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, 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:

  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 code that embeds only the required runtime surface (excel_grapher.exporter.CodeGenerator).

A minimal end‑to‑end example:

from pathlib import Path

from excel_grapher.grapher import create_dependency_graph
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)

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

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

Project links

Data verified by PyPI on Aug 7, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (11.3.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for chriscarrollsmith from gravatar.com chriscarrollsmith

Credits

Author: Teal Insights

GitHub Statistics

Data verified by PyPI on Aug 7, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT License (MIT License)

Requires

Python >=3.11

Provides Extra

all fast networkx viz

Tags

dependency excel formula graph spreadsheet transpiler

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

excel_grapher-4.1.0.tar.gz (5.8 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

excel_grapher-4.1.0-py3-none-any.whl (376.7 kB view details)

Uploaded Python 3

File details

Details for the file excel_grapher-4.1.0.tar.gz.

File metadata

  • Download URL: excel_grapher-4.1.0.tar.gz
  • Upload date:
  • Size: 5.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for excel_grapher-4.1.0.tar.gz
Algorithm Hash digest
SHA256 7820560871c3a8aad47b25ecb97017b9dd6492255092443dbdb883bd22d97782
MD5 e449080fa26ccb9f6f612ea1d034da10
BLAKE2b-256 8b010697dbb7300263843f74163ff0c455785ebdb3d87628f321a0c38fe4edea

See more details on using hashes here.

Provenance

The following attestation bundles were made for excel_grapher-4.1.0.tar.gz:

Publisher: publish.yml on Teal-Insights/excel-grapher

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file excel_grapher-4.1.0-py3-none-any.whl.

File metadata

  • Download URL: excel_grapher-4.1.0-py3-none-any.whl
  • Upload date:
  • Size: 376.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for excel_grapher-4.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 acc3e1af8b4e778592de7a38d9fb6aee58d0725a2f6ead3ed874e4c4e7160c9e
MD5 3ca90f0646e2610d9abd0b82c3ea61b3
BLAKE2b-256 c5040a9e8d9b473c877f566791a33acf01503e371cc8a5211afcde9a68334ac1

See more details on using hashes here.

Provenance

The following attestation bundles were made for excel_grapher-4.1.0-py3-none-any.whl:

Publisher: publish.yml on Teal-Insights/excel-grapher

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

11.3.0

2 files

11.2.0

2 files

11.1.0

2 files

11.0.0

2 files

10.3.0

2 files

10.2.0

2 files

10.1.0

2 files

10.0.0

2 files

9.1.0

2 files

9.0.0

2 files

8.0.0

2 files

7.0.0

2 files

6.3.3

2 files

6.3.2

2 files

6.3.1

2 files

6.3.0

2 files

6.2.0

2 files

6.1.2

2 files

6.1.1

2 files

6.1.0

2 files

6.0.0

2 files

5.2.0

2 files

5.1.6

2 files

5.1.5

2 files

5.1.4

2 files

5.1.3

2 files

5.1.2

2 files

5.1.1

2 files

5.1.0

2 files

5.0.0

2 files

4.1.2

2 files

4.1.1

2 files

This release

4.1.0 This release

2 files

4.0.2

2 files

4.0.1

2 files

4.0.0

2 files

3.21.2

2 files

3.21.1

2 files

3.21.0

2 files

3.20.2

2 files

3.20.1

2 files

3.20.0

2 files

3.19.1

2 files

3.19.0

2 files

3.18.0

2 files

3.17.1

2 files

3.17.0

2 files

3.16.0

2 files

3.15.3

2 files

3.15.2

2 files

3.15.1

2 files

3.15.0

2 files

3.14.1

2 files

3.14.0

2 files

3.13.1

2 files

3.13.0

2 files

3.12.0

2 files

3.11.0

2 files

3.10.1

2 files

3.10.0

2 files

3.9.0

2 files

3.8.0

2 files

3.7.0

2 files

3.6.0

2 files

3.5.0

2 files

3.4.3

2 files

3.4.2

2 files

3.4.1

2 files

3.4.0

2 files

3.3.0

2 files

3.2.0

2 files

3.1.0

2 files

3.0.1

2 files

3.0.0

2 files

2.5.2

2 files

2.5.1

2 files

2.5.0

2 files

2.4.1

2 files

2.4.0

2 files

2.3.0

2 files

2.2.0

2 files

2.1.3

2 files

2.1.2

2 files

2.1.1

2 files

2.1.0

2 files

2.0.0

2 files

1.2.0

2 files

1.1.0

2 files

1.0.2

2 files

1.0.1

2 files

1.0.0

2 files

0.6.9

2 files

0.6.7

2 files

0.6.6

2 files

0.6.4

2 files

0.6.3

2 files

0.6.2

2 files

0.6.1

2 files

0.6.0

2 files

0.5.1

2 files

0.5.0

2 files

0.4.0

2 files

0.3.0

2 files

0.2.0

2 files

0.1.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page