Convert Iterator to List
To transform an Iterator
into a List
in Java, use Streams and Collectors:
StreamSupport.stream() generates a sequential Stream from the iterator, while collect(Collectors.toList()) transforms it into a List.
Exploiting libraries for smooth conversions
Thanks to the rich ecosystem of Java, we have access to a variety of libraries that can expedite certain processes. For instance, when converting an Iterator
to a List
, Guava and Apache Commons Collections can be your best friends.
For instance, in Guava, we can achieve the conversion like so:
And if you are looking for an immutable list, here's how:
The methods Lists.newArrayList()
and ImmutableList.copyOf()
are specifically engineered for these scenarios, and offer performance-optimized solutions.
Apache Commons Collections provides another user-friendly utility:
But remember, IteratorUtils.toList() lacks generic support. So watch out in type-sensitive situations!
Incorporating Java 8 methods for elegance
Java 8 introduced us to new methods such as forEachRemaining
that make transforming Iterator
to List
a piece of cake. Here is how you can quickly populate an existing mutable List
:
The forEachRemaining() method makes short work of processing remaining elements. So bid goodbye to unnecessary boilerplate code!
Traversing from Iterable to List using Spliterator
In certain cases, you might need to transform an Iterable
to a List
but only have an Iterator
to work with. Don't worry, Java 8's Spliterator comes to the rescue:
The spliterator() method succeeds in bridging the gap between Iterable
and streams, thereby facilitating the conversion.
Portable conversion with generic methods
When you're repeatedly converting Iterator
s to List
s throughout your codebase, extract the logic into a generic method for higher efficiency and reusability:
With this convenient method, you can reuse it across multiple sections of your code.
Warnings and precautions
While converting an Iterator
to a List
is powerful, be mindful on data loss and performance pitfalls. Ensure you're not throwing out data unintentionally and that your dataset sizes are within acceptable bounds to avoid memory troubles.
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