Quotes About Python

This description requires elaboration when the value and the slice being assigned overlap: L[2:5]=L[3:6], for instance, works fine because the value to be inserted is fetched before the deletion happens on the left.

__next__ raises a built-in StopIteration exception at end-of-file

for calls iter, which calls __iter__

you can do everything in Python that you can in Perl, but

In fact, within Python, instance and class objects are mostly just dictionaries with links between them.

Although we could implement all class behavior as method functions, operator overloading lets objects be more tightly integrated with Python's object model.

Every time you use an expression of the form object.attr where object is an instance or class object, Python searches the namespace tree from bottom to top, beginning with object, looking for the first attr it can find.

Python "best practice" rule of thumb is to use docstrings for functional documentation (what your objects do) and hash-mark comments for more micro-level documentation (how arcane bits of code work).

Although it's possible to emulate true access controls in Python classes, this is rarely done in practice, even for large systems.

Technically, __str__ is preferred by print and str, and __repr__ is used as a fallback for these roles and in all other contexts.

In Python, practicality often beats aesthetics.

Because shelves are Python objects containing Python objects, we can process them with normal Python syntax and development modes. Here, the interactive prompt effectively becomes a database client:

Of course, as I've pointed out numerous times in this book, type checking is usually the wrong thing to do in Python programs (we code to object interfaces, not object types), and the more general isinstance built-in is more likely what you'll want to use in the rare cases where instance class types must be queried.

This search order is called the new-style MRO for "method resolution order" (and often just MRO for short when used in contrast with the DFLR order). Despite the name, this is used for all attributes in Python, not just methods.

Notice that compilation happens when a file is being imported. Because of this, you will not usually see a .pyc byte code file for the top-level file of your program, unless it is also imported elsewhere — only imported files leave behind .pyc files on your machine.

A better and less commonly used solution would be to use two underscores at the front of the method name only: __gatherAttrs for us. Python automatically expands such names to include the enclosing class's name, which makes them truly unique when looked up by the inheritance search. This is a feature usually called pseudoprivate class attributes, which we'll expand on in Chapter 31 and deploy in an expanded version of this class there.

Python has a host of tools that most would consider functional in nature, which we enumerated in the preceding chapter — closures, generators, lambdas, comprehensions, maps, decorators, function objects, and more.

Interestingly, the iteration protocol is even more pervasive in Python today than the examples so far have demonstrated — essentially everything in Python's built-in toolset that scans an object from left to right is defined to use the iteration protocol on the subject object.

In Chapter 32, we'll also meet Python static methods (akin to those in C++), which are just self-less functions that usually process class attributes.

PYTHONPATH and .pth files offer more permanent ways to modify the path — the first per user, and the second per installation.

composites. We'll explore this pattern in more detail in Chapter 31, which is really more about design than about Python. As a quick example, though, we could use this composition idea to code our Manager extension by embedding a Person, instead of inheriting from it.

In Pythons 3.3 and 2.7, you can get help for a module you have not imported by quoting the module's name as a string — for example, help('re'), help('email.message') — but support for this and other modes may differ across Python versions.

remember that generator functions simply return objects with methods that handle next operations run by for loops at each level, and don't produce any results until iterated; and

Python programmers are able to write large OOP frameworks and applications without private declarations — an interesting finding about access controls in general that is beyond the scope of our purposes here.