A generator is similar to a function returning an array. A simple explanation of the usage of list comprehension and generator expressions in Python. The heapq module in Python 2.4 includes two new reduction functions: nlargest() and nsmallest(). Generator expressions are useful when using reduction functions such as sum(), min(), or max(), as they reduce the code to a single line. Writing code in comment? Once a generator expression has been consumed, it can’t be restarted or reused. What are Generator Expressions? Generators are written just like a normal function but we use yield() instead of return() for returning a result. The main feature of generator is evaluating the elements on demand. To create a generator, you define a function as you normally would but use the yield statement instead of return, indicating to the interpreter that this function should be treated as an iterator:The yield statement pauses the function and saves the local state so that it can be resumed right where it left off.What happens when you call this function?Calling the function does not execute it. It looks like List comprehension in syntax but (} are used instead of []. In the previous lesson, you covered how to use the map() function in Python in order to apply a function to all of the elements of an iterable and output an iterator of items that are the result of that function being called on the items in the first iterator.. In this tutorial you’ll learn how to use them from the ground up. Generator Expressions. In python, a generator expression is used to generate Generators. it can be used in a for loop. We know this because the string Starting did not print. When a normal function with a return statement is called, it terminates whenever it gets a return statement. Unlike regular functions which on encountering a return statement terminates entirely, generators use yield statement in which the state of the function is saved from the last call and can be picked up or resumed the next time we call a generator function. Instead of generating a list, in Python 3, you could splat the generator expression into a print statement. It is more powerful as a tool to implement iterators. You see, class-based iterators and generator functions are two expressions of the same underlying design pattern. An iterator can be seen as a pointer to a container, e.g. It is more powerful as a tool to implement iterators. Curated by yours truly. Once the function yields, the function is paused and the control is transferred to the caller. By Dan Bader — Get free updates of new posts here. It looks like List comprehension in syntax but (} are used instead of []. Generator expressions are similar to list comprehensions. Python generator gives an alternative and simple approach to return iterators. The utility of generator expressions is greatly enhanced when combined with reduction functions like sum(), min(), and max(). If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. It is easy and more convenient to implement because it offers the evaluation of elements on demand. Python provides tools that produce results only when needed: Generator functions They are coded as normal def but use yield to return results one at a time, suspending and resuming. Once a generator expression has been consumed, it can’t be restarted or reused. In the previous lesson, you covered how to use the map() function in Python in order to apply a function to all of the elements of an iterable and output an iterator of items that are the result of that function being called on the items in the first iterator.. Question or problem about Python programming: In Python, is there any difference between creating a generator object through a generator expression versus using the yield statement? The pattern you should begin to see looks like this: The above generator expression “template” corresponds to the following generator function: Just like with list comprehensions, this gives you a “cookie-cutter pattern” you can apply to many generator functions in order to transform them into concise generator expressions. Simplified Code. In Python, to create iterators, we can use both regular functions and generators. Unsubscribe any time. In this tutorial, we will discuss what are generators in Python and how can we create a generator. See this section of the official Python tutorial if you are interested in diving deeper into generators. The major difference between a list comprehension and a generator expression is that a list comprehension produces the entire list while the generator expression produces one item at a time. These expressions are designed for situations where the generator is used right away by an enclosing function. Python Generator Expressions. When the function terminates, StopIteration is raised automatically on further calls. As you can tell, generator expressions are somewhat similar to list comprehensions: Unlike list comprehensions, however, generator expressions don’t construct list objects. Generator Expressions are somewhat similar to list comprehensions, but the former doesn’t construct list object. But they return an object that produces results on demand instead of building a result list. If you’re on the fence, try out different implementations and then select the one that seems the most readable. Generator Expressions in Python. I am trying to replicate the following from PEP 530 generator expression: (i ** 2 async for i in agen()). When you call a normal function with a return statement the function is terminated whenever it encounters a return statement. We seem to get the same results from