Intermediate Python

Intermediate Python

Oswald Campesato
Paperback
August 2023
9781501521744
More details
  • Publisher
    Mercury Learning and Information
  • Published
    22nd August
  • ISBN 9781501521744
  • Language English
  • Pages 196 pp.
  • Size 7" x 9"
$54.99
Add to Cart
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August 2023
9781501518379
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  • Publisher
    Mercury Learning and Information
  • Published
    1st August
  • ISBN 9781501518379
  • Language English
  • Pages 196 pp.
  • Size 7" x 9"
$155.00
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August 2023
9781501518386
More details
  • Publisher
    Mercury Learning and Information
  • Published
    1st August
  • ISBN 9781501518386
  • Language English
  • Pages 196 pp.
  • Size 7" x 9"
$54.99
Add to Cart

This book provides you with relevant information about using intermediate Python 3.x for a variety of topics, such as comprehensions, iterators, generators, regular expressions, OOP, queues and stacks, and recursion. Each chapter contains an assortment of code samples that illustrate the topics covered in the chapter material. Companion files including code samples are available by writing to the publisher.

FEATURES:

  • Covers intermediate Python concepts such as comprehensions, iterators, generators, regular expressions, custom classes, OOP, queues / stacks, recursion, and combinatorics
  • Features companion files with numerous Python code samples

1: Data Structures in Python

2: Comprehensions, Iterators, and Generators

3: Regular Expressions

4: Custom Classes

5: Queues and Stacks

6: Recursion and Combinatorics

Index

Oswald Campesato

Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Cruz and specializes in Deep Learning, NLP, Android, and Python. He is the author/co-author of over forty-five books including Data Science Fundamentals Pocket Primer, Python 3 for Machine Learning, and the Python Pocket Primer (Mercury Learning and Information).

comprehensions; iterators; generators; regular expressions; OOP; queues and stacks; recursion; programming; java; data processing; data mining; computer science; data analysis