financial-engine 0.1.4

A time-machine style financial backtesting and ratio analysis engine

📊 Financial Engine

Originally Developed by : Raj Adhikari

A time-machine for market data — replay and analyze historical financial data for one or more companies across single or multiple dates.

Built to backtest strategies, calculate financial ratios, and accelerate data analysis using a smart caching mechanism.

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📦 Changelog

See full CHANGELOG.md

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✨ Features

• 📈 Calculate financial ratios on-demand
• 🔁 Perform rolling computations for line items
• ⚡ Caching mechanism for fast range-date processing

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🚀 Installation

pip install financial-engine

Step-by-step

1. Create and activate a virtual environment:

   python -m venv .venv
   source .venv/bin/activate  # or .venv\Scripts\activate on Windows
   

2. Create a .env file in the root of your project:

   MONGO_URI=
   MONGO_DATABASE=
   MONGO_COLLECTION=
   AWS_ACCESS_KEY_ID=
   AWS_SECRET_ACCESS_KEY=
   BUCKET_NAME=
   

3. Install the package:

   pip install financial-engine
   

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🐍 Requirements

• Python ≥ 3.10
• Compatible with major OS environments (Linux, Windows, Mac)

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🛠 Implemented Methods

Method	Description
get_ratios()	Get financial ratios for a single company on a specific date
get_ratios_range()	Fetch financial ratios for a company across a date range
get_ratios_range_multiple()	Fetch financial ratios for multiple comapnies across a date range

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📦 Usage Example

from financial_engine.core.engine import FinancialEngine

fe = FinancialEngine()

ratios_df = await fe.get_ratios_range(
    alpha_code="RELIANCE",
    start_date="2023-01-01",
    end_date="2023-01-15"
)
print(ratios_df)

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