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excel-grapher

Build and analyze dependency graphs from Excel workbooks, evaluate formulas with Excel semantics, and export standalone Python code.

Documentation: https://teal-insights.github.io/excel-grapher/

Why this exists

  • Transpilation support: trace formula dependencies to enable Excel → Python translation.
  • Interpretability: visualize and sanity-check spreadsheet logic (GraphViz, Mermaid, NetworkX).
  • Performance-minded: focuses on targeted dependency closure from specific output cells/ranges.
  • Excel semantics in Python: run workbook logic in-process with a full Excel-like evaluator.
  • Exportable: emit standalone Python packages that embed only the runtime surface you need.

Library layout

The unified distribution is excel-grapher and exposes a single import package, excel_grapher, with five main subpackages:

  • excel_grapher/core/ — shared semantic types, coercions, and scalar operators.
  • excel_grapher/runtime/ — Excel-equivalent function implementations and runtime semantics.
  • excel_grapher/grapher/ — workbook loading, graph extraction, Excel write-back, and visualization logic.
  • excel_grapher/evaluator/FormulaEvaluator: an Excel emulator for recomputing formulas in the extracted graph in Python.
  • excel_grapher/exporter/CodeGenerator: an transpiler for exporting the extracted graph as a standalone Python library.

Typical imports:

from excel_grapher.grapher import create_dependency_graph, DependencyGraph
from excel_grapher.evaluator import FormulaEvaluator
from excel_grapher.exporter import CodeGenerator
from excel_grapher.core import XlError  # and other shared types, if needed

Installation

Released under the MIT license. Install from GitHub:

Using uv (recommended):

# Basic install (NumPy-free)
uv add git+https://github.com/Teal-Insights/excel-grapher

# With vectorized operator / SUMPRODUCT acceleration
uv add "excel-grapher[fast] @ git+https://github.com/Teal-Insights/excel-grapher"

# With NetworkX support
uv add "excel-grapher[networkx] @ git+https://github.com/Teal-Insights/excel-grapher"

# With all optional dependencies (includes `fast`)
uv add "excel-grapher[all] @ git+https://github.com/Teal-Insights/excel-grapher"

Using pip:

pip install git+https://github.com/Teal-Insights/excel-grapher

# With extras:
pip install "excel-grapher[fast] @ git+https://github.com/Teal-Insights/excel-grapher"
pip install "excel-grapher[networkx] @ git+https://github.com/Teal-Insights/excel-grapher"
pip install "excel-grapher[all] @ git+https://github.com/Teal-Insights/excel-grapher"

The default install is correct without NumPy. Install the fast extra when evaluating large workbooks and you want vectorized operator / SUMPRODUCT acceleration. Exported standalone code stays NumPy-free either way.


High-level usage

The library supports a three-stage pipeline, plus Excel write-back of the same graph views used for Python export:

  1. Build a dependency graph from an Excel workbook (excel_grapher.grapher).
  2. Evaluate formulas with Excel semantics over that graph (excel_grapher.evaluator.FormulaEvaluator).
  3. Export standalone Python (excel_grapher.exporter.CodeGenerator) and/or a new .xlsx from the same GraphReadView (excel_grapher.grapher.write_workbook).

A minimal end‑to‑end example:

from pathlib import Path

from excel_grapher.grapher import create_dependency_graph, write_workbook
from excel_grapher.evaluator import FormulaEvaluator
from excel_grapher.exporter import CodeGenerator

workbook_path = Path("model.xlsx")
targets = ["Sheet1!A10"]

# 1) Build a dependency graph
graph = create_dependency_graph(workbook_path, targets, load_values=True)
print(len(graph))  # number of visited nodes

# 2) Evaluate with Excel semantics
with FormulaEvaluator(graph) as ev:
    results = ev.evaluate(targets)

# 3a) Export standalone Python code
code = CodeGenerator(graph).generate(targets)

# 3b) Write a new workbook from the graph (or a ProjectionResult)
write_workbook(graph, Path("edited.xlsx"))

Series bindings

Optional sidecar manifests (.bindings.yaml) declare structured input/output APIs for exported code — set_* and compute_* functions over Records. Validate sidecars from the shell with excel-grapher bindings validate. See the Series bindings guide and Code export guide.

User guide

Detailed documentation lives in the User Guide:

Topic Page
Dependency graphs Read guide
Visualization Read guide
Formula evaluation Read guide
End-to-end demo Read guide
Series bindings Read guide
Code export Read guide
Parity testing Read guide
Contributing Read guide

Examples

Hands-on walkthroughs (Markdown on GitHub):

Topic Walkthrough
Graph extraction extraction_basics.md
Code generation codegen_basics.md
Series bindings series_bindings.md
Induced graph induced_graph.md

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