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https://docs.python.org/3/tutorial/datastructures.html#tut-structures | 5. Data Structures — Python 3.14.2 documentation Theme Auto Light Dark Table of Contents 5. Data Structures 5.1. More on Lists 5.1.1. Using Lists as Stacks 5.1.2. Using Lists as Queues 5.1.3. List Comprehensions 5.1.4. Nested List Comprehensions 5.2. The del statement 5.3. Tuples and Sequences 5.4. Sets 5.5. Dictionaries 5.6. Looping Techniques 5.7. More on Conditions 5.8. Comparing Sequences and Other Types Previous topic 4. More Control Flow Tools Next topic 6. Modules This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Tutorial » 5. Data Structures | Theme Auto Light Dark | 5. Data Structures ¶ This chapter describes some things you’ve learned about already in more detail, and adds some new things as well. 5.1. More on Lists ¶ The list data type has some more methods. Here are all of the methods of list objects: list. append ( x ) Add an item to the end of the list. Similar to a[len(a):] = [x] . list. extend ( iterable ) Extend the list by appending all the items from the iterable. Similar to a[len(a):] = iterable . list. insert ( i , x ) Insert an item at a given position. The first argument is the index of the element before which to insert, so a.insert(0, x) inserts at the front of the list, and a.insert(len(a), x) is equivalent to a.append(x) . list. remove ( x ) Remove the first item from the list whose value is equal to x . It raises a ValueError if there is no such item. list. pop ( [ i ] ) Remove the item at the given position in the list, and return it. If no index is specified, a.pop() removes and returns the last item in the list. It raises an IndexError if the list is empty or the index is outside the list range. list. clear ( ) Remove all items from the list. Similar to del a[:] . list. index ( x [ , start [ , end ] ] ) Return zero-based index of the first occurrence of x in the list. Raises a ValueError if there is no such item. The optional arguments start and end are interpreted as in the slice notation and are used to limit the search to a particular subsequence of the list. The returned index is computed relative to the beginning of the full sequence rather than the start argument. list. count ( x ) Return the number of times x appears in the list. list. sort ( * , key = None , reverse = False ) Sort the items of the list in place (the arguments can be used for sort customization, see sorted() for their explanation). list. reverse ( ) Reverse the elements of the list in place. list. copy ( ) Return a shallow copy of the list. Similar to a[:] . An example that uses most of the list methods: >>> fruits = [ 'orange' , 'apple' , 'pear' , 'banana' , 'kiwi' , 'apple' , 'banana' ] >>> fruits . count ( 'apple' ) 2 >>> fruits . count ( 'tangerine' ) 0 >>> fruits . index ( 'banana' ) 3 >>> fruits . index ( 'banana' , 4 ) # Find next banana starting at position 4 6 >>> fruits . reverse () >>> fruits ['banana', 'apple', 'kiwi', 'banana', 'pear', 'apple', 'orange'] >>> fruits . append ( 'grape' ) >>> fruits ['banana', 'apple', 'kiwi', 'banana', 'pear', 'apple', 'orange', 'grape'] >>> fruits . sort () >>> fruits ['apple', 'apple', 'banana', 'banana', 'grape', 'kiwi', 'orange', 'pear'] >>> fruits . pop () 'pear' You might have noticed that methods like insert , remove or sort that only modify the list have no return value printed – they return the default None . [ 1 ] This is a design principle for all mutable data structures in Python. Another thing you might notice is that not all data can be sorted or compared. For instance, [None, 'hello', 10] doesn’t sort because integers can’t be compared to strings and None can’t be compared to other types. Also, there are some types that don’t have a defined ordering relation. For example, 3+4j < 5+7j isn’t a valid comparison. 5.1.1. Using Lists as Stacks ¶ The list methods make it very easy to use a list as a stack, where the last element added is the first element retrieved (“last-in, first-out”). To add an item to the top of the stack, use append() . To retrieve an item from the top of the stack, use pop() without an explicit index. For example: >>> stack = [ 3 , 4 , 5 ] >>> stack . append ( 6 ) >>> stack . append ( 7 ) >>> stack [3, 4, 5, 6, 7] >>> stack . pop () 7 >>> stack [3, 4, 5, 6] >>> stack . pop () 6 >>> stack . pop () 5 >>> stack [3, 4] 5.1.2. Using Lists as Queues ¶ It is also possible to use a list as a queue, where the first element added is the first element retrieved (“first-in, first-out”); however, lists are not efficient for this purpose. While appends and pops from the end of list are fast, doing inserts or pops from the beginning of a list is slow (because all of the other elements have to be shifted by one). To implement a queue, use collections.deque which was designed to have fast appends and pops from both ends. For example: >>> from collections import deque >>> queue = deque ([ "Eric" , "John" , "Michael" ]) >>> queue . append ( "Terry" ) # Terry arrives >>> queue . append ( "Graham" ) # Graham arrives >>> queue . popleft () # The first to arrive now leaves 'Eric' >>> queue . popleft () # The second to arrive now leaves 'John' >>> queue # Remaining queue in order of arrival deque(['Michael', 'Terry', 'Graham']) 5.1.3. List Comprehensions ¶ List comprehensions provide a concise way to create lists. Common applications are to make new lists where each element is the result of some operations applied to each member of another sequence or iterable, or to create a subsequence of those elements that satisfy a certain condition. For example, assume we want to create a list of squares, like: >>> squares = [] >>> for x in range ( 10 ): ... squares . append ( x ** 2 ) ... >>> squares [0, 1, 4, 9, 16, 25, 36, 49, 64, 81] Note that this creates (or overwrites) a variable named x that still exists after the loop completes. We can calculate the list of squares without any side effects using: squares = list ( map ( lambda x : x ** 2 , range ( 10 ))) or, equivalently: squares = [ x ** 2 for x in range ( 10 )] which is more concise and readable. A list comprehension consists of brackets containing an expression followed by a for clause, then zero or more for or if clauses. The result will be a new list resulting from evaluating the expression in the context of the for and if clauses which follow it. For example, this listcomp combines the elements of two lists if they are not equal: >>> [( x , y ) for x in [ 1 , 2 , 3 ] for y in [ 3 , 1 , 4 ] if x != y ] [(1, 3), (1, 4), (2, 3), (2, 1), (2, 4), (3, 1), (3, 4)] and it’s equivalent to: >>> combs = [] >>> for x in [ 1 , 2 , 3 ]: ... for y in [ 3 , 1 , 4 ]: ... if x != y : ... combs . append (( x , y )) ... >>> combs [(1, 3), (1, 4), (2, 3), (2, 1), (2, 4), (3, 1), (3, 4)] Note how the order of the for and if statements is the same in both these snippets. If the expression is a tuple (e.g. the (x, y) in the previous example), it must be parenthesized. >>> vec = [ - 4 , - 2 , 0 , 2 , 4 ] >>> # create a new list with the values doubled >>> [ x * 2 for x in vec ] [-8, -4, 0, 4, 8] >>> # filter the list to exclude negative numbers >>> [ x for x in vec if x >= 0 ] [0, 2, 4] >>> # apply a function to all the elements >>> [ abs ( x ) for x in vec ] [4, 2, 0, 2, 4] >>> # call a method on each element >>> freshfruit = [ ' banana' , ' loganberry ' , 'passion fruit ' ] >>> [ weapon . strip () for weapon in freshfruit ] ['banana', 'loganberry', 'passion fruit'] >>> # create a list of 2-tuples like (number, square) >>> [( x , x ** 2 ) for x in range ( 6 )] [(0, 0), (1, 1), (2, 4), (3, 9), (4, 16), (5, 25)] >>> # the tuple must be parenthesized, otherwise an error is raised >>> [ x , x ** 2 for x in range ( 6 )] File "<stdin>" , line 1 [ x , x ** 2 for x in range ( 6 )] ^^^^^^^ SyntaxError : did you forget parentheses around the comprehension target? >>> # flatten a list using a listcomp with two 'for' >>> vec = [[ 1 , 2 , 3 ], [ 4 , 5 , 6 ], [ 7 , 8 , 9 ]] >>> [ num for elem in vec for num in elem ] [1, 2, 3, 4, 5, 6, 7, 8, 9] List comprehensions can contain complex expressions and nested functions: >>> from math import pi >>> [ str ( round ( pi , i )) for i in range ( 1 , 6 )] ['3.1', '3.14', '3.142', '3.1416', '3.14159'] 5.1.4. Nested List Comprehensions ¶ The initial expression in a list comprehension can be any arbitrary expression, including another list comprehension. Consider the following example of a 3x4 matrix implemented as a list of 3 lists of length 4: >>> matrix = [ ... [ 1 , 2 , 3 , 4 ], ... [ 5 , 6 , 7 , 8 ], ... [ 9 , 10 , 11 , 12 ], ... ] The following list comprehension will transpose rows and columns: >>> [[ row [ i ] for row in matrix ] for i in range ( 4 )] [[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]] As we saw in the previous section, the inner list comprehension is evaluated in the context of the for that follows it, so this example is equivalent to: >>> transposed = [] >>> for i in range ( 4 ): ... transposed . append ([ row [ i ] for row in matrix ]) ... >>> transposed [[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]] which, in turn, is the same as: >>> transposed = [] >>> for i in range ( 4 ): ... # the following 3 lines implement the nested listcomp ... transposed_row = [] ... for row in matrix : ... transposed_row . append ( row [ i ]) ... transposed . append ( transposed_row ) ... >>> transposed [[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]] In the real world, you should prefer built-in functions to complex flow statements. The zip() function would do a great job for this use case: >>> list ( zip ( * matrix )) [(1, 5, 9), (2, 6, 10), (3, 7, 11), (4, 8, 12)] See Unpacking Argument Lists for details on the asterisk in this line. 5.2. The del statement ¶ There is a way to remove an item from a list given its index instead of its value: the del statement. This differs from the pop() method which returns a value. The del statement can also be used to remove slices from a list or clear the entire list (which we did earlier by assignment of an empty list to the slice). For example: >>> a = [ - 1 , 1 , 66.25 , 333 , 333 , 1234.5 ] >>> del a [ 0 ] >>> a [1, 66.25, 333, 333, 1234.5] >>> del a [ 2 : 4 ] >>> a [1, 66.25, 1234.5] >>> del a [:] >>> a [] del can also be used to delete entire variables: >>> del a Referencing the name a hereafter is an error (at least until another value is assigned to it). We’ll find other uses for del later. 5.3. Tuples and Sequences ¶ We saw that lists and strings have many common properties, such as indexing and slicing operations. They are two examples of sequence data types (see Sequence Types — list, tuple, range ). Since Python is an evolving language, other sequence data types may be added. There is also another standard sequence data type: the tuple . A tuple consists of a number of values separated by commas, for instance: >>> t = 12345 , 54321 , 'hello!' >>> t [ 0 ] 12345 >>> t (12345, 54321, 'hello!') >>> # Tuples may be nested: >>> u = t , ( 1 , 2 , 3 , 4 , 5 ) >>> u ((12345, 54321, 'hello!'), (1, 2, 3, 4, 5)) >>> # Tuples are immutable: >>> t [ 0 ] = 88888 Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : 'tuple' object does not support item assignment >>> # but they can contain mutable objects: >>> v = ([ 1 , 2 , 3 ], [ 3 , 2 , 1 ]) >>> v ([1, 2, 3], [3, 2, 1]) As you see, on output tuples are always enclosed in parentheses, so that nested tuples are interpreted correctly; they may be input with or without surrounding parentheses, although often parentheses are necessary anyway (if the tuple is part of a larger expression). It is not possible to assign to the individual items of a tuple, however it is possible to create tuples which contain mutable objects, such as lists. Though tuples may seem similar to lists, they are often used in different situations and for different purposes. Tuples are immutable , and usually contain a heterogeneous sequence of elements that are accessed via unpacking (see later in this section) or indexing (or even by attribute in the case of namedtuples ). Lists are mutable , and their elements are usually homogeneous and are accessed by iterating over the list. A special problem is the construction of tuples containing 0 or 1 items: the syntax has some extra quirks to accommodate these. Empty tuples are constructed by an empty pair of parentheses; a tuple with one item is constructed by following a value with a comma (it is not sufficient to enclose a single value in parentheses). Ugly, but effective. For example: >>> empty = () >>> singleton = 'hello' , # <-- note trailing comma >>> len ( empty ) 0 >>> len ( singleton ) 1 >>> singleton ('hello',) The statement t = 12345, 54321, 'hello!' is an example of tuple packing : the values 12345 , 54321 and 'hello!' are packed together in a tuple. The reverse operation is also possible: >>> x , y , z = t This is called, appropriately enough, sequence unpacking and works for any sequence on the right-hand side. Sequence unpacking requires that there are as many variables on the left side of the equals sign as there are elements in the sequence. Note that multiple assignment is really just a combination of tuple packing and sequence unpacking. 5.4. Sets ¶ Python also includes a data type for sets . A set is an unordered collection with no duplicate elements. Basic uses include membership testing and eliminating duplicate entries. Set objects also support mathematical operations like union, intersection, difference, and symmetric difference. Curly braces or the set() function can be used to create sets. Note: to create an empty set you have to use set() , not {} ; the latter creates an empty dictionary, a data structure that we discuss in the next section. Here is a brief demonstration: >>> basket = { 'apple' , 'orange' , 'apple' , 'pear' , 'orange' , 'banana' } >>> print ( basket ) # show that duplicates have been removed {'orange', 'banana', 'pear', 'apple'} >>> 'orange' in basket # fast membership testing True >>> 'crabgrass' in basket False >>> # Demonstrate set operations on unique letters from two words >>> >>> a = set ( 'abracadabra' ) >>> b = set ( 'alacazam' ) >>> a # unique letters in a {'a', 'r', 'b', 'c', 'd'} >>> a - b # letters in a but not in b {'r', 'd', 'b'} >>> a | b # letters in a or b or both {'a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'} >>> a & b # letters in both a and b {'a', 'c'} >>> a ^ b # letters in a or b but not both {'r', 'd', 'b', 'm', 'z', 'l'} Similarly to list comprehensions , set comprehensions are also supported: >>> a = { x for x in 'abracadabra' if x not in 'abc' } >>> a {'r', 'd'} 5.5. Dictionaries ¶ Another useful data type built into Python is the dictionary (see Mapping Types — dict ). Dictionaries are sometimes found in other languages as “associative memories” or “associative arrays”. Unlike sequences, which are indexed by a range of numbers, dictionaries are indexed by keys , which can be any immutable type; strings and numbers can always be keys. Tuples can be used as keys if they contain only strings, numbers, or tuples; if a tuple contains any mutable object either directly or indirectly, it cannot be used as a key. You can’t use lists as keys, since lists can be modified in place using index assignments, slice assignments, or methods like append() and extend() . It is best to think of a dictionary as a set of key: value pairs, with the requirement that the keys are unique (within one dictionary). A pair of braces creates an empty dictionary: {} . Placing a comma-separated list of key:value pairs within the braces adds initial key:value pairs to the dictionary; this is also the way dictionaries are written on output. The main operations on a dictionary are storing a value with some key and extracting the value given the key. It is also possible to delete a key:value pair with del . If you store using a key that is already in use, the old value associated with that key is forgotten. Extracting a value for a non-existent key by subscripting ( d[key] ) raises a KeyError . To avoid getting this error when trying to access a possibly non-existent key, use the get() method instead, which returns None (or a specified default value) if the key is not in the dictionary. Performing list(d) on a dictionary returns a list of all the keys used in the dictionary, in insertion order (if you want it sorted, just use sorted(d) instead). To check whether a single key is in the dictionary, use the in keyword. Here is a small example using a dictionary: >>> tel = { 'jack' : 4098 , 'sape' : 4139 } >>> tel [ 'guido' ] = 4127 >>> tel {'jack': 4098, 'sape': 4139, 'guido': 4127} >>> tel [ 'jack' ] 4098 >>> tel [ 'irv' ] Traceback (most recent call last): File "<stdin>" , line 1 , in <module> KeyError : 'irv' >>> print ( tel . get ( 'irv' )) None >>> del tel [ 'sape' ] >>> tel [ 'irv' ] = 4127 >>> tel {'jack': 4098, 'guido': 4127, 'irv': 4127} >>> list ( tel ) ['jack', 'guido', 'irv'] >>> sorted ( tel ) ['guido', 'irv', 'jack'] >>> 'guido' in tel True >>> 'jack' not in tel False The dict() constructor builds dictionaries directly from sequences of key-value pairs: >>> dict ([( 'sape' , 4139 ), ( 'guido' , 4127 ), ( 'jack' , 4098 )]) {'sape': 4139, 'guido': 4127, 'jack': 4098} In addition, dict comprehensions can be used to create dictionaries from arbitrary key and value expressions: >>> { x : x ** 2 for x in ( 2 , 4 , 6 )} {2: 4, 4: 16, 6: 36} When the keys are simple strings, it is sometimes easier to specify pairs using keyword arguments: >>> dict ( sape = 4139 , guido = 4127 , jack = 4098 ) {'sape': 4139, 'guido': 4127, 'jack': 4098} 5.6. Looping Techniques ¶ When looping through dictionaries, the key and corresponding value can be retrieved at the same time using the items() method. >>> knights = { 'gallahad' : 'the pure' , 'robin' : 'the brave' } >>> for k , v in knights . items (): ... print ( k , v ) ... gallahad the pure robin the brave When looping through a sequence, the position index and corresponding value can be retrieved at the same time using the enumerate() function. >>> for i , v in enumerate ([ 'tic' , 'tac' , 'toe' ]): ... print ( i , v ) ... 0 tic 1 tac 2 toe To loop over two or more sequences at the same time, the entries can be paired with the zip() function. >>> questions = [ 'name' , 'quest' , 'favorite color' ] >>> answers = [ 'lancelot' , 'the holy grail' , 'blue' ] >>> for q , a in zip ( questions , answers ): ... print ( 'What is your {0} ? It is {1} .' . format ( q , a )) ... What is your name? It is lancelot. What is your quest? It is the holy grail. What is your favorite color? It is blue. To loop over a sequence in reverse, first specify the sequence in a forward direction and then call the reversed() function. >>> for i in reversed ( range ( 1 , 10 , 2 )): ... print ( i ) ... 9 7 5 3 1 To loop over a sequence in sorted order, use the sorted() function which returns a new sorted list while leaving the source unaltered. >>> basket = [ 'apple' , 'orange' , 'apple' , 'pear' , 'orange' , 'banana' ] >>> for i in sorted ( basket ): ... print ( i ) ... apple apple banana orange orange pear Using set() on a sequence eliminates duplicate elements. The use of sorted() in combination with set() over a sequence is an idiomatic way to loop over unique elements of the sequence in sorted order. >>> basket = [ 'apple' , 'orange' , 'apple' , 'pear' , 'orange' , 'banana' ] >>> for f in sorted ( set ( basket )): ... print ( f ) ... apple banana orange pear It is sometimes tempting to change a list while you are looping over it; however, it is often simpler and safer to create a new list instead. >>> import math >>> raw_data = [ 56.2 , float ( 'NaN' ), 51.7 , 55.3 , 52.5 , float ( 'NaN' ), 47.8 ] >>> filtered_data = [] >>> for value in raw_data : ... if not math . isnan ( value ): ... filtered_data . append ( value ) ... >>> filtered_data [56.2, 51.7, 55.3, 52.5, 47.8] 5.7. More on Conditions ¶ The conditions used in while and if statements can contain any operators, not just comparisons. The comparison operators in and not in are membership tests that determine whether a value is in (or not in) a container. The operators is and is not compare whether two objects are really the same object. All comparison operators have the same priority, which is lower than that of all numerical operators. Comparisons can be chained. For example, a < b == c tests whether a is less than b and moreover b equals c . Comparisons may be combined using the Boolean operators and and or , and the outcome of a comparison (or of any other Boolean expression) may be negated with not . These have lower priorities than comparison operators; between them, not has the highest priority and or the lowest, so that A and not B or C is equivalent to (A and (not B)) or C . As always, parentheses can be used to express the desired composition. The Boolean operators and and or are so-called short-circuit operators: their arguments are evaluated from left to right, and evaluation stops as soon as the outcome is determined. For example, if A and C are true but B is false, A and B and C does not evaluate the expression C . When used as a general value and not as a Boolean, the return value of a short-circuit operator is the last evaluated argument. It is possible to assign the result of a comparison or other Boolean expression to a variable. For example, >>> string1 , string2 , string3 = '' , 'Trondheim' , 'Hammer Dance' >>> non_null = string1 or string2 or string3 >>> non_null 'Trondheim' Note that in Python, unlike C, assignment inside expressions must be done explicitly with the walrus operator := . This avoids a common class of problems encountered in C programs: typing = in an expression when == was intended. 5.8. Comparing Sequences and Other Types ¶ Sequence objects typically may be compared to other objects with the same sequence type. The comparison uses lexicographical ordering: first the first two items are compared, and if they differ this determines the outcome of the comparison; if they are equal, the next two items are compared, and so on, until either sequence is exhausted. If two items to be compared are themselves sequences of the same type, the lexicographical comparison is carried out recursively. If all items of two sequences compare equal, the sequences are considered equal. If one sequence is an initial sub-sequence of the other, the shorter sequence is the smaller (lesser) one. Lexicographical ordering for strings uses the Unicode code point number to order individual characters. Some examples of comparisons between sequences of the same type: ( 1 , 2 , 3 ) < ( 1 , 2 , 4 ) [ 1 , 2 , 3 ] < [ 1 , 2 , 4 ] 'ABC' < 'C' < 'Pascal' < 'Python' ( 1 , 2 , 3 , 4 ) < ( 1 , 2 , 4 ) ( 1 , 2 ) < ( 1 , 2 , - 1 ) ( 1 , 2 , 3 ) == ( 1.0 , 2.0 , 3.0 ) ( 1 , 2 , ( 'aa' , 'ab' )) < ( 1 , 2 , ( 'abc' , 'a' ), 4 ) Note that comparing objects of different types with < or > is legal provided that the objects have appropriate comparison methods. For example, mixed numeric types are compared according to their numeric value, so 0 equals 0.0, etc. Otherwise, rather than providing an arbitrary ordering, the interpreter will raise a TypeError exception. Footnotes [ 1 ] Other languages may return the mutated object, which allows method chaining, such as d->insert("a")->remove("b")->sort(); . Table of Contents 5. Data Structures 5.1. More on Lists 5.1.1. Using Lists as Stacks 5.1.2. Using Lists as Queues 5.1.3. List Comprehensions 5.1.4. Nested List Comprehensions 5.2. The del statement 5.3. Tuples and Sequences 5.4. Sets 5.5. Dictionaries 5.6. Looping Techniques 5.7. More on Conditions 5.8. Comparing Sequences and Other Types Previous topic 4. More Control Flow Tools Next topic 6. Modules This page Report a bug Show source « Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Tutorial » 5. Data Structures | Theme Auto Light Dark | © Copyright 2001 Python Software Foundation. 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https://docs.microsoft.com/en-us/dotnet/csharp/tutorials/intro-to-csharp/branches-and-loops?tutorial-step=1 | Branches and loops - Introductory tutorial - A tour of C# | Microsoft Learn Skip to main content Skip to Ask Learn chat experience This browser is no longer supported. Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support. Download Microsoft Edge More info about Internet Explorer and Microsoft Edge Table of contents Exit editor mode Ask Learn Ask Learn Focus mode Table of contents Read in English Add Add to plan Edit Share via Facebook x.com LinkedIn Email Print Note Access to this page requires authorization. You can try signing in or changing directories . Access to this page requires authorization. You can try changing directories . Tutorial: C# if statements and loops - conditional logic Feedback Summarize this article for me In this article This tutorial teaches you how to write C# code that examines variables and changes the execution path based on those variables. You write C# code and see the results of compiling and running it. The tutorial contains a series of lessons that explore branching and looping constructs in C#. These lessons teach you the fundamentals of the C# language. In this tutorial, you: Launch a GitHub Codespace with a C# development environment. Explore if and else statements. Use loops to repeat operations. Work with nested loops. Combine branches and loops. Prerequisites You must have one of the following options: A GitHub account to use GitHub Codespaces . If you don't already have one, you can create a free account at GitHub.com . A computer with the following tools installed: The .NET 10 SDK . Visual Studio Code . The C# DevKit . Use if statements To start a GitHub Codespace with the tutorial environment, open a browser window to the tutorial codespace repository. Select the green Code button, and the Codespaces tab. Then select the + sign to create a new Codespace using this environment. If you completed other tutorials in this series, you can open that codespace instead of creating a new one. When your codespace loads, create a new file in the tutorials folder named branches-loops.cs . Open your new file. Type or copy the following code into branches-loops.cs : int a = 5; int b = 6; if (a + b > 10) Console.WriteLine("The answer is greater than 10."); Try this code by typing the following command in the integrated terminal: cd tutorials dotnet branches-loops.cs You should see the message "The answer is greater than 10." printed to your console. Modify the declaration of b so that the sum is less than 10: int b = 3; Type dotnet branches-loops.cs again in the terminal window. Because the answer is less than 10, nothing is printed. The condition you're testing is false. You don't have any code to execute because you only wrote one of the possible branches for an if statement: the true branch. Tip As you explore C# (or any programming language), you might make mistakes when you write code. The compiler finds and reports the errors. Look closely at the error output and the code that generated the error. You can also ask Copilot to find differences or spot any mistakes. The compiler error can usually help you find the problem. This first sample shows the power of if and Boolean types. A Boolean is a variable that can have one of two values: true or false . C# defines a special type, bool for Boolean variables. The if statement checks the value of a bool . When the value is true , the statement following the if executes. Otherwise, it's skipped. This process of checking conditions and executing statements based on those conditions is powerful. Let's explore more. Make if and else work together To execute different code in both the true and false branches, you create an else branch that executes when the condition is false. Try an else branch. Add the last two lines in the following code snippet (you should already have the first four): int a = 5; int b = 3; if (a + b > 10) Console.WriteLine("The answer is greater than 10"); else Console.WriteLine("The answer is not greater than 10"); The statement following the else keyword executes only when the condition being tested is false . Combining if and else with boolean conditions provides all the power you need to handle both a true and a false condition. Important The indentation under the if and else statements is for human readers. The C# language doesn't treat indentation or white space as significant. The statement following the if or else keyword executes based on the condition. All the samples in this tutorial follow a common practice to indent lines based on the control flow of statements. Because indentation isn't significant, you need to use { and } to indicate when you want more than one statement to be part of the block that executes conditionally. C# programmers typically use those braces on all if and else clauses. The following example is the same as what you created in the previous example, with the addition of { and } . Modify your code to match the following code: int a = 5; int b = 3; if (a + b > 10) { Console.WriteLine("The answer is greater than 10"); } else { Console.WriteLine("The answer is not greater than 10"); } Tip Through the rest of this tutorial, the code samples all include the braces, following accepted practices. You can test more complicated conditions. Add the following code after the code you wrote so far: int a = 5; int b = 3; int c = 4; if ((a + b + c > 10) && (a == b)) { Console.WriteLine("The answer is greater than 10"); Console.WriteLine("And the first number is equal to the second"); } else { Console.WriteLine("The answer is not greater than 10"); Console.WriteLine("Or the first number is not equal to the second"); } The == symbol tests for equality . Using == distinguishes the test for equality from assignment, which you saw in a = 5 . The && represents "and". It means both conditions must be true to execute the statement in the true branch. These examples also show that you can have multiple statements in each conditional branch, provided you enclose them in { and } . You can also use || to represent "or". Add the following code after what you wrote so far: if ((a + b + c > 10) || (a == b)) Modify the values of a , b , and c and switch between && and || to explore. You gain more understanding of how the && and || operators work. You finished the first step. Before you start the next section, let's move the current code into a separate method. That makes it easier to start working with a new example. Put the existing code in a method called ExploreIf() . Call it from the top of your program. When you finished those changes, your code should look like the following code: ExploreIf(); void ExploreIf() { int a = 5; int b = 3; if (a + b > 10) { Console.WriteLine("The