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Mastering flat_map in Python with List Comprehension

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Introduction In Python, when working with nested lists or iterables, one common challenge is flattening them into a single list while applying transformations. Many programming languages provide a built-in flatMap function, but Python does not have an explicit flat_map method. However, Python’s powerful list comprehensions offer an elegant way to achieve the same functionality. This article examines implementation behavior using Python’s list comprehensions and other methods. What is flat_map ? Functional programming  flatMap is a combination of map and flatten . It transforms the collection's element and flattens the resulting nested structure into a single sequence. For example, given a list of lists, flat_map applies a function to each sublist and returns a single flattened list. Example in a Functional Programming Language: List(List(1, 2), List(3, 4)).flatMap(x => x.map(_ * 2)) // Output: List(2, 4, 6, 8) Implementing flat_map in Python Using List Comprehension Python’...

Cloud Computing: Horizontal Vs. Vertical Scaling

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The purpose of cloud computing is resource utilization. You can scale up the resources in two ways - vertical and horizontal. Adding resources, you can do either horizontally and vertically . The advantages and drawbacks you can find in simple words. Scaling 1. Horizontal Scaling Advantages You can increase workloads in small steps. The upgrade-cost is far less. Scale the system as much as needed. Drawbacks Dependency on software applications is more for Data distribution and parallel processing. On top of that, fewer software applications exist in the market. You May Also Like:  9 Top Services AWS Provided 2. Vertical Scaling Advantages Since it is a single machine, it is easy to manage. On the fly, you can increase workloads. Drawbacks It is expensive. You need a huge investment. The machine should be powerful to take more workloads - future use. Below is the List of Resources that You can do both Horizontal and Vertical Scaling Platform Scaling Network Scaling Container Scaling...