Real-World Python by Lee Vaughan

I’m a "garage project" type of programmer. I like to piddle and play with things that interest me, including automating my investment spreadsheets, programming my drone to recognize certain objects (thanks, PyImageSearch.com!), calculating how long it takes my Polaris pool vacuum to cover my pool’s surface, etc. So, this book was right up my alley. There are 12 chapters covering an eclectic collection of projects. Not all will appeal to everyone, but I found more than enough to keep me interested and busy. You can attempt to solve the problems on your own, or type-in or download the author’s code. The nice thing is that practically every line of code is addressed in the text, so if you encounter any new functions or commands, you don’t have to break off and search the internet. As an advanced beginner, I appreciated this, though it might come across as too much hand holding for intermediate or advanced users. The author assigns you a role in each chapter, like “NASA intern” or “Space Force tech,” to make the projects feel more relevant and interesting. They tend to have a fantastic feel, but at the core, they do address real-world problems, like applying Baye’s Rule, working with text data, scraping the web, manipulating images, decrypting ciphers, plotting charts, making maps from government data, and performing face detection and recognition. The book is very well written and provides interesting information besides the programming-related content. It also takes time to explain how methods like Bayes Rule, face detection, and face recognition work, which was cool. The basis for each is fairly straightforward but requires the blinding speed of modern computers to work. While the book walks you through installing third-party packages, it uses pip, rather than Anaconda. I took the author’s advice and set up a conda (virtual) environment for each chapter and used conda to install the packages. I guess the author didn’t want to force people to use Anaconda, but having a different environment for each project is the best course of action, and conda makes setting all this up really easy. One of the reviewers on the Amazon site says to Read this book and do the work. They’re right. This isn’t a learn-to-code-in-a-day book, it goes beyond the basic snippets. You can learn a lot of functions, packages, and techniques by sticking with it and patiently working through the chapters. I was really impressed with the Searching for Mars Landing Sites chapter. Never knew you could get so much info out of an image. Multiple chapters opened my mind to what you can do with Python. I highly recommend doing all the practice and challenge projects. I feel confident I can transpose knowledge from this book to other projects.

Simple examples, very helpful.

Great Product

I received this book as a goodreads giveaway. This is not a "learn to code python" book. If you have a basic familiarity with the python language, this book helps walk you through some sample projects to apply those skills. The book does a good job of outlining the theory of the project and the tools needed to accomplish the objective. It then provides challenge project objectives using the theories you just applied.

This not a book for beginners.

Couldn't even get through the first project. The Bayes' rule project has a map image requirement that won't open at all. I saved it to my computer and even visited the authors github to download it. It simply doesn't work. I would have loved to develop a deeper understanding of python with this book but I'm disappointed in the amount of wasted time this book could cause for someone. I'm trying to save you that. Don't use this one. Choose another that was written more recently. There is no addressing of this issue anywhere.

Overall, the projects are not very useful. Who's "Real World" is the author referring to? If you can understand the examples, then you wouldn't need this book anyways. What's the point.