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Scientific Computing with Python

You're reading from   Scientific Computing with Python High-performance scientific computing with NumPy, SciPy, and pandas

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781838822323
Length 392 pages
Edition 2nd Edition
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Authors (4):
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Olivier Verdier Olivier Verdier
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Olivier Verdier
Jan Erik Solem Jan Erik Solem
Author Profile Icon Jan Erik Solem
Jan Erik Solem
Claus Führer Claus Führer
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Claus Führer
Claus Fuhrer Claus Fuhrer
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Claus Fuhrer
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Table of Contents (23) Chapters Close

Preface 1. Getting Started 2. Variables and Basic Types FREE CHAPTER 3. Container Types 4. Linear Algebra - Arrays 5. Advanced Array Concepts 6. Plotting 7. Functions 8. Classes 9. Iterating 10. Series and Dataframes - Working with Pandas 11. Communication by a Graphical User Interface 12. Error and Exception Handling 13. Namespaces, Scopes, and Modules 14. Input and Output 15. Testing 16. Symbolic Computations - SymPy 17. Interacting with the Operating System 18. Python for Parallel Computing 19. Comprehensive Examples 20. About Packt 21. Other Books You May Enjoy 22. References

9.3.3 Iterator tools

Now, we will introduce a couple of iterator tools that often come in very handy:

  • enumerate is used to enumerate another iterator. It produces a new iterator that yields pairs (iteration, element), where iteration stores the index of the iteration:
A = ['a', 'b', 'c']
for iteration, x in enumerate(A):
    print(iteration, x)     # result: (0, 'a') (1, 'b') (2, 'c')
  • reversed creates an iterator from a list by going through that list backward. Notice that this is different from creating a reversed list:
A = [0, 1, 2]
for elt in reversed(A):
    print(elt)      # result: 2 1 0
  • itertools.count is a possibly infinite iterator of integers:
for iteration in itertools.count():
    if iteration > 100:
       break # without this, the loop goes on forever
       print(f'integer: {iteration}')
       # prints the 100 first integer
  • intertools.islice truncates...
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