itertools.chain() should do it. It takes multiple iterables and yields from each one by one, roughly equivalent to: def chain(*iterables): for it in iterables: for element in it: yield element Usage example: from itertools import chain g = (c for c in ‘ABC’) # Dummy generator, just for example c = chain(g, ‘DEF’) # Chain … Read more
What is yield? The yield keyword returns data from a generator function: The heart of a generator function is the yield keyword. In its simplest form, a yield statement looks much like a return statement, except that instead of stopping execution of the function and returning, yield instead provides a value to the code looping … Read more
Create a generator using g = myfunct() Everytime you would like an item, use next(g) (or g.next() in Python 2.5 or below). If the generator exits, it will raise StopIteration. You can either catch this exception if necessary, or use the default argument to next(): next(g, default_value)
:primary_key, :string, :text, :integer, :float, :decimal, :datetime, :timestamp, :time, :date, :binary, :boolean, :references See the table definitions section.
Can I use ES6’s arrow function syntax with generators? You can’t. Sorry. According to MDN The function* statement (function keyword followed by an asterisk) defines a generator function. From a spec document (my emphasis): The function syntax is extended to add an optional * token: FunctionDeclaration: “function” “*”? Identifier “(” FormalParameterList? “)” “{” FunctionBody “}”
To write a lazy function, just use yield: def read_in_chunks(file_object, chunk_size=1024): “””Lazy function (generator) to read a file piece by piece. Default chunk size: 1k.””” while True: data = file_object.read(chunk_size) if not data: break yield data with open(‘really_big_file.dat’) as f: for piece in read_in_chunks(f): process_data(piece) Another option would be to use iter and a helper … Read more
Slicing a list top5 = array[:5] To slice a list, there’s a simple syntax: array[start:stop:step] You can omit any parameter. These are all valid: array[start:], array[:stop], array[::step] Slicing a generator import itertools top5 = itertools.islice(my_list, 5) # grab the first five elements You can’t slice a generator directly in Python. itertools.islice() will wrap an object … Read more
iterator is a more general concept: any object whose class has a __next__ method (next in Python 2) and an __iter__ method that does return self. Every generator is an iterator, but not vice versa. A generator is built by calling a function that has one or more yield expressions (yield statements, in Python 2.5 … Read more