The complete core language for existing programmers. Dead Simple Python is a thorough introduction to every feature of the Python language for programmers who are impatient to write production code. Instead of revisiting elementary computer science topics, you’ll dive deep into idiomatic Python patterns so you can write professional Python programs in no time. After speeding through Python’s basic syntax and setting up a complete programming environment, you’ll learn to work with Python’s dynamic data typing, its support for both functional and object-oriented programming techniques, special features like generator expressions, and advanced topics like concurrency. You’ll also learn how to package, distribute, debug, and test your Python project. Master how to: Make Python's dynamic typing work for you to produce cleaner, more adaptive code. Harness advanced iteration techniques to structure and process your data. Design classes and functions that work without unwanted surprises or arbitrary constraints. Use multiple inheritance and introspection to write classes that work intuitively. Improve your code's responsiveness and performance with asynchrony, concurrency, and parallelism. Structure your Python project for production-grade testing and distribution The most pedantically pythonic primer ever printed, Dead Simple Python will take you from working with the absolute basics to coding applications worthy of publication.
The complete core language for existing programmers. Dead Simple Python is a thorough introduction to every feature of the Python language for programmers who are impatient to write production code. Instead of revisiting elementary computer science topics, you’ll dive deep into idiomatic Python patterns so you can write professional Python programs in no time. After speeding through Python’s basic syntax and setting up a complete programming environment, you’ll learn to work with Python’s dynamic data typing, its support for both functional and object-oriented programming techniques, special features like generator expressions, and advanced topics like concurrency. You’ll also learn how to package, distribute, debug, and test your Python project. Master how to: Make Python's dynamic typing work for you to produce cleaner, more adaptive code. Harness advanced iteration techniques to structure and process your data. Design classes and functions that work without unwanted surprises or arbitrary constraints. Use multiple inheritance and introspection to write classes that work intuitively. Improve your code's responsiveness and performance with asynchrony, concurrency, and parallelism. Structure your Python project for production-grade testing and distribution The most pedantically pythonic primer ever printed, Dead Simple Python will take you from working with the absolute basics to coding applications worthy of publication.
A comprehensive survey on the use of bedside skills and perimetric devices to the test visual fields, and how to interpret the results. To develop the clinician's interpretative skills, the authors include a chapter on visual anatomy and an atlas of 100 real-life cases arranged in anatomic order from retina to striate cortex. By placing a brief clinical vignette with a visual field on one side of the page and a description of the field and its causal lesion on the opposite side, the reader will be able to learn interpretation in a simulated clinical setting. An additional quiz section of twenty randomly arranged visual fields provides readers with an opportunity to test their newly acquired skills.
Eye witness testimony, training, driving, and display design: these are just a few of the real-world domains in which depend on undivided attention. Emphasizing the link between theory and application, Applied Attention Theory provides a deep understanding of how theories of attention, developed from laboratory-based psychological research, can inform our understanding of everyday human performance in a wide number of applications and environments. The basic theories discussed concern divided, focused, and selective attention, and areas of application include mental workload measurement, multi-tasking, distracted driving, complex display design, education, and the training of attentional skills. Includes an extensive reference list and citations to both basic and applied work Provides intuitive descriptions of attentional phenomena in the world beyond the laboratory Discusses applications of attention theory to diverse areas such as graph design, distracted driving, and process control Offers an engineering orientation as well as a psychological orientation to research Highlights the critical role of effort in single task behavior, such as decision and choice, to the extent that humans tend to be effort-conserving in their choice of activities Examines how multiple tasks are managed in a discrete fashion
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.