Pro Python

Pro Python

Marty Alchin

Language: English

Pages: 379

ISBN: B00MY0I600

Format: PDF / Kindle (mobi) / ePub

You’ve learned the basics of Python, but how do you take your skills to the next stage? Even if you know enough to be productive, there are a number of features that can take you to the next level in Python. Pro Python, Second Edition explores concepts and features normally left to experimentation, allowing you to be even more productive and creative.

In addition to pure code concerns, Pro Python develops your programming techniques and approaches, which will help make you a better Python programmer. This book will improve not only your code but also your understanding and interaction with the many established Python communities.

This book takes your Python knowledge and coding skills to the next level. It shows you how to write clean, innovative code that will be respected by your peers. With this book, make your code do more with introspection and meta-programming. And learn and later use the nuts and bolts of an application, tier-by-tier as a complex case study along the way.

For more information, including a link to the source code referenced in the book, please visit

What you’ll learn

  • Write strong Python code that will be respected in the Python community
  • Understand the reasons behind big design decisions in Python
  • Write programs that can reconfigure themselves in Python
  • Disguise your code as different types of objects in Python
  • Inspect just about any object in Python
  • Prepare your code for international audiences
  • Ensure code quality with rigorous testing

Who this book is for

This book is for intermediate to advanced Python programmers who are looking to understand how and why Python works the way it does and how they can take their code to the next level.

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Own. Unfortunately, that would cause its own confusion when subclassing it, by requiring something like an IntegerColumn to subclass StringColumn. To keep things clearer, the base class will remain Column and each subclass will add only the necessary features on top of it, even though there’s nothing useful to add beyond the name. IntegerColumn The next field type to add manages integers. Numbers are used quite a bit in spreadsheets, storing everything from ages to sales figures to inventory.

Reading values. Because Decimal is designed to work with strings, it’s just as easy as the other columns shown so far: import decimal class DecimalColumn(Column): ŠŠŠŠ??? ŠŠŠŠA column that contains data in the form of decimal values, ŠŠŠŠrepresented in Python by decimal.Decimal. ŠŠŠŠ??? ŠŠŠŠdef to_python(self, value): ŠŠŠŠŠŠŠŠ return decimal.Decimal(value) There’s one difference about this method from those in the other classes, however. Each of the others have the added side-effect of raising a.

In their entirety in advance, and many don’t even need to have a finite upper limit at all. This category includes the set of positive odd numbers, squares of integers, and the Fibonacci sequence, all of which are infinite in length and easily computable. Therefore, they’re best suited for pure iteration, without the need to populate a list in advance. The main benefit to this is memory allocation. A program designed to print out the entire range of the Fibonacci sequence only needs to keep a.

D['spam'] 'eggs' >>> d.spam 'eggs' >>> d.spam =Š'ham' >>> d.spam 'ham' >>> del d.spam >>> d.spam Traceback (most recent call last): ŠŠ ... KeyError: 'spam' WARNING: RAISE THE RIGHT EXCEPTION This error message brings up an important point about working with these types of overridden attributes. It’s very easy to overlook how exceptions are handled inside your function, so you may end up raising an exception that doesn’t make any sense; if an attribute doesn’t exist, you would reasonably expect.

Will automatically create an iterator designed to work with it. This new iterator calls __getitem__() several times, each with a value from a series of numbers, beginning with zero, until __getitem__() raises an IndexError. Therefore, our custom Range iterable can be rewritten quite simply: class Range: ŠŠŠŠdef __init__(self, count): ŠŠŠŠŠŠŠŠself.count =Šcount ŠŠŠŠdef __getitem__(self, index): ŠŠŠŠŠŠŠŠif index < self.count: ŠŠŠŠŠŠŠŠŠŠŠŠreturn index ŠŠŠŠŠŠŠŠraise IndexError >>> rŠ= Range(5) >>>.

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