# meridianalgo/learn-quant architecture

> Architecture diagram of the GitHub repository meridianalgo/learn-quant, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-29). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/meridianalgo/learn-quant
- Repository: https://github.com/meridianalgo/learn-quant

## Overview

Learn-Quant is a learning-oriented collection of runnable, mostly self-contained Python and JavaScript lessons and quantitative-finance tools—not one integrated trading application. The principal learner workflow is to choose a topic, run its lesson or utility, and inspect calculations, examples, and (in interactive tutorials) quiz prompts. Its domain coverage spans programming foundations, quantitative methods, market and portfolio analysis, strategy simulation, and machine learning. The sampled backtester and feature-engineering module illustrate internal calculation responsibilities; the README documents additional capabilities whose wiring is not established by the sampled source.

Main entry points: [`Learning Platform`](https://github.com/meridianalgo/learn-quant/tree/main/Learning%20Platform) (Learning Platform), [`Python Basics - Functions/functions_tutorial.py`](https://github.com/meridianalgo/learn-quant/blob/main/Python%20Basics%20-%20Functions/functions_tutorial.py) (Python Basics), [`Advanced Python - AsyncIO/async_fetching.py`](https://github.com/meridianalgo/learn-quant/blob/main/Advanced%20Python%20-%20AsyncIO/async_fetching.py) (Python Engineering), [`Algorithms - Graph/graph_algorithms.py`](https://github.com/meridianalgo/learn-quant/blob/main/Algorithms%20-%20Graph/graph_algorithms.py) (Algorithms)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_learning["Learning Experience"]
  node_platform["Learning Platform"]
  node_content["Lesson Content<br/>[content.py]"]
end

subgraph group_foundations["Programming Foundations"]
  node_python["Python Basics"]
  node_engineering["Python Engineering<br/>[async_fetching.py]"]
  node_algorithms["Algorithms"]
end

subgraph group_quant["Quant Finance"]
  node_pricing["Option Pricing<br/>[black_scholes.py]"]
  node_risk["Risk Analysis<br/>[risk_summary.py]"]
  node_portfolio["Portfolio Tools<br/>[portfolio_utils.py]"]
  node_quantmethods["Quant Methods"]
end

subgraph group_trading["Trading Systems"]
  node_marketdata["Market Data"]
  node_strategies["Trading Strategies"]
  node_backtest["Backtesting<br/>[backtest_engine.py]"]
  node_execution["Execution Simulation"]
end

subgraph group_research["Data And ML"]
  node_features["Feature Engineering"]
  node_models["Machine Learning<br/>[rf_predictor.py]"]
  node_sentiment["News Sentiment"]
end

node_learner(("Learner"))
node_results["Examples And Results"]

node_learner -->|"explores lessons"| node_platform
node_platform -->|"uses lesson material"| node_content
node_learner -->|"runs lesson"| node_python
node_learner -->|"runs lesson"| node_engineering
node_learner -->|"runs lesson"| node_algorithms
node_learner -->|"runs module"| node_pricing
node_learner -->|"runs module"| node_risk
node_learner -->|"runs module"| node_portfolio
node_learner -->|"runs module"| node_quantmethods
node_learner -->|"runs module"| node_marketdata
node_learner -->|"runs module"| node_strategies
node_learner -->|"runs module"| node_backtest
node_learner -->|"runs module"| node_execution
node_learner -->|"runs module"| node_features
node_learner -->|"runs module"| node_models
node_learner -->|"runs module"| node_sentiment
node_python -->|"shows examples"| node_results
node_engineering -->|"demonstrates concepts"| node_results
node_algorithms -->|"returns results"| node_results
node_pricing -->|"computes prices"| node_results
node_risk -->|"reports metrics"| node_results
node_portfolio -->|"computes analytics"| node_results
node_quantmethods -->|"computes statistics"| node_results
node_marketdata -->|"provides data"| node_results
node_strategies -->|"demonstrates signals"| node_results
node_backtest -->|"returns performance"| node_results
node_execution -->|"simulates orders"| node_results
node_features -->|"builds features and labels"| node_results
node_models -->|"produces predictions"| node_results
node_sentiment -->|"analyzes news"| node_results