our one-line generator expression that we got from the bounded_repeater generator function. The filtering condition using the % (modulo) operator will reject any value not divisible by two: Let’s update our generator expression template. Generator Expression. brightness_4 dot net perls. The parentheses surrounding a generator expression can be dropped if the generator expression is used as the single argument to a function: This allows you to write concise and performant code. Instead, generator expressions generate values “just in time” like a class-based iterator or generator function would. How to Use Python’s Print() Without Adding an Extra New Line, Function and Method Overloading in Python, 10 Reasons To Learn Python Programming In 2018, Basic Object-Oriented Programming (OOP) Concepts in Python, Functional Programming Primitives in Python, Interfacing Python and C: The CFFI Module, Write More Pythonic Code by Applying the Things You Already Know, A Python Riddle: The Craziest Dict Expression in the West. Strengthen your foundations with the Python Programming Foundation Course and learn the basics. Generator expressions are a helpful and Pythonic tool in your toolbox, but that doesn’t mean they should be used for every single problem you’re facing. 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However, the former uses the round parentheses instead of square brackets. Let’s take a closer look at the syntactic structure of this simple generator expression. Generators a… A generator has parameter, which we can called and it generates a sequence of numbers. Through nested for-loops and chained filtering clauses, they can cover a wider range of use cases: The above pattern translates to the following generator function logic: And this is where I’d like to place a big caveat: Please don’t write deeply nested generator expressions like that. See your article appearing on the GeeksforGeeks main page and help other Geeks. No spam ever. In Python 2.4 and earlier, generators only produced output. Let’s get the sum of numbers divisible by 3 & 5 in range 1 to 1000 using Generator Expression. Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above. The iterator is an abstraction, which enables the programmer to accessall the elements of a container (a set, a list and so on) without any deeper knowledge of the datastructure of this container object.In some object oriented programming languages, like Perl, Java and Python, iterators are implicitly available and can be used in foreach loops, corresponding to for loops in Python. In a function with a yield … One can define a generator similar to the way one can define a function (which we will encounter soon). Try writing one or test the example. However, they don’t construct list objects. Tagged with python, listcomp, genexpr, listcomprehension. Like list comprehensions, generator expressions allow for more complexity than what we’ve covered so far. Those elements too can be transformed. Link to this regex. What are the Generators? So in some cases there is an advantage to using generator functions or class-based iterators. Syntactic sugar at its best: Because generator expressions are, well…expressions, you can use them in-line with other statements. Attention geek! As more developers use a design pattern in their programs, there’s a growing incentive for the language creators to provide abstractions and implementation shortcuts for it. 相信大家都用过list expression, 比如生成一列数的平方: Take a look at your generator expression separately: (itm for itm in lst if itm['a']==5) This will collect all items in the list where itm['a'] == 5. Structure of a Generator Expression A generator expression (or list/set comprehension) is a little like a for loop that has been flipped around. Specify the yield keyword and a generator expression. That’s how programming languages evolve over time—and as developers, we reap the benefits. close, link This procedure is similar to a lambda function creating an anonymous function. Python Generator Expressions. Let’s take a list for this. In addition to that, two more functions _next_() and _iter_() make the generator function more compact and reliable. For beginners, learning when to use list comprehensions and generator expressions is an excellent concept to grasp early on in your career. Just like a list comprehension, we can use expressions to create python generators shorthand. Generators are reusable—they make code simpler. We will also discuss how it is different from iterators and normal function. Python provides a sleek syntax for defining a simple generator in a single line of code; this expression is known as a generator comprehension. The following syntax is extremely useful and will appear very frequently in Python code: July 20, 2020 August 14, 2020; Today we’ll be talking about generator expressions. For complex iterators, it’s better to write a generator function or a class-based iterator. When you call next() on it, you tell Python to generate the first item from that generator expression. For this reason, a generator expression … Example : edit Generator functions give you a shortcut for supporting the iterator protocol in your own code, and they avoid much of the verbosity of class-based iterators. Generator expression allows creating a generator without a yield keyword. By using our site, you Generator expressions These are similar to the list comprehensions. If you need to use nested generators and complex filtering conditions, it’s usually better to factor out sub-generators (so you can name them) and then to chain them together again at the top level. In this Python 3 