answer is greater than 10"); } else { Console.WriteLine("The answer is not greater than 10"); } int c = 4; if ((a + b + c > 10) && (a > b)) { Console.WriteLine("The answer is greater than 10"); Console.WriteLine("And the first number is greater than the second"); } else { Console.WriteLine("The answer is not greater than 10"); Console.WriteLine("Or the first number is not greater than the second"); } if ((a + b + c > 10) || (a > b)) { Console.WriteLine("The answer is greater than 10"); Console.WriteLine("Or the first number is greater than the second"); } else { Console.WriteLine("The answer is not greater than 10"); Console.WriteLine("And the first number is not greater than the second"); } } Comment out the call to ExploreIf() . It makes the output less cluttered as you work in this section: //ExploreIf(); The // starts a comment in C#. Comments are any text you want to keep in your source code but not execute as code. The compiler doesn't generate any executable code from comments. Use loops to repeat operations Another important concept for creating larger programs is loops . Use loops to repeat statements that you want to execute more than once. Add this code after the call to ExploreIf : int counter = 0; while (counter < 10) { Console.WriteLine($"Hello World! The counter is {counter}"); counter++; } The while statement checks a condition and executes the statement following the while . It repeats checking the condition and executing those statements until the condition is false. There's one other new operator in this example. The ++ after the counter variable is the increment operator. It adds 1 to the value of counter and stores that value in the counter variable. Important Make sure that the while loop condition changes to false as you execute the code. Otherwise, you create an infinite loop where your program never ends. That behavior isn't demonstrated in this sample, because you have to force your program to quit by using CTRL-C or other means. The while loop tests the condition before executing the code following the while . The do ... while loop executes the code first, and then checks the condition. The do while loop is shown in the following code: int counter = 0; do { Console.WriteLine($"Hello World! The counter is {counter}"); counter++; } while (counter < 10); This do loop and the earlier while loop produce the same output. Let's move on to one last loop statement. Work with the for loop Another common loop statement that you see in C# code is the for loop. Try this code: for (int counter = 0; counter < 10; counter++) { Console.WriteLine($"Hello World! The counter is {counter}"); } The preceding for loop does the same work as the while loop and the do loop you already used. The for statement has three parts that control how it works: The first part is the for initializer : int counter = 0; declares that counter is the loop variable, and sets its initial value to 0 . The middle part is the for condition : counter < 10 declares that this for loop continues to execute as long as the value of counter is less than 10. The final part is the for iterator : counter++ specifies how to modify the loop variable after executing the block following the for statement. Here, it specifies that counter increments by 1 each time the block executes. Experiment with these conditions yourself. Try each of the following changes: Change the initializer to start at a different value. Change the condition to stop at a different value. When you're done, move on to the next section to write some code yourself and use what you learned. There's one other looping statement that isn't covered in this tutorial: the foreach statement. The foreach statement repeats its statement for every item in a sequence of items. You most often use it with collections . It's covered in the next tutorial. Created nested loops You can nest a while , do , or for loop inside another loop to create a matrix by combining each item in the outer loop with each item in the inner loop. Let's build a set of alphanumeric pairs to represent rows and columns. Add the following for loop that generates the rows: for (int row = 1; row < 11; row++) { Console.WriteLine($"The row is {row}"); } Add another loop to generate the columns: for (char column = 'a'; column < 'k'; column++) { Console.WriteLine($"The column is {column}"); } Finally, nest the columns loop inside the rows to form pairs: for (int row = 1; row < 11; row++) { for (char column = 'a'; column < 'k'; column++) { Console.WriteLine($"The cell is ({row}, {column})"); } } The outer loop increments once for each full run of the inner loop. Reverse the row and column nesting, and see the changes for yourself. When you're done, place the code from this section in a method called ExploreLoops() . Combine branches and loops Now that you used the if statement and the looping constructs in the C# language, see if you can write C# code to find the sum of all integers 1 through 20 that are divisible by 3. Here are a few hints: The % operator gives you the remainder of a division operation. The if statement gives you the condition to see if a number should be part of the sum. The for loop can help you repeat a series of steps for all the numbers 1 through 20. Try it yourself. Then check how you did. As a hint, you should get 63 for an answer. Did you come up with something like this? int sum = 0; for (int number = 1; number < 21; number++) { if (number % 3 == 0) { sum = sum + number; } } Console.WriteLine($"The sum is {sum}"); You completed the "branches and loops" tutorial. You can learn more about these concepts in these articles: Selection statements Iteration statements Cleanup resources GitHub automatically deletes your Codespace after 30 days of inactivity. If you plan to explore more tutorials in this series, you can leave your Codespace provisioned. If you're ready to visit the .NET site to download the .NET SDK, you can delete your Codespace. To delete your Codespace, open a browser window and navigate to your Codespaces . You should see a list of your codespaces in the window. Select the three dots ( ... ) in the entry for the learn tutorial codespace and select delete . Next step Learn about collections Collaborate with us on GitHub The source for this content can be found on GitHub, where you can also create and review issues and pull requests. For more information, see our contributor guide . .NET Open a documentation issue Provide product feedback Feedback Was this page helpful? Yes No No Need help with this topic? Want to try using Ask Learn to clarify or guide you through this topic? Ask Learn Ask Learn Suggest a fix? Additional resources Last updated on 2025-12-11 In this article Was this page helpful? Yes No No Need help with this topic? Want to try using Ask Learn to clarify or guide you through this topic? 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Joined Joined on Dec 6, 2025 Twitter logo GitHub logo External link icon Meet the team Post 36 posts published Member 1 member Weather Service Project (Part 2): Building the Interactive Frontend with GitHub Pages or Netlify and JavaScript Daniel Daniel Daniel Follow Jan 13 Weather Service Project (Part 2): Building the Interactive Frontend with GitHub Pages or Netlify and JavaScript # frontend # javascript # tutorial # webdev Comments Add Comment 6 min read Proyecto Weather Service (Parte 2): Construyendo el Frontend Interactivo con GitHub Pages o Netlify y JavaScript Daniel Daniel Daniel Follow Jan 13 Proyecto Weather Service (Parte 2): Construyendo el Frontend Interactivo con GitHub Pages o Netlify y JavaScript # frontend # javascript # spanish # tutorial Comments Add Comment 7 min read Weather Service Project (Part 1): Building the Data Collector with Python and GitHub Actions or Netlify Daniel Daniel Daniel Follow Jan 12 Weather Service Project (Part 1): Building the Data Collector with Python and GitHub Actions or Netlify # api # automation # python # tutorial 3 reactions Comments Add Comment 9 min read Proyecto Weather Service (Parte 1): Construyendo el Recolector de Datos con Python y GitHub Actions o Netlify Daniel Daniel Daniel Follow Jan 12 Proyecto Weather Service (Parte 1): Construyendo el Recolector de Datos con Python y GitHub Actions o Netlify # dataengineering # python # spanish # tutorial 1 reaction Comments Add Comment 10 min read Carto: De una Factura a la ONU a Conquistar la Nube Geoespacial Daniel Daniel Daniel Follow Jan 11 Carto: De una Factura a la ONU a Conquistar la Nube Geoespacial # startup # cloud # datascience # spanish Comments 1 comment 5 min read Carto: From a UN Invoice to Conquering the Geospatial Cloud Daniel Daniel Daniel Follow Jan 11 Carto: From a UN Invoice to Conquering the Geospatial Cloud # cloud # datascience # startup Comments Add Comment 4 min read AI-Powered Programming: Creating My Own Magical Flashcards Study App Daniel Daniel Daniel Follow Jan 10 AI-Powered Programming: Creating My Own Magical Flashcards Study App # showdev # ai # programming 5 reactions Comments 2 comments 5 min read Programando con IA: Creando mi Propia App mágica de Flashcards para Estudiar Daniel Daniel Daniel Follow Jan 10 Programando con IA: Creando mi Propia App mágica de Flashcards para Estudiar # showdev # ai # programming # spanish Comments Add Comment 5 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.pocketgamer.com/cookie-run-kingdom/tier-list/ | Cookie Run Kingdom tier list [January 2026] | Pocket Gamer Our Network Arrow Down PocketGamer.com AppSpy.com 148Apps.com PocketGamer.fr PocketGamer.biz PCGamesInsider.biz The Sims News PocketGamer.fun BlockchainGamer.biz PG Connects BigIndiePitch.com MobileGamesAwards.com U.GG Icy Veins The Sims Resource Fantasy Football Scout GameKnot Addicting Games Arcade Cloud EV.IO Menu PocketGamer.com Facebook X YouTube RSS Search Search Tier Lists Cookie Run Kingdom tier list [January 2026] By Mihail Katsoris | Jan 3 iOS + Android | Cookie Run: Kingdom Sweetest list ever! Twitter Facebook Reddit Left Arrow 0 / 4 Right Arrow Updated on January 3rd, 2026 - Version: 6.12.101 - Added: Millennial Tree Cookie Today, we've got a Cookie Run Kingdom tier list for and if you're not familiar with how we do things around here, then it's only natural we share a few words beforehand, right? Cookie Run Kingdom is a free-to-play mobile game where you battle in a world full of monster cakes and sweet treats! Sugar gnomes, wild cakes, and cookies much like yourself all live and fight in this world. You are building up the titular cookie kingdom, which has long fallen into a world full of evil - a masterfully delicious evil. The sweetest of the sweets We bring you a complete tier list of all the cookies available in the game, so if you want to learn who you should aim to get in the gacha, then we've got a list of cookies divided by type and ranked from best to worst. Feel free to use the quick links below to check them out! PvE Tier List | PvP Tier List What's the rarest cookie in CRK ? | About the cookie types Fire Spirit Cookie | Agar Agar Cookie When it comes to having the best team, you might want to know about all of the cookies that there are! On this Cookie Run Kingdom tier list , you will find every single cookie type listed by rarity, along with their powers. Hopefully, this helps you build the strongest team out there! Click Here To View The List » 1 CRK tier list for PvE Tier Cookies S+ S A B C D E 2 CRK tier list for PvP Tier Cookies S+ S A B C D E F 3 What's the rarest cookie in Cookie Run Kingdom? When it comes to the rarest cookie in CRK, there are a few contenders that are extremely rare because of their drop rate. These are the Beast cookies. They have some of the lowest drop rates in the game because they are also the rarest to come by. If we're talking about the overall rarest cookies in the game, then we have two major contenders: Special cookies and Guest cookies. Special cookies are only obtainable for a very limited time, and they can't be recruited from the normal gachas (or any gachas for that matter, once their events are finished). Meanwhile, Guest cookies are non-playable cookies that can be obtained, just like the Special ones, from limited events or bought from the Shop. 4 About the cookie types Ambush Cookies are typically Assassin-type cookies that excel at taking down single-target enemies or sniping your opponents in the Rear line. They are mainly great in PvP and during boss battles, and occasionally for story stages. Support Cookies offer ATK, DEF or crowd control dispels and other similar buffs for the team. They can also inflict considerable damage, as we've seen with Eclair Cookie, which has the capability to single-handedly clear out story stages (if he has a good healer or front line). As the name suggests, Healing cookies are great support units that can provide a lot of health regeneration for the team, as well as buffs and shields (as is the case with Pure Vanilla Cookie). Defense Cookies are your typical front line units, that will mitigate a lot of the damage directed toward your team. They also have DMG reduction buffs (for the entire team) or Taunt skills. Cookies that belong to the Charge type are more or less the equivalent of fighters. They have some damage reduction, but they also provide a lot of damage from the front line, as well as crowd control (such as knock-ups and stuns). Magic cookies are typically great damage dealers, casting forth skills that can deal damage over time, or continuous damage (which is a sort of damage over time), just like in the case of Latte Cookie. However, Magic cookies can also inflict crowd control on top of that damage, which makes them such a popular cookie type in Cookie Run Kingdom. Bombers are very similar to Magic cookies, except they deal a lot of damage after (usually) charging their skills for a little while. They are what one could call burst AoE damage dealers, making them great for any sort of content. Ranged cookies are represented by a crossbow and arrow, which is an extremely accurate representation of their skills. They have range and deal continuous damage to one or multiple enemies from a safe distance. With this, we conclude our Cookie Run Kingdom tier list. In case you have anything to add or if we are missing any new characters, please leave a comment below, and we will fix it in no time! Download now! Cookie Run: Kingdom Left Arrow 0 / 4 Right Arrow Mihail Katsoris I've enjoyed playing games ever since I was a kid (which was a long long time ago at this point). It all started off with an Atari 65XE, then came an Amiga 500+, a Sega Genesis, a 386, and the rest was history. I consider myself lucky to have been able to experience the gaming evolution over the years - this is my passion, and what I will continue to do for as long as I can. Next Up : Brawlhalla tier list [January 2026] See Comments Please enable JavaScript to view the comments powered by Disqus. Related Cookie Run Kingdom codes (December 2025) iOS + Android Cookie Run: Kingdom Holiday Square event guide - All hidden object locations and answers iOS + Android Cookie Run Kingdom: Millennial Tree Cookie Toppings and Beascuits guide iOS + Android Cookie Run: Kingdom opens the Arcade Arena and Winter Night Campfire in its December update iOS + Android Cookie Run Kingdom: Elphaba Cookie Toppings and Beascuits guide [WICKED x CRK] iOS + Android Sign up! Get Pocket Gamer tips, news & features in your inbox Daily Updates Weekly Updates Your sign up will be strictly used in accordance with our Terms of Use and Privacy Policy . Get social! Facebook X YouTube RSS | 2026-01-13T08:48:44 |
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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse TI Posted on Jan 12 Announcing Kreuzberg v4 # opensource # python # rust # ai We're excited to announce that Kreuzberg v4.0.0 is released! What is Kreuzberg: Kreuzberg is a document intelligence library that extracts structured data from 56+ formats, including PDFs, Office docs, HTML, emails, images and many more. Built for RAG/LLM pipelines with OCR, semantic chunking, embeddings, and metadata extraction. The new v4 is a ground-up rewrite in Rust with bindings for 9 other languages! What changed: Rust core: Significantly faster extraction and lower memory usage. No more Python GIL bottlenecks. Pandoc is gone: Native Rust parsers for all formats. One less system dependency to manage. 10 language bindings: Python, TypeScript/Node.js, Java, Go, C#, Ruby, PHP, Elixir, Rust, and WASM for browsers. Same API, same behavior, pick your stack. Plugin system: Register custom document extractors, swap OCR backends (Tesseract, EasyOCR, PaddleOCR), add post-processors for cleaning/normalization, and hook in validators for content verification. Production-ready: REST API, MCP server, Docker images, async-first throughout. ML pipeline features: ONNX embeddings on CPU (requires ONNX Runtime 1.22.x), streaming parsers for large docs, batch processing, byte-accurate offsets for chunking. Why polyglot matters: Document processing shouldn't force your language choice. Your Python ML pipeline, Go microservice, and TypeScript frontend can all use the same extraction engine with identical results. The Rust core is the single source of truth; bindings are thin wrappers that expose idiomatic APIs for each language. Why the Rust rewrite: The Python implementation hit a ceiling, and it also prevented us from offering the library in other languages. Rust gives us predictable performance, lower memory, and a clean path to multi-language support through FFI. Open-Source License: Kreuzberg is and will remain MIT-licensed. This is one of the most permissive licenses, which allows unrestricted use, modification, and redistribution of the code. Users are free to incorporate the software into proprietary systems without imposing copyleft or other licensing obligations. The codebase, issue tracker, and contribution process remain entirely public. Document Intelligence Features: Document intelligence in Kreuzberg extends beyond basic text extraction. In v4, the engine supports: Text extraction across broad formats: 56+ document formats are supported, including .pdf, .docx, .pptx, .xls, .eml, .msg, and structured XML formats. Metadata generation: Output includes structural metadata such as page boundaries, section headings, and encoding information. Chunking strategies: Configurable chunking that respects document structure, enabling finer control over segment sizes for downstream use. Byte-accurate position tracking: Offsets within extracted text are tracked at the byte level for accurate slicing and reference. Token reduction methods: Built-in strategies to reduce token counts for model context windows without external preprocessing libraries. Embeddings support: Optional local embedding generation, using ONNX models, to enable semantic indexing as part of standard pipelines. These capabilities are exposed through both library APIs and standalone executable components. The v4 release consolidates Kreuzberg’s role as an open, high-performance document processing and intelligence engine suitable for embedding into production workflows, pipelines, and services. v4 recognizes that document intelligence is a foundational layer for AI systems, compliance workflows, and enterprise data operations. The new release represents a maturation of both the system and the thinking behind it: open, extensible, performant, and designed to integrate into the systems that depend on it. Links Star us on GitHub Read the Docs Subreddit Join our Discord Server Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse TI Follow Location Berlin Education Freie Universität Berlin Work Founder's Associate Joined Dec 13, 2025 More from TI Kreuzberg.dev now supports PHP and Elixir- and covers most of the backend landscape # opensource # php # elixir # rust Kreuzberg v4.0.0-rc14 released: optimization phase and stable v4 ahead # opensource # product # python # rust 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:44 |
https://deno.com/ | Deno, the next-generation JavaScript runtime Skip to main content Deno 2.6 is here 🎉 Learn more -> Dismiss ⌘K ↑↓ Up or down to navigate ↵ Enter to select ESC Escape to close Products Open Source Current path Deno Modern runtime for JavaScript and TypeScript Fresh Web framework designed for the edge JSR TypeScript-first ESM package registry Commercial Deno Deploy Easy serverless hosting for your JavaScript projects Deno for Enterprise Enterprise support for runtime projects Subhosting Securely run untrusted code in a scalable sandbox Docs Modules Standard Library JSR Node.js & npm Community Discord GitHub Bluesky X YouTube Mastodon Blog ⌘K ↑↓ Up or down to navigate ↵ Enter to select ESC Escape to close Uncomplicate JavaScript Deno is the open-source JavaScript runtime for the modern web. Docs GitHub Install Deno 2.6.4 Release notes MacOS/Linux (Currently selected) Windows curl -fsSL https://deno.land/install.sh | sh Copy command Deno is the open-source JavaScript runtime for the modern web. Built on web standards with zero-config TypeScript, unmatched security, and a complete built-in toolchain. Rating 100k+ Stars on GitHub Community 400k+ Active Deno users Ecosystem 2M+ Community modules Enterprise-grade JavaScript Now offering enterprise support for the Deno runtime Learn more All your favorite tools, built-in and ready to go Deno natively supports TypeScript, JSX, and modern ECMAScript features with zero configuration. account.ts type User = { name : string ; balance : number } ; function getBalance ( user : User ) : string { return ` Balance: $ ${ user . balance . toFixed ( 2 ) } ` ; } console . log ( getBalance ( { name : "Alice" , balance : 42 } ) ) ; $ deno run account.ts Balance: $42.00 $ deno check Check account.ts ✅ Type check successful Just run Run .ts files directly with built-in type checking and compilation—no additional tooling or configuration required! More about TypeScript in Deno Seamless With first-class support for npm and Node, Deno can read your package.json automatically, or you can import packages from npm directly. Node and npm support Using package.json or import maps { return c.text("Hello Hono!"); }); Deno.serve(app.fetch);" mode="light" data-animate-code="true" class="text-gray-50 text-base max-w-full rounded-none break-normal"> import { Hono } from "hono" ; const app = new Hono ( ) ; app . get ( "/" , ( c ) => { return c . text ( "Hello Hono!" ) ; } ) ; Deno . serve ( app . fetch ) ; Using inline imports { return c.text("Hello Hono!"); }); Deno.serve(app.fetch);" mode="light" data-animate-code="true" class="text-gray-50 text-base max-w-full rounded-none break-normal"> import { Hono } from "npm:hono@4" ; const app = new Hono ( ) ; app . get ( "/" , ( c ) => { return c . text ( "Hello Hono!" ) ; } ) ; Deno . serve ( app . fetch ) ; Built on web standards Whenever possible, Deno implements web standard APIs on the server. Deno actively participates in TC39 and WinterCG to help move the web forward. Consistent code from browser to backend Deno prioritizes web standard APIs, maximizing code reuse between browser and server and future-proofing your code. Web APIs in Deno Skip past APIs list Worker MessageEvent WritableStreamDefaultController structuredClone DecompressionStream CompressionStream setInterval PromiseRejectionEvent clearInterval Blob fetch btoa localStorage Navigator clearTimeout ReadableStreamDefaultController Response.json() EventTarget caches CacheStorage MessagePort Location DedicatedWorkerGlobalScope WebSocket queueMicrotask CryptoKey ErrorEvent PerformanceMark WorkerNavigator ReadableStreamBYOBRequest TextDecoder WorkerLocation TextEncoderStream ReadableByteStreamController TransformStream File CustomEvent Event performance DOMException ReadableStreamBYOBReader crypto CloseEvent URLPattern PerformanceEntry console globalThis.close() Crypto Request ReadableStream Storage WebAssembly TextDecoderStream URLSearchParams ProgressEvent FileReader ByteLengthQueuingStrategy BeforeUnloadEvent TextEncoder atob globalThis.alert() setTimeout Performance Headers WorkerGlobalScope AbortSignal FormData Response MessageChannel URL BroadcastChannel TransformStreamDefaultController SubtleCrypto Cache WritableStream AbortController ReadableStreamDefaultReader PerformanceMeasure WritableStreamDefaultWriter Batteries included The essential tools you need to build, test, and deploy your applications are all included out of the box. Code linter Deno ships with a built-in code linter to help you avoid bugs and code rot. Learn more › $ deno lint -- watch Test runner Deno provides a test runner and assertion libraries as a part of the runtime and standard library. Learn more › { const x = 1 + 2; console.assert(x == 3); });" data-animate-code="true"> // server_test.ts Deno . test ( "1 + 2 = 3" , ( ) => { const x = 1 + 2 ; console . assert ( x == 3 ) ; } ) ; $ deno test server_test . ts Standalone executables Instantly create standalone executables from your Deno program. It even supports cross-compiling for other platforms! Learn more › new Response("Hello!"));" data-animate-code="true"> Deno . serve ( req => new Response ( "Hello!" ) ) ; $ deno compile -- allow - net server . ts Compile file : / //tmp/server.ts to server $ . / server Listening on http : / / localhost:8000 / Code formatter Deno's built-in code formatter (based on dprint) beautifies JavaScript, TypeScript, JSON, and Markdown. Learn more › $ deno fmt -- line - width = 120 Secure by default A program run with Deno has no file, network, or environment access unless explicitly enabled. Prevent supply chain attacks Stop worrying about npm modules introducing unexpected vulnerabilities. Deno restricts access to the file system, network, and system environment by default, so code can access only what you allow. Security in Deno Other runtimes $ node random.js Executing random.js ... 🚨 File system compromised! Deno $ deno random.js ⚠️ Deno requests write access Allow? [y/n/A] $ n ❌ Denied write access Exited High-performance networking Out of the box support for: HTTPS (encryption) WebSocket HTTP2 Automatic response body compression View documentation Requests per second* More is better Deno 105200 Node 48700 * Ubuntu 22 on ec2 m5.metal; Deno 2.5.2 vs. Node 18.12.1 Built for the cloud Whether you deploy with our lightning-fast Deno Deploy or on other cloud providers, Deno streamlines your experience. — Deno runs on — Official Docker image hayd/deno-lambda How to Deploy Deno to Digital Ocean Run a Deno App - Fly.io Docs skymethod/denoflare anthonychu/azure-functions-deno-worker How to Deploy to Google Cloud Run — The cloud built for modern JavaScript — Project hosting made for Deno Unlock the full potential of your JavaScript and TypeScript projects with the all-new, completely reimagined Deno Deploy Unlock the full power of Deno Deno users can enjoy first-class support for features like OpenTelemetry, Deno KV, and the Deno Deploy CLI—plus exclusives like Playgrounds, Databases, and more. Built for anything built with JavaScript Because Deno is compatible with Node, your teams and projects can enjoy Deno Deploy's powerful features—even if you're not using Deno Fresh logo Vue logo Hono logo Next logo Solid Start logo Nuxt logo SvelteKit logo Docusaurus logo React React logo Astro logo Solid logo Remix logo Vite logo Express logo Deno logo Node logo Learn more about Deno Deploy Pricing Sign in Get the most out of Deno with Fresh 2.0 Fresh is the Deno web framework, built with Preact and fully compatible with Vite for blazing speed and instant productivity. Build fast sites fast Author routes as the JSX (or TSX) components you already know and love, and Fresh handles dynamic server-side rendering by default. /routes/index.tsx <h1>HTML fresh from the server!</h1> <p> Delivered at {new Date().toLocaleTimeString()} </p> </div> ); }" language="jsx" class="text-gray-50 text-base max-w-full rounded-md"> export default function HomePage ( ) { return ( < div > < h1 > HTML fresh from the server! </ h1 > < p > Delivered at { new Date ( ) . toLocaleTimeString ( ) } </ p > </ div > ) ; } /islands/Counter.tsx (0); return ( <button onClick={() => count.value += 1}> The count is {count.value} </button> ); } " language="jsx" class="text-gray-50 text-base max-w-full rounded-md"> import { useSignal } from "@preact/signals" ; export default function Counter ( ) { const count = useSignal < number > (0); return ( < button onClick = { ( ) => count . value += 1 } > The count is { count . value } </ button > ); } Ship less JavaScript Island-based architecture lets you opt in to only the JavaScript you need, for absolutely minimal runtime overhead. Learn more about Fresh Our vibrant community “I knew this was gonna happen! Deno is truly building the fastest, most secure and personalizable JS runtime!” Manu (Qwik) “Deno's security model is PERFECT for this type of script. Running a script from a rando off the internet? It asks for read access to only the CWD and then asks for access to the file it wants to write to. 👏” Wes Bos “I really think Deno is the easiest and most capable JS runtime. URL imports are slept on.” Atalocke “npm packages in Deno 👀 That’s an exciting development for those of us building at the edge.” Jason Lengstorf “This Deno thing is fast, no doubt about it. #denoland” Poorly Funded Snob “Deno: I have to use the browser APIs cause they are everywhere, and everywhere is my target runtime (the web). The runtime that tries to mirror browser APIs server side makes my life easiest.” Taylor Young “Deno is fantastic. I am using it to level up a bit in terms of JavaScript and TypeScript and it is the easiest way to get going. Their tooling is like 100x simpler than all the usual Node stacks.” Stefan Arentz Manu (Qwik)(active) Wes Bos Atalocke Jason Lengstorf Poorly Funded Snob Taylor Young Stefan Arentz Ready to get started with Deno? Install now Read the docs Products Deno Runtime Deno Deploy Deploy Subhosting Fresh Resources Runtime Manual Runtime API Deploy Docs Standard Library Third-Party Modules Examples Company Blog Pricing News Merch Privacy Policy Terms and Conditions GitHub Discord Bluesky Mastodon Twitter or X or whatever YouTube Copyright © 2026 Deno Land Inc. All rights reserved. | All systems operational | 2026-01-13T08:48:44 |
https://u.gg/ | U GG: The Best League of Legends Builds LoL Build Champion Probuilds LoL Runes Tier List Counters Guides League of Legends Valorant Marvel Rivals Rematch Teamfight Tactics Deadlock NEW World of Warcraft Helldivers 2 2XKO SOON™ Download Now Year in Review Tier List N ARAM Mayhem NEW Champions Multisearch Leaderboards Live Games Items N Watch NEW News Probuild Stats Guest Logged Out © 2017- 2026 Outplayed Inc. U.GG Stats isn't endorsed by Riot Games and doesn't reflect the views or opinions of Riot Games or anyone officially involved in producing or managing League of Legends. Links FAQ Terms Privacy Policy Terms of Service Socials Discord Twitter YouTube Instagram Facebook Our Brands Icy Veins The Sims Resource Addicting Games Fantasy Football Scout Pocket Gamer | 2026-01-13T08:48:44 |
