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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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What is IBM InfoSphere DataStage

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It integrates data across multiple systems using a high-performance parallel framework, and it supports extended metadata management and enterprise connectivity.

IBM InfoSphere

Powerful, scalable ETL platform—supports the collection, integration, and transformation of large volumes of data, with data structures ranging from simple to complex.
  • Support for big data and Hadoop—enables you to directly access big data on a distributed file system, and helps clients more efficiently leverage new data sources by providing JSON support and a new JDBC connector. 
  • Near real-time data integration—as well as connectivity between data sources and applications. 
  • Workload and business rules management—helps you optimize hardware utilization and prioritize mission-critical tasks. 
  • Ease of use—helps improve speed, flexibility, and effectiveness to build, deploy, update and manage your data integration infrastructure. 
  • Rich support for DB2Z and DB2 for z/OS—including data load optimization for DB2Z and balanced optimization for DB2 on z/OS 
  • Ref: IBM

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