🌐 PBIX‑Atlas

Full lineage graph for Power BI — from source to visual field

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

Code

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

Install

Terminal

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

Quick start

server.ts

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

server.ts

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).

Terminal

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

server.ts

from pbix_atlas import generate_python_pipeline

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

HTTP API / MCP server

bash

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

bash

uv sync --extra dev
uv run pytest
uv build