https://zh-hans.react.dev/learn | 快速入门 – React 中文文档 React v 19.2 搜索 ⌘ Ctrl K 教程 参考 社区 博客 起步 快速入门 教程：井字棋游戏 React 哲学 安装 创建一个 React 应用 从零构建一个 React 应用 将 React 添加到现有项目中 配置 编辑器设置 使用 TypeScript React 开发者工具 React Compiler 介绍 安装 逐步使用 调试和故障排除 学习 React 描述 UI 你的第一个组件 组件的导入与导出 使用 JSX 书写标签语言 在 JSX 中通过大括号使用 JavaScript 将 Props 传递给组件 条件渲染 渲染列表 保持组件纯粹 将 UI 视为树 添加交互 响应事件 state：组件的记忆 渲染和提交 state 如同一张快照 把一系列 state 更新加入队列 更新 state 中的对象 更新 state 中的数组 状态管理 用 State 响应输入 选择 State 结构 在组件间共享状态 对 state 进行保留和重置 迁移状态逻辑至 Reducer 中 使用 Context 深层传递参数 使用 Reducer 和 Context 拓展你的应用 脱围机制 使用 ref 引用值 使用 ref 操作 DOM 使用 Effect 进行同步 你可能不需要 Effect 响应式 Effect 的生命周期 将事件从 Effect 中分开 移除 Effect 依赖 使用自定义 Hook 复用逻辑 这个页面对你有帮助吗？ 学习 React 快速入门 欢迎来到 React 文档！本章节将介绍你每天都会使用的 80% 的 React 概念。 你将会学习到 如何创建和嵌套组件 如何添加标签和样式 如何显示数据 如何渲染条件和列表 如何对事件做出响应并更新界面 如何在组件间共享数据 创建和嵌套组件 React 应用程序是由 组件 组成的。一个组件是 UI（用户界面）的一部分，它拥有自己的逻辑和外观。组件可以小到一个按钮，也可以大到整个页面。 React 组件是返回标签的 JavaScript 函数： function MyButton ( ) { return ( < button > 我是一个按钮 </ button > ) ; } 至此，你已经声明了 MyButton ，现在把它嵌套到另一个组件中： export default function MyApp ( ) { return ( < div > < h1 > 欢迎来到我的应用 </ h1 > < MyButton /> </ div > ) ; } 你可能已经注意到 <MyButton /> 是以大写字母开头的。你可以据此识别 React 组件。React 组件必须以大写字母开头，而 HTML 标签则必须是小写字母。 来看下效果： App.js App.js Reload Clear Fork function MyButton ( ) { return ( < button > 我是一个按钮 </ button > ) ; } export default function MyApp ( ) { return ( < div > < h1 > 欢迎来到我的应用 </ h1 > < MyButton /> </ div > ) ; } 显示更多 export default 关键字指定了文件中的主要组件。如果你对 JavaScript 某些语法不熟悉，可以参考 MDN 和 javascript.info 。 使用 JSX 编写标签 上面所使用的标签语法被称为 JSX 。它是可选的，但大多数 React 项目会使用 JSX，主要是它很方便。所有 我们推荐的本地开发工具 都开箱即用地支持 JSX。 JSX 比 HTML 更加严格。你必须闭合标签，如 <br /> 。你的组件也不能返回多个 JSX 标签。你必须将它们包裹到一个共享的父级中，比如 <div>...</div> 或使用空的 <>...</> 包裹： function AboutPage ( ) { return ( < > < h1 > 关于 </ h1 > < p > 你好。 < br /> 最近怎么样？ </ p > </ > ) ; } 如果你有大量的 HTML 需要移植到 JSX 中，你可以使用 在线转换器 。 添加样式 在 React 中，你可以使用 className 来指定一个 CSS 的 class。它与 HTML 的 class 属性的工作方式相同： < img className = "avatar" /> 然后，你可以在一个单独的 CSS 文件中为它编写 CSS 规则： /* 在你的 CSS 文件中修改 */ .avatar { border-radius : 50 % ; } React 并没有规定你如何添加 CSS 文件。最简单的方式是使用 HTML 的 <link> 标签。如果你使用了构建工具或框架，请阅读其文档来了解如何将 CSS 文件添加到你的项目中。 显示数据 JSX 会让你把标签放到 JavaScript 中。而大括号会让你 “回到” JavaScript 中，这样你就可以从你的代码中嵌入一些变量并展示给用户。例如，这将显示 user.name ： return ( < h1 > { user . name } </ h1 > ) ; 你还可以将 JSX 属性 “转义到 JavaScript”，但你必须使用大括号 而非 引号。例如， className="avatar" 是将 "avatar" 字符串传递给 className ，作为 CSS 的 class。但 src={user.imageUrl} 会读取 JavaScript 的 user.imageUrl 变量，然后将该值作为 src 属性传递： return ( < img className = "avatar" src = { user . imageUrl } /> ) ; 你也可以把更为复杂的表达式放入 JSX 的大括号内，例如 字符串拼接 ： App.js App.js Reload Clear Fork const user = { name : 'Hedy Lamarr' , imageUrl : 'https://i.imgur.com/yXOvdOSs.jpg' , imageSize : 90 , } ; export default function Profile ( ) { return ( < > < h1 > { user . name } </ h1 > < img className = "avatar" src = { user . imageUrl } alt = { 'Photo of ' + user . name } style = { { width : user . imageSize , height : user . imageSize } } /> </ > ) ; } 显示更多 在上面示例中， style={{}} 并不是一个特殊的语法，而是 style={ } JSX 大括号内的一个普通 {} 对象。当你的样式依赖于 JavaScript 变量时，你可以使用 style 属性。 条件渲染 React 没有特殊的语法来编写条件语句，因此你使用的就是普通的 JavaScript 代码。例如使用 if 语句根据条件引入 JSX： let content ; if ( isLoggedIn ) { content = < AdminPanel /> ; } else { content = < LoginForm /> ; } return ( < div > { content } </ div > ) ; 如果你喜欢更为紧凑的代码，可以使用 条件 ? 运算符 。与 if 不同的是，它工作于 JSX 内部： < div > { isLoggedIn ? ( < AdminPanel /> ) : ( < LoginForm /> ) } </ div > 当你不需要 else 分支时，你也可以使用更简短的 逻辑 && 语法 ： < div > { isLoggedIn && < AdminPanel /> } </ div > 所有这些方法也适用于有条件地指定属性。如果你对 JavaScript 语法不熟悉，你可以先使用 if...else 。 渲染列表 你将依赖 JavaScript 的特性，例如 for 循环 和 array 的 map() 函数 来渲染组件列表。 假设你有一个产品数组： const products = [ { title : 'Cabbage' , id : 1 } , { title : 'Garlic' , id : 2 } , { title : 'Apple' , id : 3 } , ] ; 在你的组件中，使用 map() 函数将这个数组转换为 <li> 标签构成的列表: const listItems = products . map ( product => < li key = { product . id } > { product . title } </ li > ) ; return ( < ul > { listItems } </ ul > ) ; 注意， <li> 有一个 key 属性。对于列表中的每一个元素，你都应该传递一个字符串或者数字给 key ，用于在其兄弟节点中唯一标识该元素。通常 key 来自你的数据，比如数据库中的 ID。如果你在后续插入、删除或重新排序这些项目，React 将依靠你提供的 key 来思考发生了什么。 App.js App.js Reload Clear Fork const products = [ { title : '卷心菜' , isFruit : false , id : 1 } , { title : '大蒜' , isFruit : false , id : 2 } , { title : '苹果' , isFruit : true , id : 3 } , ] ; export default function ShoppingList ( ) { const listItems = products . map ( product => < li key = { product . id } style = { { color : product . isFruit ? 'magenta' : 'darkgreen' } } > { product . title } </ li > ) ; return ( < ul > { listItems } </ ul > ) ; } 显示更多 响应事件 你可以通过在组件中声明 事件处理 函数来响应事件： function MyButton ( ) { function handleClick ( ) { alert ( 'You clicked me!' ) ; } return ( < button onClick = { handleClick } > 点我 </ button > ) ; } 注意， onClick={handleClick} 的结尾没有小括号！不要 调用 事件处理函数：你只需 把函数传递给事件 即可。当用户点击按钮时 React 会调用你传递的事件处理函数。 更新界面 通常你会希望你的组件 “记住” 一些信息并展示出来，比如一个按钮被点击的次数。要做到这一点，你需要在你的组件中添加 state 。 首先，从 React 引入 useState ： import { useState } from 'react' ; 现在你可以在你的组件中声明一个 state 变量 ： function MyButton ( ) { const [ count , setCount ] = useState ( 0 ) ; // ... 你将从 useState 中获得两样东西：当前的 state（ count ），以及用于更新它的函数（ setCount ）。你可以给它们起任何名字，但按照惯例会像 [something, setSomething] 这样为它们命名。 第一次显示按钮时， count 的值为 0 ，因为你把 0 传给了 useState() 。当你想改变 state 时，调用 setCount() 并将新的值传递给它。点击该按钮计数器将递增： function MyButton ( ) { const [ count , setCount ] = useState ( 0 ) ; function handleClick ( ) { setCount ( count + 1 ) ; } return ( < button onClick = { handleClick } > Clicked { count } times </ button > ) ; } React 将再次调用你的组件函数。第一次 count 变成 1 。接着点击会变成 2 。继续点击会逐步递增。 如果你多次渲染同一个组件，每个组件都会拥有自己的 state。你可以尝试点击不同的按钮： App.js App.js Reload Clear Fork import { useState } from 'react' ; export default function MyApp ( ) { return ( < div > < h1 > 独立更新的计数器 </ h1 > < MyButton /> < MyButton /> </ div > ) ; } function MyButton ( ) { const [ count , setCount ] = useState ( 0 ) ; function handleClick ( ) { setCount ( count + 1 ) ; } return ( < button onClick = { handleClick } > 点了 { count } 次 </ button > ) ; } 显示更多 注意，每个按钮会 “记住” 自己的 count ，而不影响其他按钮。 使用 Hook 以 use 开头的函数被称为 Hook 。 useState 是 React 提供的一个内置 Hook。你可以在 React API 参考 中找到其他内置的 Hook。你也可以通过组合现有的 Hook 来编写属于你自己的 Hook。 Hook 比普通函数更为严格。你只能在你的组件（或其他 Hook）的 顶层 调用 Hook。如果你想在一个条件或循环中使用 useState ，请提取一个新的组件并在组件内部使用它。 组件间共享数据 在前面的示例中，每个 MyButton 都有自己独立的 count ，当每个按钮被点击时，只有被点击按钮的 count 才会发生改变： 起初，每个 MyButton 的 count state 均为 0 第一个 MyButton 会将 count 更新为 1 然而，你经常需要组件 共享数据并一起更新 。 为了使得 MyButton 组件显示相同的 count 并一起更新，你需要将各个按钮的 state “向上” 移动到最接近包含所有按钮的组件之中。 在这个示例中，它是 MyApp ： 起初， MyApp 的 count state 为 0 并传递给了两个子组件 点击后， MyApp 将 count state 更新为 1 ，并将其传递给两个子组件 此刻，当你点击任何一个按钮时， MyApp 中的 count 都将改变，同时会改变 MyButton 中的两个 count。具体代码如下： 首先，将 MyButton 的 state 上移到 MyApp 中： export default function MyApp ( ) { const [ count , setCount ] = useState ( 0 ) ; function handleClick ( ) { setCount ( count + 1 ) ; } return ( < div > < h1 > 独立更新的计数器 </ h1 > < MyButton /> < MyButton /> </ div > ) ; } function MyButton ( ) { // ... 我们正在从这里移动代码... } 接着，将 MyApp 中的点击事件处理函数以及 state 一同向下传递到 每个 MyButton 中。你可以使用 JSX 的大括号向 MyButton 传递信息。就像之前向 <img> 等内置标签所做的那样: export default function MyApp ( ) { const [ count , setCount ] = useState ( 0 ) ; function handleClick ( ) { setCount ( count + 1 ) ; } return ( < div > < h1 > 共同更新的计数器 </ h1 > < MyButton count = { count } onClick = { handleClick } /> < MyButton count = { count } onClick = { handleClick } /> </ div > ) ; } 使用这种方式传递的信息被称作 prop 。此时 MyApp 组件包含了 count state 以及 handleClick 事件处理函数，并将它们作为 prop 传递给 了每个按钮。 最后，改变 MyButton 以 读取 从父组件传递来的 prop： function MyButton ( { count , onClick } ) { return ( < button onClick = { onClick } > 点了 { count } 次 </ button > ) ; } 当你点击按钮时， onClick 处理程序会启动。每个按钮的 onClick prop 会被设置为 MyApp 内的 handleClick 函数，所以函数内的代码会被执行。该代码会调用 setCount(count + 1) ，使得 state 变量 count 递增。新的 count 值会被作为 prop 传递给每个按钮，因此它们每次展示的都是最新的值。这被称为“状态提升”。通过向上移动 state，我们实现了在组件间共享它。 App.js App.js Reload Clear Fork import { useState } from 'react' ; export default function MyApp ( ) { const [ count , setCount ] = useState ( 0 ) ; function handleClick ( ) { setCount ( count + 1 ) ; } return ( < div > < h1 > 共同更新的计数器 </ h1 > < MyButton count = { count } onClick = { handleClick } /> < MyButton count = { count } onClick = { handleClick } /> </ div > ) ; } function MyButton ( { count , onClick } ) { return ( < button onClick = { onClick } > 点了 { count } 次 </ button > ) ; } 显示更多 下一节 至此，你已经了解了如何编写 React 代码的基本知识。 接下来你可以查看 实战教程 并把它们付诸实践，用 React 建立第一个迷你应用程序。 Next 教程：井字棋游戏 Copyright © Meta Platforms, Inc no uwu plz uwu? Logo by @sawaratsuki1004 学习 React 快速入门 安装 描述 UI 添加交互 状态管理 脱围机制 API 参考 React API React DOM API 社区 行为准则 团队 文档贡献者 鸣谢 了解更多 博客 React Native 隐私政策 条款 目录 概览 创建和嵌套组件 使用 JSX 编写标签 添加样式 显示数据 条件渲染 渲染列表 响应事件 更新界面 使用 Hook 组件间共享数据 下一节 | 2026-01-13T08:48:44 |
https://ja.react.dev/community | React コミュニティ – React React v 19.2 Search ⌘ Ctrl K Learn Reference Community Blog 参加する コミュニティ React カンファレンス React ミーティング React 関連動画 チーム紹介 ドキュメント貢献者 翻訳 謝辞 バージョニングポリシー Is this page useful? コミュニティ React コミュニティ React には何百万人もの開発者のコミュニティが存在します。このページでは、あなたが参加できる React 関連のコミュニティを紹介しています。オンラインや個別での学習資料については、このセクションの他のページをご覧ください。 行動規範 React のコミュニティに参加する前に、 私たちの行動規範 (Code of Conduct) をお読みください 。私たちは Contributor Covenant を採用しており、すべてのコミュニティメンバが記載されているガイドラインを遵守することを期待しています。 Stack Overflow Stack Overflow は、コードレベルの質問をしたい場合や、特定のエラーで困っている場合に人気のフォーラムです。 reactjs タグの付いた 既存の質問 を読んだり、 自分で質問 したりしてみてください！ 人気のディスカッションフォーラム ベストプラクティスやアプリケーションアーキテクチャ、さらには React の未来についての議論に最適なオンラインフォーラムはたくさんあります。コードレベルで答えられる質問の場合は、通常 Stack Overflow がより適しています。 各コミュニティは何千人もの React ユーザで構成されています。 DEV の React コミュニティ Hashnode の React コミュニティ Reactiflux オンラインチャット Reddit の React コミュニティ ニュース React の最新ニュースについては、 Twitter の @reactjs 、 Bluesky の @react.dev や、このウェブサイトの 公式 React ブログ をフォローしてください。 Next React カンファレンス Copyright © Meta Platforms, Inc no uwu plz uwu? Logo by @sawaratsuki1004 React を学ぶ クイックスタート インストール UI の記述 インタラクティビティの追加 state の管理 避難ハッチ API リファレンス React APIs React DOM APIs コミュニティ 行動規範 チーム紹介 ドキュメント貢献者 謝辞 More ブログ React Native プライバシー 利用規約 このページの内容 概要 行動規範 Stack Overflow 人気のディスカッションフォーラム ニュース | 2026-01-13T08:48:44 |
https://porkbun.com/about/porkbun-faq | porkbun.com | Porkbun FAQs (Frequently Asked Questions) Toggle navigation porkbun $0.00 (0) products Domains Transfers Local Marketplace Local Auctions 3rd Party Aftermarket Web Hosting All Web Hosting Options Easy WordPress Link In Bio Articulation Sitebuilder Cloud WordPress Shared cPanel Hosting Static Hosting Website Builder Easy PHP Email Hosting All Email Hosting Options Proton Mail Porkbun Email Free Email Forwarding Marketing Tools Textla - SMS Marketing Free WHOIS Privacy Free SSL Certificates Free URL Forwarding transfer Free WordPress SALE! .COM SALE! About --> About Who We Are Why Choose Porkbun Porkbun vs Cloudflare FAQs Resources Knowledge Base Porkbun Blog Service Status Help $0.00 (0) sign in Porkbun FAQs (Frequently Asked Questions) Just the FAQs, ha'am. Welcome to the Porkbun FAQ! We've gathered the most common questions our customers ask to help you make the right choice for the best domain registrar. 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https://cassidoo.co/post/css-quote-attr/ | CSS for markdown blockquote attribution Cassidy Williams Software Engineer in Chicago home newsletter blog github bluesky twitter --> codepen --> linkedin patreon --> CSS for markdown blockquote attribution Dec 22, 2025 #technical It’s Blogvent, day 22 where I blog daily in December! I write my blog posts in markdown, and I write quotes like so: > I miscounted the men! > > - Gavin Volure This results in the following: I miscounted the men! Gavin Volure It always bugged me how the HTML generated a <ul> for the quote author, because the default bullet point is the disc (•) and looked like a stray list out of nowhere. But, I didn’t want to un-style lists entirely, in case something I quoted had a list in it. Now, the way my blog is styled, I target the author by selecting the last <ul> in the generated <blockquote> , and going from there! Here’s the code and a demo: See the Pen Fading away text effect by Cassidy ( @cassidoo ) on CodePen . So now, I can have quotes like what you saw above, but also quotes like this: Basketballs Hula hoops Rollercoaster loop-the-loops You just heard the Woggels sing a very silly list of things! Woggel power! The Woggels Hope this was helpful for you! ← Newer post • Random post • Older post → View posts by tag #advice #personal #musings #events #recommendation #learning #work #technical #project #meta © 2026 Cassidy Williams. This site is open source ! | 2026-01-13T08:48:44 |
https://docs.python.org/3/tutorial/controlflow.html#id2 | 4. More Control Flow Tools — Python 3.14.2 documentation Theme Auto Light Dark Table of Contents 4. More Control Flow Tools 4.1. if Statements 4.2. for Statements 4.3. The range() Function 4.4. break and continue Statements 4.5. else Clauses on Loops 4.6. pass Statements 4.7. match Statements 4.8. Defining Functions 4.9. More on Defining Functions 4.9.1. Default Argument Values 4.9.2. Keyword Arguments 4.9.3. Special parameters 4.9.3.1. Positional-or-Keyword Arguments 4.9.3.2. Positional-Only Parameters 4.9.3.3. Keyword-Only Arguments 4.9.3.4. Function Examples 4.9.3.5. Recap 4.9.4. Arbitrary Argument Lists 4.9.5. Unpacking Argument Lists 4.9.6. Lambda Expressions 4.9.7. Documentation Strings 4.9.8. Function Annotations 4.10. Intermezzo: Coding Style Previous topic 3. An Informal Introduction to Python Next topic 5. Data Structures This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Tutorial » 4. More Control Flow Tools | Theme Auto Light Dark | 4. More Control Flow Tools ¶ As well as the while statement just introduced, Python uses a few more that we will encounter in this chapter. 4.1. if Statements ¶ Perhaps the most well-known statement type is the if statement. For example: >>> x = int ( input ( "Please enter an integer: " )) Please enter an integer: 42 >>> if x < 0 : ... x = 0 ... print ( 'Negative changed to zero' ) ... elif x == 0 : ... print ( 'Zero' ) ... elif x == 1 : ... print ( 'Single' ) ... else : ... print ( 'More' ) ... More There can be zero or more elif parts, and the else part is optional. The keyword ‘ elif ’ is short for ‘else if’, and is useful to avoid excessive indentation. An if … elif … elif … sequence is a substitute for the switch or case statements found in other languages. If you’re comparing the same value to several constants, or checking for specific types or attributes, you may also find the match statement useful. For more details see match Statements . 4.2. for Statements ¶ The for statement in Python differs a bit from what you may be used to in C or Pascal. Rather than always iterating over an arithmetic progression of numbers (like in Pascal), or giving the user the ability to define both the iteration step and halting condition (as C), Python’s for statement iterates over the items of any sequence (a list or a string), in the order that they appear in the sequence. For example (no pun intended): >>> # Measure some strings: >>> words = [ 'cat' , 'window' , 'defenestrate' ] >>> for w in words : ... print ( w , len ( w )) ... cat 3 window 6 defenestrate 12 Code that modifies a collection while iterating over that same collection can be tricky to get right. Instead, it is usually more straight-forward to loop over a copy of the collection or to create a new collection: # Create a sample collection users = { 'Hans' : 'active' , 'Éléonore' : 'inactive' , '景太郎' : 'active' } # Strategy: Iterate over a copy for user , status in users . copy () . items (): if status == 'inactive' : del users [ user ] # Strategy: Create a new collection active_users = {} for user , status in users . items (): if status == 'active' : active_users [ user ] = status 4.3. The range() Function ¶ If you do need to iterate over a sequence of numbers, the built-in function range() comes in handy. It generates arithmetic progressions: >>> for i in range ( 5 ): ... print ( i ) ... 0 1 2 3 4 The given end point is never part of the generated sequence; range(10) generates 10 values, the legal indices for items of a sequence of length 10. It is possible to let the range start at another number, or to specify a different increment (even negative; sometimes this is called the ‘step’): >>> list ( range ( 5 , 10 )) [5, 6, 7, 8, 9] >>> list ( range ( 0 , 10 , 3 )) [0, 3, 6, 9] >>> list ( range ( - 10 , - 100 , - 30 )) [-10, -40, -70] To iterate over the indices of a sequence, you can combine range() and len() as follows: >>> a = [ 'Mary' , 'had' , 'a' , 'little' , 'lamb' ] >>> for i in range ( len ( a )): ... print ( i , a [ i ]) ... 0 Mary 1 had 2 a 3 little 4 lamb In most such cases, however, it is convenient to use the enumerate() function, see Looping Techniques . A strange thing happens if you just print a range: >>> range ( 10 ) range(0, 10) In many ways the object returned by range() behaves as if it is a list, but in fact it isn’t. It is an object which returns the successive items of the desired sequence when you iterate over it, but it doesn’t really make the list, thus saving space. We say such an object is iterable , that is, suitable as a target for functions and constructs that expect something from which they can obtain successive items until the supply is exhausted. We have seen that the for statement is such a construct, while an example of a function that takes an iterable is sum() : >>> sum ( range ( 4 )) # 0 + 1 + 2 + 3 6 Later we will see more functions that return iterables and take iterables as arguments. In chapter Data Structures , we will discuss in more detail about list() . 4.4. break and continue Statements ¶ The break statement breaks out of the innermost enclosing for or while loop: >>> for n in range ( 2 , 10 ): ... for x in range ( 2 , n ): ... if n % x == 0 : ... print ( f " { n } equals { x } * { n // x } " ) ... break ... 4 equals 2 * 2 6 equals 2 * 3 8 equals 2 * 4 9 equals 3 * 3 The continue statement continues with the next iteration of the loop: >>> for num in range ( 2 , 10 ): ... if num % 2 == 0 : ... print ( f "Found an even number { num } " ) ... continue ... print ( f "Found an odd number { num } " ) ... Found an even number 2 Found an odd number 3 Found an even number 4 Found an odd number 5 Found an even number 6 Found an odd number 7 Found an even number 8 Found an odd number 9 4.5. else Clauses on Loops ¶ In a for or while loop the break statement may be paired with an else clause. If the loop finishes without executing the break , the else clause executes. In a for loop, the else clause is executed after the loop finishes its final iteration, that is, if no break occurred. In a while loop, it’s executed after the loop’s condition becomes false. In either kind of loop, the else clause is not executed if the loop was terminated by a break . Of course, other ways of ending the loop early, such as a return or a raised exception, will also skip execution of the else clause. This is exemplified in the following for loop, which searches for prime numbers: >>> for n in range ( 2 , 10 ): ... for x in range ( 2 , n ): ... if n % x == 0 : ... print ( n , 'equals' , x , '*' , n // x ) ... break ... else : ... # loop fell through without finding a factor ... print ( n , 'is a prime number' ) ... 2 is a prime number 3 is a prime number 4 equals 2 * 2 5 is a prime number 6 equals 2 * 3 7 is a prime number 8 equals 2 * 4 9 equals 3 * 3 (Yes, this is the correct code. Look closely: the else clause belongs to the for loop, not the if statement.) One way to think of the else clause is to imagine it paired with the if inside the loop. As the loop executes, it will run a sequence like if/if/if/else. The if is inside the loop, encountered a number of times. If the condition is ever true, a break will happen. If the condition is never true, the else clause outside the loop will execute. When used with a loop, the else clause has more in common with the else clause of a try statement than it does with that of if statements: a try statement’s else clause runs when no exception occurs, and a loop’s else clause runs when no break occurs. For more on the try statement and exceptions, see Handling Exceptions . 4.6. pass Statements ¶ The pass statement does nothing. It can be used when a statement is required syntactically but the program requires no action. For example: >>> while True : ... pass # Busy-wait for keyboard interrupt (Ctrl+C) ... This is commonly used for creating minimal classes: >>> class MyEmptyClass : ... pass ... Another place pass can be used is as a place-holder for a function or conditional body when you are working on new code, allowing you to keep thinking at a more abstract level. The pass is silently ignored: >>> def initlog ( * args ): ... pass # Remember to implement this! ... For this last case, many people use the ellipsis literal ... instead of pass . This use has no special meaning to Python, and is not part of the language definition (you could use any constant expression here), but ... is used conventionally as a placeholder body as well. See The Ellipsis Object . 4.7. match Statements ¶ A match statement takes an expression and compares its value to successive patterns given as one or more case blocks. This is superficially similar to a switch statement in C, Java or JavaScript (and many other languages), but it’s more similar to pattern matching in languages like Rust or Haskell. Only the first pattern that matches gets executed and it can also extract components (sequence elements or object attributes) from the value into variables. If no case matches, none of the branches is executed. The simplest form compares a subject value against one or more literals: def http_error ( status ): match status : case 400 : return "Bad request" case 404 : return "Not found" case 418 : return "I'm a teapot" case _ : return "Something's wrong with the internet" Note the last block: the “variable name” _ acts as a wildcard and never fails to match. You can combine several literals in a single pattern using | (“or”): case 401 | 403 | 404 : return "Not allowed" Patterns can look like unpacking assignments, and can be used to bind variables: # point is an (x, y) tuple match point : case ( 0 , 0 ): print ( "Origin" ) case ( 0 , y ): print ( f "Y= { y } " ) case ( x , 0 ): print ( f "X= { x } " ) case ( x , y ): print ( f "X= { x } , Y= { y } " ) case _ : raise ValueError ( "Not a point" ) Study that one carefully! The first pattern has two literals, and can be thought of as an extension of the literal pattern shown above. But the next two patterns combine a literal and a variable, and the variable binds a value from the subject ( point ). The fourth pattern captures two values, which makes it conceptually similar to the unpacking assignment (x, y) = point . If you are using classes to structure your data you can use the class name followed by an argument list resembling a constructor, but with the ability to capture attributes into variables: class Point : def __init__ ( self , x , y ): self . x = x self . y = y def where_is ( point ): match point : case Point ( x = 0 , y = 0 ): print ( "Origin" ) case Point ( x = 0 , y = y ): print ( f "Y= { y } " ) case Point ( x = x , y = 0 ): print ( f "X= { x } " ) case Point (): print ( "Somewhere else" ) case _ : print ( "Not a point" ) You can use positional parameters with some builtin classes that provide an ordering for their attributes (e.g. dataclasses). You can also define a specific position for attributes in patterns by setting the __match_args__ special attribute in your classes. If it’s set to (“x”, “y”), the following patterns are all equivalent (and all bind the y attribute to the var variable): Point ( 1 , var ) Point ( 1 , y = var ) Point ( x = 1 , y = var ) Point ( y = var , x = 1 ) A recommended way to read patterns is to look at them as an extended form of what you would put on the left of an assignment, to understand which variables would be set to what. Only the standalone names (like var above) are assigned to by a match statement. Dotted names (like foo.bar ), attribute names (the x= and y= above) or class names (recognized by the “(…)” next to them like Point above) are never assigned to. Patterns can be arbitrarily nested. For example, if we have a short list of Points, with __match_args__ added, we could match it like this: class Point : __match_args__ = ( 'x' , 'y' ) def __init__ ( self , x , y ): self . x = x self . y = y match points : case []: print ( "No points" ) case [ Point ( 0 , 0 )]: print ( "The origin" ) case [ Point ( x , y )]: print ( f "Single point { x } , { y } " ) case [ Point ( 0 , y1 ), Point ( 0 , y2 )]: print ( f "Two on the Y axis at { y1 } , { y2 } " ) case _ : print ( "Something else" ) We can add an if clause to a pattern, known as a “guard”. If the guard is false, match goes on to try the next case block. Note that value capture happens before the guard is evaluated: match point : case Point ( x , y ) if x == y : print ( f "Y=X at { x } " ) case Point ( x , y ): print ( f "Not on the diagonal" ) Several other key features of this statement: Like unpacking assignments, tuple and list patterns have exactly the same meaning and actually match arbitrary sequences. An important exception is that they don’t match iterators or strings. Sequence patterns support extended unpacking: [x, y, *rest] and (x, y, *rest) work similar to unpacking assignments. The name after * may also be _ , so (x, y, *_) matches a sequence of at least two items without binding the remaining items. Mapping patterns: {"bandwidth": b, "latency": l} captures the "bandwidth" and "latency" values from a dictionary. Unlike sequence patterns, extra keys are ignored. An unpacking like **rest is also supported. (But **_ would be redundant, so it is not allowed.) Subpatterns may be captured using the as keyword: case ( Point ( x1 , y1 ), Point ( x2 , y2 ) as p2 ): ... will capture the second element of the input as p2 (as long as the input is a sequence of two points) Most literals are compared by equality, however the singletons True , False and None are compared by identity. Patterns may use named constants. These must be dotted names to prevent them from being interpreted as capture variable: from enum import Enum class Color ( Enum ): RED = 'red' GREEN = 'green' BLUE = 'blue' color = Color ( input ( "Enter your choice of 'red', 'blue' or 'green': " )) match color : case Color . RED : print ( "I see red!" ) case Color . GREEN : print ( "Grass is green" ) case Color . BLUE : print ( "I'm feeling the blues :(" ) For a more detailed explanation and additional examples, you can look into PEP 636 which is written in a tutorial format. 4.8. Defining Functions ¶ We can create a function that writes the Fibonacci series to an arbitrary boundary: >>> def fib ( n ): # write Fibonacci series less than n ... """Print a Fibonacci series less than n.""" ... a , b = 0 , 1 ... while a < n : ... print ( a , end = ' ' ) ... a , b = b , a + b ... print () ... >>> # Now call the function we just defined: >>> fib ( 2000 ) 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597 The keyword def introduces a function definition . It must be followed by the function name and the parenthesized list of formal parameters. The statements that form the body of the function start at the next line, and must be indented. The first statement of the function body can optionally be a string literal; this string literal is the function’s documentation string, or docstring . (More about docstrings can be found in the section Documentation Strings .) There are tools which use docstrings to automatically produce online or printed documentation, or to let the user interactively browse through code; it’s good practice to include docstrings in code that you write, so make a habit of it. The execution of a function introduces a new symbol table used for the local variables of the function. More precisely, all variable assignments in a function store the value in the local symbol table; whereas variable references first look in the local symbol table, then in the local symbol tables of enclosing functions, then in the global symbol table, and finally in the table of built-in names. Thus, global variables and variables of enclosing functions cannot be directly assigned a value within a function (unless, for global variables, named in a global statement, or, for variables of enclosing functions, named in a nonlocal statement), although they may be referenced. The actual parameters (arguments) to a function call are introduced in the local symbol table of the called function when it is called; thus, arguments are passed using call by value (where the value is always an object reference , not the value of the object). [ 1 ] When a function calls another function, or calls itself recursively, a new local symbol table is created for that call. A function definition associates the function name with the function object in the current symbol table. The interpreter recognizes the object pointed to by that name as a user-defined function. Other names can also point to that same function object and can also be used to access the function: >>> fib <function fib at 10042ed0> >>> f = fib >>> f ( 100 ) 0 1 1 2 3 5 8 13 21 34 55 89 Coming from other languages, you might object that fib is not a function but a procedure since it doesn’t return a value. In fact, even functions without a return statement do return a value, albeit a rather boring one. This value is called None (it’s a built-in name). Writing the value None is normally suppressed by the interpreter if it would be the only value written. You can see it if you really want to using print() : >>> fib ( 0 ) >>> print ( fib ( 0 )) None It is simple to write a function that returns a list of the numbers of the Fibonacci series, instead of printing it: >>> def fib2 ( n ): # return Fibonacci series up to n ... """Return a list containing the Fibonacci series up to n.""" ... result = [] ... a , b = 0 , 1 ... while a < n : ... result . append ( a ) # see below ... a , b = b , a + b ... return result ... >>> f100 = fib2 ( 100 ) # call it >>> f100 # write the result [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89] This example, as usual, demonstrates some new Python features: The return statement returns with a value from a function. return without an expression argument returns None . Falling off the end of a function also returns None . The statement result.append(a) calls a method of the list object result . A method is a function that ‘belongs’ to an object and is named obj.methodname , where obj is some object (this may be an expression), and methodname is the name of a method that is defined by the object’s type. Different types define different methods. Methods of different types may have the same name without causing ambiguity. (It is possible to define your own object types and methods, using classes , see Classes ) The method append() shown in the example is defined for list objects; it adds a new element at the end of the list. In this example it is equivalent to result = result + [a] , but more efficient. 