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pro_dotnet_design_pattern_framework-4.5 icon pro_dotnet_design_pattern_framework-4.5

Design patterns are solutions to software design problems you find again and again in real-world application development. Patterns are about reusable designs and interactions of objects. The 23 Gang of Four (GoF) patterns are generally considered the foundation for all other patterns. They are categorized in three groups: Creational, Structural, and Behavioral (for a complete list see below). To give you a head start, the C# source code for each pattern is provided in 2 forms: structural and real-world. Structural code uses type names as defined in the pattern definition and UML diagrams. Real-world code provides real-world programming situations where you may use these patterns. A third form, .NET optimized, demonstrates design patterns that fully exploit built-in .NET 4.5 features, such as, generics, attributes, delegates, reflection, and more. These and much more are available in our .NET Design Pattern Framework 4.5. You can see the Singleton page for a .NET 4.5 Optimized example.

propalyzer icon propalyzer

Web app that helps investors evaluate residential investment property opportunities

py-quantmod icon py-quantmod

Powerful financial charting library based on R's Quantmod | http://py-quantmod.readthedocs.io/en/latest/

pyex icon pyex

Complete Python interface to IEX and IEX cloud APIs

pyfx icon pyfx

Forex Trading Platform written in Python

pyportfolioopt icon pyportfolioopt

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

python-bigone icon python-bigone

BigONE Exchange API python implementation for automated trading

python-binance icon python-binance

Binance Exchange API python implementation for automated trading

pythonic icon pythonic

Trading platform for digital currencies

pytrade icon pytrade

Django project for online trading simulator

pytrading icon pytrading

A library for stock market analysis and automated trading, powered by sklearn.

qbit icon qbit

The Java microservice lib

qfipy icon qfipy

Financial markets modeling & Portfolio optimization

qq-pat icon qq-pat

The qq-pat library provides you with an easy interface for the creation of graphs and the calculation of statistics for financial time series. It provides functionality similar to the R library PerformanceAnalystics in Python. It allows you to draw graphs, calculate general statistics and perform some advanced analysis such as Monte Carlo simulations and minimum variance portfolio optimizations.

quant icon quant

Codera Quant is a Java framework for algorithmic trading strategies development, execution and backtesting via Interactive Brokers TWS API or other brokers API

quantcomponents icon quantcomponents

QuantComponents - Free Java components for Quantitative Finance and Algorithmic Trading

quantdom icon quantdom

Python-based framework for backtesting trading strategies & analyzing financial markets [GUI :neckbeard:]

quantitative-notebooks icon quantitative-notebooks

Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy

quantpp icon quantpp

quant++: A C++ quantitative trading framework.

quantshim icon quantshim

A Python framework for R&D of financial investment strategies, and trading them algorithmiclly via Quantopian.com

quantstats icon quantstats

Portfolio analytics for quants, written in Python

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