![]() Justice_league_fav = Team ( ) print ( len (justice_league_fav ) ) # TypeError: object of type 'Team' has no len() If a type has the methods specified in the protocol, then it implements the protocol.įor instance, the len function requires a Sized type as its argument, which is every type that implements the _len_ function: class Team : def _init_ (self, members ) : While the concept is the same as Clojure, Python does not need explicit protocol declaration. Protocols in Python work a little bit differently. The rationale behind the Protocols is well explained in Simple made easy or in the documentation page Protocols In Python The original type is not even aware that a protocol implementation is being attached to it. This allows us to obtain what is called "polymorphism a la carte", where classes and inheritance are not involved/required. In this example, we have indeed implemented the same protocol on a type that has been precedently created ( Square) and then even implemented the protocol on the built-in String type. (area 1 ) (perimeter 10 ) ) ( def s ->Square 10 ) (area s ) 100.0 (area "hello world" ) 1 (area (Math/pow ( :l s ) 2 ) ) (perimeter ( * 4 ( :l s ) ) ) ) (extend-protocol Shape It is also possible to implement a protocol on a type that is already existing, even on types we do not own: (extend-protocol Shape Also, note that no class or inheritance is involved in this. We can see that the methods are called correctly in the first two instances, but it fails on the Square object because it does not implement the Shape Protocol. No implementation of method: :area of protocol: #'user/Shape found for class: user.Square Because of this, we can call any of the protocol methods on any of the type instance implementing it: ( def c ( ->Circle 10 ) ) (area c ) 314.1592653589793 ( def r ( ->Rectangle 10 12 ) ) (area r ) 120 ( def s ( ->Square 10 ) ) (area s ) Execution error (IllegalArgumentException) at user/eval147$fn$G (REPL:1). Successively, we create two new types - Circle and Rectangle where we implement the area and perimeter methods that are defined in the protocol. ![]() This code is basically creating a set of functions grouped in a Protocol called Shape every type that wants to adhere to such Protocol has to implement such methods. (area ( * w h ) ) (perimeter ( * 2 ( + w h ) ) ) ) (area ( * Math/PI (Math/pow r 2 ) ) ) (perimeter ( * r Math/PI ) ) ) ( defrecord Rectangle (area ) (perimeter ) ) ( defrecord Square ) ( defrecord Circle For instance, Clojure supports protocols explicitly. Protocols are indeed not a new idea and have been around for a long time. By removing some of the constraints of the previous definition, it is possible to reason about protocols in the context of a programming language. In fact, the nature of the protocol we're going to be talking about today. Let's notice the difference with the previous definition we found above: The accepted or established code of procedure or behavior in any group, organization, or situation. We can answer the question by taking a look at another more generic definition that is not coupled with computer science: After all, there is no communication involved in a program, so what is the meaning of it? On the other hand, it might be kind of weird for people to talk about protocols in a programming language. In the case of TCP, for instance, the protocol mandates the shape of the message, the possible operations, the error policies as well as the rules for possible retransmission of a message. All the examples listed above are communication protocols between two remote devices with a set of rules that are governing the transmission. Dictionaries have also dedicated definitions for it:Ī set of rules governing the exchange or the transmission of data between devices Most of us are probably familiar with it from hearing TCP Protocol, UDP Protocol or also HTTP Protocol. Protocol is a very generic word, both in regular language as well as in Computer Science. In this article, we're going to take a look at the new Protocol classes introduced in Python 3.8 and how it enables, even in typed contexts, structural typing, and other idiomatic patterns in Python. ![]() In the previous installment, we have seen how to type annotations enable gradual typing in Python and some of the common typing patterns that Python developers use when writing code.
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