4.9. More on Defining Functions ¶ It is also possible to define functions with a variable number of arguments. There are three forms, which can be combined. 4.9.1. Default Argument Values ¶ The most useful form is to specify a default value for one or more arguments. This creates a function that can be called with fewer arguments than it is defined to allow. For example: def ask_ok ( prompt , retries = 4 , reminder = 'Please try again!' ): while True : reply = input ( prompt ) if reply in { 'y' , 'ye' , 'yes' }: return True if reply in { 'n' , 'no' , 'nop' , 'nope' }: return False retries = retries - 1 if retries < 0 : raise ValueError ( 'invalid user response' ) print ( reminder ) This function can be called in several ways: giving only the mandatory argument: ask_ok('Do you really want to quit?') giving one of the optional arguments: ask_ok('OK to overwrite the file?', 2) or even giving all arguments: ask_ok('OK to overwrite the file?', 2, 'Come on, only yes or no!') This example also introduces the in keyword. This tests whether or not a sequence contains a certain value. The default values are evaluated at the point of function definition in the defining scope, so that i = 5 def f ( arg = i ): print ( arg ) i = 6 f () will print 5 . Important warning: The default value is evaluated only once. This makes a difference when the default is a mutable object such as a list, dictionary, or instances of most classes. For example, the following function accumulates the arguments passed to it on subsequent calls: def f ( a , L = []): L . append ( a ) return L print ( f ( 1 )) print ( f ( 2 )) print ( f ( 3 )) This will print [ 1 ] [ 1 , 2 ] [ 1 , 2 , 3 ] If you don’t want the default to be shared between subsequent calls, you can write the function like this instead: def f ( a , L = None ): if L is None : L = [] L . append ( a ) return L 4.9.2. Keyword Arguments ¶ Functions can also be called using keyword arguments of the form kwarg=value . For instance, the following function: def parrot ( voltage , state = 'a stiff' , action = 'voom' , type = 'Norwegian Blue' ): print ( "-- This parrot wouldn't" , action , end = ' ' ) print ( "if you put" , voltage , "volts through it." ) print ( "-- Lovely plumage, the" , type ) print ( "-- It's" , state , "!" ) accepts one required argument ( voltage ) and three optional arguments ( state , action , and type ). This function can be called in any of the following ways: parrot ( 1000 ) # 1 positional argument parrot ( voltage = 1000 ) # 1 keyword argument parrot ( voltage = 1000000 , action = 'VOOOOOM' ) # 2 keyword arguments parrot ( action = 'VOOOOOM' , voltage = 1000000 ) # 2 keyword arguments parrot ( 'a million' , 'bereft of life' , 'jump' ) # 3 positional arguments parrot ( 'a thousand' , state = 'pushing up the daisies' ) # 1 positional, 1 keyword but all the following calls would be invalid: parrot () # required argument missing parrot ( voltage = 5.0 , 'dead' ) # non-keyword argument after a keyword argument parrot ( 110 , voltage = 220 ) # duplicate value for the same argument parrot ( actor = 'John Cleese' ) # unknown keyword argument In a function call, keyword arguments must follow positional arguments. All the keyword arguments passed must match one of the arguments accepted by the function (e.g. actor is not a valid argument for the parrot function), and their order is not important. This also includes non-optional arguments (e.g. parrot(voltage=1000) is valid too). No argument may receive a value more than once. Here’s an example that fails due to this restriction: >>> def function ( a ): ... pass ... >>> function ( 0 , a = 0 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : function() got multiple values for argument 'a' When a final formal parameter of the form **name is present, it receives a dictionary (see Mapping Types — dict ) containing all keyword arguments except for those corresponding to a formal parameter. This may be combined with a formal parameter of the form *name (described in the next subsection) which receives a tuple containing the positional arguments beyond the formal parameter list. ( *name must occur before **name .) For example, if we define a function like this: def cheeseshop ( kind , * arguments , ** keywords ): print ( "-- Do you have any" , kind , "?" ) print ( "-- I'm sorry, we're all out of" , kind ) for arg in arguments : print ( arg ) print ( "-" * 40 ) for kw in keywords : print ( kw , ":" , keywords [ kw ]) It could be called like this: cheeseshop ( "Limburger" , "It's very runny, sir." , "It's really very, VERY runny, sir." , shopkeeper = "Michael Palin" , client = "John Cleese" , sketch = "Cheese Shop Sketch" ) and of course it would print: -- Do you have any Limburger ? -- I'm sorry, we're all out of Limburger It's very runny, sir. It's really very, VERY runny, sir. ---------------------------------------- shopkeeper : Michael Palin client : John Cleese sketch : Cheese Shop Sketch Note that the order in which the keyword arguments are printed is guaranteed to match the order in which they were provided in the function call. 4.9.3. Special parameters ¶ By default, arguments may be passed to a Python function either by position or explicitly by keyword. For readability and performance, it makes sense to restrict the way arguments can be passed so that a developer need only look at the function definition to determine if items are passed by position, by position or keyword, or by keyword. A function definition may look like: def f(pos1, pos2, /, pos_or_kwd, *, kwd1, kwd2): ----------- ---------- ---------- | | | | Positional or keyword | | - Keyword only -- Positional only where / and * are optional. If used, these symbols indicate the kind of parameter by how the arguments may be passed to the function: positional-only, positional-or-keyword, and keyword-only. Keyword parameters are also referred to as named parameters. 4.9.3.1. Positional-or-Keyword Arguments ¶ If / and * are not present in the function definition, arguments may be passed to a function by position or by keyword. 4.9.3.2. Positional-Only Parameters ¶ Looking at this in a bit more detail, it is possible to mark certain parameters as positional-only . If positional-only , the parameters’ order matters, and the parameters cannot be passed by keyword. Positional-only parameters are placed before a / (forward-slash). The / is used to logically separate the positional-only parameters from the rest of the parameters. If there is no / in the function definition, there are no positional-only parameters. Parameters following the / may be positional-or-keyword or keyword-only . 4.9.3.3. Keyword-Only Arguments ¶ To mark parameters as keyword-only , indicating the parameters must be passed by keyword argument, place an * in the arguments list just before the first keyword-only parameter. 4.9.3.4. Function Examples ¶ Consider the following example function definitions paying close attention to the markers / and * : >>> def standard_arg ( arg ): ... print ( arg ) ... >>> def pos_only_arg ( arg , / ): ... print ( arg ) ... >>> def kwd_only_arg ( * , arg ): ... print ( arg ) ... >>> def combined_example ( pos_only , / , standard , * , kwd_only ): ... print ( pos_only , standard , kwd_only ) The first function definition, standard_arg , the most familiar form, places no restrictions on the calling convention and arguments may be passed by position or keyword: >>> standard_arg ( 2 ) 2 >>> standard_arg ( arg = 2 ) 2 The second function pos_only_arg is restricted to only use positional parameters as there is a / in the function definition: >>> pos_only_arg ( 1 ) 1 >>> pos_only_arg ( arg = 1 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : pos_only_arg() got some positional-only arguments passed as keyword arguments: 'arg' The third function kwd_only_arg only allows keyword arguments as indicated by a * in the function definition: >>> kwd_only_arg ( 3 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : kwd_only_arg() takes 0 positional arguments but 1 was given >>> kwd_only_arg ( arg = 3 ) 3 And the last uses all three calling conventions in the same function definition: >>> combined_example ( 1 , 2 , 3 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : combined_example() takes 2 positional arguments but 3 were given >>> combined_example ( 1 , 2 , kwd_only = 3 ) 1 2 3 >>> combined_example ( 1 , standard = 2 , kwd_only = 3 ) 1 2 3 >>> combined_example ( pos_only = 1 , standard = 2 , kwd_only = 3 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : combined_example() got some positional-only arguments passed as keyword arguments: 'pos_only' Finally, consider this function definition which has a potential collision between the positional argument name and **kwds which has name as a key: def foo ( name , ** kwds ): return 'name' in kwds There is no possible call that will make it return True as the keyword 'name' will always bind to the first parameter. For example: >>> foo ( 1 , ** { 'name' : 2 }) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : foo() got multiple values for argument 'name' >>> But using / (positional only arguments), it is possible since it allows name as a positional argument and 'name' as a key in the keyword arguments: >>> def foo ( name , / , ** kwds ): ... return 'name' in kwds ... >>> foo ( 1 , ** { 'name' : 2 }) True In other words, the names of positional-only parameters can be used in **kwds without ambiguity. 4.9.3.5. Recap ¶ The use case will determine which parameters to use in the function definition: def f ( pos1 , pos2 , / , pos_or_kwd , * , kwd1 , kwd2 ): As guidance: Use positional-only if you want the name of the parameters to not be available to the user. This is useful when parameter names have no real meaning, if you want to enforce the order of the arguments when the function is called or if you need to take some positional parameters and arbitrary keywords. Use keyword-only when names have meaning and the function definition is more understandable by being explicit with names or you want to prevent users relying on the position of the argument being passed. For an API, use positional-only to prevent breaking API changes if the parameter’s name is modified in the future. 4.9.4. Arbitrary Argument Lists ¶ Finally, the least frequently used option is to specify that a function can be called with an arbitrary number of arguments. These arguments will be wrapped up in a tuple (see Tuples and Sequences ). Before the variable number of arguments, zero or more normal arguments may occur. def write_multiple_items ( file , separator , * args ): file . write ( separator . join ( args )) Normally, these variadic arguments will be last in the list of formal parameters, because they scoop up all remaining input arguments that are passed to the function. Any formal parameters which occur after the *args parameter are ‘keyword-only’ arguments, meaning that they can only be used as keywords rather than positional arguments. >>> def concat ( * args , sep = "/" ): ... return sep . join ( args ) ... >>> concat ( "earth" , "mars" , "venus" ) 'earth/mars/venus' >>> concat ( "earth" , "mars" , "venus" , sep = "." ) 'earth.mars.venus' 4.9.5. Unpacking Argument Lists ¶ The reverse situation occurs when the arguments are already in a list or tuple but need to be unpacked for a function call requiring separate positional arguments. For instance, the built-in range() function expects separate start and stop arguments. If they are not available separately, write the function call with the * -operator to unpack the arguments out of a list or tuple: >>> list ( range ( 3 , 6 )) # normal call with separate arguments [3, 4, 5] >>> args = [ 3 , 6 ] >>> list ( range ( * args )) # call with arguments unpacked from a list [3, 4, 5] In the same fashion, dictionaries can deliver keyword arguments with the ** -operator: >>> def parrot ( voltage , state = 'a stiff' , action = 'voom' ): ... print ( "-- This parrot wouldn't" , action , end = ' ' ) ... print ( "if you put" , voltage , "volts through it." , end = ' ' ) ... print ( "E's" , state , "!" ) ... >>> d = { "voltage" : "four million" , "state" : "bleedin' demised" , "action" : "VOOM" } >>> parrot ( ** d ) -- This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised ! 4.9.6. Lambda Expressions ¶ Small anonymous functions can be created with the lambda keyword. This function returns the sum of its two arguments: lambda a, b: a+b . Lambda functions can be used wherever function objects are required. They are syntactically restricted to a single expression. Semantically, they are just syntactic sugar for a normal function definition. Like nested function definitions, lambda functions can reference variables from the containing scope: >>> def make_incrementor ( n ): ... return lambda x : x + n ... >>> f = make_incrementor ( 42 ) >>> f ( 0 ) 42 >>> f ( 1 ) 43 The above example uses a lambda expression to return a function. Another use is to pass a small function as an argument. For instance, list.sort() takes a sorting key function key which can be a lambda function: >>> pairs = [( 1 , 'one' ), ( 2 , 'two' ), ( 3 , 'three' ), ( 4 , 'four' )] >>> pairs . sort ( key = lambda pair : pair [ 1 ]) >>> pairs [(4, 'four'), (1, 'one'), (3, 'three'), (2, 'two')] 4.9.7. Documentation Strings ¶ Here are some conventions about the content and formatting of documentation strings. The first line should always be a short, concise summary of the object’s purpose. For brevity, it should not explicitly state the object’s name or type, since these are available by other means (except if the name happens to be a verb describing a function’s operation). This line should begin with a capital letter and end with a period. If there are more lines in the documentation string, the second line should be blank, visually separating the summary from the rest of the description. The following lines should be one or more paragraphs describing the object’s calling conventions, its side effects, etc. The Python parser strips indentation from multi-line string literals when they serve as module, class, or function docstrings. Here is an example of a multi-line docstring: >>> def my_function (): ... """Do nothing, but document it. ... ... No, really, it doesn't do anything: ... ... >>> my_function() ... >>> ... """ ... pass ... >>> print ( my_function . __doc__ ) Do nothing, but document it. No, really, it doesn't do anything: >>> my_function() >>> 4.9.8. Function Annotations ¶ Function annotations are completely optional metadata information about the types used by user-defined functions (see PEP 3107 and PEP 484 for more information). Annotations are stored in the __annotations__ attribute of the function as a dictionary and have no effect on any other part of the function. Parameter annotations are defined by a colon after the parameter name, followed by an expression evaluating to the value of the annotation. Return annotations are defined by a literal -> , followed by an expression, between the parameter list and the colon denoting the end of the def statement. The following example has a required argument, an optional argument, and the return value annotated: >>> def f ( ham : str , eggs : str = 'eggs' ) -> str : ... print ( "Annotations:" , f . __annotations__ ) ... print ( "Arguments:" , ham , eggs ) ... return ham + ' and ' + eggs ... >>> f ( 'spam' ) Annotations: {'ham': <class 'str'>, 'return': <class 'str'>, 'eggs': <class 'str'>} Arguments: spam eggs 'spam and eggs' 4.10. Intermezzo: Coding Style ¶ Now that you are about to write longer, more complex pieces of Python, it is a good time to talk about coding style . Most languages can be written (or more concise, formatted ) in different styles; some are more readable than others. Making it easy for others to read your code is always a good idea, and adopting a nice coding style helps tremendously for that. For Python, PEP 8 has emerged as the style guide that most projects adhere to; it promotes a very readable and eye-pleasing coding style. Every Python developer should read it at some point; here are the most important points extracted for you: Use 4-space indentation, and no tabs. 4 spaces are a good compromise between small indentation (allows greater nesting depth) and large indentation (easier to read). Tabs introduce confusion, and are best left out. Wrap lines so that they don’t exceed 79 characters. This helps users with small displays and makes it possible to have several code files side-by-side on larger displays. Use blank lines to separate functions and classes, and larger blocks of code inside functions. When possible, put comments on a line of their own. Use docstrings. Use spaces around operators and after commas, but not directly inside bracketing constructs: a = f(1, 2) + g(3, 4) . Name your classes and functions consistently; the convention is to use UpperCamelCase for classes and lowercase_with_underscores for functions and methods. Always use self as the name for the first method argument (see A First Look at Classes for more on classes and methods). Don’t use fancy encodings if your code is meant to be used in international environments. Python’s default, UTF-8, or even plain ASCII work best in any case. Likewise, don’t use non-ASCII characters in identifiers if there is only the slightest chance people speaking a different language will read or maintain the code. Footnotes [ 1 ] Actually, call by object reference would be a better description, since if a mutable object is passed, the caller will see any changes the callee makes to it (items inserted into a list). Table of Contents 4. More Control Flow Tools 4.1. if Statements 4.2. for Statements 4.3. The range() Function 4.4. break and continue Statements 4.5. else Clauses on Loops 4.6. pass Statements 4.7. match Statements 4.8. Defining Functions 4.9. More on Defining Functions 4.9.1. Default Argument Values 4.9.2. Keyword Arguments 4.9.3. Special parameters 4.9.3.1. Positional-or-Keyword Arguments 4.9.3.2. Positional-Only Parameters 4.9.3.3. Keyword-Only Arguments 4.9.3.4. Function Examples 4.9.3.5. Recap 4.9.4. Arbitrary Argument Lists 4.9.5. Unpacking Argument Lists 4.9.6. Lambda Expressions 4.9.7. Documentation Strings 4.9.8. Function Annotations 4.10. Intermezzo: Coding Style Previous topic 3. An Informal Introduction to Python Next topic 5. Data Structures This page Report a bug Show source « Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Tutorial » 4. More Control Flow Tools | Theme Auto Light Dark | © Copyright 2001 Python Software Foundation. This page is licensed under the Python Software Foundation License Version 2. Examples, recipes, and other code in the documentation are additionally licensed under the Zero Clause BSD License. See History and License for more information. The Python Software Foundation is a non-profit corporation. Please donate. 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https://zilliz.com/learn/what-is-vector-database | What is a Vector Database and How Does It Work? - Zilliz Learn Products Zilliz Cloud Fully-managed vector database service designed for speed, scale and high performance. Zilliz Cloud vs. Milvus Milvus Open-source vector database built for billion-scale vector similarity search. BYOC Migration Benchmark Integrations Open Source Support Portal High-Performance Vector Database Made Serverless. 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By Frank Liu Read the entire series Introduction to Unstructured Data What is a Vector Database and how does it work: Implementation, Optimization & Scaling for Production Applications Understanding Vector Databases: Compare Vector Databases, Vector Search Libraries, and Vector Search Plugins Introduction to Milvus Vector Database Milvus Quickstart: Install Milvus Vector Database in 5 Minutes Introduction to Vector Similarity Search Everything You Need to Know about Vector Index Basics Scalar Quantization and Product Quantization Hierarchical Navigable Small Worlds (HNSW) Approximate Nearest Neighbors Oh Yeah (Annoy) Choosing the Right Vector Index for Your Project DiskANN and the Vamana Algorithm Safeguard Data Integrity: Backup and Recovery in Vector Databases Dense Vectors in AI: Maximizing Data Potential in Machine Learning Integrating Vector Databases with Cloud Computing: A Strategic Solution to Modern Data Challenges A Beginner's Guide to Implementing Vector Databases Maintaining Data Integrity in Vector Databases From Rows and Columns to Vectors: The Evolutionary Journey of Database Technologies Decoding Softmax Activation Function Harnessing Product Quantization for Memory Efficiency in Vector Databases How to Spot Search Performance Bottleneck in Vector Databases Ensuring High Availability of Vector Databases Mastering Locality Sensitive Hashing: A Comprehensive Tutorial and Use Cases Vector Library vs Vector Database: Which One is Right for You? Maximizing GPT 4.x's Potential Through Fine-Tuning Techniques Deploying Vector Databases in Multi-Cloud Environments An Introduction to Vector Embeddings: What They Are and How to Use Them A vector database indexes and stores vector embeddings for fast retrieval and similarity search, with capabilities like CRUD operations, metadata filtering, and horizontal scaling designed specifically for AI applications. Introduction: The Rise of Vector Databases in the AI Era In the early days of ImageNet, it took 25,000 human curators to manually label the dataset. This staggering number highlights a fundamental challenge in AI: manually categorizing unstructured data simply doesn’t scale. With billions of images, videos, documents, and audio files generated daily, a paradigm shift was needed in how computers understand and interact with content. Traditional relational database systems excel at managing structured data with predefined formats and executing precise search operations. In contrast, vector databases specialize in storing and retrieving unstructured data types, such as images, audio, videos, and textual content, through high-dimensional numerical representations known as vector embeddings. Vector databases support large language models by providing efficient data retrieval and management. Modern vector databases outperform traditional systems by 2-10x through hardware-aware optimization (AVX512, SIMD, GPUs, NVMe SSDs), highly optimized search algorithms (HNSW, IVF, DiskANN), and column-oriented storage design. Their cloud-native, decoupled architecture enables independent scaling of search, data insertion, and indexing components, allowing systems to efficiently handle billions of vectors while maintaining performance for enterprise AI applications at companies like Salesforce, PayPal, eBay, and NVIDIA. This represents what experts call a “semantic gap”—traditional databases operate on exact matches and predefined relationships, while human understanding of content is nuanced, contextual, and multidimensional. This gap becomes increasingly problematic as AI applications demand: Finding conceptual similarities rather than exact matches Understanding contextual relationships between different pieces of content Capturing the semantic essence of information beyond keywords Processing multimodal data within a unified framework Vector databases have emerged as the critical technology to bridge this gap, becoming an essential component in the modern AI infrastructure. They enhance the performance of machine learning models by facilitating tasks like clustering and classification. Understanding Vector Embeddings: The Foundation Vector embeddings serve as the critical bridge across the semantic gap. These high-dimensional numerical representations capture the semantic essence of unstructured data in a form computers can efficiently process. Modern embedding models transform raw content—whether text, images, or audio—into dense vectors where similar concepts cluster together in the vector space, regardless of surface-level differences. For example, properly constructed embeddings would position concepts like “automobile,” “car,” and “vehicle” in proximity within the vector space, despite having different lexical forms. This property enables semantic search , recommendation systems , and AI applications to understand content beyond simple pattern matching. The power of embeddings extends across modalities. Advanced vector databases support various unstructured data types—text, images, audio—in a unified system, enabling cross-modal searches and relationships that were previously impossible to model efficiently. These vector database capabilities are crucial for AI-driven technologies such as chatbots and image recognition systems, supporting advanced applications like semantic search and recommendation systems. However, storing, indexing, and retrieving embeddings at scale presents unique computational challenges that traditional databases weren’t built to address. Vector Databases: Core Concepts Vector databases represent a paradigm shift in how we store and query unstructured data. Unlike traditional relational database systems that excel at managing structured data with predefined formats, vector databases specialize in handling unstructured data through numerical vector representations. At their core, vector databases are designed to solve a fundamental problem: enabling efficient similarity searches across massive datasets of unstructured data. They accomplish this through three key components: Vector Embeddings : High-dimensional numerical representations that capture semantic meaning of unstructured data (text, images, audio, etc.) Specialized Indexing : Algorithms optimized for high-dimensional vector spaces that enable fast approximate searches. Vector database indexes vectors to enhance the speed and efficiency of similarity searches, utilizing various ML algorithms to create indexes on vector embeddings. Distance Metrics : Mathematical functions that quantify similarity between vectors The primary operation in a vector database is the k-nearest neighbors (KNN) query, which finds the k vectors most similar to a given query vector. For large-scale applications, these databases typically implement approximate nearest neighbor (ANN) algorithms, trading a small amount of accuracy for significant gains in search speed. Mathematical Foundations of Vector Similarity Understanding vector databases requires grasping the mathematical principles behind vector similarity. Here are the foundational concepts: Vector Spaces and Embeddings A vector embedding is a fixed-length array of floating-point numbers (they can range from 100-32,768 dimensions!) that represents unstructured data in a numerical format. These embeddings position similar items closer together in a high-dimensional vector space. For example, the words "king" and "queen" would have vector representations that are closer to each other than either is to "automobile" in a well-trained word embedding space. Distance Metrics The choice of distance metric fundamentally affects how similarity is calculated. Common distance metrics include: Euclidean Distance : The straight-line distance between two points in Euclidean space. Cosine Similarity : Measures the cosine of the angle between two vectors, focusing on orientation rather than magnitude Dot Product : For normalized vectors, represents how aligned two vectors are. Manhattan Distance (L1 Norm) : Sum of absolute differences between coordinates. Different use cases may require different distance metrics. For example, cosine similarity often works well for text embeddings, while Euclidean distance may be better suited for certain types of image embeddings . Semantic similarity between vectors in a vector space Semantic similarity between vectors in a vector space Understanding these mathematical foundations leads to an important question about implementation: So just add a vector index to any database, right? Simply adding a vector index to a relational database isn't sufficient, nor is using a standalone vector index library . While vector indices provide the critical ability to find similar vectors efficiently, they lack the infrastructure needed for production applications: They don't provide CRUD operations for managing vector data They lack metadata storage and filtering capabilities They offer no built-in scaling, replication, or fault tolerance They require custom infrastructure for data persistence and management Vector databases emerged to address these limitations, providing complete data management capabilities designed specifically for vector embeddings. They combine the semantic power of vector search with the operational capabilities of database systems. Unlike traditional databases that operate on exact matches, vector databases focus on semantic search—finding vectors that are "most similar" to a query vector according to specific distance metrics. This fundamental difference drives the unique architecture and algorithms that power these specialized systems. Vector Database Architecture: A Technical Framework Modern vector databases implement a sophisticated multi-layered architecture that separates concerns, enables scalability, and ensures maintainability. This technical framework goes far beyond simple search indices to create systems capable of handling production AI workloads. Vector databases work by processing and retrieving information for AI and ML applications, utilizing algorithms for approximate nearest neighbor searches, converting various types of raw data into vectors, and efficiently managing diverse data types through semantic searches. Four-Tier Architecture A production vector database typically consists of four primary architectural layers: Storage Layer : Manages persistent storage of vector data and metadata, implements specialized encoding and compression strategies, and optimizes I/O patterns for vector-specific access. Index Layer : Maintains multiple indexing algorithms, manages their creation and updates, and implements hardware-specific optimizations for performance. Query Layer : Processes incoming queries, determines execution strategies, handles result processing, and implements caching for