Tutorials
Hands-On Python
Hands-On Python
  • Hands-On Python Tutorial For Real-World Business Analytics Problems
  • Preface
    • Section I. A Note From The Author
    • Section II. Tutorial Overview
    • Section III. What Is The Preflight Checklist?
    • Section IV. Supplimentery Material
  • Preflight Checklist
    • Section V. Select Your Difficulty Setting
    • Section VI. Download Anaconda
    • Section VII. Download PyCharm (Optional)
    • Section VIII. Download SQL Server Developer Edition
    • Section IX. Configure Database Environment
    • Section X. Download The Source Code
    • Section XI. Starting JupyterLab
    • Section XII. How To Get Help With This Tutorial
  • Language Basics
    • Lesson 1. Obligatory Hello World
    • Lesson 2. Code Comments
    • Lesson 3. Data Types
    • Lesson 4. Variables
    • Lesson 5. String Concatenation
    • Lesson 6. Arithmetic Operators
    • Lesson 7. Making Decisions
    • Lesson 8. Control Flow With if-elif-else
    • Lesson 9. Control Flow With while
    • Lesson 10. Data Structures Part I: List
    • Lesson 11. Data Structures Part II: Tuples
    • Lesson 12. Data Structures Part III: Dictionaries
    • Lesson 13. Looping With for
    • Lesson 14. Functions
    • Lesson 15. Importing Modules
    • Lesson 16. Python Programming Standards
  • Advanced Topics
    • Lesson 17. Functional Programing With map
    • Lesson 18. Generators
    • Lesson 19. Comprehensions
    • Lesson 20. Basic File Operations
    • Lesson 21. Working With Data In Numpy
    • Lesson 22. Working With Data In Pandas
    • Lesson 23. Working With JSON
    • Lesson 24. Making File Request Over HTTP And SFTP
    • Lesson 25. Interacting With Databases
    • Lesson 26. Saving Objects With Pickle
    • Lesson 27. Error Handling
    • Lesson 28. Bringing It All Together
  • Solutions To Real World Problems
    • Lesson 29. Download A Zip File Over HTTP
    • Lesson 30. Looping Over Files In A Directory
    • Lesson 31. Convert Comma Delmited Files To Pipe Delimited
    • Lesson 32. Combining Multiple CSVs Into One File
    • Lesson 33. Load Large CSVs Into Data Warehouse Staging Tables
    • Lesson 34. Efficiently Write Large Database Query Results To Disk
    • Lesson 35. Working With SFTP In The Real World
    • Lesson 36. Executing Python From SQL Server Agent
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  • Comprehension Syntax
  • Examples
  • Now you try it!
  1. Advanced Topics

Lesson 19. Comprehensions

Comprehensions are another Python goodie that lets you write code in the functional programming paradigm. I am only going to talk about them here very lightly as functional programming is a bit beyond this tutorial. We will see them later in the solutions section.

A comprehension is another construct that allows you to loop over an iterable object. Specifically, it lets you iterate over lists, dictionaries, and sets which we have not talked about nor will we in this particular tutorial.

Comprehensions are a way to write Pythonic code. You can use comprehensions to take a lot of complex logic and reduce it to a line of code. Be aware that the return datatype of a comprehension is a list.

Comprehension Syntax

[[function] for x in [list, dict, or set]]

Examples

Example #1 A Different Kind Of Loop Redux

In this example we are going to take example #2 from lesson 17 and rewrite it as a comprehension.

#The original function using map.
count = [1,2,3,4,5]

newcount = list(map(lambda x: x + 1, count))

print(newcount)
#The new function using a comprehension.

count = [1,2,3,4,5]

newcount = [x + 1 for x in count]

print(newcount)

Now you try it!

Don't copy and past. Type the code yourself!

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