formualizer 0.4.0

Embeddable spreadsheet engine — parse, evaluate & mutate Excel workbooks at native speed

Formualizer for Python

Parse, evaluate, and mutate Excel workbooks at native speed from Python.

A Rust-powered spreadsheet engine with 320+ Excel-compatible functions, exposed through a clean Pythonic API. Tokenize formulas, walk ASTs, evaluate workbooks, and use SheetPort to treat spreadsheets as typed APIs.

Installation

pip install formualizer

Prebuilt wheels are available for Python 3.10-3.13 on Linux, macOS, and Windows. No Rust toolchain required.

Quick start

Evaluate a workbook

import formualizer as fz

wb = fz.Workbook()
s = wb.sheet("Sheet1")

s.set_value(1, 1, fz.LiteralValue.number(1000.0))   # A1: principal
s.set_value(2, 1, fz.LiteralValue.number(0.05))      # A2: annual rate
s.set_value(3, 1, fz.LiteralValue.number(12.0))       # A3: periods

s.set_formula(1, 2, "=PMT(A2/12, A3, -A1)")
print(wb.evaluate_cell("Sheet1", 1, 2))  # ~85.61

Load an XLSX and evaluate

import formualizer as fz

wb = fz.load_workbook("financial_model.xlsx", strategy="eager_all")
print(wb.evaluate_cell("Summary", 1, 2))

Recalculate XLSX cached values (writeback)

import formualizer as fz

# in-place
summary = fz.recalculate_file("financial_model.xlsx")
print(summary["status"], summary["evaluated"], summary["errors"])

# write to a new file
summary = fz.recalculate_file("financial_model.xlsx", output="financial_model.recalc.xlsx")

Current limitation: cached values for formula cells are currently written as string-typed payloads by the underlying umya writer. Formula text is preserved.

Parse and analyze formulas

from formualizer import parse
from formualizer.visitor import collect_references, collect_function_names

ast = parse("=SUMIFS(Revenue,Region,A1,Year,B1)")
print(ast.pretty())                          # indented AST tree
print(ast.to_formula())                      # canonical Excel string
print(collect_references(ast))               # [Revenue, Region, A1, Year, B1]
print(collect_function_names(ast))           # ['SUMIFS']

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Key features

Capability	Description
Tokenization	Break formulas into structured Token objects with byte spans and operator metadata
Parsing	Produce a rich AST with reference normalization, source tracking, and 64-bit structural fingerprints
320+ built-in functions	Math, text, lookup (XLOOKUP, VLOOKUP), date/time, financial, statistics, database, engineering
Workbook evaluation	Set values and formulas, evaluate cells/ranges, load XLSX/CSV/JSON
XLSX cache writeback	recalculate_file(path, output=None) recalculates formulas and writes cached values back
Batch operations	set_values_batch / set_formulas_batch for efficient bulk updates
Undo / redo	Optional changelog with automatic action grouping — single edits are individually undoable
Evaluation planning	Inspect the dependency graph and evaluation schedule before computing
SheetPort	Treat spreadsheets as typed functions with YAML manifests, schema validation, and batch scenarios
Deterministic mode	Inject clock, timezone, and RNG seed for reproducible evaluation
Visitor utilities	walk_ast, collect_references, collect_function_names for ergonomic tree traversal
Rich errors	Typed TokenizerError / ParserError / ExcelEvaluationError with position info

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Workbook evaluation

import formualizer as fz

wb = fz.Workbook()
s = wb.sheet("Data")

# Set values and formulas
s.set_value(1, 1, fz.LiteralValue.number(100.0))
s.set_value(2, 1, fz.LiteralValue.number(200.0))
s.set_value(3, 1, fz.LiteralValue.number(300.0))
s.set_formula(4, 1, "=SUM(A1:A3)")
s.set_formula(4, 2, "=AVERAGE(A1:A3)")

print(wb.evaluate_cell("Data", 4, 1))  # 600.0
print(wb.evaluate_cell("Data", 4, 2))  # 200.0

Batch operations

# Bulk-set values (auto-grouped as one undo step when changelog is enabled)
s.set_values_batch(1, 1, 3, 2, [
    [fz.LiteralValue.number(10.0), fz.LiteralValue.number(20.0)],
    [fz.LiteralValue.number(30.0), fz.LiteralValue.number(40.0)],
    [fz.LiteralValue.number(50.0), fz.LiteralValue.number(60.0)],
])