repeated queries. Service Layer : Manages client connections, handles request routing, provides monitoring and logging, and implements security and multi-tenancy. Vector Search Workflow Complete workflow of a vector search operation.png A typical vector database implementation follows this workflow: A machine learning model transforms unstructured data (text, images, audio) into vector embeddings These vector embeddings are stored in the database along with relevant metadata When a user performs a query, it is converted into a vector embedding using the same model The database compares the query vector to stored vectors using an approximate nearest neighbor algorithm The system returns the top-K most relevant results based on vector similarity Optional post-processing may apply additional filters or reranking This pipeline enables efficient semantic search across massive collections of unstructured data that would be impossible with traditional database approaches. Consistency in Vector Databases Ensuring consistency in distributed vector databases is a challenge due to the trade-off between performance and correctness. While eventual consistency is common in large-scale systems, strong consistency models are required for mission-critical applications like fraud detection and real-time recommendations. Techniques like quorum-based writes and distributed consensus (e.g., Raft , Paxos) ensure data integrity without excessive performance trade-offs. Production implementations adopt a shared-storage architecture featuring storage and computing disaggregation. This separation follows the principle of data plane and control plane disaggregation, with each layer being independently scalable for optimal resource utilization. Managing Connections, Security, and Multitenancy As these databases are used in multi-user and multi-tenant environments, securing data and managing access control are critical for maintaining confidentiality. Security measures like encryption (both at rest and in transit) protect sensitive data, such as embeddings and metadata. Authentication and authorization ensure only authorized users can access the system, with fine-grained permissions for managing access to specific data. Access control defines roles and permissions to restrict data access. This is particularly important for databases storing sensitive information like customer data or proprietary AI models. Multitenancy involves isolating each tenant's data to prevent unauthorized access while enabling resource sharing. This is achieved through sharding, partitioning, or row-level security to ensure scalable and secure access for different teams or clients. External identity and access management (IAM) systems integrate with vector databases to enforce security policies and ensure compliance with industry standards. Advantages of Vector Databases Vector databases offer several advantages over traditional databases, making them an ideal choice for handling vector data. Here are some of the key benefits: Efficient Similarity Search : One of the standout features of vector databases is their ability to perform efficient semantic searches. Unlike traditional databases that rely on exact matches, vector databases excel at finding data points that are similar to a given query vector. This capability is crucial for applications like recommendation systems, where finding items similar to a user’s past interactions can significantly enhance user experience. Handling High-Dimensional Data : Vector databases are specifically designed to manage high-dimensional data efficiently. This makes them particularly suitable for applications in natural language processing, computer vision , and genomics, where data often exists in high-dimensional spaces. By leveraging advanced indexing and search algorithms, vector databases can quickly retrieve relevant data points, even in complex, vector embedding datasets. Scalability : Scalability is a critical requirement for modern AI applications, and vector databases are built to scale efficiently. Whether dealing with millions or billions of vectors, vector databases can handle the growing demands of AI applications through horizontal scaling. This ensures that performance remains consistent even as data volumes increase. Flexibility : Vector databases offer remarkable flexibility in terms of data representation. They can store and manage various types of data, including numerical features, embeddings from text or images, and even complex data like molecular structures. This versatility makes vector databases a powerful tool for a wide range of applications, from text analysis to scientific research. Real-time Applications : Many vector databases are optimized for real-time or near-real-time querying. This is particularly important for applications that require quick responses, such as fraud detection, real-time recommendations, and interactive AI systems. The ability to perform rapid similarity searches ensures that these applications can deliver timely and relevant results. Use Cases for Vector Databases Vector databases have a wide range of applications across various industries, demonstrating their versatility and power. Here are some notable use cases: Natural Language Processing : In the realm of natural language processing (NLP), vector databases play a crucial role. They are used for tasks such as text classification, sentiment analysis, and language translation. By converting text into high-dimensional vector embeddings, vector databases enable efficient similarity searches and semantic understanding, enhancing the performance of NLP models . Computer Vision : Vector databases are also widely used in computer vision applications. Tasks like image recognition, object detection , and image segmentation benefit from the ability of vector databases to handle high-dimensional image embeddings. This allows for quick and accurate retrieval of visually similar images, making vector databases indispensable in fields like autonomous driving, medical imaging, and digital asset management. Genomics : In genomics, vector databases are used to store and analyze genetic sequences, protein structures, and other molecular data. The high-dimensional nature of this data makes vector databases an ideal choice for managing and querying large genomic datasets. Researchers can perform vector searches to find genetic sequences with similar patterns, aiding in the discovery of genetic markers and the understanding of complex biological processes. Recommendation Systems : Vector databases are a cornerstone of modern recommendation systems. By storing user interactions and item features as vector embeddings, these databases can quickly identify items that are similar to those a user has previously interacted with. This capability enhances the accuracy and relevance of recommendations, improving user satisfaction and engagement. Chatbots and Virtual Assistants : Vector databases are used in chatbots and virtual assistants to provide real-time contextual answers to user queries. By converting user inputs into vector embeddings, these systems can perform similarity searches to find the most relevant responses. This enables chatbots and virtual assistants to deliver more accurate and contextually appropriate answers, enhancing the overall user experience. By leveraging the unique capabilities of vector databases, organizations across various industries can build more intelligent, responsive, and scalable AI applications. Vector Search Algorithms: From Theory to Practice Vector databases require specialized indexing algorithms to enable efficient similarity search in high-dimensional spaces. The algorithm selection directly impacts accuracy, speed, memory usage, and scalability. Graph-Based Approaches HNSW ( Hierarchical Navigable Small World ) creates navigable structures by connecting similar vectors, enabling efficient traversal during search. HNSW limits maximum connections per node and search scope to balance performance and accuracy, making it one of the most widely used algorithms for vector similarity search. Cagra is a graph-based index optimized specifically for GPU acceleration. It constructs navigable graph structures that align with GPU processing patterns, enabling massively parallel vector comparisons. What makes Cagra particularly effective is its ability to balance recall and performance through configurable parameters like graph degree and search width. Using inference-grade GPUs with Cagra can be more cost-effective than expensive training-grade hardware while still delivering high throughput, especially for large-scale vector collections. However, it's worth noting that GPU indexes like Cagra may not necessarily reduce latency compared to CPU indexes unless operating under high query pressure. Quantization Techniques Product Quantization (PQ) decomposes high-dimensional vectors into smaller subvectors, quantizing each separately. This significantly reduces storage needs (often by 90%+) but introduces some accuracy loss. Scalar Quantization (SQ) converts 32-bit floats to 8-bit integers, reducing memory usage by 75% with minimal accuracy impact. On-Disk Indexing: Cost-Effective Scaling For large-scale vector collections (100M+ vectors), in-memory indexes become prohibitively expensive. For example, 100 million 1024-dimensional vectors would require approximately 400GB of RAM. This is where on-disk indexing algorithms like DiskANN provide significant cost benefits. DiskANN , based on the Vamana graph algorithm, enables efficient disk-based vector search while storing most of the index on NVMe SSDs rather than RAM. This approach offers several cost advantages: Reduced hardware costs : Organizations can deploy vector search at scale using commodity hardware with modest RAM configurations Lower operational expenses : Less RAM means lower power consumption and cooling costs in data centers Linear cost scaling : Memory costs scale linearly with data volume, while performance remains relatively stable Optimized I/O patterns : DiskANN's specialized design minimizes disk reads through careful graph traversal strategies The trade-off is typically a modest increase in query latency (often just 2-3ms) compared to purely in-memory approaches, which is acceptable for many production use cases. Specialized Index Types Binary Embedding Indexes are specialized for computer vision, image fingerprinting, and recommendation systems where data can be represented as binary features. These indexes serve different application needs. For image deduplication, digital watermarking, and copyright detection where exact matching is critical, optimized binary indexes provide precise similarity detection. For high-throughput recommendation systems, content-based image retrieval, and large-scale feature matching where speed is prioritized over perfect recall, binary indexes offer exceptional performance advantages. Sparse Vector Indexes are optimized for vectors where most elements are zero, with only a few non-zero values. Unlike dense vectors (where most or all dimensions contain meaningful values), sparse vectors efficiently represent data with many dimensions but few active features. This representation is particularly common in text processing where a document might use only a small subset of all possible words in a vocabulary. Sparse Vector Indexes excel in natural language processing tasks like semantic document search, full-text querying, and topic modeling. These indexes are particularly valuable for enterprise search across large document collections, legal document discovery where specific terms and concepts must be efficiently located, and academic research platforms indexing millions of papers with specialized terminology. Advanced Query Capabilities At the core of vector databases lies their ability to perform efficient semantic searches. Vector search capabilities range from basic similarity matching to advanced techniques for improving relevance and diversity. Basic ANN Search Approximate Nearest Neighbor (ANN) search is the foundational search method in vector databases. Unlike exact k-Nearest Neighbors (kNN) search, which compares a query vector against every vector in the database, ANN search uses indexing structures to quickly identify a subset of vectors likely to be most similar, dramatically improving performance. The key components of ANN search include: Query vectors : The vector representation of what you're searching for Index structures : Pre-built data structures that organize vectors for efficient retrieval Metric types : Mathematical functions like Euclidean (L2), Cosine, or Inner Product that measure similarity between vectors Top-K results : The specified number of most similar vectors to return Vector databases provide optimizations to improve search efficiency: Bulk vector search : Searching with multiple query vectors in parallel Partitioned search : Limiting search to specific data partitions Pagination : Using limit and offset parameters for retrieving large result sets Output field selection : Controlling which entity fields are returned with results Advanced Search Techniques Range Search Range search improves result relevancy by restricting results to vectors with similarity scores falling within a specific range. Unlike standard ANN search which returns the top-K most similar vectors, range search defines an "annular region" using: An outer boundary (radius) that sets the maximum allowable distance An inner boundary (range_filter) that can exclude vectors that are too similar This approach is particularly useful when you want to find "similar but not identical" items, such as product recommendations that are related but not exact duplicates of what a user has already viewed. Filtered Search Filtered search combines vector similarity with metadata constraints to narrow results to vectors that match specific criteria. For example, in a product catalog, you could find visually similar items but restrict results to a specific brand or price range. Highly Scalable vector databases support two filtering approaches: Standard filtering : Applies metadata filters before vector search, significantly reducing the candidate pool Iterative filtering : Performs vector search first, then applies filters to each result until reaching the desired number of matches Text Match Text match enables precise document retrieval based on specific terms, complementing vector similarity search with exact text matching capabilities. Unlike semantic search, which finds conceptually similar content, text match focuses on finding exact occurrences of query terms. For example, a product search might combine text match to find products that explicitly mention "waterproof" with vector similarity to find visually similar products, ensuring both semantic relevance and specific feature requirements are met. Grouping Search Grouping search aggregates results by a specified field to improve result diversity. For example, in a document collection where each paragraph is a separate vector, grouping ensures results come from different documents rather than multiple paragraphs from the same document. This technique is valuable for: Document retrieval systems where you want representation from different sources Recommendation systems that need to present diverse options Search systems where result diversity is as important as similarity Hybrid Search Hybrid search combines results from multiple vector fields, each potentially representing different aspects of the data or using different embedding models. This enables: Sparse-dense vector combinations : Combining semantic understanding (dense vectors) with keyword matching (sparse vectors) for more comprehensive text search Multimodal search : Finding matches across different data types, such as searching for products using both image and text inputs Hybrid search implementations use sophisticated reranking strategies to combine results: Weighted ranking : Prioritizes results from specific vector fields Reciprocal Rank Fusion : Balances results across all vector fields without specific emphasis Full-Text Search Full-text search capabilities in modern vector databases bridge the gap between traditional text search and vector similarity. These systems: Automatically convert raw text queries into sparse embeddings Retrieve documents containing specific terms or phrases Rank results based on both term relevance and semantic similarity Complement vector search by catching exact matches that semantic search might miss This hybrid approach is particularly valuable for comprehensive information retrieval systems that need both precise term matching and semantic understanding. Performance Engineering: Metrics That Matter Performance optimization in vector databases requires understanding key metrics and their tradeoffs. The Recall-Throughput Tradeoff Recall measures the proportion of true nearest neighbors found among returned results. Higher recall requires more extensive search, reducing throughput (queries per second). Production systems balance these metrics based on application requirements, typically targeting 80-99% recall depending on use case. When evaluating vector database performance, standardized benchmarking environments like ANN-Benchmarks provide valuable comparative data. These tools measure critical metrics including: Search recall: The proportion of queries for which true nearest neighbors are found among returned results Queries per second (QPS): The rate at which the database processes queries under standardized conditions Performance across different dataset sizes and dimensions An alternative is an open source benchmark system called VDB Bench . VectorDBBench is an open-source benchmarking tool designed to evaluate and compare the performance of mainstream vector databases such as Milvus and Zilliz Cloud using their own datasets. It also helps developers choose the most suitable vector database for their use cases. These benchmarks allow organizations to identify the most suitable vector database implementation for their specific requirements, considering the balance between accuracy, speed, and scalability. Memory Management Efficient memory management enables vector databases to scale to billions of vectors while maintaining performance: Dynamic allocation adjusts memory usage based on workload characteristics Caching policies retain frequently accessed vectors in memory Vector compression techniques significantly reduce memory requirements For datasets that exceed memory capacity, disk-based vector search solutions provide a crucial capability. These algorithms optimize I/O patterns for NVMe SSDs through techniques like beam search and graph-based navigation. Advanced Filtering and Hybrid Search Vector databases combine semantic similarity with traditional filtering to create powerful query capabilities: Pre-filtering applies metadata constraints before vector search, reducing the candidate set for similarity comparison Post-filtering executes vector search first, then applies filters to results Metadata indexing improves filtering performance through specialized indexes for different data types Performant vector databases support complex query patterns combining multiple vector fields with scalar constraints. Multi-vector queries find entities similar to multiple reference points simultaneously, while negative vector queries exclude vectors similar to specified examples. Scaling Vector Databases in Production Vector databases require thoughtful deployment strategies to ensure optimal performance at different scales: Small-scale deployments (millions of vectors) can operate effectively on a single machine with sufficient memory Mid-scale deployments (tens to hundreds of millions) benefit from vertical scaling with high-memory instances and SSD storage Billion-scale deployments require horizontal scaling across multiple nodes with specialized roles Sharding and replication form the foundation of scalable vector database architecture: Horizontal sharding divides collections across multiple nodes Replication creates redundant copies of data, improving both fault tolerance and query throughput Modern systems adjust replication factors dynamically based on query patterns and reliability requirements. Real-World Impact The flexibility of high performant vector databases is evident in their deployment options. Systems can run across a spectrum of environments, from lightweight installations on laptops for prototyping to massive distributed clusters managing tens of billions of vectors. This scalability has enabled organizations to move from concept to production without changing database technologies. Companies like Salesforce, PayPal, eBay, NVIDIA, IBM, and Airbnb now rely on vector databases like open source Milvus to power large-scale AI applications. These implementations span diverse use cases—from sophisticated product recommendation systems to content moderation, fraud detection, and customer support automation—all built on the foundation of vector search. In recent years, vector databases became vital in addressing the hallucination issues common in LLMs by providing domain-specific, up-to-date, or confidential data. For example, Zilliz Cloud stores specialized data as vector embeddings. When a user asks a question, it transforms the query into vectors, performs ANN searches for the most relevant results, and combines these with the original question to create a comprehensive context for the large language models. This framework serves as the foundation for developing reliable LLM-powered applications that produce more accurate and contextually relevant responses. Conclusion The rise of vector databases represents more than just a new technology—it signifies a fundamental shift in how we approach data management for AI applications. By bridging the gap between unstructured data and computational systems, vector databases have become an essential component of the modern AI infrastructure, enabling applications that understand and process information in increasingly human-like ways. The key advantages of vector databases over traditional database systems include: High-dimensional search: Efficient similarity searches on high-dimensional vectors used in machine learning and Generative AI applications Scalability: Horizontal scaling for efficient storage and retrieval of large vector collections Flexibility with hybrid search: Handling various vector data types, including sparse and dense vectors Performance: Significantly faster vector similarity searches compared to traditional databases Customizable indexing: Support for custom indexing schemes optimized for specific use cases and data types As AI applications become increasingly sophisticated, the demands on vector databases continue to evolve. Modern systems must balance performance, accuracy, scaling, and cost-effectiveness while integrating seamlessly with the broader AI ecosystem. For organizations looking to implement AI at scale, understanding vector database technology isn't just a technical consideration—it's a strategic imperative. Updated on May 07, 2025 Frank Liu Frank Liu is the Director of Operations & ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University. previous Next: Understanding Vector Databases: Compare Vector Databases, Vector Search Libraries, and Vector Search Plugins Content Introduction: The Rise of Vector Databases in the AI Era Understanding Vector Embeddings: The Foundation Vector Databases: Core Concepts Vector Database Architecture: A Technical Framework Advantages of Vector Databases Use Cases for Vector Databases Vector Search Algorithms: From Theory to Practice Advanced Query Capabilities Performance Engineering: Metrics That Matter Scaling Vector Databases in Production Real-World Impact Conclusion Start Free, Scale Easily Try the fully-managed vector database built for your GenAI applications. Try Zilliz Cloud for Free Share this article Copied Keep Reading Choosing the Right Vector Index for Your Project Understanding in-memory vector search algorithms, indexing strategies, and guidelines on choosing the right vector index for your project. Read Now Decoding Softmax Activation Function This article will discuss the Softmax Activation Function, its applications, challenges, and tips for better performance. Read Now Harnessing Product Quantization for Memory Efficiency in Vector Databases Exploring product quantization's intricacies and practical implementation through hands-on examples. 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https://dev.to/dinesh_04 | Dinesh - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account Forem Close Follow User actions Dinesh I am currently learning Game Designing and Development. I also share my learning journey on Medium site (profile link in website url). Location Chennai, India Joined Joined on Dec 27, 2025 Personal website https://medium.com/@dineshrajasekaran04 Education Monolith Research and Training labs More info about @dinesh_04 Badges 1 Week Community Wellness Streak For actively engaging with the community by posting at least 2 comments in a single week. Got it Close Writing Debut Awarded for writing and sharing your first DEV post! Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close Currently learning Game Designing and Development Post 17 posts published Comment 3 comments written Tag 0 tags followed How Speed Finally Made My Character Feel Alive Dinesh Dinesh Dinesh Follow Jan 12 How Speed Finally Made My Character Feel Alive # gamedev # unrealengine # beginners # animation Comments Add Comment 2 min read Want to connect with Dinesh? Create an account to connect with Dinesh. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in Why My First Animation Blueprint Didn’t Work in Unreal Engine Dinesh Dinesh Dinesh Follow Jan 11 Why My First Animation Blueprint Didn’t Work in Unreal Engine # gamedev # unrealengine # beginners # animation Comments Add Comment 2 min read How I Turned a Static Character into a Moving One in Unreal Engine Dinesh Dinesh Dinesh Follow Jan 10 How I Turned a Static Character into a Moving One in Unreal Engine # gamedev # unrealengine # beginners # animation Comments Add Comment 2 min read Creating Materials in Unreal Engine 5 and Understanding ORM Textures (Day 14) Dinesh Dinesh Dinesh Follow Jan 9 Creating Materials in Unreal Engine 5 and Understanding ORM Textures (Day 14) # gamedev # unrealengine # beginners # learning Comments Add Comment 2 min read Learning the Foliage Tool in Unreal Engine (Day 13) Dinesh Dinesh Dinesh Follow Jan 8 Learning the Foliage Tool in Unreal Engine (Day 13) # gamedev # unrealengine # beginners # learning Comments Add Comment 2 min read Learning Landscape Heightmaps and Sculpting Tools in Unreal Engine (Day 12) Dinesh Dinesh Dinesh Follow Jan 7 Learning Landscape Heightmaps and Sculpting Tools in Unreal Engine (Day 12) # gamedev # unrealengine # beginners # learning Comments Add Comment 2 min read Actor Panel and Landscape Tool Basics in Unreal Engine (Day 11) Dinesh Dinesh Dinesh Follow Jan 6 Actor Panel and Landscape Tool Basics in Unreal Engine (Day 11) # gamedev # unrealengine # beginners # learning Comments Add Comment 2 min read Understanding Starter Content and Selection Mode in Unreal Engine (Day 10) Dinesh Dinesh Dinesh Follow Jan 5 Understanding Starter Content and Selection Mode in Unreal Engine (Day 10) # beginners # devjournal # gamedev Comments Add Comment 2 min read 🎮 Learning Game Development – Day 9 Dinesh Dinesh Dinesh Follow Jan 4 🎮 Learning Game Development – Day 9 # gamedev # cpp # webdev # beginners Comments Add Comment 2 min read 🎮 Learning Game Development – Day 8 Dinesh Dinesh Dinesh Follow Jan 3 🎮 Learning Game Development – Day 8 # gamedev # software # cpp # gamechallenge Comments Add Comment 2 min read 🎮 Learning Game Development – Day 7 Dinesh Dinesh Dinesh Follow Jan 2 🎮 Learning Game Development – Day 7 # gamedev # developer # programming # godotengine Comments Add Comment 2 min read I thought materials in Unreal Engine were just about colors. I was wrong. They’re more about logic than visuals. Dinesh Dinesh Dinesh Follow Jan 1 I thought materials in Unreal Engine were just about colors. I was wrong. They’re more about logic than visuals. # gamedev # computerscience # resources # gamechallenge Comments 4 comments 2 min read 🎮 Learning Game Development – Day 5 Basics of Color Theory Dinesh Dinesh Dinesh Follow Dec 31 '25 🎮 Learning Game Development – Day 5 Basics of Color Theory # gamedev # devplusplus # beginners # design Comments Add Comment 2 min read 🎮 Learning Game Development – Day 4 Dinesh Dinesh Dinesh Follow Dec 30 '25 🎮 Learning Game Development – Day 4 # webdev # cpp # gamedev # devops Comments 2 comments 2 min read 🎮 Day 3 – Understanding GDD (Game Design Document) Dinesh Dinesh Dinesh Follow Dec 29 '25 🎮 Day 3 – Understanding GDD (Game Design Document) # design # documentation # opensource # gamedev Comments Add Comment 1 min read 🎮 Day 2 – Foundation for Game Designers Dinesh Dinesh Dinesh Follow Dec 28 '25 🎮 Day 2 – Foundation for Game Designers # design # gamedev # computerscience # gamechallenge Comments Add Comment 1 min read 🕹️ Game Designer or Game Developer? Don’t Decide Too Early Dinesh Dinesh Dinesh Follow Dec 27 '25 🕹️ Game Designer or Game Developer? Don’t Decide Too Early # beginners # gamedev # gamechallenge # design Comments Add Comment 1 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Forem — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . Forem © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close # development Follow Hide Tracking and discussing physical and cognitive milestones. Create Post Older #development posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Stop Fighting Context Limits: How Multi-Agent Systems Solved My Development Chaos(Part 1) Nour Mohamed Amine Nour Mohamed Amine Nour Mohamed Amine Follow Dec 28 '25 Stop Fighting Context Limits: How Multi-Agent Systems Solved My Development Chaos(Part 1) # architecture # development # productivity # ai Comments Add Comment 6 min read Why Developers Struggle With Social Media Data (And How I’m Fixing It) ImbueData ImbueData ImbueData Follow Dec 27 '25 Why Developers Struggle With Social Media Data (And How I’m Fixing It) # api # webdev # saas # development Comments Add Comment 2 min read THE MORTUARY ASSISTANT: How One Developer Made a Career Out of Embalming Haunted Corpses Faisal Mujahid Faisal Mujahid Faisal Mujahid Follow Dec 27 '25 THE MORTUARY ASSISTANT: How One Developer Made a Career Out of Embalming Haunted Corpses # gamedev # gamechallenge # programming # development Comments Add Comment 1 min read No Install, No Sign-up, No Bloat: The Instant Issue Tracker for Busy Devs techno kraft techno kraft techno kraft Follow Dec 27 '25 No Install, No Sign-up, No Bloat: The Instant Issue Tracker for Busy Devs # showdev # development # webdev # programming 1 reaction Comments Add Comment 2 min read Future Trends in Wearable Tech: What Developers Should Expect Lucas Wade Lucas Wade Lucas Wade Follow Dec 26 '25 Future Trends in Wearable Tech: What Developers Should Expect # wearableappdevelopment # development # programming # ai Comments Add Comment 4 min read How to Scrape Any Website Using Bright Data MCP Server and AI Agents oteri oteri oteri Follow Jan 9 How to Scrape Any Website Using Bright Data MCP Server and AI Agents # python # ai # development # opensource 7 reactions Comments Add Comment 2 min read Day 33 of improving my Data Science skills🎄 Sylvester Promise Sylvester Promise Sylvester Promise Follow Dec 25 '25 Day 33 of improving my Data Science skills🎄 # development # tooling # datascience # machinelearning Comments Add Comment 2 min read Pinning GitHub Actions for Reproducibility and Security Cloud Native Engineer Cloud Native Engineer Cloud Native Engineer Follow Dec 26 '25 Pinning GitHub Actions for Reproducibility and Security # development # devops # programming # beginners Comments Add Comment 1 min read Devoting December to developer enrichment Shipyard DevRel Shipyard DevRel Shipyard DevRel Follow Dec 22 '25 Devoting December to developer enrichment # learning # productivity # programming # development 2 reactions Comments Add Comment 4 min read Development Workflow: Why Most Teams Fail (And How to Fix It) CodeCraft Diary CodeCraft Diary CodeCraft Diary Follow Dec 23 '25 Development Workflow: Why Most Teams Fail (And How to Fix It) # programming # webdev # development # software Comments Add Comment 5 min read Build in Public: Week 8. We Finally Deployed This Thing Olga Braginskaya Olga Braginskaya Olga Braginskaya Follow Jan 8 Build in Public: Week 8. We Finally Deployed This Thing # ai # buildinpublic # development # saas 28 reactions Comments 6 comments 6 min read Visual Studio 2026: How AI Is Transforming the Way Developers Code Phinter Atieno Phinter Atieno Phinter Atieno Follow for Syncfusion, Inc. Dec 24 '25 Visual Studio 2026: How AI Is Transforming the Way Developers Code # syncfusion # development # githubcopilot # visualstudio Comments Add Comment 9 min read Tech Trading | Mobile Developer & NSE Trader Dilip Kumar (DK) Dilip Kumar (DK) Dilip Kumar (DK) Follow Dec 23 '25 Tech Trading | Mobile Developer & NSE Trader # firebase # mobileapp # development # sentiment Comments Add Comment 2 min read Mobile Supply Chain Security: SBOM and Dependency Risk for App Teams M Sikandar M Sikandar M Sikandar Follow Dec 22 '25 Mobile Supply Chain Security: SBOM and Dependency Risk for App Teams # edtec # ai # learning # development Comments Add Comment 5 min read Why Good API Documentation Feels Invisible (Until It’s Missing) Surhid Amatya Surhid Amatya Surhid Amatya Follow Dec 25 '25 Why Good API Documentation Feels Invisible (Until It’s Missing) # webdev # programming # development Comments Add Comment 3 min read I Saw an Instagram Reel Last Night. Now I Built a Bionic Reading Extension. 