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  • Testing In Python: Robust Testing For Professionals

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Testing In Python: Robust Testing For Professionals

by Noah Gift (Author), Alfredo Deza (Author) Format: Paperback
90 days free of Amazon Music with purchase Terms
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Getting started with testing can be hard, and this book aims make it all very easy by using examples and explaining the process in a straightforward way. Testing is a core principle of robust software implementations and should be a prime skill to master that can be applied to any project.
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  1. ISBN-13
    979-8616960641
  2. Publication date
    February 27, 2020
  3. Language
    English
  4. Dimensions
    8.5 x 0.45 x 11 inches
  5. Print length
    177 pages
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Product details

About the authors

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  1. Alfredo Deza

    Alfredo Deza

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    Alfredo Deza is a passionate software engineer, avid open source developer, Vim plugin author, photographer, and former Olympic athlete. He has given several lectures around the world about Open Source Software, personal development, and professional sports. He has rebuilt company infrastructure, designed shared storage, and replaced complex build systems, always in search of efficient and resilient environments. With a strong belief in testing and documentation, he continues to drive robust development practices wherever he is.

    As a spirited knowledge-craving developer Alfredo can be found giving presentations in local groups about Python, file systems and storage, system administration, and professional sports.

    See more on the author's page
  2. Noah Gift

    Noah Gift

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    Noah Gift is the founder of Pragmatic AI Labs. Noah Gift lectures at MSDS, at Northwestern, Duke MIDS Graduate Data Science Program, and the Graduate Data Science program at UC Berkeley and the UC Davis Graduate School of Management MSBA program, and UNC Charlotte Data Science Initiative. He is teaching and designing graduate machine learning, A.I., Data Science courses, and consulting on Machine Learning and Cloud Architecture for students and faculty. These responsibilities include leading a multi-cloud certification initiative for students.

    Noah is a Python Software Foundation Fellow, and AWS ML Hero. He currently holds the following industry certifications for AWS: AWS Subject Matter Expert (SME) on Machine Learning, AWS Certified Solutions Architect, and AWS Certified Machine Learning Specialist, AWS Certified Big Data Specialist, AWS Academy Accredited Instructor, AWS Faculty Ambassador. He also is certified on both the Google and Azure platform: Google Certified Professional Cloud Architect, Certified Microsoft MTA on Python. He has published over 100 technical publications including multiple books on subjects ranging from Cloud Machine Learning to DevOps. Publications appear in Forbes, IBM, Red Hat, Microsoft, O’Reilly, Pearson, Udacity, Coursera, datascience.com, and DataCamp. Workshops and Talks around the world for organizations including NASA, PayPal, PyCon, Strata, O’Reilly Software Architecture Conference, and FooCamp. As an SME on Machine Learning for AWS, he helped created the AWS Machine Learning certification.

    He has worked in roles ranging from CTO, General Manager, Consulting CTO, Consulting Chief Data Scientist, and Cloud Architect. This experience has been with a wide variety of companies: ABC, Caltech, Sony Imageworks, Disney Feature Animation, Weta Digital, AT&T, Turner Studios, and Linden Lab, and industries: Television, Film, Games, SaaS, Sports, Telecommunications. He has film credits in many major motion pictures for technical work, including Avatar, Spider-Man 3, and Superman Returns.

    He has been responsible for shipping many new products at multiple companies that generated millions of dollars of revenue and had a global scale. Currently, he is consulting startups and other companies, on Machine Learning, Cloud Architecture, and CTO level consulting as the founder of Pragmatic A.I. Labs.

    See more on the author's page
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Customer reviews

4 out of 5 stars
9 global ratings

Top reviews from the United States

  • L. Reding
    3 out of 5 stars
    Useful book but plagued by lack of consistency
    Reviewed in the United States on September 19, 2020
    Format: Kindle
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    Overall, this book contains a lot of useful information. I just wish the authors applied the same care to quality-controlling their book as they do their code:

    - There are typos throughout the book

    - pytest is not even invoked consistently throughout the book

    - The book is physically huge, needlessly and obnoxiously so

    - Some of the chapters don't integrate well (e.g., Chapters 5 and 10 feel out of place)

    - In some cases (e.g., the use of fixtures in Chapter 6), the authors use frameworks prior to the sections where they explain them

    - At times I felt the book was unfocused. There were pages where I had to double-check the title of the book because I felt the authors had steered so far away from testing.

    2 people found this helpful
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  • Alberto Artasanchez
    5 out of 5 stars
    Promising book
    Reviewed in the United States on February 23, 2020
    Format: Kindle
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    I had the pleasure of receiving an advance copy of this book.

    I really enjoyed reading the book and I was able to learn a few new tricks. I like the fact that the authors assume you have some familiarity with Python and technology already and therefore don't waste much time explaining too many basics. They quickly get to the core of the book which is how to create well-architected tests in Python. They cover how these tests can set up locally as well as in some of the most popular cloud environments like AWS and GCP.

    By the time you read this, the authors might have completed the book but at least in the copy I received the authors did mention that the book was work in progress and a few of the chapters are currently stubs. I revisit this review when the chapters are done. I am looking forward to using the lessons of this book in my current projects.

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  • Rigo Roche
    5 out of 5 stars
    Easy to follow and to the point. Great guide!!
    Reviewed in the United States on March 18, 2020
    Format: Kindle
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    Very easy to follow. The examples are clear and to the point. If you need to do unit testing for your python apps, this is the book for you. The price of not wasting time by googling how to do things that you don’t remember is worth one order of magnitude the cost of the book. Great for a quick reference guide. Saves me time and makes my algorithms code come out with very clean logic.

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  • Patric G.
    5 out of 5 stars
    Perfect if you're new to software testing in Python
    Reviewed in the United States on April 5, 2020
    Format: Kindle
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    As a data scientist increasingly tasked with production deployments of my Python-based models, this was exactly what I needed. Testing is critical to ensuring that my algorithms and applications behave as intended for my clients, and -- with a focus on the pytest library -- this book covers everything on the topic from the ground up.

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  • Sruthi
    5 out of 5 stars
    Very Helpful
    Reviewed in the United States on March 22, 2020
    Format: Paperback
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    This is a gift aspiring data engineers! Must Read!

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