Python is not just powerful for writing algorithms, but it is also easy to use, making it an excellent choice for traders. Python supports functional programming, which makes writing algorithmic trading structures easier. The pyodbc module, for example, imports data from relational databases, using a comma as a delimiter. Python also allows users to connect to database servers.

Programming in Python is easier than in other languages, making it an ideal choice for short and medium-term trades. In addition to allowing algorithmic traders to skip steps that they would normally have to complete using other languages, it also reduces maintenance costs. Python also provides a huge variety of scientific libraries that make it easy for quant traders to conduct data analysis at high speed. With these qualities, Python is the most popular programming language for algorithmic trading.

Although C++ is not as user-friendly as Python, thousands of professionals believe that it is the best programming language for building algorithmic trading software. It is a reliable language, which is important when working with large amounts of data. Thousands of professional programmers use C++ for many legacy systems in the financial industry. However, you will need to have some knowledge of C before moving on to Python. A good place to learn the latter is a C++ tutorial.

Another great choice for algorithmic trading is Julia, a fusion of Python and C++. Julia combines the advantages of both languages and solves the problem of two-languages. This language also has a robust developer community. But you should be aware of the language's learning curve. Those who choose Python should know it well. It is not a bad choice, but it will take some time to get used to it.