msdev-kit

Microsoft developer toolkit for Python: Fabric/Power BI, MS Graph (Entra), and SharePoint.

Until 2026-06-17 this package was developed in a private repository. The git history was squashed when the project was opened to the public, so commits before that date are not preserved.

Supported OS

• Windows x64
• macOS Apple ARM
• Linux

Unsupported OS

• Currently, because of updates to cryptography package (>=50.0.0), Windows 32-bit and macOS Intel are not supported.

Installation

pip install msdev-kit

Or install from GitHub:

pip install git+https://github.com/Bernardo-Rufino/msdev-kit.git

For local development:

git clone https://github.com/Bernardo-Rufino/msdev-kit.git
cd msdev-kit
pip install -e .

Requirements: Python >= 3.10, an Azure app registration with a client ID and client secret.

Quick Start

from msdev_kit import Auth
from msdev_kit.fabric import Workspace
from msdev_kit.graph import GraphClient
from msdev_kit.sharepoint import SharePointClient

# authenticate
auth = Auth(tenant_id="...", client_id="...", client_secret="...")

# fabric: list workspaces
ws = Workspace(auth.get_token('fabric'))
workspaces = ws.list_workspaces_for_user()

# graph: look up a user
graph = GraphClient(auth)
user_id = graph.get_user_id('user@company.com')

# sharepoint: download a file
sp = SharePointClient(auth, sp_hostname='company', sp_site_path='sites/DataTeam')
sp.download_file('/Reports/monthly.xlsx', local_dir='./downloads')

Authentication

All classes use a shared Auth object. You can use different service principals for different services — instantiate one Auth per SPN:

from msdev_kit import Auth

# service principal auth
fabric_auth = Auth(tenant_id="...", client_id="spn-a", client_secret="...")
graph_auth  = Auth(tenant_id="...", client_id="spn-b", client_secret="...")

Supported scopes

Interactive user auth

For scenarios requiring user context (e.g., RLS-enabled datasets), omit the client-secret arguments to use browser authentication by default:

auth = Auth()
token = auth.get_token('fabric')

You can also request a fresh user token from a service-principal Auth instance:

token = auth.get_token_for_user('pbi')     # opens browser for login
token = auth.get_token_for_user('fabric')

Credentials

Set up credentials via environment variables or a .env file:

TENANT_ID='<YOUR_TENANT_ID>'
CLIENT_ID='<YOUR_CLIENT_ID>'
CLIENT_SECRET='<YOUR_CLIENT_SECRET>'

Fabric & Power BI

from msdev_kit import Auth
from msdev_kit.fabric import Workspace, Dataset, Report, Dataflow, Pipeline

auth = Auth(tenant_id, client_id, client_secret)

Fabric classes take a token string — call auth.get_token('fabric') or auth.get_token('pbi') depending on the API.

• Workspace — workspaces, users, permissions
• Dataset — semantic models, DAX queries, permissions
• Report — metadata, definitions, visuals, measures
• Dataflow — Gen1, Gen2, Gen2 CI/CD management
• Pipeline — Data Pipeline management
• Other modules — Capacity, Admin, KQL, Notebook, Database

Workspace

Manage Power BI workspaces, users, and permissions.

ws = Workspace(auth.get_token('pbi'))
workspaces = ws.list_workspaces_for_user()
ws.add_user('user@company.com', workspace_id, 'Member', 'User')

Dataset

Manage datasets (semantic models), permissions, and execute DAX queries.

ds = Dataset(auth.get_token('pbi'))
result = ds.execute_query(workspace_id, dataset_id, "EVALUATE Sales")

Report

Retrieve report metadata, definitions, visuals, and report-level measures.

rpt = Report(auth.get_token('pbi'))
pages = rpt.list_report_pages(workspace_id, report_id)

Dataflow

Manage Power BI and Fabric dataflows, including Gen1, Gen2, and Gen2 CI/CD.

df = Dataflow(auth.get_token('fabric'))

# upgrade Gen1 to Gen2 CI/CD
result = df.upgrade_to_gen2_cicd(
    workspace_id='<workspace_id>',
    dataflow_id='<gen1_dataflow_id>',
    display_name='my_dataflow_cicd',
    source_type='gen1'
)