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Now I Built a Bionic Reading Extension. # extensions # programming # development # tooling 6 reactions Comments 4 comments 3 min read What does it mean to be a “Technical” Product Manager in the AI era? bfuller bfuller bfuller Follow Jan 6 What does it mean to be a “Technical” Product Manager in the AI era? # product # ai # development # devops 8 reactions Comments Add Comment 3 min read 🚀 A Wake-Up Call for Developers: Don’t Just Build — Publish Your Ideas to the Linux Ecosystem BHUVANESH M BHUVANESH M BHUVANESH M Follow Dec 31 '25 🚀 A Wake-Up Call for Developers: Don’t Just Build — Publish Your Ideas to the Linux Ecosystem # setbian # linux # development # code 2 reactions Comments Add Comment 2 min read MVC View-First vs MVP: An Architectural Comparison Elanat Framework Elanat Framework Elanat Framework Follow Dec 16 '25 MVC View-First vs MVP: An Architectural Comparison # mvc # architecture # development # dotnet Comments Add Comment 3 min read Zero-Release Mobile Architecture: The Path Every Server-Driven UI Takes Digia Digia Digia Follow Dec 16 '25 Zero-Release Mobile Architecture: The Path Every Server-Driven UI Takes # development # serverdrivenui # zerorelease # productivity Comments Add Comment 9 min read MongoDB Document Model and CRUD in Practice James Miller James Miller James Miller Follow Dec 15 '25 MongoDB Document Model and CRUD in Practice # mongodb # database # development 1 reaction Comments Add Comment 5 min read Experiences using AI codegen tools like Lovable or Base44? 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Right menu How Speed Finally Made My Character Feel Alive Dinesh Dinesh Dinesh Follow Jan 12 How Speed Finally Made My Character Feel Alive # gamedev # unrealengine # beginners # animation Comments Add Comment 2 min read Unlocking the Power of Inheritance in Python Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 12 Unlocking the Power of Inheritance in Python # beginners # programming # python # tutorial Comments Add Comment 2 min read **More Than a Bootcamp: Why I Chose the German 'Umschulung' Path into Tech** Ali-Funk Ali-Funk Ali-Funk Follow Jan 11 **More Than a Bootcamp: Why I Chose the German 'Umschulung' Path into Tech** # watercooler # career # devops # beginners Comments Add Comment 3 min read EU Digital Omnibus: New Requirements for Websites and Online Services Mehwish Malik Mehwish Malik Mehwish Malik Follow Jan 12 EU Digital Omnibus: New Requirements for Websites and Online Services # webdev # ai # beginners # productivity 17 reactions Comments Add Comment 3 min read Who is Krishna Mohan Kumar? | Full Stack Developer & B.Tech CSE Student Krishna Mohan Kumar Krishna Mohan Kumar Krishna Mohan Kumar Follow Jan 12 Who is Krishna Mohan Kumar? | Full Stack Developer & B.Tech CSE Student # webdev # beginners # portfolio # google Comments Add Comment 1 min read Sharing: How to Build Competitiveness and Soft Skills, and Write a Good Resume Evan Lin Evan Lin Evan Lin Follow Jan 11 Sharing: How to Build Competitiveness and Soft Skills, and Write a Good Resume # learning # beginners # writing # career Comments Add Comment 9 min read Sharing a Talk: "How to Build Your Own Open Source Project" Evan Lin Evan Lin Evan Lin Follow Jan 11 Sharing a Talk: "How to Build Your Own Open Source Project" # beginners # opensource # softwaredevelopment Comments Add Comment 7 min read Sharing: "How to Build Your Own Open Source Project" Evan Lin Evan Lin Evan Lin Follow Jan 11 Sharing: "How to Build Your Own Open Source Project" # beginners # opensource # tutorial Comments Add Comment 11 min read Singleton vs Observer Pattern: When and Why to Use Each Arun Teja Arun Teja Arun Teja Follow Jan 11 Singleton vs Observer Pattern: When and Why to Use Each # architecture # beginners # javascript Comments Add Comment 3 min read Singleton vs Observer Pattern: When and Why to Use Each Arun Teja Arun Teja Arun Teja Follow Jan 11 Singleton vs Observer Pattern: When and Why to Use Each # architecture # beginners # javascript Comments Add Comment 3 min read Observer Pattern Explained Simply With JavaScript Examples Arun Teja Arun Teja Arun Teja Follow Jan 11 Observer Pattern Explained Simply With JavaScript Examples # designpatterns # javascript # beginners # programming Comments Add Comment 3 min read The Non-Drinker's Guide to Clustering Algorithms 🎉 Seenivasa Ramadurai Seenivasa Ramadurai Seenivasa Ramadurai Follow Jan 11 The Non-Drinker's Guide to Clustering Algorithms 🎉 # algorithms # beginners # datascience # machinelearning Comments Add Comment 2 min read My First Beginner Projects Vivash Kshitiz Vivash Kshitiz Vivash Kshitiz Follow Jan 12 My First Beginner Projects # discuss # beginners # python # learning Comments Add Comment 1 min read Accounting 101: Learn how to build financial applications Favor Onuoha Favor Onuoha Favor Onuoha Follow Jan 11 Accounting 101: Learn how to build financial applications # beginners # fintech Comments Add Comment 10 min read Sitemaps & robots.txt: The Secret to Faster, Smarter Scraping Muhammad Ikramullah Khan Muhammad Ikramullah Khan Muhammad Ikramullah Khan Follow Jan 11 Sitemaps & robots.txt: The Secret to Faster, Smarter Scraping # webdev # programming # python # beginners Comments Add Comment 10 min read [TIL][Android] Common Android Studio Project Opening Issues Evan Lin Evan Lin Evan Lin Follow Jan 11 [TIL][Android] Common Android Studio Project Opening Issues # help # beginners # android # kotlin Comments Add Comment 2 min read APCSCamp 2021: How to Learn Programming and Intern at LINE Evan Lin Evan Lin Evan Lin Follow Jan 11 APCSCamp 2021: How to Learn Programming and Intern at LINE # learning # beginners # career # programming Comments Add Comment 10 min read LINE Platform and Messaging API Introduction - 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Report Abuse Dinesh Posted on Jan 12 How Speed Finally Made My Character Feel Alive # gamedev # unrealengine # beginners # animation Game Designing and Development (9 Part Series) 1 🎮 Learning Game Development – Day 4 2 Understanding Starter Content and Selection Mode in Unreal Engine (Day 10) ... 5 more parts... 3 Actor Panel and Landscape Tool Basics in Unreal Engine (Day 11) 4 Learning Landscape Heightmaps and Sculpting Tools in Unreal Engine (Day 12) 5 Learning the Foliage Tool in Unreal Engine (Day 13) 6 Creating Materials in Unreal Engine 5 and Understanding ORM Textures (Day 14) 7 How I Turned a Static Character into a Moving One in Unreal Engine 8 Why My First Animation Blueprint Didn’t Work in Unreal Engine 9 How Speed Finally Made My Character Feel Alive My character was moving… but it felt wrong. Walking and running looked the same. Speed was the missing piece. This post is part of my daily learning journey in game development. I’m sharing what I learn each day — the basics, the confusion, and the real progress — from the perspective of a beginner. On Day 17 of my game development journey, I learned about Blend Spaces and basic movement logic in Unreal Engine. What I tried / learned today I created a Blend Space 1D for my character using a Speed parameter. I set a reasonable speed range so it matches natural movement: Idle at 0 Walk at a mid value Run at the max value Then I connected the Blend Space inside the Idle/Walk/Run state in the Animation Blueprint. To drive the Blend Space, I calculated speed using: Character movement velocity Vector length That value controlled how the animations blended smoothly. What confused me At first, the animation changes didn’t feel natural. I didn’t understand why walking and running looked almost the same. What worked or finally clicked Once I matched the movement speed values with the animation speeds, everything felt right. Matching animation speed with movement speed was the key . In the Character Blueprint, I added simple logic: Normal speed for walking Increased speed while holding Shift This made walking and running feel intentional and different. One lesson for beginners Blend Spaces depend on correct speed values Movement logic and animation must match Small tweaks create big improvements Slow progress — but I’m building a strong foundation. If you’re also learning game development, what was the first thing that confused you when you started? See you in the next post 🎮🚀 Game Designing and Development (9 Part Series) 1 🎮 Learning Game Development – Day 4 2 Understanding Starter Content and Selection Mode in Unreal Engine (Day 10) ... 5 more parts... 3 Actor Panel and Landscape Tool Basics in Unreal Engine (Day 11) 4 Learning Landscape Heightmaps and Sculpting Tools in Unreal Engine (Day 12) 5 Learning the Foliage Tool in Unreal Engine (Day 13) 6 Creating Materials in Unreal Engine 5 and Understanding ORM Textures (Day 14) 7 How I Turned a Static Character into a Moving One in Unreal Engine 8 Why My First Animation Blueprint Didn’t Work in Unreal Engine 9 How Speed Finally Made My Character Feel Alive Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Dinesh Follow I am currently learning Game Designing and Development. I also share my learning journey on Medium site (profile link in website url). Location Chennai, India Education Monolith Research and Training labs Joined Dec 27, 2025 More from Dinesh Why My First Animation Blueprint Didn’t Work in Unreal Engine # gamedev # unrealengine # beginners # animation How I Turned a Static Character into a Moving One in Unreal Engine # gamedev # unrealengine # beginners # animation Creating Materials in Unreal Engine 5 and Understanding ORM Textures (Day 14) # gamedev # unrealengine # beginners # learning 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:44 |
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https://docs.suprsend.com/docs/ios-preferences | Preferences - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection Developer Resources Overview Updates and Versioning Versioning and Support Policy SDK Changelog Authentication API Keys and Secrets Service Token Best Practices for Key & Token Management MCP Overview BETA Quickstart Tool List Building with LLMs Security Security SDKs and APIs SDKs SDK Overview SuprSend Backend SDK SuprSend Client SDK Authentication Javascript Android iOS Integration Events and User methods APNS Push Integration Preferences React Native Flutter React Management API REST API Postman Collection Features Validate Trigger Payload Type Safety Testing Testing the Template Test Mode Monitoring and Logging Logs Data Out Contact Us Get Started SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Ask AI Contact Us Get Started Get Started Search... Navigation iOS Preferences Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog iOS Preferences OpenAI Open in ChatGPT Preferences in your iOS application OpenAI Open in ChatGPT Pre-Requisites Integration of iOS SDK Configure notification categories on SuprSend dashboard Understanding preference structure This is how a typical preference page will look like: Preference Page contains 2 sections: Category-level preference settings (Sections) Sections Categories Category Channel Overall Channel-level preference Preferences data structure Preferences Types Example Copy Ask AI struct PreferenceData : Codable { var sections: [Section] ? var channelPreferences: [ChannelPreference] ? enum CodingKeys : String , CodingKey { case sections case channelPreferences = "channel_preferences" } } struct ChannelPreference : Codable { var channel: String var isRestricted: Bool enum CodingKeys : String , CodingKey { case channel case isRestricted = "is_restricted" } } struct Section : Codable { var name: String ? var description: String ? var subcategories: [Category] ? } struct Category : Codable { var name: String var category: String var description: String ? var preference: PreferenceOptions var isEditable: Bool var channels: [CategoryChannel] ? enum CodingKeys : String , CodingKey { case name case category case description case preference case isEditable = "is_editable" case channels } } struct CategoryChannel : Codable { var channel: String var preference: PreferenceOptions var isEditable: Bool enum CodingKeys : String , CodingKey { case channel case preference case isEditable = "is_editable" } } enum PreferenceOptions : String , Codable { case optIn = "opt_in" case optOut = "opt_out" } enum ChannelLevelPreferenceOptions : String , Codable { case all = "all" case required = "required" } 1.1 Sections This contains the name, description, and subcategories. We have to loop through the sections list and for every section item if there is a name and description present, then show the heading, and if a subcategories list is present, loop through that subcategories list and show all subcategories under that section heading. Subcategories can exist without sections as the section is an optional field. In that case, the section’s name will not be available. For sections where the name is not present, you can directly show its subcategories list without showing Heading for the section in UI. syntax Copy Ask AI struct Section : Codable { var name: String ? var description: String ? var subcategories: [Category] ? } Property Description name name of the section description description of the section subcategories data of all sub-categories to be shown inside the section 1.2 Categories (sections -> sub-categories) This is the place where the user sets his category-level preferences. While looping through the subcategories list for every subcategory item, show the name and description in UI. syntax Copy Ask AI struct Category : Codable { var name: String var category: String var description: String ? var preference: PreferenceOptions var isEditable: Bool var channels: [CategoryChannel] ? enum CodingKeys : String , CodingKey { case name case category case description case preference case isEditable = "is_editable" case channels } } Property Description category This key is the id of the category which is used while updating the preference. name name of the category to be shown on the UI description description of the category to be shown on the UI preference This key indicates if the category’s preference switch is on or off. Get OPT_IN when the switch is on and OPT_OUT when the switch is off is_editable Indicates if the preference switch button is disabled or not. If its value is false then the preference setting for that category can’t be edited channels data of all category channels to be shown below the sub-category. Loop through it to show checkboxes under every subcategory item. 1.3 Category channels (sections -> sub-categories -> channels) This contains a list of channels, channel preference status and whether it’s editable or not. While looping through the subcategory list for every subcategory item we have to loop through its channels list and for every channel to show channel level checkbox. syntax Copy Ask AI struct CategoryChannel : Codable { var channel: String var preference: PreferenceOptions var isEditable: Bool enum CodingKeys : String , CodingKey { case channel case preference case isEditable = "is_editable" } } Property Description channel name of the channel to be shown on UI. The same key will be used as id of the channel while updating the preference. preference This key indicates if the channel’s preference switch is on or off. Get OPT_IN when the switch is on and OPT_OUT when the switch is off is_editable Indicates if the preference checkbox is disabled or not. If its value is false then the preference setting for that channel can’t be edited 2. Overall channel preferences It’s a list of all channel-level preferences. We have to loop through the list and for each item, show the UI as given in the below image. syntax Copy Ask AI struct ChannelPreference : Codable { var channel: String var isRestricted: Bool enum CodingKeys : String , CodingKey { case channel case isRestricted = "is_restricted" } } Property Description channel name of the channel to be shown on UI. The same key will be used as id of the channel while updating the preference. is_restricted This key indicates the restriction level of channel. If restricted, notification will only be sent in the category where this channel is added as mandatory in notification category settings. True means Required radio button is selected. False means All radio button is selected. Integration Get preferences data Use this method to get preferences data and create the preferences UI by following the above sections. This method should be called first before any update preference methods. syntax Copy Ask AI await SuprSend. shared . preferences . getPreferences ( args : Preferences. Args ( tenantId : "" )) Returns: async -> PreferenceAPIResponse Update channel preference in category Calling this method will opt-in/opt-out users from that category-level channel. When the category’s channel checkbox is editable and the user clicks on the checkbox you can call this method. syntax Copy Ask AI await SuprSend. shared . preferences . updateChannelPreferenceInCategory ( channel : "channel" , preference : PreferenceOptions, category : "category" ) enum PreferenceOptions : String , Codable { case optIn = "opt_in" case optOut = "opt_out" } Returns: async -> PreferenceAPIResponse Update category preference This is category level preference changing method. Calling this method will opt-in/opt-out user from that category. When the category is editable and the switch is toggled you can call this method. syntax Copy Ask AI await SuprSend. shared . preferences . updateCategoryPreference ( category : "category_value" , preference : PreferenceOptions) enum PreferenceOptions : String , Codable { case optIn = "opt_in" case optOut = "opt_out" } Returns: async -> PreferenceAPIResponse Update overall channel preference This method updated the channel-level preference of the user. syntax Copy Ask AI await SuprSend. shared . preferences . updateOverallChannelPreference ( channel : "channel" , preference : ChannelLevelPreferenceOptions ) enum ChannelLevelPreferenceOptions : String , Codable { case all = "all" case required = "required" } Returns: async -> PreferenceAPIResponse Event listeners All preferences update api’s are optimistic updates. Actual API call will happen in background with 1 second debounce. Since its a background task SDK provides event listeners to get updated preference data based on API call status. Listen to this event listeners and update the UI accordingly. syntax Copy Ask AI SuprSend. shared . emitter . on (. preferencesUpdated ) { data in // update local store so that UI is updated with latest data } SuprSend. shared . emitter . on (. preferencesError ) { error in // show error toast to user } Example Preferences UI example code: PreferencesView.swift and PreferenceModel.swift Was this page helpful? Yes No Suggest edits Raise issue Previous Android Integration This document will cover integration steps for Android side of your ReactNative application. Next ⌘ I x github linkedin youtube Powered by On this page Pre-Requisites Understanding preference structure Preferences data structure 1.1 Sections 1.2 Categories (sections -> sub-categories) 1.3 Category channels (sections -> sub-categories -> channels) 2. Overall channel preferences Integration Get preferences data Update channel preference in category Update category preference Update overall channel preference Event listeners Example | 2026-01-13T08:48:44 |
https://ko.react.dev/ | React React v 19.2 검색 ⌘ Ctrl K 학습하기 API 참고서 커뮤니티 블로그 React 웹 및 네이티브 사용자 인터페이스를 위한 라이브러리 React 학습하기 API 참고서 React v18 한글 컴포넌트를 사용하여 사용자 인터페이스 만들기 React를 사용하면 컴포넌트라 불리는 조각들을 사용하여 사용자 인터페이스를 만들 수 있습니다. Thumbnail , LikeButton , 그리고 Video 같은 컴포넌트를 만들어 보세요. 그런 다음 전체 화면, 페이지 및 앱에서 이들을 결합할 수 있습니다. Video.js function Video ( { video } ) { return ( < div > < Thumbnail video = { video } /> < a href = { video . url } > < h3 > { video . title } </ h3 > < p > { video . description } </ p > </ a > < LikeButton video = { video } /> </ div > ) ; } My video Video description 혼자서 작업하든, 수천 명의 다른 개발자와 함께 작업하든, React를 사용하는 느낌은 동일합니다. 개인, 팀, 조직에서 작성한 컴포넌트를 원활하게 결합할 수 있도록 설계하였습니다. 코드와 마크업으로 컴포넌트 작성하기 React 컴포넌트는 자바스크립트 함수입니다. 조건부로 내용을 표시하려면 if 문을 사용할 수 있습니다. 목록을 표시하려면 배열에 map() 을 사용할 수 있습니다. React를 배우는 것은 프로그래밍을 배우는 것입니다. VideoList.js function VideoList ( { videos , emptyHeading } ) { const count = videos . length ; let heading = emptyHeading ; if ( count > 0 ) { const noun = count > 1 ? 'Videos' : 'Video' ; heading = count + ' ' + noun ; } return ( < section > < h2 > { heading } </ h2 > { videos . map ( video => < Video key = { video . id } video = { video } /> ) } </ section > ) ; } 3 Videos First video Video description Second video Video description Third video Video description 이 마크업 구문을 JSX라 부릅니다. 이것은 React에 의해서 대중화된 자바스크립트 구문의 확장입니다. JSX 마크업을 관련된 렌더링 로직과 가까이 두면, React 컴포넌트를 쉽게 만들고 관리하고 삭제할 수 있습니다. 필요한 곳에 상호작용 요소 추가하기 React 컴포넌트는 데이터를 받고 화면에 표시할 내용을 반환합니다. 사용자가 입력란에 입력하는 것과 같이 상호작용에 응답하여 새 데이터를 전달할 수 있습니다. 그런 다음 React는 새 데이터와 일치하도록 화면을 업데이트합니다. SearchableVideoList.js import { useState } from 'react' ; function SearchableVideoList ( { videos } ) { const [ searchText , setSearchText ] = useState ( '' ) ; const foundVideos = filterVideos ( videos , searchText ) ; return ( < > < SearchInput value = { searchText } onChange = { newText => setSearchText ( newText ) } /> < VideoList videos = { foundVideos } emptyHeading = { `No matches for “ ${ searchText } ”` } /> </ > ) ; } example.com / videos.html React Videos A brief history of React Search 5 Videos React: The Documentary The origin story of React Rethinking Best Practices Pete Hunt (2013) Introducing React Native Tom Occhino (2015) Introducing React Hooks Sophie Alpert and Dan Abramov (2018) Introducing Server Components Dan Abramov and Lauren Tan (2020) 전체 페이지를 React로 빌드할 필요는 없습니다. React를 기존 HTML 페이지에 추가하고, 페이지 어디에서나 상호작용하는 React 컴포넌트를 렌더링할 수 있습니다. 페이지에 React 추가하기 프레임워크를 통해 풀스택으로 만들기 React는 라이브러리입니다. 컴포넌트를 조합할 수 있도록 도와주지만, 라우팅이나 데이터를 가져오는 방법을 규정하지는 않습니다. React로 완전한 앱을 만들려면, Next.js 또는 React Router 같은 풀스택 React 프레임워크를 추천합니다. confs/[slug].js import { db } from './database.js' ; import { Suspense } from 'react' ; async function ConferencePage ( { slug } ) { const conf = await db . Confs . find ( { slug } ) ; return ( < ConferenceLayout conf = { conf } > < Suspense fallback = { < TalksLoading /> } > < Talks confId = { conf . id } /> </ Suspense > </ ConferenceLayout > ) ; } async function Talks ( { confId } ) { const talks = await db . Talks . findAll ( { confId } ) ; const videos = talks . map ( talk => talk . video ) ; return < SearchableVideoList videos = { videos } /> ; } example.com / confs/react-conf-2021 React Conf 2021 React Conf 2019 Search 19 Videos React Conf React 18 Keynote The React Team React Conf React 18 for App Developers Shruti Kapoor React Conf Streaming Server Rendering with Suspense Shaundai Person React Conf The First React Working Group Aakansha Doshi React Conf React Developer Tooling Brian Vaughn React Conf React without memo Xuan Huang (黄玄) React Conf React Docs Keynote Rachel Nabors React Conf Things I Learnt from the New React Docs Debbie O'Brien React Conf Learning in the Browser Sarah Rainsberger React Conf The ROI of Designing with React Linton Ye React Conf Interactive Playgrounds with React Delba de Oliveira React Conf Re-introducing Relay Robert Balicki React Conf React Native Desktop Eric Rozell and Steven Moyes React Conf On-device Machine Learning for React Native Roman Rädle React Conf React 18 for External Store Libraries Daishi Kato React Conf Building Accessible Components with React 18 Diego Haz React Conf Accessible Japanese Form Components with React Tafu Nakazaki React Conf UI Tools for Artists Lyle Troxell React Conf Hydrogen + React 18 Helen Lin React는 아키텍처이기도 합니다. 이를 구현하는 프레임워크는 서버에서 실행되는 비동기 컴포넌트 혹은 빌드 중에 실행되는 비동기 컴포넌트에서 데이터를 가져올 수 있도록 합니다. 파일이나 데이터베이스에서 데이터를 읽고, 이를 상호작용하는 컴포넌트에 전달할 수 있습니다. 프레임워크로 시작하기 모든 플랫폼에서 사용하기 사람들은 다양한 이유로 웹과 네이티브 앱을 좋아합니다. React는 동일한 기술을 사용하여 웹 앱과 네이티브 앱을 모두 만들 수 있습니다. 각 플랫폼의 장점을 활용하여 모든 플랫폼에서 적합한 인터페이스를 구현할 수 있습니다. example.com 웹에 충실하기 사람들은 웹 앱이 빠르게 로드되길 기대합니다. 서버에서 React를 사용하면 데이터를 가져오는 동안 HTML을 스트리밍하여 자바스크립트 코드가 로드되기 전에 남은 내용을 점진적으로 채울 수 있습니다. 클라이언트에서 React는 표준 웹 API를 사용하여 렌더링 중에도 UI가 반응하도록 유지할 수 있습니다. 7:34 AM 진정한 네이티브에서 사용하기 사람들은 네이티브 Native 앱이 해당 플랫폼의 모습과 느낌을 갖기를 기대합니다. React Native 와 Expo 를 사용하면 React를 통해 Android, iOS 등을 위한 앱을 빌드할 수 있습니다. UI가 진정한 네이티브이기 때문에 네이티브처럼 보이고 느껴집니다. 이것은 웹 뷰 Web View 가 아닙니다. React 컴포넌트들은 실제 Android, iOS 플랫폼에서 제공하는 뷰 View 를 렌더링합니다. React를 사용하면 웹 및 네이티브 개발자가 될 수 있습니다. 사용자 경험의 저하 없이 여러 플랫폼에 출시할 수 있습니다. 조직에서는 플랫폼 간의 격차를 줄이고, 기능을 완전히 소유하는 팀을 구성할 수 있습니다. 네이티브 플랫폼에서 React 사용하기 새로운 기능에 맞춰 업그레이드 하기 React는 변화에 신중하게 접근합니다. 모든 React 커밋은 10억명 이상의 사용자가 있는 비즈니스의 크리티컬한 영역에서 테스트를 진행합니다. Meta에서는 10만 개 이상의 React 컴포넌트가 모든 마이그레이션 전략을 검증합니다. React 팀은 항상 React를 개선하는 방법을 연구합니다. 몇 년이 걸리는 연구도 있습니다. React는 연구 아이디어를 제품에 적용하는 데에 높은 기준을 가지고 있습니다. 검증된 접근 방식만이 React 일부가 됩니다. 더 많은 React 뉴스 읽기 최신 React 뉴스 React Conf 2025 요약 2025.10.16 React 컴파일러 v1.0 2025.10.08 React Foundation 소개 2025.10.07 React 19.2 2025.10.01 React 뉴스 더 보기 수백만 명이 있는 커뮤니티 여러분은 혼자가 아닙니다. 전세계의 200만 명이 넘는 개발자들이 React 문서를 매달 방문합니다. React는 사람들과 팀이 동의할 수 있는 것입니다. 이것이 바로 React가 단순한 라이브러리, 아키텍처, 혹은 생태계 그 이상인 이유입니다. React는 바로 커뮤니티입니다. 도움을 요청하고, 기회를 찾고, 새로운 친구를 만날 수 있는 곳입니다. 개발자와 디자이너, 초보자와 전문가, 연구원과 예술가, 교사와 학생을 만날 수 있습니다. 배경은 모두 다를 수 있지만, React를 통해 함께 사용자 인터페이스를 만들 수 있습니다. React 커뮤니티에 오신 것을 환영합니다 시작하기 Copyright © Meta Platforms, Inc no uwu plz uwu? Logo by @sawaratsuki1004 React 학습하기 빠르게 시작하기 설치하기 UI 표현하기 상호작용성 더하기 State 관리하기 탈출구 API 참고서 React APIs React DOM APIs 커뮤니티 행동 강령 팀 소개 문서 기여자 감사의 말 더 보기 블로그 React Native 개인 정보 보호 약관 | 2026-01-13T08:48:44 |
https://highlight.io/docs | Welcome to highlight.io Star us on GitHub Star Docs Sign in Sign up General Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. 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Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Welcome to highlight.io Welcome to highlight.io Highlight has been acquired by LaunchDarkly ! Want to know more about our plans for the future? Read the press release . This docs site is no longer being updated. Instead, check out the LaunchDarkly observability docs . highlight.io is monitoring software for the next generation of developers. And it's all open source :). Get Started Get started with highlight.io. Instrument your frontend & backend. Our product highlight.io gives you fullstack visibility into your application by pairing session replay, error monitoring, and logging, allowing you to tie frontend issues with backend logs and performance issues. When highlight.io is fully integrated, this is what it looks like: About us Mission & Values. Details about our company, our values, and open source. Compliance & Security. Our security certificates, and contact details. Contributing to highlight.io Open source, self hosting highlight, and contributing. Self hosting highlight.io Open source, self hosting highlight, and contributing. Features Session Replay. Session replay features, how to get started, etc.. Error Monitoring. Error monitoring features, how to get started, etc.. Logging. Logging features, how to get started, etc.. Tracing. Tracing features, how to get started, etc.. Highlight Docs Get Started Overview Community / Support Suggest Edits? Follow us! [object Object] | 2026-01-13T08:48:44 |
