io.github.fabienfrfr/pbix-atlas

<h1 align="center"> <p>🌐 PBIX‑Atlas</p> </h1>

<p align="center"> <a href="https://pypi.org/project/pbix-atlas/"> <img alt="PyPI" src="https://img.shields.io/pypi/v/pbix-atlas?color=orange"> </a> <a href="https://github.com/fabienfrfr/pbix-atlas/"> <img alt="GitHub" src="https://img.shields.io/badge/github-fabienfrfr%2Fpbix--atlas-black?logo=github"> </a> <a href="https://github.com/fabienfrfr/pbix-atlas/actions"> <img alt="CI" src="https://img.shields.io/github/actions/workflow/status/fabienfrfr/pbix-atlas/tests.yml?label=tests"> <a href="https://registry.modelcontextprotocol.io/?q=pbix-atlas"> <img alt="MCP Registry" src="https://img.shields.io/badge/MCP-registry-purple?logo=protocols"> </a> </p>

<h3 align="center"> <p>Full lineage graph for Power BI — from source to visual field</p> </h3>

<!-- mcp-name: io.github.fabienfrfr/pbix-atlas -->

PbixAtlas is an Universal lineage graph for Power BI .pbix files: source to visual field in one traversable graph.

source (HTTP, OData, SQL, file...) --> Power Query (M)
    --> column / calculated column --> measure (DAX)
        --> field displayed in a report visual

Install

pip install pbix-atlas
# or
uv add pbix-atlas

Quick start

from pbix_atlas import LineageGraphBuilder, upstream, downstream, print_tree, find_nodes

graph = LineageGraphBuilder().build("my_report.pbix")

find_nodes(graph, "customer_name")
print_tree(graph, "visual_field::my_report.pbix::Page1::16::customer_name", direction="upstream")
print_tree(graph, "source::odata::example.com/odata/", direction="downstream")

Export

from pbix_atlas import export_graphml, export_nodes_csv, export_edges_csv, graph_summary

graph_summary(graph)  # {'query': 70, 'column': 183, ...}
export_graphml(graph, "lineage.graphml")  # Gephi / yEd
export_nodes_csv(graph, "nodes.csv")
export_edges_csv(graph, "edges.csv")

Codegen — standalone Python pipeline

Generates a single Python file reproducing a report's full chain: source → extraction → Power Query → semantic model → Vizro dashboard. The M source is executed at runtime by the built-in interpreter, not pattern-matched. Unimplemented functions raise MRuntimeError (no silent stubs).

pip install "pbix-atlas[codegen]"
pbix-atlas-codegen my_report.pbix -o pipeline.py

from pbix_atlas import generate_python_pipeline

generate_python_pipeline("my_report.pbix", "pipeline.py")

HTTP API / MCP server

uv sync --extra api
uv run pbix-atlas    # http://127.0.0.1:8080

• REST: POST /graphs, /search, /upstream, /downstream, /tree, /export, /codegen
• MCP (streamable HTTP): http://127.0.0.1:8080/mcp/
• Env vars: PBIX_LINEAGE_HOST, PBIX_LINEAGE_PORT

Architecture

Module	Responsibility
models.py	Node/edge types and shared data structures
sources.py	Physical source detection (configurable patterns)
pbix_model.py	Adapter isolating from pbixray
m_lexer.py / m_parser.py	Built-in M tokenizer and parser
m_interpreter.py	M runtime interpreter + stdlib
dax_translate.py	DAX → Python (supported subset)
dax.py	DAX reference parsing
mquery.py	Power Query dependencies (table-level)
layout.py	Internal Report/Layout format parsing
graph_builder.py	Orchestrator: builds the networkx.DiGraph
navigation.py	Upstream/downstream traversal, search, export
codegen.py	Python pipeline code generation
api/app.py	FastAPI + MCP mount (FastMCP)

Sample files

• Retail Analysis Sample PBIX (Microsoft)
• Sales & Returns Sample v201912 (Microsoft)

Development

uv sync --extra dev
uv run pytest
uv build