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Python map() and lambda() Use Cases and Examples

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 In Python, map() and lambda functions are often used together for functional programming. Here are some examples to illustrate how they work. Python map and lambda top use cases 1. Using map() with lambda The map() function applies a given function to all items in an iterable (like a list) and returns a map object (which can be converted to a list). Example: Doubling Numbers numbers = [ 1 , 2 , 3 , 4 , 5 ] doubled = list ( map ( lambda x: x * 2 , numbers)) print (doubled) # Output: [2, 4, 6, 8, 10] 2. Using map() to Convert Data Types Example: Converting Strings to Integers string_numbers = [ "1" , "2" , "3" , "4" , "5" ] integers = list ( map ( lambda x: int (x), string_numbers)) print (integers) # Output: [1, 2, 3, 4, 5] 3. Using map() with Multiple Iterables You can also use map() with more than one iterable. The lambda function can take multiple arguments. Example: Adding Two Lists Element-wise list1 = [ 1 , 2 , 3 ]
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Amazon web services -Object Storage

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Object Storage:

Object storage provides the ability to store, well, objects — which are essentially collections of digital bits. Those bits may represent a digital photo, an MRI scan, a structured document such as an XML file — or the video of your cousin's embarrassing attempt to ride a skateboard down the steps at the public library (the one you premiered at his wedding).

Object storage offers the reliable (and highly scalable) storage of collections of bits, but imposes no structure on the bits.

The structure is chosen by the user, who needs to know, for example, whether an object is a photo (which can be edited), or an MRI scan (which requires a special application for viewing it). The user has to know both the format as well as the manipulation methods of the object. The object storage service simply provides reliable storage of the bits.

Difference between Object storage and File storage

Object storage differs from file storage, which you may be more familiar with from using a PC. File storage offers update functionality, and object storage does not. For example, suppose you are storing logging output from a program.

The program constantly adds new logging entries as events occur; creating a new object each time an additional log record is created would be incredibly inconvenient. By contrast, using file storage allows you to continuously update the file by appending new information to it — in other words, you update the file as the program creates new log records.


Related: 30 high paying Technology (IT) Jobs


Object storage offers no such update ability. You can insert or retrieve an object, but you can't change it. Instead, you update the object in the local application and then insert the object into the object store. To let the new version retain the same name as the old version, delete the original object before inserting the new object with the same name. The difference may seem minor, but it requires different approaches to managing stored objects.

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