{"id":44105,"date":"2020-05-05T10:21:03","date_gmt":"2020-05-05T14:21:03","guid":{"rendered":"https:\/\/ibkrcampus.com\/?p=44105"},"modified":"2022-11-21T09:45:28","modified_gmt":"2022-11-21T14:45:28","slug":"python-itertools-tutorial-part-i","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/python-itertools-tutorial-part-i\/","title":{"rendered":"Python Itertools Tutorial – Part I"},"content":{"rendered":"\n

Python itertools is quite simply, one of the best and elegant solutions to implement an iterator in Python. But what are Iterators?<\/p>\n\n\n\n

An iterator is an object that can be iterated upon and which will return data, one element at a time. It allows us to traverse through all elements of a collection, regardless of its specific implementation.<\/p>\n\n\n\n

While iterators are a great way to list the contents of a list, sometimes you wonder if we can just hide all the complexity into one single line of code. For example, we don\u2019t want to worry about the number of elements when we are comparing two different dataframes. This is where the Python itertools module shines through.<\/p>\n\n\n\n

Let\u2019s understand what are the prerequisites for using itertools.<\/p>\n\n\n\n

Iterators and itertools in Python<\/strong><\/p>\n\n\n\n

Technically, in Python, an iterator is an object which implements the iterator protocol, which in turn consists of the methods __next__()<\/code> and __iter__()<\/code>.<\/p>\n\n\n\n