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YAML-driven Excel financial model generator

Project description

excel-model

CI License: MIT

YAML-driven Excel financial model generator.

Build professional financial models (P&L, DCF, Budget vs Actuals, Scenario Analysis) from declarative YAML specs. Generates .xlsx workbooks with named ranges, styled sheets, and Excel formulas using openpyxl.

Documentation

Installation

pip install excel-model

Or for development:

pixi install

Quick Start

CLI

# Build a P&L model
excel-model build --spec model.yaml --output model.xlsx --mode batch

# Validate a spec
excel-model validate --spec model.yaml

# Describe what a spec would produce
excel-model describe --spec model.yaml --format text

Python API

from excel_model.spec_loader import load_spec
from excel_model.validator import validate_spec
from excel_model.excel_writer import build_workbook
from excel_model.config import load_style

spec = load_spec("model.yaml")
errors = validate_spec(spec)
assert not errors

style = load_style(None)  # uses bundled defaults
build_workbook(spec=spec, inputs=None, output_path="model.xlsx", style=style)

Model Types

Type Description
p_and_l Profit & Loss statement
dcf Discounted Cash Flow valuation
budget_vs_actuals Budget vs Actuals comparison
scenario Multi-scenario analysis (Base/Bull/Bear)
comparison Cross-entity comparison

Formula Types

21 built-in formula types including growth_projected, pct_of_revenue, sum_of_rows, subtraction, ratio, discounted_pv, terminal_value, npv_sum, variance, variance_pct, constant, custom, and more.

Custom formula security: The custom formula type rejects formulas containing dangerous patterns (DDE, WEBSERVICE, IMPORTDATA, CALL, EXEC, FILTERXML, REGISTER.ID, etc.) to prevent Excel formula injection attacks. Standard Excel functions like SUM, IF, ROUND, and MAX are allowed.

Configuration

Style config controls Excel formatting (colors, fonts, number formats). A bundled default is included; override with --style:

header_fill_hex: "1F3864"
header_font_color: "FFFFFF"
font_name: "Calibri"
font_size: 10
number_format_currency: '#,##0'
number_format_percent: '0.0%'

Looking for Financial Modeling Input

This library was built by a software engineer, not a financial analyst. The model structures, formula types, and default assumptions reflect a developer's interpretation of common financial models.

If you work in finance, FP&A, investment banking, or accounting, your input would be incredibly valuable:

  • Are the formula types correct? Do growth_projected, pct_of_revenue, discounted_pv, and terminal_value follow standard conventions?
  • Missing model patterns? Are there common financial model structures (e.g., waterfall, three-statement, LBO) that should be supported?
  • Named range conventions -- do the Excel named range naming patterns match what analysts expect?
  • Number formatting -- are the default currency/percent/integer formats appropriate for professional models?
  • Scenario analysis -- does the base/bull/bear override pattern match how scenarios are typically structured?

Please open an issue with the type:feat label, or start a discussion. All feedback is welcome, from quick corrections to detailed model reviews.

License

MIT

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