A Python Library for interacting with the Power BI Rest API.
Project description
pbipy
pbipy
is a Python Library for interacting with the Power BI Rest API. It aims to simplyify working with the Power BI Rest API and support programatic administration of Power BI in Python.
pbipy
supports operations for Apps, Datasets, Groups (Workspaces) and Reports, allowing users to perform actions on their PowerBI instance using Python.
See development progress below for what's been implemented and what's coming.
Installation
pip install pbipy
Or to install the latest development code:
pip install git+https://github.com/andrewvillazon/pbipy
Getting Started: Authentication
To use pbipy
you'll first need to acquire a bearer_token
.
How do I get a bearer_token
?
To acquire a bearer_token
you'll need to authenticate against your Registered Azure Power BI App. Registering is the first step in turning on the Power BI Rest API, so from this point on it's assumed your Power BI Rest API is up and running.
To authenticate against the Registered App, Microsoft provides the MSAL
and azure-identity
python libraries. These libraries support many different ways of acquiring a bearer_token
.
Because there are multiple ways to acquire the token, pbipy
assumes you'll do this in the way that suits, rather than directly handling authentication (of course, this might change in future).
This README
doesn't cover Authentication in detail, however, these are some helpful resources that look at acquiring a bearer_token
in the context of Power BI:
- Power BI REST API with Python and MSAL. Part II.
- Power BI REST API with Python Part III, azure-identity
- Monitoring Power BI using REST APIs from Python
The example below uses the msal
library to to get a bearer_token
.
Useage
Start by creating the PowerBI()
client. All interactions with the Power BI Rest API go through this object.
import msal
from pbipy import PowerBI
# msal auth setup
def acquire_bearer_token(username, password, azure_tenant_id, client_id, scopes):
app = msal.PublicClientApplication(client_id, authority=azure_tenant_id)
result = app.acquire_token_by_username_password(username, password, scopes)
return result["access_token"]
bearer_token = acquire_bearer_token(
username="your-username",
password="your-password",
azure_tenant_id="https://login.microsoftonline.com/your-azure-tenant-id",
client_id="your-pbi-client-id",
scopes=["https://analysis.windows.net/powerbi/api/.default"],
)
# Create Client
pbi = PowerBI(bearer_token)
To interact with the API, simply call the relevant method from the client.
# Grab the datasets from a workspace
pbi.datasets(group="f089354e-8366-4e18-aea3-4cb4a3a50b48")
pbipy
converts API responses into regular Python objects, with snake case included! 🐍🐍
sales = pbi.dataset("cfafbeb1-8037-4d0c-896e-a46fb27ff229")
print(type(sales))
print(hasattr(sales, "configured_by"))
# <class 'pbipy.resources.Dataset'>
# True
Most methods take in an object id...
dataset = pbi.dataset("cfafbeb1-8037-4d0c-896e-a46fb27ff229", group="a2f89923-421a-464e-bf4c-25eab39bb09f")
... or just pass in the object itself.
group = pbi.group("a2f89923-421a-464e-bf4c-25eab39bb09f")
dataset = pbi.dataset("cfafbeb1-8037-4d0c-896e-a46fb27ff229", group=group)
If you need to access the raw json representation, this is supported to.
sales = pbi.dataset("cfafbeb1-8037-4d0c-896e-a46fb27ff229")
print(sales.raw)
# {
# "id": "cfafbeb1-8037-4d0c-896e-a46fb27ff229",
# "name": "SalesMarketing",
# "addRowsAPIEnabled": False,
# "configuredBy": "john@contoso.com",
# ...
# }
Example: Working with Datasets
Let's see how pbipy
works by performing some operations on a Dataset.
First, we need to load the Dataset from the API. To do this, we call the dataset()
method from the pbi
client we created above.