Tutorial, we take a look at generator expressions. code, Difference between Generator function and Normal function –. With a generator, we specify what elements are looped over. Generator functions allow you to declare a function that behaves like an iterator, i.e. To illustrate this, we will compare different implementations that implement a function, \"firstn\", that represents the first n non-negative integers, where n is a really big number, and assume (for the sake of the examples in this section) that each integer takes up a lot of space, say 10 megabytes each. Tip: There are two ways to specify a generator. As I learned more about Python’s iterator protocol and the different ways to implement it in my own code, I realized that “syntactic sugar” was a recurring theme. The syntax of Generator Expression is similar to List Comprehension except it uses parentheses ( ) instead of square brackets [ ]. Summary: in this tutorial, you’ll learn about the Python generator expression to create a generator object.. Introduction to generator expressions. Generator expressions are a high-performance, memory–efficient generalization of list comprehensions and generators. Generator expressions aren’t complicated at all, and they make python written code efficient and scalable. Just like a list comprehension, we can use expressions to create python generators shorthand. with the following code: import asyncio async def agen(): for x in range(5): yield x async def main(): x = tuple(i ** 2 async for i in agen()) print(x) asyncio.run(main()) but I get TypeError: 'async_generator' object is not iterable. We get to work with more and more powerful building blocks, which reduces busywork and lets us achieve more in less time. Generator expressions¶ A generator expression is a compact generator notation in parentheses: generator_expression::= "(" expression comp_for ")" A generator expression yields a new generator object. In Python, generators provide a convenient way to implement the iterator protocol. Lambda Functions in Python: What Are They Good For? However, they don’t construct list objects. pythex / Your regular expression: IGNORECASE MULTILINE DOTALL VERBOSE. ... generator expression. Instead of creating a list and keeping the whole sequence in the memory, the generator generates the next element in demand. Python if/else list comprehension (generator expression) - Python if else list comprehension (generator expression).py But I’m getting ahead of myself. In this lesson, you’ll see how the map() function relates to list comprehensions and generator expressions. Generator comprehensions are not the only method for defining generators in Python. Just like with list comprehensions, I personally try to stay away from any generator expression that includes more than two levels of nesting. Dadurch muss nicht die gesamte Liste im Speicher gehalten werden, sondern immer nur das aktuelle Objekt. Local variables and their states are remembered between successive calls. Match result: Match captures: Regular expression cheatsheet Special characters \ escape special characters. Once a generator’s code was invoked to create an iterator, there was no way to pass any new information into the function when its execution is resumed. Your test string: pythex is a quick way to test your Python regular expressions. But a … There are various other expressions that can be simply coded similar to list comprehensions but instead of brackets we use parenthesis. >>> mylist=[1,3,6,10] >>> (x**2 for x in mylist) at 0x003CC330> As is visible, this gave us a Python generator object. Python Regular Expression's Cheat Sheet (borrowed from pythex) Special Characters \ escape special characters. The point of using it, is to generate a sequence of items without having to store them in memory and this is why you can use Generator only once. >>> mylist=[1,3,6,10] >>> (x**2 for x in mylist) at 0x003CC330> As is visible, this gave us a Python generator object. In one of my previous tutorials you saw how Python’s generator functions and the yield keyword provide syntactic sugar for writing class-based iterators more easily. Generator Expressions are somewhat similar to list comprehensions, but the former doesn’t construct list object. Though we can make our own Iterators using a class, __iter__() and __next__() methods, but this could be tedious and complex. pythex is a quick way to test your Python regular expressions. All you get by assigning a generator expression to a variable is an iterable “generator object”: To access the values produced by the generator expression, you need to call next() on it, just like you would with any other iterator: Alternatively, you can also call the list() function on a generator expression to construct a list object holding all generated values: Of course, this was just a toy example to show how you can “convert” a generator expression (or any other iterator for that matter) into a list. Ie) print(*(generator-expression)). Its syntax is the same as for comprehensions, except that it is enclosed in parentheses instead of brackets or curly braces. The generator expressions we’ll cover in this tutorial add another layer of syntactic sugar on top—they give you an even more effective shortcut for writing iterators: With a simple and concise syntax that looks like a list comprehension, you’ll be able to define iterators in a single line of code. Experience. Python Generator Examples: Yield, Expressions Use generators. Because generator expressions generate values “just in time” like a class-based iterator or a generator function would, they are very memory efficient. Instead of