The source code of the talk is under talk/src. Clean-Code-in-Python-Second-Edition/service.py at main - GitHub Another piece of good advice derived from this example is as followsdon't do more than one thing in a method. We have seen the main features of Python with respect to its peculiar syntax. Clean Code in Python - Second Edition: Develop maintainable and The previous function should be more maintainable than our first example, but still requires two statements. Adhering to a coding style guide on your project, Comprehensions and assignment expressions, Properties, attributes, and different types of methods for objects, Creating classes with a more compact syntax, A brief introduction to asynchronous code, Compact function signatures that take too many arguments, Final remarks on good practices for software design, Example of maintainability perils for not following the OCP, Refactoring the events system for extensibility, Using mypy to detect incorrect method signatures, Detecting incompatible signatures with pylint, Effective decorators avoiding common mistakes, Preserving data about the original wrapped object, Incorrect handling of side effects in a decorator, Creating decorators that will always work, Getting More Out of Our Objects with Descriptors, Exploring each method of the descriptor protocol, A first attempt without using descriptors, Different forms of implementing descriptors, Object-oriented design of the descriptors, Generators, Iterators, and Asynchronous Programming, throw(ex_type[, ex_value[, ex_traceback]]), Delegating into smaller coroutines the 'yield from' syntax, A note about other forms of automated testing, Unit testing and agile software development, Frameworks and libraries for unit testing, Production code isn't the only one that evolves, A brief introduction to test-driven development, The influence of patterns over the design, Monolithic applications and microservices, Other considerations when managing dependencies, Enhance your coding skills using the new features introduced in Python 3.9, Implement the refactoring techniques and SOLID principles in Python, Apply microservices to your legacy systems by implementing practical techniques, Set up a productive development environment by leveraging automatic tools, Leverage the magic methods in Python to write better code, abstracting complexity away and encapsulating details, Create advanced object-oriented designs using unique features of Python, such as descriptors, Eliminate duplicated code by creating powerful abstractions using software engineering principles of object-oriented design, Create Python-specific solutions using decorators and descriptors, Refactor code effectively with the help of unit tests, Build the foundations for solid architecture with a clean code base as its cornerstone. Before finishing the chapter, I wanted to give a quick introduction to asynchronous programming, because while it is not strictly related to clean code per se, asynchronous code has become more and more popular, following up with the idea that, in order to work effectively with code, we must be able to read it and understand it, because being able to read asynchronous code is important. Terms of service Privacy policy Editorial independence. If you do, make sure that this is exactly what you want, and that there is a good reason for it. For example, if you're creating a wrapper object on top of another one by means of composition, and you want to delegate most of the methods to the wrapped object, instead of copying and defining all of those methods, you canimplement __getattr__ that will internally call the same method on the wrappedobject. As long as the library you choose complies with that API, you should be ableto use it, without having to change how your coroutines were declared. If you call range with an interval, itwill construct an iterable object that knows how to produce the values in the selected range. His speakerdeck username is rmariano. This is why we create validation methods, typically to be used in the setter operations. In general, the iteration is preferable (and generators even more), but keep in mind the requirements of every case. It will appeal to team leads, software architects and senior software engineers who would like to write Pythonic code to save on costs and improve efficiency. This is optionalwe don't really need to return anything specific on the __enter__ method, and even if we do, there is still no strict reason to assign it to a variable if it is not required. What it does is create the attribute with the following name instead: "___". If you need to define attributes as private, use a single underscore, and respect the Pythonic convention that it is a private attribute. The magic method __call__ will be called when we try to execute our object as if it were a regular function. Give it enough time, and the reverse effect will take place: Python will start programming you. To calculate the overall star rating and percentage breakdown by star, we dont use a simple average. When the Python interpreter parses the file, it'll read the function, and find a statement in the signature that creates the dictionary and assigns it to the parameter. In addition to getting just one element, we can obtain many by using slice, as shown in the following commands: In this case, the syntax on the square brackets means that we get all of the elements on the tuple, starting from the index of the first number (inclusive), up to the index on the second one (not including it). This changes the programming model. The source code of the talk is under talk/src. What do you get with eBook + Subscription? Most of the points discussed in this section are things to avoid entirely, and I will dare to say that there is almost no possible scenario that justifies the presence of the anti-pattern (or idiom, in this case). However, in Python, sometimes we can encapsulate these setter and getter methods more compactly by using properties. Again, details on generators are not relevant in this case. Despite the fact that context managers are very often found when dealing with resources (like the example we mentioned with files, connections, and so on), this is not the sole application they have. You should always prefer to use this built-in syntax for slices, as opposed to manually trying to iterate the tuple, string, or list inside a for loop, excluding the elements by hand. Attain a deep understanding of building, maintaining, packaging, and shipping robust Python applications, Discover how to describe your data in detail, identify data issues, and find out how to solve them using commonly used techniques and tips and tricks, Build, monitor, and manage real-time data pipelines to create data engineering infrastructure efficiently using open-source Apache projects, Tackle security and networking issues using Python libraries such as Nmap, requests, asyncio, and scapy. When we pass a value to it, this will take the place of the default argument we just created. To know more about him, you can refer to his GitHub account with the username rmariano. Experienced professionals in every field face several instances of disorganization, poor readability, and testability due to unstructured code. In the previous example, if we decided that we wanted to return the coordinates with a precision of up to four decimal places (regardless of how many decimal places the original number was provided with), we can make the computation for rounding this in the @property method that reads the value. The idea behind asynchronous programming is to have parts in our code that are able to suspend so that other parts of our code can run. Clean Code in Python, 2nd Edition - Section 1 | SitePoint Premium Introduction, Code Formatting, and Tools In this chapter, we will explore the first concepts related to clean code,. Read instantly on your browser with Kindle for Web. You can imagine how much more readable (and Pythonic!) The former is public and the latter private. A key takeaway of the topics of this book is that clean code goes beyond following the formatting rules (which, of course, are essential to a good code base). All programming languages have their caveats, and Python is no exception, so in order to have a more complete understanding of Python, we'll review some of them in the next section. https://packt.link/free-ebook/9781800560215. This issue is actually an implementation detail of CPython, while in other platforms such as PyPy this doesn't happen (see the differences between PyPy and CPython inthe references at the end of this chapter). Even thatis a too far-fetched use case as to justify the use of this mechanism. It is a must buy for python developers. The following listing uses this method to construct an object that, when called with a parameter, returns the number of times it has been called with the very same value: Some examples of this class in action are as follows: Later in this book, we will find out that this method comes in handy when creating decorators. To see our price, add these items to your cart. Examples of this can be functions we would like to implement with memoization, or internal caches. Overall, you could find better information on YouTube or Stack Overflow for free. Moreover, we'll discuss the different ways of exposing or hiding data in Python objects. EuroPython 2016 Talk Sources of the talk, as presented at EuroPython 2016. However, unlike those languages, when we want to access the elements in a different order than usual, Python provides extra features. At this point, Python will call the iter() function on it, which, in turn, will call the __iter__ magic method. Let's now explore the opposite case, that is, when we do want to access some attributes of an object that are intended to be public. It is the way things should be written when we want to perform a particular task. 9781800560215 Download code from GitHub Pythonic Code In this chapter, we will explore the way ideas are expressed in Python, with its own peculiarities. Maybe our object does not define the __iter__() method, but we still want to be able to iterate over it. Learning to work with coroutines will prepare readers for new programming models that are more frequent in modern cloud architectures.
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