The Power BI Rest API will look for the Dataset in the current user's workspace if we don't provide a group argument.
sales = pbi.dataset(id="cfafbeb1-8037-4d0c-896e-a46fb27ff229")
print(sales)
# <Dataset id='cfafbeb1-8037-4d0c-896e-a46fb27ff229', name='SalesMarketing', ...>
But we likely want to target a Dataset in a Workspace. To do this, we provide the group_id
when we call the dataset()
method.
sales = pbi.dataset(
"cfafbeb1-8037-4d0c-896e-a46fb27ff229",
group="f089354e-8366-4e18-aea3-4cb4a3a50b48",
)
Now that we've got our target Dataset let's look at its Refresh History. We call the refresh_history()
method on our Dataset. Easy.
dataset = pbi.dataset(
"cfafbeb1-8037-4d0c-896e-a46fb27ff229",
group="f089354e-8366-4e18-aea3-4cb4a3a50b48",
)
refresh_history = dataset.refresh_history()
for entry in refresh_history:
print(entry)
# {"refreshType":"ViaApi", "startTime":"2017-06-13T09:25:43.153Z", "status": "Completed" ...}
How about adding some user permissions to our Dataset? That's easy too. Just call the add_user()
method with the User's details and permissions.
sales_ds = pbi.dataset( "cfafbeb1-8037-4d0c-896e-a46fb27ff229")
# Give John 'Read' access on the dataset
sales_ds.add_user("john@contoso.com", "User", "Read")
Lastly, if we're feeling adventurous, we can execute DAX against a Dataset and use the results in Python.
dataset = pbi.dataset( "cfafbeb1-8037-4d0c-896e-a46fb27ff229")
dxq_result = dataset.execute_queries("EVALUATE VALUES(MyTable)")
print(dxq_result)
# {
# "results": [
# {
# "tables": [
# {
# "rows": [
# {
# "MyTable[Year]": 2010,
# "MyTable[Quarter]": "Q1"
# },
# ...
# }
More examples
Datasets in a Workspace
datasets = pbi.datasets(group="f089354e-8366-4e18-aea3-4cb4a3a50b48")
for dataset in datasets:
print(dataset)
# <Dataset id='cfafbeb1-8037-4d0c-896e-a46fb27ff229', ...>
# <Dataset id='f7fc6510-e151-42a3-850b-d0805a391db0', ...>
List Workspaces
groups = pbi.groups()
for group in groups:
print(group)
# <Group id='a2f89923-421a-464e-bf4c-25eab39bb09f', name='contoso'>
# <Group id='3d9b93c6-7b6d-4801-a491-1738910904fd', name='marketing'>
Create a Workspace
group = pbi.create_group("contoso")
print(group)
# <Group id='a2f89923-421a-464e-bf4c-25eab39bb09f', name='contoso'>
Users and their access
group = pbi.group("a2f89923-421a-464e-bf4c-25eab39bb09f")
users = group.users()
for user in users:
print(user)
# {"identifier": "john@contoso.com", "groupUserAccessRight": "Admin", ... }
# {"identifier": "Adam@contoso.com", "groupUserAccessRight": "Member", ... }
Power BI Rest API Operations
pbipy
methods wrap around the Operations described in the Power BI Rest API Reference:
Power BI REST APIs for embedded analytics and automation - Power BI REST API
Development Progress
pbipy
is in development so expect a few features to be missing. The aim is to cover off most of the core stuff like Datasets, Workspaces (Groups), Reports, Apps, etc., and the rest later on. Check back regularly to see what's been added or still in the pipeline.
PowerBI Component | Progress | Notes |
---|---|---|
Datasets | Done | |
Groups (Workspaces) | Done | |
Reports | Done | |
Apps | Done | |
Dataflows | Doing | |
Admin Operations | Todo | |
Dashboards | Todo | |
Everything else | Backlog |
Contributing
Contributions such as bug reports, fixes, documentation or docstrings, enhancements, and ideas are welcome. pbipy
uses github to host code, track issues, record feature requests, and accept pull requests.
A contributing.md
is in the works, but in the meantime below is a general guide.
Making a contribution
Pull requests are the best way to make a contribution to the code:
- Fork the repo and create your branch from master.
- If you've added code that should be tested, add tests.
- Add docstrings.
- Ensure the test suite passes.
- Format your code (
pbipy
uses black). - Issue that pull request!
Reporting a bug
Great Bug Reports tend to have:
- A quick summary and/or background
- Steps to reproduce. Be specific! Give sample code if you can.
- What you expected would happen
- What actually happens
- Notes (possibly including why you think this might be happening, or stuff you tried that didn't work)
Acknowledgements
The design of this library was heavily inspired by (basically copied) the pycontribs/jira library. It also borrows elements of cmberryay's pypowerbi wrapper.
Thank You to all the contributors to these libraries for the great examples of what an API Wrapper can be.
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