creating a list and keeping the whole sequence in the memory, the generator generates the next element in demand. Python provides ways to make looping easier. a list structure that can iterate over all the elements of this container. If you need a list object right away, you’d normally just write a list comprehension from the get-go. A Generator Expression is doing basically the same thing as a List Comprehension does, but the GE does it lazily. They can be very difficult to maintain in the long run. However, it doesn’t share the whole power of generator created with a yield function. Generator is an iterable created using a function with a yield statement. Pythex is a real-time regular expression editor for Python, a quick way to test your regular expressions. Generators are written just like a normal function but we use yield () instead of return () for returning a result. Generator expressions are best for implementing simple “ad hoc” iterators. The simplification of code is a result of generator function and generator expression support provided by Python. generator expression - An expression that returns an iterator. When iterated over, the above generator expression yields the same sequence of values as the bounded_repeater generator function we implemented in my generators tutorial. Please write to us at contribute@geeksforgeeks.org to report any issue with the above content. Python | Generator Expressions. Schon seit Python 2.3 bzw. In Python, to create iterators, we can use both regular functions and generators. Funktionen wie filter(), map() und zip() geben seit Python 3 keine Liste, sondern einen Iterator zurück. Once a generator expression has been consumed, it can’t be restarted or reused. The difference is quite similar to the difference between range and xrange.. A List Comprehension, just like the plain range function, executes immediately and returns a list.. A Generator Expression, just like xrange returns and object that can be iterated over. This is one of those “the dose makes the poison” situations where a beautiful and simple tool can be overused to create hard to read and difficult to debug programs. There’s one more useful addition we can make to this template, and that’s element filtering with conditions. Let’s make sure our iterator defined with a generator expression actually works as expected: That looks pretty good to me! Generators. Generators are special iterators in Python which returns the generator object. © 2012–2018 Dan Bader ⋅ Newsletter ⋅ Twitter ⋅ YouTube ⋅ FacebookPython Training ⋅ Privacy Policy ⋅ About❤️ Happy Pythoning! Python allows writing generator expressions to create anonymous generator functions. … In this lesson, you’ll see how the map() function relates to list comprehensions and generator expressions. Instead, they generate values “just in time” like a class-based iterator or generator function would. generator expression; 接下来, 我们分别来看看这些概念: {list, set, tuple, dict} comprehension and container. Instead, generator expressions generate values “just in time” like a class-based iterator or generator function would. Another great advantage of the generator over a list is that it takes much less memory. They're also much shorter to type than a full Python generator function. Here it is again to refresh your memory: Isn’t it amazing how a single-line generator expression now does a job that previously required a four-line generator function or a much longer class-based iterator? Example : We can also generate a list using generator expressions : This article is contributed by Chinmoy Lenka. Here’s an example: This generator yields the square numbers of all even integers from zero to nine. Try writing one or test the example. Improve Your Python with a fresh  Python Trick  every couple of days. generator expression是Python的另一种generator. After adding element filtering via if-conditions, the template now looks like this: And once again, this pattern corresponds to a relatively straightforward, but longer, generator function. They have lazy execution ( producing items only when asked for ). The simplification of code is a result of generator function and generator expression support provided by Python. Generator expressions aren’t complicated at all, and they make python written code efficient and scalable. Generator function contains one or more yield statement instead of return statement. But unlike functions, which return a whole array, a generator yields one value at a time which requires less memory. Dies ist wesentlich effizienter und eine gute Vorlage für das Design von eigenem Code. Create a Generator expression that returns a Generator object i.e. Both work well with generator expressions and keep no more than n items in memory at one time. Generator in python are special routine that can be used to control the iteration behaviour of a loop. In python, a generator expression is used to generate Generators. We use cookies to ensure you have the best browsing experience on our website. But only the first. The syntax of a generator expression is the same as of list comprehension in Python. Trust me, it’ll save you time in the long run. Generator Expressions in Python – Summary. To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. A generator expression is an expression that returns a generator object.. Basically, a generator function is a function that contains a yield statement and returns a generator object.. For example, the following defines a generator function: For complex iterators, it’s often better to write a generator function or even a class-based iterator. list( generator-expression ) isn't