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https://docs.python.org/3/reference/compound_stmts.html#while | 8. Compound statements — Python 3.14.2 documentation Theme Auto Light Dark Table of Contents 8. Compound statements 8.1. The if statement 8.2. The while statement 8.3. The for statement 8.4. The try statement 8.4.1. except clause 8.4.2. except* clause 8.4.3. else clause 8.4.4. finally clause 8.5. The with statement 8.6. The match statement 8.6.1. Overview 8.6.2. Guards 8.6.3. Irrefutable Case Blocks 8.6.4. Patterns 8.6.4.1. OR Patterns 8.6.4.2. AS Patterns 8.6.4.3. Literal Patterns 8.6.4.4. Capture Patterns 8.6.4.5. Wildcard Patterns 8.6.4.6. Value Patterns 8.6.4.7. Group Patterns 8.6.4.8. Sequence Patterns 8.6.4.9. Mapping Patterns 8.6.4.10. Class Patterns 8.7. Function definitions 8.8. Class definitions 8.9. Coroutines 8.9.1. Coroutine function definition 8.9.2. The async for statement 8.9.3. The async with statement 8.10. Type parameter lists 8.10.1. Generic functions 8.10.2. Generic classes 8.10.3. Generic type aliases 8.11. Annotations Previous topic 7. Simple statements Next topic 9. Top-level components This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Language Reference » 8. Compound statements | Theme Auto Light Dark | 8. Compound statements ¶ Compound statements contain (groups of) other statements; they affect or control the execution of those other statements in some way. In general, compound statements span multiple lines, although in simple incarnations a whole compound statement may be contained in one line. The if , while and for statements implement traditional control flow constructs. try specifies exception handlers and/or cleanup code for a group of statements, while the with statement allows the execution of initialization and finalization code around a block of code. Function and class definitions are also syntactically compound statements. A compound statement consists of one or more ‘clauses.’ A clause consists of a header and a ‘suite.’ The clause headers of a particular compound statement are all at the same indentation level. Each clause header begins with a uniquely identifying keyword and ends with a colon. A suite is a group of statements controlled by a clause. A suite can be one or more semicolon-separated simple statements on the same line as the header, following the header’s colon, or it can be one or more indented statements on subsequent lines. Only the latter form of a suite can contain nested compound statements; the following is illegal, mostly because it wouldn’t be clear to which if clause a following else clause would belong: if test1 : if test2 : print ( x ) Also note that the semicolon binds tighter than the colon in this context, so that in the following example, either all or none of the print() calls are executed: if x < y < z : print ( x ); print ( y ); print ( z ) Summarizing: compound_stmt : if_stmt | while_stmt | for_stmt | try_stmt | with_stmt | match_stmt | funcdef | classdef | async_with_stmt | async_for_stmt | async_funcdef suite : stmt_list NEWLINE | NEWLINE INDENT statement + DEDENT statement : stmt_list NEWLINE | compound_stmt stmt_list : simple_stmt ( ";" simple_stmt )* [ ";" ] Note that statements always end in a NEWLINE possibly followed by a DEDENT . Also note that optional continuation clauses always begin with a keyword that cannot start a statement, thus there are no ambiguities (the ‘dangling else ’ problem is solved in Python by requiring nested if statements to be indented). The formatting of the grammar rules in the following sections places each clause on a separate line for clarity. 8.1. The if statement ¶ The if statement is used for conditional execution: if_stmt : "if" assignment_expression ":" suite ( "elif" assignment_expression ":" suite )* [ "else" ":" suite ] It selects exactly one of the suites by evaluating the expressions one by one until one is found to be true (see section Boolean operations for the definition of true and false); then that suite is executed (and no other part of the if statement is executed or evaluated). If all expressions are false, the suite of the else clause, if present, is executed. 8.2. The while statement ¶ The while statement is used for repeated execution as long as an expression is true: while_stmt : "while" assignment_expression ":" suite [ "else" ":" suite ] This repeatedly tests the expression and, if it is true, executes the first suite; if the expression is false (which may be the first time it is tested) the suite of the else clause, if present, is executed and the loop terminates. A break statement executed in the first suite terminates the loop without executing the else clause’s suite. A continue statement executed in the first suite skips the rest of the suite and goes back to testing the expression. 8.3. The for statement ¶ The for statement is used to iterate over the elements of a sequence (such as a string, tuple or list) or other iterable object: for_stmt : "for" target_list "in" starred_expression_list ":" suite [ "else" ":" suite ] The starred_expression_list expression is evaluated once; it should yield an iterable object. An iterator is created for that iterable. The first item provided by the iterator is then assigned to the target list using the standard rules for assignments (see Assignment statements ), and the suite is executed. This repeats for each item provided by the iterator. When the iterator is exhausted, the suite in the else clause, if present, is executed, and the loop terminates. A break statement executed in the first suite terminates the loop without executing the else clause’s suite. A continue statement executed in the first suite skips the rest of the suite and continues with the next item, or with the else clause if there is no next item. The for-loop makes assignments to the variables in the target list. This overwrites all previous assignments to those variables including those made in the suite of the for-loop: for i in range ( 10 ): print ( i ) i = 5 # this will not affect the for-loop # because i will be overwritten with the next # index in the range Names in the target list are not deleted when the loop is finished, but if the sequence is empty, they will not have been assigned to at all by the loop. Hint: the built-in type range() represents immutable arithmetic sequences of integers. For instance, iterating range(3) successively yields 0, 1, and then 2. Changed in version 3.11: Starred elements are now allowed in the expression list. 8.4. The try statement ¶ The try statement specifies exception handlers and/or cleanup code for a group of statements: try_stmt : try1_stmt | try2_stmt | try3_stmt try1_stmt : "try" ":" suite ( "except" [ expression [ "as" identifier ]] ":" suite )+ [ "else" ":" suite ] [ "finally" ":" suite ] try2_stmt : "try" ":" suite ( "except" "*" expression [ "as" identifier ] ":" suite )+ [ "else" ":" suite ] [ "finally" ":" suite ] try3_stmt : "try" ":" suite "finally" ":" suite Additional information on exceptions can be found in section Exceptions , and information on using the raise statement to generate exceptions may be found in section The raise statement . Changed in version 3.14: Support for optionally dropping grouping parentheses when using multiple exception types. See PEP 758 . 8.4.1. except clause ¶ The except clause(s) specify one or more exception handlers. When no exception occurs in the try clause, no exception handler is executed. When an exception occurs in the try suite, a search for an exception handler is started. This search inspects the except clauses in turn until one is found that matches the exception. An expression-less except clause, if present, must be last; it matches any exception. For an except clause with an expression, the expression must evaluate to an exception type or a tuple of exception types. Parentheses can be dropped if multiple exception types are provided and the as clause is not used. The raised exception matches an except clause whose expression evaluates to the class or a non-virtual base class of the exception object, or to a tuple that contains such a class. If no except clause matches the exception, the search for an exception handler continues in the surrounding code and on the invocation stack. [ 1 ] If the evaluation of an expression in the header of an except clause raises an exception, the original search for a handler is canceled and a search starts for the new exception in the surrounding code and on the call stack (it is treated as if the entire try statement raised the exception). When a matching except clause is found, the exception is assigned to the target specified after the as keyword in that except clause, if present, and the except clause’s suite is executed. All except clauses must have an executable block. When the end of this block is reached, execution continues normally after the entire try statement. (This means that if two nested handlers exist for the same exception, and the exception occurs in the try clause of the inner handler, the outer handler will not handle the exception.) When an exception has been assigned using as target , it is cleared at the end of the except clause. This is as if except E as N : foo was translated to except E as N : try : foo finally : del N This means the exception must be assigned to a different name to be able to refer to it after the except clause. Exceptions are cleared because with the traceback attached to them, they form a reference cycle with the stack frame, keeping all locals in that frame alive until the next garbage collection occurs. Before an except clause’s suite is executed, the exception is stored in the sys module, where it can be accessed from within the body of the except clause by calling sys.exception() . When leaving an exception handler, the exception stored in the sys module is reset to its previous value: >>> print ( sys . exception ()) None >>> try : ... raise TypeError ... except : ... print ( repr ( sys . exception ())) ... try : ... raise ValueError ... except : ... print ( repr ( sys . exception ())) ... print ( repr ( sys . exception ())) ... TypeError() ValueError() TypeError() >>> print ( sys . exception ()) None 8.4.2. except* clause ¶ The except* clause(s) specify one or more handlers for groups of exceptions ( BaseExceptionGroup instances). A try statement can have either except or except* clauses, but not both. The exception type for matching is mandatory in the case of except* , so except*: is a syntax error. The type is interpreted as in the case of except , but matching is performed on the exceptions contained in the group that is being handled. An TypeError is raised if a matching type is a subclass of BaseExceptionGroup , because that would have ambiguous semantics. When an exception group is raised in the try block, each except* clause splits (see split() ) it into the subgroups of matching and non-matching exceptions. If the matching subgroup is not empty, it becomes the handled exception (the value returned from sys.exception() ) and assigned to the target of the except* clause (if there is one). Then, the body of the except* clause executes. If the non-matching subgroup is not empty, it is processed by the next except* in the same manner. This continues until all exceptions in the group have been matched, or the last except* clause has run. After all except* clauses execute, the group of unhandled exceptions is merged with any exceptions that were raised or re-raised from within except* clauses. This merged exception group propagates on.: >>> try : ... raise ExceptionGroup ( "eg" , ... [ ValueError ( 1 ), TypeError ( 2 ), OSError ( 3 ), OSError ( 4 )]) ... except * TypeError as e : ... print ( f 'caught { type ( e ) } with nested { e . exceptions } ' ) ... except * OSError as e : ... print ( f 'caught { type ( e ) } with nested { e . exceptions } ' ) ... caught <class 'ExceptionGroup'> with nested (TypeError(2),) caught <class 'ExceptionGroup'> with nested (OSError(3), OSError(4)) + Exception Group Traceback (most recent call last): | File "<doctest default[0]>", line 2, in <module> | raise ExceptionGroup("eg", | [ValueError(1), TypeError(2), OSError(3), OSError(4)]) | ExceptionGroup: eg (1 sub-exception) +-+---------------- 1 ---------------- | ValueError: 1 +------------------------------------ If the exception raised from the try block is not an exception group and its type matches one of the except* clauses, it is caught and wrapped by an exception group with an empty message string. This ensures that the type of the target e is consistently BaseExceptionGroup : >>> try : ... raise BlockingIOError ... except * BlockingIOError as e : ... print ( repr ( e )) ... ExceptionGroup('', (BlockingIOError(),)) break , continue and return cannot appear in an except* clause. 8.4.3. else clause ¶ The optional else clause is executed if the control flow leaves the try suite, no exception was raised, and no return , continue , or break statement was executed. Exceptions in the else clause are not handled by the preceding except clauses. 8.4.4. finally clause ¶ If finally is present, it specifies a ‘cleanup’ handler. The try clause is executed, including any except and else clauses. If an exception occurs in any of the clauses and is not handled, the exception is temporarily saved. The finally clause is executed. If there is a saved exception it is re-raised at the end of the finally clause. If the finally clause raises another exception, the saved exception is set as the context of the new exception. If the finally clause executes a return , break or continue statement, the saved exception is discarded. For example, this function returns 42. def f (): try : 1 / 0 finally : return 42 The exception information is not available to the program during execution of the finally clause. When a return , break or continue statement is executed in the try suite of a try … finally statement, the finally clause is also executed ‘on the way out.’ The return value of a function is determined by the last return statement executed. Since the finally clause always executes, a return statement executed in the finally clause will always be the last one executed. The following function returns ‘finally’. def foo (): try : return 'try' finally : return 'finally' Changed in version 3.8: Prior to Python 3.8, a continue statement was illegal in the finally clause due to a problem with the implementation. Changed in version 3.14: The compiler emits a SyntaxWarning when a return , break or continue appears in a finally block (see PEP 765 ). 8.5. The with statement ¶ The with statement is used to wrap the execution of a block with methods defined by a context manager (see section With Statement Context Managers ). This allows common try … except … finally usage patterns to be encapsulated for convenient reuse. with_stmt : "with" ( "(" with_stmt_contents "," ? ")" | with_stmt_contents ) ":" suite with_stmt_contents : with_item ( "," with_item )* with_item : expression [ "as" target ] The execution of the with statement with one “item” proceeds as follows: The context expression (the expression given in the with_item ) is evaluated to obtain a context manager. The context manager’s __enter__() is loaded for later use. The context manager’s __exit__() is loaded for later use. The context manager’s __enter__() method is invoked. If a target was included in the with statement, the return value from __enter__() is assigned to it. Note The with statement guarantees that if the __enter__() method returns without an error, then __exit__() will always be called. Thus, if an error occurs during the assignment to the target list, it will be treated the same as an error occurring within the suite would be. See step 7 below. The suite is executed. The context manager’s __exit__() method is invoked. If an exception caused the suite to be exited, its type, value, and traceback are passed as arguments to __exit__() . Otherwise, three None arguments are supplied. If the suite was exited due to an exception, and the return value from the __exit__() method was false, the exception is reraised. If the return value was true, the exception is suppressed, and execution continues with the statement following the with statement. If the suite was exited for any reason other than an exception, the return value from __exit__() is ignored, and execution proceeds at the normal location for the kind of exit that was taken. The following code: with EXPRESSION as TARGET : SUITE is semantically equivalent to: manager = ( EXPRESSION ) enter = type ( manager ) . __enter__ exit = type ( manager ) . __exit__ value = enter ( manager ) hit_except = False try : TARGET = value SUITE except : hit_except = True if not exit ( manager , * sys . exc_info ()): raise finally : if not hit_except : exit ( manager , None , None , None ) With more than one item, the context managers are processed as if multiple with statements were nested: with A () as a , B () as b : SUITE is semantically equivalent to: with A () as a : with B () as b : SUITE You can also write multi-item context managers in multiple lines if the items are surrounded by parentheses. For example: with ( A () as a , B () as b , ): SUITE Changed in version 3.1: Support for multiple context expressions. Changed in version 3.10: Support for using grouping parentheses to break the statement in multiple lines. See also PEP 343 - The “with” statement The specification, background, and examples for the Python with statement. 8.6. The match statement ¶ Added in version 3.10. The match statement is used for pattern matching. Syntax: match_stmt : 'match' subject_expr ":" NEWLINE INDENT case_block + DEDENT subject_expr : `!star_named_expression` "," `!star_named_expressions`? | `!named_expression` case_block : 'case' patterns [ guard ] ":" `!block` Note This section uses single quotes to denote soft keywords . Pattern matching takes a pattern as input (following case ) and a subject value (following match ). The pattern (which may contain subpatterns) is matched against the subject value. The outcomes are: A match success or failure (also termed a pattern success or failure). Possible binding of matched values to a name. The prerequisites for this are further discussed below. The match and case keywords are soft keywords . See also PEP 634 – Structural Pattern Matching: Specification PEP 636 – Structural Pattern Matching: Tutorial 8.6.1. Overview ¶ Here’s an overview of the logical flow of a match statement: The subject expression subject_expr is evaluated and a resulting subject value obtained. If the subject expression contains a comma, a tuple is constructed using the standard rules . Each pattern in a case_block is attempted to match with the subject value. The specific rules for success or failure are described below. The match attempt can also bind some or all of the standalone names within the pattern. The precise pattern binding rules vary per pattern type and are specified below. Name bindings made during a successful pattern match outlive the executed block and can be used after the match statement . Note During failed pattern matches, some subpatterns may succeed. Do not rely on bindings being made for a failed match. Conversely, do not rely on variables remaining unchanged after a failed match. The exact behavior is dependent on implementation and may vary. This is an intentional decision made to allow different implementations to add optimizations. If the pattern succeeds, the corresponding guard (if present) is evaluated. In this case all name bindings are guaranteed to have happened. If the guard evaluates as true or is missing, the block inside case_block is executed. Otherwise, the next case_block is attempted as described above. If there are no further case blocks, the match statement is completed. Note Users should generally never rely on a pattern being evaluated. Depending on implementation, the interpreter may cache values or use other optimizations which skip repeated evaluations. A sample match statement: >>> flag = False >>> match ( 100 , 200 ): ... case ( 100 , 300 ): # Mismatch: 200 != 300 ... print ( 'Case 1' ) ... case ( 100 , 200 ) if flag : # Successful match, but guard fails ... print ( 'Case 2' ) ... case ( 100 , y ): # Matches and binds y to 200 ... print ( f 'Case 3, y: { y } ' ) ... case _ : # Pattern not attempted ... print ( 'Case 4, I match anything!' ) ... Case 3, y: 200 In this case, if flag is a guard. Read more about that in the next section. 8.6.2. Guards ¶ guard : "if" `!named_expression` A guard (which is part of the case ) must succeed for code inside the case block to execute. It takes the form: if followed by an expression. The logical flow of a case block with a guard follows: Check that the pattern in the case block succeeded. If the pattern failed, the guard is not evaluated and the next case block is checked. If the pattern succeeded, evaluate the guard . If the guard condition evaluates as true, the case block is selected. If the guard condition evaluates as false, the case block is not selected. If the guard raises an exception during evaluation, the exception bubbles up. Guards are allowed to have side effects as they are expressions. Guard evaluation must proceed from the first to the last case block, one at a time, skipping case blocks whose pattern(s) don’t all succeed. (I.e., guard evaluation must happen in order.) Guard evaluation must stop once a case block is selected. 8.6.3. Irrefutable Case Blocks ¶ An irrefutable case block is a match-all case block. A match statement may have at most one irrefutable case block, and it must be last. A case block is considered irrefutable if it has no guard and its pattern is irrefutable. A pattern is considered irrefutable if we can prove from its syntax alone that it will always succeed. Only the following patterns are irrefutable: AS Patterns whose left-hand side is irrefutable OR Patterns containing at least one irrefutable pattern Capture Patterns Wildcard Patterns parenthesized irrefutable patterns 8.6.4. Patterns ¶ Note This section uses grammar notations beyond standard EBNF: the notation SEP.RULE+ is shorthand for RULE (SEP RULE)* the notation !RULE is shorthand for a negative lookahead assertion The top-level syntax for patterns is: patterns : open_sequence_pattern | pattern pattern : as_pattern | or_pattern closed_pattern : | literal_pattern | capture_pattern | wildcard_pattern | value_pattern | group_pattern | sequence_pattern | mapping_pattern | class_pattern The descriptions below will include a description “in simple terms” of what a pattern does for illustration purposes (credits to Raymond Hettinger for a document that inspired most of the descriptions). Note that these descriptions are purely for illustration purposes and may not reflect the underlying implementation. Furthermore, they do not cover all valid forms. 8.6.4.1. OR Patterns ¶ An OR pattern is two or more patterns separated by vertical bars | . Syntax: or_pattern : "|" . closed_pattern + Only the final subpattern may be irrefutable , and each subpattern must bind the same set of names to avoid ambiguity. An OR pattern matches each of its subpatterns in turn to the subject value, until one succeeds. The OR pattern is then considered successful. Otherwise, if none of the subpatterns succeed, the OR pattern fails. In simple terms, P1 | P2 | ... will try to match P1 , if it fails it will try to match P2 , succeeding immediately if any succeeds, failing otherwise. 8.6.4.2. AS Patterns ¶ An AS pattern matches an OR pattern on the left of the as keyword against a subject. Syntax: as_pattern : or_pattern "as" capture_pattern If the OR pattern fails, the AS pattern fails. Otherwise, the AS pattern binds the subject to the name on the right of the as keyword and succeeds. capture_pattern cannot be a _ . In simple terms P as NAME will match with P , and on success it will set NAME = <subject> . 8.6.4.3. Literal Patterns ¶ A literal pattern corresponds to most literals in Python. Syntax: literal_pattern : signed_number | signed_number "+" NUMBER | signed_number "-" NUMBER | strings | "None" | "True" | "False" signed_number : [ "-" ] NUMBER The rule strings and the token NUMBER are defined in the standard Python grammar . Triple-quoted strings are supported. Raw strings and byte strings are supported. f-strings and t-strings are not supported. The forms signed_number '+' NUMBER and signed_number '-' NUMBER are for expressing complex numbers ; they require a real number on the left and an imaginary number on the right. E.g. 3 + 4j . In simple terms, LITERAL will succeed only if <subject> == LITERAL . For the singletons None , True and False , the is operator is used. 8.6.4.4. Capture Patterns ¶ A capture pattern binds the subject value to a name. Syntax: capture_pattern : ! '_' NAME A single underscore _ is not a capture pattern (this is what !'_' expresses). It is instead treated as a wildcard_pattern . In a given pattern, a given name can only be bound once. E.g. case x, x: ... is invalid while case [x] | x: ... is allowed. Capture patterns always succeed. The binding follows scoping rules established by the assignment expression operator in PEP 572 ; the name becomes a local variable in the closest containing function scope unless there’s an applicable global or nonlocal statement. In simple terms NAME will always succeed and it will set NAME = <subject> . 8.6.4.5. Wildcard Patterns ¶ A wildcard pattern always succeeds (matches anything) and binds no name. Syntax: wildcard_pattern : '_' _ is a soft keyword within any pattern, but only within patterns. It is an identifier, as usual, even within match subject expressions, guard s, and case blocks. In simple terms, _ will always succeed. 8.6.4.6. Value Patterns ¶ A value pattern represents a named value in Python. Syntax: value_pattern : attr attr : name_or_attr "." NAME name_or_attr : attr | NAME The dotted name in the pattern is looked up using standard Python name resolution rules . The pattern succeeds if the value found compares equal to the subject value (using the == equality operator). In simple terms NAME1.NAME2 will succeed only if <subject> == NAME1.NAME2 Note If the same value occurs multiple times in the same match statement, the interpreter may cache the first value found and reuse it rather than repeat the same lookup. This cache is strictly tied to a given execution of a given match statement. 8.6.4.7. Group Patterns ¶ A group pattern allows users to add parentheses around patterns to emphasize the intended grouping. Otherwise, it has no additional syntax. Syntax: group_pattern : "(" pattern ")" In simple terms (P) has the same effect as P . 8.6.4.8. Sequence Patterns ¶ A sequence pattern contains several subpatterns to be matched against sequence elements. The syntax is similar to the unpacking of a list or tuple. sequence_pattern : "[" [ maybe_sequence_pattern ] "]" | "(" [ open_sequence_pattern ] ")" open_sequence_pattern : maybe_star_pattern "," [ maybe_sequence_pattern ] maybe_sequence_pattern : "," . maybe_star_pattern + "," ? maybe_star_pattern : star_pattern | pattern star_pattern : "*" ( capture_pattern | wildcard_pattern ) There is no difference if parentheses or square brackets are used for sequence patterns (i.e. (...) vs [...] ). Note A single pattern enclosed in parentheses without a trailing comma (e.g. (3 | 4) ) is a group pattern . While a single pattern enclosed in square brackets (e.g. [3 | 4] ) is still a sequence pattern. At most one star subpattern may be in a sequence pattern. The star subpattern may occur in any position. If no star subpattern is present, the sequence pattern is a fixed-length sequence pattern; otherwise it is a variable-length sequence pattern. The following is the logical flow for matching a sequence pattern against a subject value: If the subject value is not a sequence [ 2 ] , the sequence pattern fails. If the subject value is an instance of str , bytes or bytearray the sequence pattern fails. The subsequent steps depend on whether the sequence pattern is fixed or variable-length. If the sequence pattern is fixed-length: If the length of the subject sequence is not equal to the number of subpatterns, the sequence pattern fails Subpatterns in the sequence pattern are matched to their corresponding items in the subject sequence from left to right. Matching stops as soon as a subpattern fails. If all subpatterns succeed in matching their corresponding item, the sequence pattern succeeds. Otherwise, if the sequence pattern is variable-length: If the length of the subject sequence is less than the number of non-star subpatterns, the sequence pattern fails. The leading non-star subpatterns are matched to their corresponding items as for fixed-length sequences. If the previous step succeeds, the star subpattern matches a list formed of the remaining subject items, excluding the remaining items corresponding to non-star subpatterns following the star subpattern. Remaining non-star subpatterns are matched to their corresponding subject items, as for a fixed-length sequence. Note The length of the subject sequence is obtained via len() (i.e. via the __len__() protocol). This length may be cached by the interpreter in a similar manner as value patterns . In simple terms [P1, P2, P3, … , P<N>] matches only if all the following happens: check <subject> is a sequence len(subject) == <N> P1 matches <subject>[0] (note that this match can also bind names) P2 matches <subject>[1] (note that this match can also bind names) … and so on for the corresponding pattern/element. 