By Magnus Lie Hetland
Achieve a primary knowing of Python's syntax and contours with the second one version of starting Python, an up–to–date advent and functional reference. overlaying a wide range of Python–related programming subject matters, together with addressing language internals, database integration, community programming, and internet prone, you'll be guided through sound improvement rules. Ten accompanying tasks will make sure you can get your palms soiled in no time.
Updated to mirror the most recent in Python programming paradigms and several other of the main the most important positive factors present in Python 3.0 (otherwise often called Python 3000), complex subject matters, equivalent to extending Python and packaging/distributing Python functions, also are lined.
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Advance sensible web of items prototypes and functions with Arduino and Python
About This Book
Transform your principles into real-world purposes utilizing Arduino and Python
Design and strengthen prototypes, interactive consumer interfaces, and cloud-connected purposes to your projects
Explore and extend examples to complement your attached device's purposes with this step by step guide
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Seasoned Python procedure management, moment variation explains and indicates easy methods to practice Python scripting in perform. it's going to help you method and get to the bottom of real-world matters that almost all approach directors will stumble upon of their careers. This publication has been up to date utilizing Python 2. 7 and Python three the place applicable.
You’ve discovered the fundamentals of Python, yet how do you're taking your talents to the following level? whether you recognize sufficient to be efficient, there are many gains which may take you to the following point in Python. seasoned Python, moment version explores ideas and contours ordinarily left to experimentation, permitting you to be much more effective and inventive.
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Extra resources for Beginning Python: From Novice to Professional (2nd Edition)
Keying on the ID Another thing that can be done for relatively safe places to store on the instance is to use the id() of the descriptor to generate a location on the instance, somehow. It may seem strange, but the id of the descriptor can be used as the key on the instance's location. It seems strange that a non-string can be used as the key in an instance dictionary, but it can. __dict__[id(desc)] and not via dot notation or get/set/hasattr(). This may actually seem like a plus, since it prevents unwanted access to the attribute, but it also messes up dir(instance), which raises an exception when it finds a non-string key.
Part 2 is filled to the brim with those. CHAPTER 6 Which Methods Are Needed? When designing a descriptor, it must be decided which methods will be included. It can sometimes help to decide right away if the descriptor should be a data or nondata descriptor, but sometimes it works better to first “discover” which kind of descriptor it is. The method __delete__() is rarely ever needed, even if it is a data descriptor. That doesn’t mean it shouldn’t ever be included, however. If the descriptor is going to be released into open domain, it wouldn’t hurt to add the __delete__() method simply for completeness for cases when a user decides to call del on it.
Jacob Zimmerman 2016 J. 1007/978-1-4842-2505-9_6 25 Chapter 6 ■ Which Methods Are Needed? When the descriptor is a class-level descriptor (usually nondata), implementing __get__() without using instance is trivial, since that’s the intended use. But when a descriptor is meant for instance-level use and the descriptor is not being called from an instance, it can be difficult to figure out what to do. Here, I present a few options. Raise Exception or Return self The first thing that may come to mind is to raise an exception, since class-level access is not intended, but this should be avoided.