Download Foundations of Agile Python Development by Jeff Younker PDF

By Jeff Younker

ISBN-10: 1430206357

ISBN-13: 9781430206354

The agile improvement stream represents the newest advances in instruments and methods meant to spice up developer productiveness. Programming language-agnostic, this flow is taking pictures the eye of builders of all disciplines, and is very accepted in state of the art open resource groups equivalent to Python and Ruby.

This is the 1st publication to use those wanted rules to Python builders, introducing either the instruments and methods outfitted and supported by means of the Python neighborhood. Authored via Jeff Younker, a well known member of Python's agile group who's possibly top identified for his construction of a well-liked Python trying out framework, this ebook is bound to be successful between readers who could have reached their limits of data concerning the Python language, but are searching for to enhance their figuring out of the way sound methods can increase productiveness to unprecedented heights.

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Choosing the module name The window has three fields: Source Folder, Package, and Name. The first two are filled in for you. Enter standard into the Name field, and then click Finish. You will be taken back to the workbench, which should look something like Figure 2-21. Figure 2-21. The module has been created. py shows up in the Package Explorer on the left, and that the editor in the center pane is open to this file. main() You’ll notice several things while you type, the most interesting of which is that Pydev makes guesses about what you’re about to type.

The code is the design. You don’t need extensive commenting. The code and unit tests should be clear and readable. Extensive design 17 18 CHAPTER 1 ■ WHAT IS AGILE DEVELOPMENT? documentation is the pinnacle violation of DRY. The impression of the design invariably falls out of sync with the reality of the design. These practices have a common focus. They are about predictability. They are about minimizing waste, both in process and in design effort, and continuous feedback to identify the sources of waste.

The events that are going to happen in the next few weeks are likely to be known. Your estimates should be more accurate because of this, and you’ll have many opportunities to learn from your misjudgments. Fewer inaccuracies should creep in, and you’ll have many chances to tune the estimates before they damage the project. Compare this with long-term estimates. The causes of inaccuracies are likely to have happened months ago. It will be hard to remember them when trying to learn how to estimate for the next project.

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