List comprehensions: List comprehensions are pretty neat. Before studying Python I did not know what they were. This is a wonderful way to perform some operation on an entire list. Let me explain with an example. Let's say we have a list of numbers and want another list containing the double of all the numbers greater than 5 from the first list. In Java we would have to do something like this:
However, in Python we can perform this operation using list comprehension like this:
Isn't this nice?
Lambda expressions: Python supports Lambda expressions but it does not support closures like Groovy. I wish Python supported closures.
Unchecked exceptions: The blogosphere has had more than it's share of discussions on checked vs. unchecked exceptions. I will not spam your feed reader with any more on this topic. Suffice to say, I like them. In case you want to read more about this debate, this Developer works article is a good starting point.
Pickle: Python has a module called pickle for object serialization and deserialization. Using pickle we can save an object to a file and then reconstruct it as well. We can also use pickle to transmit objects over Internet sockets. There is C implementation of pickle called cPickle which is many times faster. Python does not seem to use anything to signify that an object can be pickled (like the Serializable interface of Java), however, it does have a notion of picklable and non picklable objects. I am still not sure if Python has the equivalent of SerialVerUID for forward compatibility of serialized objects.
repr: Python has a function called repr() which converts an object into a canonical (stringified... if that is a word :-) ) form.
Call
I like this statement. Joshua Bloch wrote in his book Effective Java, Item 9, that if a class's toString() method is documented, then it should return a string such that we should be able to recreate a similar object from that string using the class's String constructer. The repr() function fulfills that criteria.
private static ListgetDoubleOfMembers(List numbers) {
Listresult = new ArrayList ();
for(int num : numbers) {
if(num > 5) {
result.add(num*2);
}
}
return result;
}
However, in Python we can perform this operation using list comprehension like this:
[n*2 for n in numbers n > 5]
Isn't this nice?
Lambda expressions: Python supports Lambda expressions but it does not support closures like Groovy. I wish Python supported closures.
Unchecked exceptions: The blogosphere has had more than it's share of discussions on checked vs. unchecked exceptions. I will not spam your feed reader with any more on this topic. Suffice to say, I like them. In case you want to read more about this debate, this Developer works article is a good starting point.
Pickle: Python has a module called pickle for object serialization and deserialization. Using pickle we can save an object to a file and then reconstruct it as well. We can also use pickle to transmit objects over Internet sockets. There is C implementation of pickle called cPickle which is many times faster. Python does not seem to use anything to signify that an object can be pickled (like the Serializable interface of Java), however, it does have a notion of picklable and non picklable objects. I am still not sure if Python has the equivalent of SerialVerUID for forward compatibility of serialized objects.
repr: Python has a function called repr() which converts an object into a canonical (stringified... if that is a word :-) ) form.
Call
repr(obj)
to get the string form of an obejct. The return value can be controlled by implementing the __repr__() function in the class. Typically the following should be true:
eval(repr(obj)) == obj
I like this statement. Joshua Bloch wrote in his book Effective Java, Item 9, that if a class's toString() method is documented, then it should return a string such that we should be able to recreate a similar object from that string using the class's String constructer. The repr() function fulfills that criteria.
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