Crystal vs. Python vs. QuantConnect vs. test_coverage Comparison Chart

Crystal’s syntax is heavily inspired by Ruby’s, so it feels natural to read and easy to write, and has the added benefit of a lower learning curve for experienced Ruby devs. Crystal is statically type-checked, so any type errors will be caught early by the compiler rather than fail on runtime. Moreover, and to keep the language clean, Crystal has built-in type inference, so most type annotations are unneeded. All types are non-nilable in Crystal, and available variables are represented as a union between the type and nil. As a consequence, the compiler will automatically check for null references in compile time. Crystal’s answer to metaprogramming is a powerful macro system, which ranges from basic templating and AST inspection to types inspection and running arbitrary external programs.

World class interactive tutorials to introduce you to the fundamentals of algorithmic trading. We provide everything you need to bring your ideas to reality, from high quality data, powerful compute, and an online coding lab. Deploy your strategy to institutional grade live-trading architecture on one of our 12 supported brokerages. Design and test your strategy on our free data and when you're ready deploy it live to your brokerage. Code in multiple programming languages and harness our cluster of hundreds of servers to run your backtest to analyse your strategy in Equities, FX, Crypto, CFD, Options or Futures Markets. Build your quantitative organization from our cloud platform to leverage our 8 years of experience. With over 100,000 users we have proven we can scale to meet even the most ambitious of requirements. With code encryption and version control you can be sure your intellectual property is safe.