A Python package for financial modeling and reporting
Project description
Pyproforma
A Python package for financial modeling and reporting that provides a flexible framework for building financial models with line items, formulas, constraints, and rich output formatting.
Installation
Install from PyPI:
pip install pyproforma
For local development:
pip install -e .
Quick Start
from pyproforma import Model, LineItem, Category
# Create line items
revenue = LineItem(
name="revenue",
category="income",
label="Total Revenue",
values={2024: 100000, 2025: 120000, 2026: 150000}
)
expenses = LineItem(
name="expenses",
category="income",
label="Total Expenses",
formula="revenue * 0.6" # 60% of revenue
)
# Create a model
model = Model(
line_items=[revenue, expenses],
years=[2024, 2025, 2026]
)
# Calculate results
results = model.calculate()
print(results.to_dataframe())
Key Features
📊 Financial Modeling
- Create line items with explicit values or formulas
- Organize items into categories with automatic totals
- Support for complex financial calculations using numexpr
📈 Interactive Charts
- Built-in Plotly integration for data visualization
- Line charts, bar charts, and mixed chart types
- Cumulative change and percent change charts
📋 Flexible Tables
- Generate formatted tables for financial statements
- Export to Excel with styling and formatting
- Configurable row types and table structures
🔧 Advanced Features
- Constraint validation for model integrity
- YAML/JSON serialization for model persistence
- Debt and financing generators
- Rich HTML output for Jupyter notebooks
Usage Examples
Working with Formulas
# Line items can reference other line items in formulas
profit = LineItem(
name="profit",
category="income",
formula="revenue - expenses"
)
# Support for complex expressions
margin = LineItem(
name="margin",
category="ratios",
formula="profit / revenue",
value_format="percent"
)
Creating Categories
from pyproforma import Category
# Categories automatically calculate totals
revenue_category = Category(
name="revenue",
label="Revenue Sources",
include_total=True
)
model.add.category(revenue_category)
Generating Reports
# Create formatted tables
table = model.tables.generate_table([
{"type": "category", "name": "income"},
{"type": "line_item", "name": "revenue"},
{"type": "line_item", "name": "expenses"},
{"type": "total", "category": "income"}
])
# Export to Excel
table.to_excel("financial_report.xlsx")
# Create interactive charts
chart = model.charts.item("revenue", chart_type="line")
chart.show()
Model Persistence
# Save model to YAML
model.save_yaml("model.yaml")
# Load model from YAML
model = Model.load_yaml("model.yaml")
Development
Install in development mode with testing dependencies:
pip install -e .[dev]
Run tests:
pytest
Run tests with coverage:
pytest --cov=pyproforma
Requirements
- Python 3.9+
- pandas >= 1.3.0
- openpyxl >= 3.0.0
- numexpr >= 2.7.0
- jinja2 >= 3.0.0
- plotly >= 5.0.0
- PyYAML >= 6.0.0
License
MIT License - see LICENSE file for details.
Project details
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