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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 ]

IoT Project in auto industry real guidelines you need to implement

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IoT enabling traffic management and control: Cars should be able to organise themselves in order to avoid traffic jams and to optimise drive energy usage. 1# Why IoT in auto industry This may be done in coordination and cooperation with the infrastructure of a smart city’s traffic control and management system. Additionally dynamic road pricing and parking tax can be important elements of such a system. Further mutual communications between the vehicles and with the infrastructure enable new methods for considerably increasing traffic safety, thus contributing to the reduction in the number of traffic accidents. IOT implementation #2 New Opportunities IoT enabling new transport scenarios (multi-modal transport): In such scenarios, e.g. automotive OEMs see themselves as mobility providers rather than manufacturers of vehicles. The user will be offered an optimal solution for transportation from Ato B, based on all available and suitable transport means. Thus, based