printing the generator expression; it is generating a list (and then printing it in an interactive shell). For beginners, learning when to use list comprehensions and generator expressions is an excellent concept to grasp early on in your career. Let’s get the sum of numbers divisible by 3 & 5 in range 1 to 1000 using Generator Expression. Using yield: def Generator(x, y): for i in xrange(x): for j in xrange(y): yield(i, j) Using generator expression: def Generator(x, y): return ((i, j) for i in xrange(x) for […] So far so good. But the square brackets are replaced with round parentheses. Get a short & sweet Python Trick delivered to your inbox every couple of days. The procedure to create the generator is as simple as writing a regular function.There are two straightforward ways to create generators in Python. With a little bit of specialized syntax, or syntactic sugar, they save you time and make your life as a developer easier: This is a recurring theme in Python and in other programming languages. The syntax for generator expression is similar to that of a list comprehension in Python. Generator Expression. For example, you can define an iterator and consume it right away with a for-loop: There’s another syntactic trick you can use to make your generator expressions more beautiful. Let’s take a list for this. Generator expressions are similar to list comprehensions. Difficult to maintain in the memory, the former uses the round parentheses a., we will encounter soon ) more convenient to implement iterators function and generator is! Excellent concept to grasp early on in your career but ( } are used instead of return )! Use ide.geeksforgeeks.org, generate link and share the link here the former doesn t! Our website, try out different implementations and then select the one that seems most. The square brackets are replaced with round parentheses use both regular functions and generators at generator expressions are similar... See how the map ( ) and _iter_ ( ) for returning a.!, sondern immer nur das aktuelle Objekt memory at one time simply coded to... It encounters a return statement is called, it terminates whenever it encounters a return statement function. Tutorial you ’ ll see how the map ( ) for returning a.... The fence, try out different implementations and then select the one that seems the most readable write if. & 5 in range 1 to 1000 using generator expression this template, that. One or more yield statement or a class-based iterator or generator function more compact reliable! And generators anything incorrect, or you want to share more information about the topic above. Die gesamte Liste im Speicher gehalten werden, sondern immer nur das aktuelle Objekt create the generator is as as... More functions _next_ ( ) for returning a result list a python generator expression Python Trick every couple days! Often better to write a generator expression and lets us achieve more in less time implement iterators, and make! Iterator can be very difficult to maintain in the long run fresh Python Trick every couple of days to iterators... Topic discussed above procedure to create generators in Python, generators provide a convenient way to test your regular.... To your inbox every couple of days terminated whenever it encounters a return statement building,... Are designed for situations where the generator over a list and keeping the sequence. Allow for more complexity than what we ’ ll see how the map ( instead... Can ’ t construct list objects & sweet Python Trick every couple of days we... 1000 using generator functions allow you to declare a function that behaves like an iterator Python tutorial python generator expression you interested! An array allow for more complexity than what we ’ ve covered so far Twitter ⋅ YouTube FacebookPython! _Next_ ( ) make the generator expression … Python generator gives an alternative simple! Python, generators only produced output we will discuss what are generators in.! Building blocks, which return a whole array, a quick way to test your Python with a statement. Generator-Expression ) ) away, you ’ re on the GeeksforGeeks main page and help other Geeks an function..., class-based iterators issue with the above content you to declare a function returning an array Difference generator! Dotall VERBOSE but ( } are used instead of square brackets [ ] generator... The usage of list comprehensions, but the former doesn ’ t construct list object right,! Variables and their states are remembered between successive calls only method for defining generators in Python 2.4 includes two reduction. Difficult to maintain in the memory, the function is terminated whenever gets... To the caller very difficult to maintain in the long run generators only produced output they for! A result of generator expression - an expression that returns an iterator,.! Inbox every couple of days statement is called, it can ’ t construct list object explanation the! Training ⋅ Privacy Policy ⋅ About❤️ Happy Pythoning it can ’ t construct list.... Function relates to list comprehension in syntax but ( } are used instead of return statement is,... Python tutorial if you need a list comprehension in syntax but ( } are used instead brackets... Expression actually works as expected: that looks pretty good to me the iterator protocol there. Yields one value at a time which requires less memory learning when to use list comprehensions generator... Of numbers divisible by 3 & 5 in range 1 to 1000 using generator expressions are somewhat similar list... Used right away, you ’ ll learn how to use them in-line with other.. Designed for situations where the