Pipeline

Manage Fabric Data Pipelines.

pipe = Pipeline(auth.get_token('fabric'))
activities = pipe.get_pipeline_activities(workspace_id, 'My Pipeline')

from msdev_kit import Auth
from msdev_kit.fabric import Dataflow, Pipeline

auth = Auth(tenant_id, client_id, client_secret)
dataflow = Dataflow(auth.get_token('pbi'))
pipeline = Pipeline(auth.get_token('fabric'))

workspace_id = '<workspace_id>'
old_dataflow_id = '<dataflow_id>'

# 1. replace dataflow destination (creates new CI/CD, deletes original)
result = dataflow.change_data_destination(
    workspace_id=workspace_id,
    dataflow_id=old_dataflow_id,
    destination_type='Warehouse',
    destination_workspace_id=workspace_id,
    destination_item_id='<warehouse_id>',
    mode='replace'
)
new_dataflow_id = result['content']['id']

# 2. find pipelines referencing the old dataflow ID
matches = pipeline.find_pipelines_by_dataflow(workspace_id, old_dataflow_id)

# 3. update each pipeline to use the new ID
for m in matches['content']:
    pipeline.replace_dataflow_id_in_pipeline(
        workspace_id, m['pipeline_id'], old_dataflow_id, new_dataflow_id
    )

Other modules

MS Graph (Entra)

Manage Entra ID (Azure AD) users and groups via the MS Graph API.

from msdev_kit import Auth
from msdev_kit.graph import GraphClient

auth = Auth(tenant_id, client_id, client_secret)
graph = GraphClient(auth)

# look up a user and add them to a group
user_id = graph.get_user_id('user@company.com')
group_id = graph.get_group_id('Data Team')
graph.add_group_member(group_id, user_id)

# list all members of a group
members = graph.list_group_members(group_id)

SharePoint

Manage SharePoint files and folders via MS Graph API (no ACS/Office365 dependency).

from msdev_kit import Auth
from msdev_kit.sharepoint import SharePointClient

auth = Auth(tenant_id, client_id, client_secret)
sp = SharePointClient(auth, sp_hostname='company', sp_site_path='sites/DataTeam')

# download a file
sp.download_file('/Reports/monthly.xlsx', local_dir='./downloads')

# upload a file (from path or bytes)
sp.upload_file('/Reports/updated.xlsx', source='./local/updated.xlsx')
sp.upload_file('/Reports/data.csv', source=csv_bytes, content_type='text/csv')

# create nested folders
sp.create_folder('/Reports/2026/Q1')

Hostname and site path inputs are normalized automatically:

Limitations

• The Power BI REST API has a 200 requests per hour rate limit.
• Not all users can be updated via the API. See Microsoft docs: Dataset permissions.
• Dataset query limits (executeQueries API):
  • Max 100,000 rows or 1,000,000 values (rows x columns) per query, whichever is hit first.
  • Max 15 MB of data per query.
  • 120 query requests per minute per user.
  • Only DAX queries are supported (no MDX, INFO functions, or DMV).
  • Datasets hosted in Azure Analysis Services or with a live connection to on-premises AAS are not supported.
  • Service Principals are not supported for datasets with RLS or SSO enabled.

Examples

End-to-end scripts for the most common scenarios live in examples/. They share a small _setup.py that builds Auth and the service clients from environment variables (or ./utils/.env). Run any of them from the repo root:

python -m examples.workspaces
python -m examples.dataflows

Contributing

External contributions are welcome via pull requests. Please:

1. Open an issue first for non-trivial changes so the design can be discussed.
2. Use feature/<name> / fix/<name> branches. Direct pushes to main are blocked by repository rulesets.
3. Keep PRs focused. Add or update tests under tests/ for any behavior change.
4. Run pytest locally before opening a PR; the Collaboration workflow runs the same suite on every PR and must pass before merging.

PyPI releases are published automatically from main by the Publish to PyPI workflow, gated by a manual approval on the pypi environment.