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Financial infrastructure toolkit: banking connections, market data, credit, cashflows, and brokerage integrations

Project description

fin-infra

PyPI Docs

Financial infrastructure toolkit for fintech applications. fin-infra provides production-ready building blocks for banking connections, market data, credit scores, tax data, brokerage integrations, and cashflow analysis—everything needed to build comprehensive personal finance management applications.

What is fin-infra?

fin-infra is the financial data layer for fintech apps. While svc-infra handles generic backend operations (auth, API scaffolding, database, billing), fin-infra is purpose-built for financial applications where users need to:

  • Connect bank accounts and pull transaction history
  • Link brokerage accounts and view portfolio holdings
  • Check credit scores and monitor credit reports
  • Access tax documents and data
  • View real-time market data (stocks, crypto, forex)
  • Perform financial calculations (NPV, IRR, loan amortization)

Status

Alpha. Core functionality is stable, but the surface is intentionally small while we stabilize models and provider contracts.

Helper Index

Area What it covers Guide
Getting Started Overview and installation Getting Started
Banking Account aggregation, transactions, statements Banking
Market Data Stocks, crypto, forex quotes and historical data Market Data
Credit Scores Credit reports and monitoring Credit
Brokerage Trading accounts and portfolio data Brokerage
Tax Data Tax documents and data management Tax
Cashflows NPV, IRR, loan calculations Cashflows
Contributing Dev setup and quality gates Contributing
Acceptance Acceptance testing guide Acceptance

Quick Start

Installation

# From PyPI (when published)
pip install fin-infra

# For backend infrastructure (auth, API, DB, cache, jobs), also install:
pip install svc-infra

# For development
git clone https://github.com/your-org/fin-infra
cd fin-infra
poetry install

Note: fin-infra provides ONLY financial data integrations. For backend infrastructure (API framework, auth, database, caching, jobs), you need svc-infra. Applications typically use both packages together.

One-Call Setup

from fin_infra.banking import easy_banking
from fin_infra.markets import easy_market, easy_crypto
from fin_infra.credit import easy_credit
from fin_infra.cashflows import npv, irr

# Banking
banking = easy_banking()
accounts = await banking.get_accounts("access_token")
transactions = await banking.get_transactions("account_id")

# Market Data
market = easy_market()
quote = market.quote("AAPL")

crypto = easy_crypto()
ticker = crypto.ticker("BTC/USDT")

# Credit Scores
credit = easy_credit()
score = await credit.get_credit_score("user_123")

# Cashflows
cashflows = [-1000, 300, 300, 300, 300]
net_value = npv(0.08, cashflows)
rate_of_return = irr(cashflows)

Architecture Overview

fin-infra/
├── src/fin_infra/
│   ├── banking/            # Bank account aggregation
│   │   ├── plaid/          # Plaid provider
│   │   └── teller/         # Teller provider
│   ├── brokerage/          # Trading account connections
│   ├── credit/             # Credit score providers
│   ├── markets/            # Market data (stocks/crypto)
│   ├── tax/                # Tax data and documents
│   ├── cashflows/          # Financial calculations
│   ├── models/             # Pydantic data models
│   ├── providers/          # Provider implementations
│   └── docs/               # Packaged documentation
├── tests/
│   ├── unit/               # Fast unit tests
│   └── acceptance/         # Provider integration tests
└── examples/               # Example applications

Configuration

fin-infra uses environment variables for provider credentials:

# Banking providers
PLAID_CLIENT_ID=your_client_id
PLAID_SECRET=your_secret
PLAID_ENV=sandbox

# Market data providers
ALPHAVANTAGE_API_KEY=your_api_key

# Credit providers
EXPERIAN_USERNAME=your_username
EXPERIAN_PASSWORD=your_password

Development

# Install dependencies
poetry install

# Format code
make format

# Run linting
make lint

# Type check
make type

# Run tests
make unit      # Unit tests only
make accept    # Acceptance tests
make test      # All tests

Acceptance tests and CI

  • Acceptance tests are marked with @pytest.mark.acceptance and are excluded by default.
  • To run locally, export any required API keys (only Alpha Vantage is needed by default):
    • ALPHAVANTAGE_API_KEY – required for Alpha Vantage market data tests.
  • Run: poetry run pytest -q -m acceptance.

GitHub Actions secrets

The acceptance workflow in .github/workflows/acceptance.yml expects:

  • ALPHAVANTAGE_API_KEY – add it under Repository Settings → Secrets and variables → Actions → New repository secret.

If the secret isn’t configured, acceptance tests will still run and CoinGecko tests (public) will pass, but Alpha Vantage tests will be skipped.

Contributing

  • Keep APIs small and typed. Prefer Pydantic models for IO boundaries.
  • Add or update tests for any behavior changes. Keep pytest passing and mypy clean.

License: MIT

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