click node_platform "https://github.com/meridianalgo/learn-quant/tree/main/Learning%20Platform"
click node_content "https://github.com/meridianalgo/learn-quant/blob/main/Learning%20Platform/content.py"
click node_python "https://github.com/meridianalgo/learn-quant/blob/main/Python%20Basics%20-%20Functions/functions_tutorial.py"
click node_engineering "https://github.com/meridianalgo/learn-quant/blob/main/Advanced%20Python%20-%20AsyncIO/async_fetching.py"
click node_algorithms "https://github.com/meridianalgo/learn-quant/blob/main/Algorithms%20-%20Graph/graph_algorithms.py"
click node_pricing "https://github.com/meridianalgo/learn-quant/blob/main/Black-Scholes%20Option%20Pricing/black_scholes.py"
click node_risk "https://github.com/meridianalgo/learn-quant/blob/main/Risk%20Metrics/risk_summary.py"
click node_portfolio "https://github.com/meridianalgo/learn-quant/blob/main/Portfolio%20Management/portfolio_utils.py"
click node_quantmethods "https://github.com/meridianalgo/learn-quant/blob/main/Quantitative%20Methods%20-%20Statistics/statistical_analysis.py"
click node_marketdata "https://github.com/meridianalgo/learn-quant/blob/main/Market%20Data/market_data_utils.py"
click node_strategies "https://github.com/meridianalgo/learn-quant/blob/main/Strategies%20-%20Momentum%20Trading/momentum_strategy.py"
click node_backtest "https://github.com/meridianalgo/learn-quant/blob/main/Strategies%20-%20Backtesting%20Engine/backtest_engine.py"
click node_execution "https://github.com/meridianalgo/learn-quant/blob/main/Order%20Execution%20Simulator/order_execution_simulator.py"
click node_features "https://github.com/meridianalgo/learn-quant/blob/main/Machine%20Learning%20-%20Feature%20Engineering/feature_engineering.py"
click node_models "https://github.com/meridianalgo/learn-quant/blob/main/Machine%20Learning%20-%20Random%20Forest/rf_predictor.py"
click node_sentiment "https://github.com/meridianalgo/learn-quant/blob/main/Sentiment%20Analysis%20on%20News/sentiment_analysis.py"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_platform,node_content toneBlue
class node_python,node_engineering,node_algorithms toneAmber
class node_pricing,node_risk,node_portfolio,node_quantmethods toneMint
class node_marketdata,node_strategies,node_backtest,node_execution toneRose
class node_features,node_models,node_sentiment,node_learner,node_results toneIndigo
```

## Components

### Learning Experience

- [Learning Platform](https://github.com/meridianalgo/learn-quant/tree/main/Learning%20Platform): `Learning Platform`
- [Lesson Content](https://github.com/meridianalgo/learn-quant/blob/main/Learning%20Platform/content.py): `Learning Platform/content.py`

### Programming Foundations

- [Python Basics](https://github.com/meridianalgo/learn-quant/blob/main/Python%20Basics%20-%20Functions/functions_tutorial.py): `Python Basics - Functions/functions_tutorial.py`
- [Python Engineering](https://github.com/meridianalgo/learn-quant/blob/main/Advanced%20Python%20-%20AsyncIO/async_fetching.py): `Advanced Python - AsyncIO/async_fetching.py`
- [Algorithms](https://github.com/meridianalgo/learn-quant/blob/main/Algorithms%20-%20Graph/graph_algorithms.py): `Algorithms - Graph/graph_algorithms.py`

### Quant Finance

- [Option Pricing](https://github.com/meridianalgo/learn-quant/blob/main/Black-Scholes%20Option%20Pricing/black_scholes.py): `Black-Scholes Option Pricing/black_scholes.py`
- [Risk Analysis](https://github.com/meridianalgo/learn-quant/blob/main/Risk%20Metrics/risk_summary.py): `Risk Metrics/risk_summary.py`
- [Portfolio Tools](https://github.com/meridianalgo/learn-quant/blob/main/Portfolio%20Management/portfolio_utils.py): `Portfolio Management/portfolio_utils.py`
- [Quant Methods](https://github.com/meridianalgo/learn-quant/blob/main/Quantitative%20Methods%20-%20Statistics/statistical_analysis.py): `Quantitative Methods - Statistics/statistical_analysis.py`

### Trading Systems

- [Market Data](https://github.com/meridianalgo/learn-quant/blob/main/Market%20Data/market_data_utils.py): `Market Data/market_data_utils.py`
- [Trading Strategies](https://github.com/meridianalgo/learn-quant/blob/main/Strategies%20-%20Momentum%20Trading/momentum_strategy.py): `Strategies - Momentum Trading/momentum_strategy.py`
- [Backtesting](https://github.com/meridianalgo/learn-quant/blob/main/Strategies%20-%20Backtesting%20Engine/backtest_engine.py): `Strategies - Backtesting Engine/backtest_engine.py`
- [Execution Simulation](https://github.com/meridianalgo/learn-quant/blob/main/Order%20Execution%20Simulator/order_execution_simulator.py): `Order Execution Simulator/order_execution_simulator.py`

### Data And ML

- [Feature Engineering](https://github.com/meridianalgo/learn-quant/blob/main/Machine%20Learning%20-%20Feature%20Engineering/feature_engineering.py): `Machine Learning - Feature Engineering/feature_engineering.py`
- [Machine Learning](https://github.com/meridianalgo/learn-quant/blob/main/Machine%20Learning%20-%20Random%20Forest/rf_predictor.py): `Machine Learning - Random Forest/rf_predictor.py`
- [News Sentiment](https://github.com/meridianalgo/learn-quant/blob/main/Sentiment%20Analysis%20on%20News/sentiment_analysis.py): `Sentiment Analysis on News/sentiment_analysis.py`

### Other components

- **Learner**
- **Examples And Results**

## Connections

- Learner → Learning Platform: explores lessons
- Learning Platform → Lesson Content: uses lesson material
- Learner → Python Basics: runs lesson
- Learner → Python Engineering: runs lesson
- Learner → Algorithms: runs lesson
- Learner → Option Pricing: runs module
- Learner → Risk Analysis: runs module
- Learner → Portfolio Tools: runs module
- Learner → Quant Methods: runs module
- Learner → Market Data: runs module
- Learner → Trading Strategies: runs module
- Learner → Backtesting: runs module
- Learner → Execution Simulation: runs module
- Learner → Feature Engineering: runs module
- Learner → Machine Learning: runs module
- Learner → News Sentiment: runs module
- Python Basics → Examples And Results: shows examples
- Python Engineering → Examples And Results: demonstrates concepts
- Algorithms → Examples And Results: returns results
- Option Pricing → Examples And Results: computes prices
- Risk Analysis → Examples And Results: reports metrics
- Portfolio Tools → Examples And Results: computes analytics
- Quant Methods → Examples And Results: computes statistics
- Market Data → Examples And Results: provides data
- Trading Strategies → Examples And Results: demonstrates signals
- Backtesting → Examples And Results: returns performance
- Execution Simulation → Examples And Results: simulates orders
- Feature Engineering → Examples And Results: builds features and labels
- Machine Learning → Examples And Results: produces predictions
- News Sentiment → Examples And Results: analyzes news