generator function regular expression cheatsheet special characters \ escape characters. To that, two more functions _next_ ( ) instead of square brackets are with. Create the generator generates the next element in demand the former uses the round parentheses of. Your foundations with the Python DS Course square brackets same results from our one-line generator expression support provided by.!, we take a closer look at the syntactic structure of this simple generator expression when asked for.. Of nesting structure of this simple generator expression allows creating a generator I personally try to stay from... You are interested in diving deeper into generators: pythex is a result generator. ; Today we ’ ve covered so far generators only produced output how to use list comprehensions instead. Pythex / your regular expression cheatsheet special characters \ escape special characters \ escape special characters \ special! About❤️ Happy Pythoning a list comprehension in syntax but ( } are used instead of [ ] discuss how is... Expression 's Cheat Sheet ( borrowed from pythex ) special characters \ escape special characters \ special... Usage of list comprehensions support provided by Python ) instead of square brackets are replaced with round parentheses of! Allows writing generator expressions these are similar to list comprehensions and generator expression that returns iterator. Are similar to list comprehensions and generator expressions aren ’ t construct list objects powerful building blocks, reduces! ( generator-expression ) ) create a generator expression has been consumed, it ’. Great advantage of the generator over a list object © 2012–2018 Dan Bader get. Function returning an array fresh Python Trick delivered to your inbox every couple of days lesson... Eigenem code for this reason, a generator, we take a look at generator expressions are for... Written just like a normal function but we use yield ( ) function relates to list and... Seems the most readable will also discuss how it is different from iterators and normal function © 2012–2018 Dan —!, but the former doesn ’ t share the link here different from iterators and normal.! Twitter ⋅ YouTube ⋅ FacebookPython Training ⋅ Privacy Policy ⋅ About❤️ Happy Pythoning the same results from our generator... Encounters a return statement designed for situations where the generator function or a class-based iterator or function... In parentheses instead of [ ] july 20, 2020 August 14, 2020 August 14 2020. Expressions of the same as for comprehensions, generator expressions to create Python generators.! A fresh Python Trick every couple of days { list, in Python, a quick way to test Python! Functions allow you to declare a function ( which we will encounter soon ) this because string. Automatically on further calls can called and it generates a sequence of numbers the evaluation of elements demand... About❤️ Happy Pythoning d normally just write a list comprehension from the get-go pretty to! It is enclosed in parentheses instead of creating a list and keeping the whole sequence in the memory the... Your inbox every couple of days excellent concept to grasp early on in your career an! Ll see how the map ( ) instead of square brackets [.... Bounded_Repeater generator function and normal function with a return statement the function terminates, is... Design von eigenem code call a normal function but we use parenthesis produces... ⋅ YouTube ⋅ FacebookPython Training ⋅ Privacy Policy ⋅ About❤️ Happy Pythoning you want to python generator expression more information the... Expression actually works as expected: that looks pretty good to me and... When the function is paused and the control is transferred to the way one define. Talking about generator expressions in Python and how can we create a similar... Less time creating a list comprehension in Python, to create iterators, we take a closer look generator! Expressions allow for more complexity than what we ’ ll save you in. A fresh Python Trick every couple of days 1 to 1000 using generator is. But unlike functions, which return a whole array, a generator expression that returns a generator, interview... Make to this template, and that ’ s how Programming languages over... Write to us at contribute @ geeksforgeeks.org to report any issue with the Python DS Course allow you declare..., 2020 August 14, 2020 August 14, 2020 August 14, 2020 August 14, 2020 August,!, I personally try to stay away from any generator expression support provided by Python simple of! Fence, try out different implementations and then select the one that seems the most readable official..., I personally try to stay away from any generator expression into a print statement Python Programming Foundation Course learn! Generator similar to list comprehensions and generator expression has been consumed, it can ’ t complicated at,. Both work well with generator expressions: this article is contributed by Chinmoy Lenka that produces results on.. Simple generator expression is similar to a python generator expression, e.g by Dan —... Brackets [ ] make to this template, and they make Python written efficient! A lambda function creating an anonymous function return iterators of nesting Speicher gehalten werden, sondern nur. Code is a result of generator expression former uses the round parentheses provided by Python write a generator.... Regular functions and generators the first item from that generator expression allows creating a list and keeping whole... Time in the memory, the generator generates the next element in demand by an function!
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