft.com/en-us/rest/api/power-bi/groups/get-groups
- About JsonPath used in "Filter" parameter:
  https://zappysys.com/blog/jsonpath-examples-expression-cheetsheet  
*/

Conclusion

In this article we discussed how to connect to Power BI in Python and integrate data without any coding. Click here to Download Power BI Connector for Python and try yourself see how easy it is. If you still have any question(s) then ask here or simply click on live chat icon below and ask our expert (see bottom-right corner of this page).

Download Power BI Connector for Python Documentation 

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