Undo / redo

The changelog is opt-in. Once enabled, every edit is tracked:

wb.set_changelog_enabled(True)

s.set_value(1, 1, fz.LiteralValue.number(10.0))
s.set_value(1, 1, fz.LiteralValue.number(20.0))
wb.undo()  # back to 10
wb.redo()  # back to 20

# Batch methods are auto-grouped as one undo step.
# For manual grouping of multiple calls:
wb.begin_action("update prices")
s.set_value(1, 1, fz.LiteralValue.number(100.0))
s.set_value(2, 1, fz.LiteralValue.number(200.0))
wb.end_action()
wb.undo()  # reverts both values at once

Evaluation planning

Inspect what the engine will compute before running:

plan = wb.get_eval_plan([("Sheet1", 1, 2)])
print(f"Vertices to evaluate: {plan.total_vertices_to_evaluate}")
print(f"Parallel layers: {plan.estimated_parallel_layers}")
for layer in plan.layers:
    print(f"  Layer: {layer.vertex_count} vertices, parallel={layer.parallel_eligible}")

SheetPort: spreadsheets as typed APIs

Define a YAML manifest to treat a spreadsheet as a typed function with validated inputs/outputs:

from formualizer import SheetPortSession, Workbook

manifest_yaml = """
spec: fio
spec_version: "0.3.0"
manifest:
  id: pricing-model
  name: Pricing Model
  workbook:
    uri: memory://pricing.xlsx
    locale: en-US
    date_system: 1900
ports:
  - id: base_price
    dir: in
    shape: scalar
    location: { a1: Inputs!A1 }
    schema: { type: number }
  - id: final_price
    dir: out
    shape: scalar
    location: { a1: Outputs!A1 }
    schema: { type: number }
"""

wb = Workbook()
wb.add_sheet("Inputs")
wb.add_sheet("Outputs")
wb.set_formula("Outputs", 1, 1, "=Inputs!A1*1.2")

session = SheetPortSession.from_manifest_yaml(manifest_yaml, wb)
session.write_inputs({"base_price": 100.0})
result = session.evaluate_once(freeze_volatile=True)
print(result["final_price"])  # 120.0

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API reference

Top-level functions

tokenize(formula: str, dialect: FormulaDialect = None) -> Tokenizer
parse(formula: str, dialect: FormulaDialect = None) -> ASTNode
load_workbook(path: str, strategy: str = None) -> Workbook
recalculate_file(path: str, output: str | None = None) -> dict

Core classes

• Workbook — create, load, evaluate, undo/redo. Supports from_path() and load_path() class methods.
• Sheet — per-sheet facade for set_value, set_formula, get_cell, batch operations.
• LiteralValue — typed values: .int(), .number(), .text(), .boolean(), .date(), .empty(), .error(), .array().
• Tokenizer — iterable token sequence with .render() and .tokens.
• ASTNode — .pretty(), .to_formula(), .fingerprint(), .children(), .walk_refs().
• CellRef / RangeRef / TableRef / NamedRangeRef — typed references.
• SheetPortSession — bind manifests to workbooks, read/write typed ports, evaluate.
• EvaluationConfig — tune parallel evaluation, warmup, range limits, date systems.

Visitor helpers (formualizer.visitor)

walk_ast(node, visitor_fn)              # DFS with VisitControl (CONTINUE/SKIP/STOP)
collect_references(node)                # -> list[ReferenceLike]
collect_function_names(node)            # -> list[str]
collect_nodes_by_type(node, "Function") # -> list[ASTNode]

Full type stubs are included in the package (.pyi files) for IDE autocompletion and mypy.

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Building from source

Requires Rust >= 1.70 and maturin:

pip install maturin
cd bindings/python
maturin develop          # debug build
maturin develop --release  # optimized build

Testing

pip install formualizer[dev]
pytest bindings/python/tests
ruff check bindings/python
mypy bindings/python/formualizer

Workspace layout

formualizer/
  crates/                    # Rust core (parse, eval, workbook, sheetport)
  bindings/python/
    formualizer/             # Python package (helpers, visitor, type stubs)
    src/                     # PyO3 bridge (Rust -> Python)

The Python wheel links directly against the Rust crates — there is no runtime FFI overhead beyond the initial C-to-Rust boundary.

License

Dual-licensed under MIT or Apache-2.0, at your option.