This content originally appeared on DEV Community and was authored by Dylan
For most of my career, I've worked primarily as a Python developer. There were occasional trips into the frontend for some JavaScript or a brief detour through a Go application, but the vast majority of my work was solidly Python.
That is, until I joined Square. Square might be better known for its Ruby code, but there is also a sizable chunk of Java within its codebase. So when I came to Square, I knew I'd be putting away my list comprehensions, generators, and @decorators, and instead I'd be learning some new programming language patterns and idioms.
But of course, my Python experience would not be for nothing. As it turns out, we can find parallel ideas throughout most programming languages. In this series, I'll be highlighting some of these parallels I've encountered switching from Python to Java in hopes that it might help someone else who also finds themselves crossing this language barrier!
Introduction
It's impossible to avoid list (and dictionary!) comprehensions when working in Python. Whether you need to create a sublist by filtering out certain values, transform each element in an existing list, or rearrange keys and values into a new dictionary, comprehensions are a quintessential Python tool.
They're so useful in Python and so numerous that you might find yourself afraid that you can't do even the simplest tasks in Java. You might recall hearing other developers groan about Java's verbosity and heavy-handedness as you start writing...
List<Integer> evenIntegers = new ArrayList<Integer>();
for (Integer integer : allIntegers) {
if (integer % 2 == 0) {
evenIntegers.add(integer);
}
}
...at least that's how I felt, until I learned about Streams. With Streams, we don't have to rewire our brains or begrudgingly write lengthy boilerplate for simple tasks.
.stream(), .collect()
However, this is Java and we are going to be writing some boilerplate. Types are everything in Java and in order to leverage the Streams API, we'll have to have an object of type Stream<T>. Luckily this is often as easy as calling .stream() on our object (assuming our object is iterable: a list, set, array, etc).
Once we have our Stream<T> object, we can apply a series of filters and transformations, but in the end we're going to want a list again (or a set, map, etc). This is where .collect() comes in along with various Collectors. In this post, we'll only focus on two Collector methods, Collectors.toList() and Collectors.toMap().
The basic structure of a stream is like so
obj.stream()
<intermediate actions>
.collect(...)
More verbose than Python, certainly, but not too bad!
So without further ado, let's check out a few common operations and how we might do them with Python's comprehensions and then with Java's Streams.
Filtering
Imagine we have a list of integers and we want only the even numbers. (The example is trivial, but I think it generalizes well enough.)
In Python we would solve this problem with a simple list comprehension1:
even_nums = [n for n in list_of_nums if n % 2 == 0]
With Java Streams, we could accomplish this like so:
List<Integer> evenNums = listOfNums.stream()
.filter(n -> n % 2 == 0)
.collect(Collectors.toList());
Transforming
Sometimes we want to take one list of elements and transform them into something else. For a simple example, let's take our same list of integers and multiple each by two.
First in Python2,
doubled_nums = [n * 2 for n in list_of_nums]
and then with Java Streams,
List<Integer> doubledNums = listOfNums.stream()
.map(n -> n * 2)
.collect(Collectors.toList());
Lists to Dictionaries
Not everything can be accomplished with lists3, sometimes we need to put things into a dictionary (or a Map, as they're called in Java land).
Suppose we have a list of User objects and we want a dictionary of each user.name keyed by their user.id.
names_by_id = {user.id: user.name for user in users}
It's a little more complicated in Java. In our previous examples, we used Collectors.toList(). Now that we want a Map, we'll have to use Collectors.toMap(). This collector asks for a lambda function to produce the key and another one to produce the value:
Map<Integer, String> namesById = users.stream()
.collect(Collectors.toMap(
user -> user.getId(),
user -> user.getName()));
Conclusion
Java has a reputation for having a verbose syntax, and Streams are no exception. But they are a marked improvement over excessive loops and temporary variables for otherwise simple transformations and collections.
While this post highlighted some ways that we can use Streams when we would otherwise write a comprehension in Python, it's important to know that Streams are much more than this and are capable of some really cool things (parallelization, lazy evaluation, sorting, querying, etc, etc)!
To learn more about Streams, check out this post by Eugen Paraschiv on Stackify and of course the Java documentation
-
Python does have support for the more functional programming-style
filterthat more closely mirrors Java's implementation. Though list comprehensions are generally considered to be more Pythonic thanfilter. ↩ -
Like the previous note, Python has support for
mapbut in most cases the list comprehension is preferred. ↩ -
Lisp programmers might take issue with this statement. ↩
This content originally appeared on DEV Community and was authored by Dylan
Dylan | Sciencx (2022-04-08T17:36:25+00:00) From Python to Java: Comprehensions and Streams. Retrieved from https://www.scien.cx/2022/04/08/from-python-to-java-comprehensions-and-streams/
Please log in to upload a file.
There are no updates yet.
Click the Upload button above to add an update.