8.6.4.9. Mapping Patterns ¶ A mapping pattern contains one or more key-value patterns. The syntax is similar to the construction of a dictionary. Syntax: mapping_pattern : "{" [ items_pattern ] "}" items_pattern : "," . key_value_pattern + "," ? key_value_pattern : ( literal_pattern | value_pattern ) ":" pattern | double_star_pattern double_star_pattern : "**" capture_pattern At most one double star pattern may be in a mapping pattern. The double star pattern must be the last subpattern in the mapping pattern. Duplicate keys in mapping patterns are disallowed. Duplicate literal keys will raise a SyntaxError . Two keys that otherwise have the same value will raise a ValueError at runtime. The following is the logical flow for matching a mapping pattern against a subject value: If the subject value is not a mapping [ 3 ] ,the mapping pattern fails. If every key given in the mapping pattern is present in the subject mapping, and the pattern for each key matches the corresponding item of the subject mapping, the mapping pattern succeeds. If duplicate keys are detected in the mapping pattern, the pattern is considered invalid. A SyntaxError is raised for duplicate literal values; or a ValueError for named keys of the same value. Note Key-value pairs are matched using the two-argument form of the mapping subject’s get() method. Matched key-value pairs must already be present in the mapping, and not created on-the-fly via __missing__() or __getitem__() . In simple terms {KEY1: P1, KEY2: P2, ... } matches only if all the following happens: check <subject> is a mapping KEY1 in <subject> P1 matches <subject>[KEY1] … and so on for the corresponding KEY/pattern pair. 8.6.4.10. Class Patterns ¶ A class pattern represents a class and its positional and keyword arguments (if any). Syntax: class_pattern : name_or_attr "(" [ pattern_arguments "," ?] ")" pattern_arguments : positional_patterns [ "," keyword_patterns ] | keyword_patterns positional_patterns : "," . pattern + keyword_patterns : "," . keyword_pattern + keyword_pattern : NAME "=" pattern The same keyword should not be repeated in class patterns. The following is the logical flow for matching a class pattern against a subject value: If name_or_attr is not an instance of the builtin type , raise TypeError . If the subject value is not an instance of name_or_attr (tested via isinstance() ), the class pattern fails. If no pattern arguments are present, the pattern succeeds. Otherwise, the subsequent steps depend on whether keyword or positional argument patterns are present. For a number of built-in types (specified below), a single positional subpattern is accepted which will match the entire subject; for these types keyword patterns also work as for other types. If only keyword patterns are present, they are processed as follows, one by one: The keyword is looked up as an attribute on the subject. If this raises an exception other than AttributeError , the exception bubbles up. If this raises AttributeError , the class pattern has failed. Else, the subpattern associated with the keyword pattern is matched against the subject’s attribute value. If this fails, the class pattern fails; if this succeeds, the match proceeds to the next keyword. If all keyword patterns succeed, the class pattern succeeds. If any positional patterns are present, they are converted to keyword patterns using the __match_args__ attribute on the class name_or_attr before matching: The equivalent of getattr(cls, "__match_args__", ()) is called. If this raises an exception, the exception bubbles up. If the returned value is not a tuple, the conversion fails and TypeError is raised. If there are more positional patterns than len(cls.__match_args__) , TypeError is raised. Otherwise, positional pattern i is converted to a keyword pattern using __match_args__[i] as the keyword. __match_args__[i] must be a string; if not TypeError is raised. If there are duplicate keywords, TypeError is raised. See also Customizing positional arguments in class pattern matching Once all positional patterns have been converted to keyword patterns, the match proceeds as if there were only keyword patterns. For the following built-in types the handling of positional subpatterns is different: bool bytearray bytes dict float frozenset int list set str tuple These classes accept a single positional argument, and the pattern there is matched against the whole object rather than an attribute. For example int(0|1) matches the value 0 , but not the value 0.0 . In simple terms CLS(P1, attr=P2) matches only if the following happens: isinstance(<subject>, CLS) convert P1 to a keyword pattern using CLS.__match_args__ For each keyword argument attr=P2 : hasattr(<subject>, "attr") P2 matches <subject>.attr … and so on for the corresponding keyword argument/pattern pair. See also PEP 634 – Structural Pattern Matching: Specification PEP 636 – Structural Pattern Matching: Tutorial 8.7. Function definitions ¶ A function definition defines a user-defined function object (see section The standard type hierarchy ): funcdef : [ decorators ] "def" funcname [ type_params ] "(" [ parameter_list ] ")" [ "->" expression ] ":" suite decorators : decorator + decorator : "@" assignment_expression NEWLINE parameter_list : defparameter ( "," defparameter )* "," "/" [ "," [ parameter_list_no_posonly ]] | parameter_list_no_posonly parameter_list_no_posonly : defparameter ( "," defparameter )* [ "," [ parameter_list_starargs ]] | parameter_list_starargs parameter_list_starargs : "*" [ star_parameter ] ( "," defparameter )* [ "," [ parameter_star_kwargs ]] | "*" ( "," defparameter )+ [ "," [ parameter_star_kwargs ]] | parameter_star_kwargs parameter_star_kwargs : "**" parameter [ "," ] parameter : identifier [ ":" expression ] star_parameter : identifier [ ":" [ "*" ] expression ] defparameter : parameter [ "=" expression ] funcname : identifier A function definition is an executable statement. Its execution binds the function name in the current local namespace to a function object (a wrapper around the executable code for the function). This function object contains a reference to the current global namespace as the global namespace to be used when the function is called. The function definition does not execute the function body; this gets executed only when the function is called. [ 4 ] A function definition may be wrapped by one or more decorator expressions. Decorator expressions are evaluated when the function is defined, in the scope that contains the function definition. The result must be a callable, which is invoked with the function object as the only argument. The returned value is bound to the function name instead of the function object. Multiple decorators are applied in nested fashion. For example, the following code @f1 ( arg ) @f2 def func (): pass is roughly equivalent to def func (): pass func = f1 ( arg )( f2 ( func )) except that the original function is not temporarily bound to the name func . Changed in version 3.9: Functions may be decorated with any valid assignment_expression . Previously, the grammar was much more restrictive; see PEP 614 for details. A list of type parameters may be given in square brackets between the function’s name and the opening parenthesis for its parameter list. This indicates to static type checkers that the function is generic. At runtime, the type parameters can be retrieved from the function’s __type_params__ attribute. See Generic functions for more. Changed in version 3.12: Type parameter lists are new in Python 3.12. When one or more parameters have the form parameter = expression , the function is said to have “default parameter values.” For a parameter with a default value, the corresponding argument may be omitted from a call, in which case the parameter’s default value is substituted. If a parameter has a default value, all following parameters up until the “ * ” must also have a default value — this is a syntactic restriction that is not expressed by the grammar. Default parameter values are evaluated from left to right when the function definition is executed. This means that the expression is evaluated once, when the function is defined, and that the same “pre-computed” value is used for each call. This is especially important to understand when a default parameter value is a mutable object, such as a list or a dictionary: if the function modifies the object (e.g. by appending an item to a list), the default parameter value is in effect modified. This is generally not what was intended. A way around this is to use None as the default, and explicitly test for it in the body of the function, e.g.: def whats_on_the_telly ( penguin = None ): if penguin is None : penguin = [] penguin . append ( "property of the zoo" ) return penguin Function call semantics are described in more detail in section Calls . A function call always assigns values to all parameters mentioned in the parameter list, either from positional arguments, from keyword arguments, or from default values. If the form “ *identifier ” is present, it is initialized to a tuple receiving any excess positional parameters, defaulting to the empty tuple. If the form “ **identifier ” is present, it is initialized to a new ordered mapping receiving any excess keyword arguments, defaulting to a new empty mapping of the same type. Parameters after “ * ” or “ *identifier ” are keyword-only parameters and may only be passed by keyword arguments. Parameters before “ / ” are positional-only parameters and may only be passed by positional arguments. Changed in version 3.8: The / function parameter syntax may be used to indicate positional-only parameters. See PEP 570 for details. Parameters may have an annotation of the form “ : expression ” following the parameter name. Any parameter may have an annotation, even those of the form *identifier or **identifier . (As a special case, parameters of the form *identifier may have an annotation “ : *expression ”.) Functions may have “return” annotation of the form “ -> expression ” after the parameter list. These annotations can be any valid Python expression. The presence of annotations does not change the semantics of a function. See Annotations for more information on annotations. Changed in version 3.11: Parameters of the form “ *identifier ” may have an annotation “ : *expression ”. See PEP 646 . It is also possible to create anonymous functions (functions not bound to a name), for immediate use in expressions. This uses lambda expressions, described in section Lambdas . Note that the lambda expression is merely a shorthand for a simplified function definition; a function defined in a “ def ” statement can be passed around or assigned to another name just like a function defined by a lambda expression. The “ def ” form is actually more powerful since it allows the execution of multiple statements and annotations. Programmer’s note: Functions are first-class objects. A “ def ” statement executed inside a function definition defines a local function that can be returned or passed around. Free variables used in the nested function can access the local variables of the function containing the def. See section Naming and binding for details. See also PEP 3107 - Function Annotations The original specification for function annotations. PEP 484 - Type Hints Definition of a standard meaning for annotations: type hints. PEP 526 - Syntax for Variable Annotations Ability to type hint variable declarations, including class variables and instance variables. PEP 563 - Postponed Evaluation of Annotations Support for forward references within annotations by preserving annotations in a string form at runtime instead of eager evaluation. PEP 318 - Decorators for Functions and Methods Function and method decorators were introduced. Class decorators were introduced in PEP 3129 . 8.8. Class definitions ¶ A class definition defines a class object (see section The standard type hierarchy ): classdef : [ decorators ] "class" classname [ type_params ] [ inheritance ] ":" suite inheritance : "(" [ argument_list ] ")" classname : identifier A class definition is an executable statement. The inheritance list usually gives a list of base classes (see Metaclasses for more advanced uses), so each item in the list should evaluate to a class object which allows subclassing. Classes without an inheritance list inherit, by default, from the base class object ; hence, class Foo : pass is equivalent to class Foo ( object ): pass The class’s suite is then executed in a new execution frame (see Naming and binding ), using a newly created local namespace and the original global namespace. (Usually, the suite contains mostly function definitions.) When the class’s suite finishes execution, its execution frame is discarded but its local namespace is saved. [ 5 ] A class object is then created using the inheritance list for the base classes and the saved local namespace for the attribute dictionary. The class name is bound to this class object in the original local namespace. The order in which attributes are defined in the class body is preserved in the new class’s __dict__ . Note that this is reliable only right after the class is created and only for classes that were defined using the definition syntax. Class creation can be customized heavily using metaclasses . Classes can also be decorated: just like when decorating functions, @f1 ( arg ) @f2 class Foo : pass is roughly equivalent to class Foo : pass Foo = f1 ( arg )( f2 ( Foo )) The evaluation rules for the decorator expressions are the same as for function decorators. The result is then bound to the class name. Changed in version 3.9: Classes may be decorated with any valid assignment_expression . Previously, the grammar was much more restrictive; see PEP 614 for details. A list of type parameters may be given in square brackets immediately after the class’s name. This indicates to static type checkers that the class is generic. At runtime, the type parameters can be retrieved from the class’s __type_params__ attribute. See Generic classes for more. Changed in version 3.12: Type parameter lists are new in Python 3.12. Programmer’s note: Variables defined in the class definition are class attributes; they are shared by instances. Instance attributes can be set in a method with self.name = value . Both class and instance attributes are accessible through the notation “ self.name ”, and an instance attribute hides a class attribute with the same name when accessed in this way. Class attributes can be used as defaults for instance attributes, but using mutable values there can lead to unexpected results. Descriptors can be used to create instance variables with different implementation details. See also PEP 3115 - Metaclasses in Python 3000 The proposal that changed the declaration of metaclasses to the current syntax, and the semantics for how classes with metaclasses are constructed. PEP 3129 - Class Decorators The proposal that added class decorators. Function and method decorators were introduced in PEP 318 . 8.9. Coroutines ¶ Added in version 3.5. 8.9.1. Coroutine function definition ¶ async_funcdef : [ decorators ] "async" "def" funcname "(" [ parameter_list ] ")" [ "->" expression ] ":" suite Execution of Python coroutines can be suspended and resumed at many points (see coroutine ). await expressions, async for and async with can only be used in the body of a coroutine function. Functions defined with async def syntax are always coroutine functions, even if they do not contain await or async keywords. It is a SyntaxError to use a yield from expression inside the body of a coroutine function. An example of a coroutine function: async def func ( param1 , param2 ): do_stuff () await some_coroutine () Changed in version 3.7: await and async are now keywords; previously they were only treated as such inside the body of a coroutine function. 8.9.2. The async for statement ¶ async_for_stmt : "async" for_stmt An asynchronous iterable provides an __aiter__ method that directly returns an asynchronous iterator , which can call asynchronous code in its __anext__ method. The async for statement allows convenient iteration over asynchronous iterables. The following code: async for TARGET in ITER : SUITE else : SUITE2 Is semantically equivalent to: iter = ( ITER ) iter = type ( iter ) . __aiter__ ( iter ) running = True while running : try : TARGET = await type ( iter ) . __anext__ ( iter ) except StopAsyncIteration : running = False else : SUITE else : SUITE2 See also __aiter__() and __anext__() for details. It is a SyntaxError to use an async for statement outside the body of a coroutine function. 8.9.3. The async with statement ¶ async_with_stmt : "async" with_stmt An asynchronous context manager is a context manager that is able to suspend execution in its enter and exit methods. The following code: async with EXPRESSION as TARGET : SUITE is semantically equivalent to: manager = ( EXPRESSION ) aenter = type ( manager ) . __aenter__ aexit = type ( manager ) . __aexit__ value = await aenter ( manager ) hit_except = False try : TARGET = value SUITE except : hit_except = True if not await aexit ( manager , * sys . exc_info ()): raise finally : if not hit_except : await aexit ( manager , None , None , None ) See also __aenter__() and __aexit__() for details. It is a SyntaxError to use an async with statement outside the body of a coroutine function. See also PEP 492 - Coroutines with async and await syntax The proposal that made coroutines a proper standalone concept in Python, and added supporting syntax. 8.10. Type parameter lists ¶ Added in version 3.12. Changed in version 3.13: Support for default values was added (see PEP 696 ). type_params : "[" type_param ( "," type_param )* "]" type_param : typevar | typevartuple | paramspec typevar : identifier ( ":" expression )? ( "=" expression )? typevartuple : "*" identifier ( "=" expression )? paramspec : "**" identifier ( "=" expression )? Functions (including coroutines ), classes and type aliases may contain a type parameter list: def max [ T ]( args : list [ T ]) -> T : ... async def amax [ T ]( args : list [ T ]) -> T : ... class Bag [ T ]: def __iter__ ( self ) -> Iterator [ T ]: ... def add ( self , arg : T ) -> None : ... type ListOrSet [ T ] = list [ T ] | set [ T ] Semantically, this indicates that the function, class, or type | 2026-01-13T08:48:45 |
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https://commission.europa.eu/law/law-topic/data-protection/international-dimension-data-protection/standard-contractual-clauses-scc_en#main-content | Standard Contractual Clauses (SCC) - European Commission Skip to main content en Select your language Close bg български es español cs čeština da dansk de Deutsch et eesti el ελληνικά en English fr français ga Gaeilge hr hrvatski it italiano lv latviešu lt lietuvių hu magyar mt Malti nl Nederlands pl polski pt português ro română sk slovenčina sl slovenščina fi suomi sv svenska Search Search European Commission Menu Back Home About us About us Learn more about the role of the European Commission, its leadership and corporate policies Organisation President Commissioners Departments and executive agencies Staff See all Role In strategy and policy In law In budget and funding In international relations See all Service standards and principles Transparency Ethics and Good Administration Modernising the European Commission The Commission’s use of languages See all Contact Discover more FEATURED 2024-2029 Commission: Priorities and leadership Our priorities Our priorities Learn how the EU is building a sustainable, digital, and inclusive future through its seven key priorities. 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Page contents Page contents EU Standard Contractual Clauses According to the General Data Protection Regulation (GDPR), contractual clauses ensuring appropriate data protection safeguards can be used as a ground for data transfers from the EU to third countries. This includes model contract clauses – so-called standard contractual clauses (SCCs) – that have been “pre-approved” by the European Commission. On 4 June 2021 , the Commission issued modernised standard contractual clauses under the GDPR for data transfers from controllers or processors in the EU/EEA (or otherwise subject to the GDPR) to controllers or processors established outside the EU/EEA (and not subject to the GDPR). These modernised SCCs replace the three sets of SCCs that were adopted under the previous Data Protection Directive 95/46. The Commission developed Questions and Answers (Q&As) to provide practical guidance on the use of the SCCs and assist stakeholders in their compliance efforts under the GDPR. These Q&As are based on feedback received from various stakeholders on their experience with using the new SCCs in the first months after their adoption. The Q&As are intended to be a ‘dynamic’ source of information and will be updated as new questions arise. The Commission is in the process of developing additional sets of SCCs for data transfers to third countries by EU institutions and bodies, and for data transfers to controllers or processors outside the EU whose processing operations are directly subject to the GDPR. Model clauses around the world Several organisations and third countries are developing or have issued their own model contractual clauses on the basis of converging principles that are also shared by the EU SCCs. Some jurisdictions have endorsed the EU SCCs as a transfer mechanism under their own national data protection legislation, with limited formal adaptations to their domestic legal order (e.g. the United Kingdom and Switzerland . Others have developed model clauses that share a number of commonalities with the EU SCCs. This for instance includes: - the Model Contractual Clauses for transborder data flows of personal data developed on the basis of Convention 108+ by the Council of Europe Consultative Committee of Convention 108, - the Model Contractual Clauses developed by the Ibero-American Data Protection Network, as well as the accompanying implementation Guide , - the ASEAN Model Contractual Clauses for Cross Border Data Flows developed by the Association of Southeast Asian Nations, - as well as clauses developed at national level, e.g. in New Zealand , Argentina , and the United Kingdom . EU and ASEAN develop joint guidance on the use of model clauses for data transfers The Commission is intensifying its cooperation with international partners to further facilitate data transfers between different regions of the world on the basis of model clauses. ASEAN (the Association of Southeast Asian Nations) is a key partner in this respect. Together with ASEAN, the Commission has developed a Guide on the EU standard contractual clauses and ASEAN model contractual clauses, to assist companies present in both jurisdictions with their compliance efforts under both sets of clauses. The Guide identifies the commonalities between the two sets of clauses and provides non-exhaustive examples of best practices companies can consider to operationalise safeguards required under the clauses. Documents General publications 4 June 2021 Directorate-General for Justice and Consumers Publications on the Standard Contractual Clauses (SCCs) Access documents related to the two sets of Standard Contractual Clauses (SCCs), including questions and answers on their use. 24 MAY 2023 Joint Guide to ASEAN Model Contractual Clauses and EU Standard Contractual Clauses English (535.22 KB - PDF) Download 25 MAY 2022 Questions and Answers for the two sets of Standard Contractual Clauses English (435.42 KB - PDF) Download Share this page This site is managed by: Directorate-General for Communication About us Contact us Priorities Topics Funding and tenders Jobs Press corner Events Follow us Facebook Instagram X LinkedIn Other networks Report an IT vulnerability Languages on our websites Cookies Privacy policy Legal notice Accessibility | 2026-01-13T08:48:45 |
https://calebporzio.com/using-inline-svgs-in-vue-compoments | Using inline SVGs in Vue components | Caleb Porzio Caleb Porzio Posts • Creations • Talks • Tweets Using inline SVGs in Vue components Feb 2018 Note: This blog post is less of a technical guide and more of a story around a campfire. ...so there I was, working on my new personal finance app for Fancy Finance Man . It's a dark night in February, and I finally come to the realization that I've held off too long; this app is ready for an icon library. Normally, I would just pull in Font-awesome, but this time I decide to Do It Right™️ and use SVGs. I recall Steve Schoger recently put out an SVG icon set called Heroicons UI , so I pull up the GitHub repo to see what it’s all about. Hoping for some instructions in the README, like npm install steves-pretty-icons , I see it’s just a folder called svg with a bunch of .svg files inside (totally respect that btw). After contemplating whether or not to find a way to pull the files in with Composer or NPM, I decide to skip the hassle and manually download them into a new folder in my app: resources/assets/svg . From what I’ve heard, using img tags for SVGs is not as cool as inlining the HTML (SVG tag). Not cool <img src=“/some/image.svg”></img> Super cool <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" … Fortunately, Adam Wathan has a nifty little package that makes inlining these bad boys a breeze ( Adam’s Blade SVG package ). However, because it’s a blade plugin, I would have to do some finagling to use it in my single file Vue components (passing them through as props, or some other fanciness). Because most of the app is written using SFCs (Single File Components), I decide this package isn’t ideal and instead attempt to hand-roll my own Vue component. I already have an idea in my head of how I want to use the component: <svg-icon icon="trash"></svg-icon> … and I know the rendered output needs to look something like this: <div> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" width="24" height="24"><path class="heroicon-ui" d="M8 6V4c0-1.1.9-2 2-2h4a2 2 0 0 1 2 2v2h5a1 1 0 0 1 0 2h-1v12a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V8H3a1 1 0 1 1 0-2h5zM6 8v12h12V8H6zm8-2V4h-4v2h4zm-4 4a1 1 0 0 1 1 1v6a1 1 0 0 1-2 0v-6a1 1 0 0 1 1-1zm4 0a1 1 0 0 1 1 1v6a1 1 0 0 1-2 0v-6a1 1 0 0 1 1-1z"/></svg> </div> First step: importing SVGs into .vue files I'm thinking I will end up using webpack's require() syntax, but before I jump in, I want to set myself up for proper importing. Relative url's ( requre('./../../../ugh') ) are visually repulsive to me and annoying to deal with later if you need to restructure your files Instead of having to do this (from a Vue component in resources/assets/js/components ): require('./../../svg/icon-trash.svg') …I want to be able to do this: require('icon-trash.svg') …so I add this kinda-nasty kinda-not bit to my webpack.mix.js file: mix.webpackConfig({ resolve: { modules: [ 'node_modules', path.resolve(__dirname, 'resources/assets/js'), path.resolve(__dirname, 'resources/assets/svg') ] } }); Turns out this works fine when you write require(’icon-trash.svg') explicitly, but if you use an expression inside require() like: require(‘icon-‘ + icon + ‘.svg') everything blows up. Webpack's "require expressions" only work when you are resolving directories (ex. require(‘./../../svg/icon-‘ + icon + ‘.svg') ). As much as I’d like to not use relative directories, this seems to be the only option for now. Ok, where were we… The following setup would be ideal, but I’m 99% positive this won’t do what I want it to do out of the box: // SvgIcon.vue <template> <div v-html="require(`./../../svg/icon-${icon}.svg`)"></div> </template> …again, this is the desired output: <div> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" width="24" height="24"><path class="heroicon-ui" d="M8 6V4c0-1.1.9-2 2-2h4a2 2 0 0 1 2 2v2h5a1 1 0 0 1 0 2h-1v12a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V8H3a1 1 0 1 1 0-2h5zM6 8v12h12V8H6zm8-2V4h-4v2h4zm-4 4a1 1 0 0 1 1 1v6a1 1 0 0 1-2 0v-6a1 1 0 0 1 1-1zm4 0a1 1 0 0 1 1 1v6a1 1 0 0 1-2 0v-6a1 1 0 0 1 1-1z"/></svg> </div> As expected, this does not work out of the box. When I compile and load in the browser, I get the following rendered output: <div>/images/icon-trash.svg?cdd2695e96c36122af7cb47739a28cea</div> So I visit that endpoint for kicks ( my-finance-app.boots/images/icon-trash.svg?cdd2695e96c36122af7cb47739a28cea ) and my browser actually displays the SVG! This is confusing to me because I put the original SVG in a folder called resources/assets/svg . Turns out, during the build, Laravel Mix actually created a folder called public/images and put icon-trash.svg inside it. So clearly there is some magic being performed by Laravel Mix behind the scenes. Normally I would be delighted by this sorcery, but in this case, I want to import the raw text content of a file, not a public URL. After a bit of googling, I discover a webpack loader called html-loader ( html-loader GitHub repo ) which seems to do exactly what I want: allow the importing of a file’s HTML content. So I pull it into my project via npm install --save-dev html-loader . Quick webpack trick I learned along the way: Before I roll up my sleeves and attempt to configure web pack to use this loader (which tires me out just thinking about it), I discover a cool nifty way to use webpack loaders without messing with any configuration, saweet! The tiring way: // webpack.mix.js mix.webpackConfig({ module: { rules: [{ test: /\.svg$/, use: [{ loader: 'html-loader' }] }] } }); // Some .vue file require('./../../svg/icon-trash.svg'); The cool new quick way: // Some .vue file require('html-loader!./../../svg/icon-trash.svg'); Back to work By now, I’m excited and ready to use my handy new html-loader to pull SVGs into my Vue component. I add the new syntax to the require statement: // SvgIcon.vue <template> <div v-html="require('html-loader!./../../svg/icon-trash.svg')"></div> </template> ...and much to my dismay, this is the rendered output I receive now: <div class="text-grey">module.exports = "/images/icon-trash.svg?869001c277c880324f6ebcfb92ab5d71";</div> Note the new module.exports = string in the output. This tells me the loader worked, but Laravel Mix did it’s transformation before html-loader got to it. After a good amount of source diving, I come up for air and start searching the Laravel Mix GitHub repository to see if other people have encountered this problem. Luckily they have! But the solution is pretty hairy. I decide to just go with it for the sake of time. Also, I’m no stranger to a messy webpack.mix.js file. I add the following code to my webpack.mix.js file. This tells Laravel Mix to not touch .svg s and let html-loader handle everything. (This is pretty much copy and pasted from this GitHub issue ) // Make Laravel Mix ignore .svgs Mix.listen('configReady', function (config) { const rules = config.module.rules; const targetRegex = /(\.(png|jpe?g|gif)$|^((?!font).)*\.svg$)/; for (let rule of rules) { if (rule.test.toString() == targetRegex.toString()) { rule.exclude = /\.svg$/; break; } } }); // Hande .svgs with html-loader instead mix.webpackConfig({ module: { rules: [{ test: /\.svg$/, use: [{ loader: 'html-loader', options: { minimize: true } }] }] } }); Did we fix everything? After completely wrecking my webpack.mix.js file, I’m eager to test this baby out and see if it did the trick. (A small part of me has that bad feeling that comes with anything I ever do in webpack - the feeling of knowing it will definitely not work and I will lose at least a half day of work to debugging the darn tootin’ thing - only to revert my attempt entirely and quit programming) Despite my gut feeling, it worked! My Vue component: // SvgIcon.vue <template> <div v-html="require(`./../../svg/icon-${icon}.svg`)"></div> </template> Rendered output: <div><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" width="1em" height="1em" fill="rgb(184, 194, 204)" style="vertical-align: middle; display: inline-block; margin-top: -4px;"><path class="heroicon-ui" d="M8 6V4c0-1.1.9-2 2-2h4a2 2 0 0 1 2 2v2h5a1 1 0 0 1 0 2h-1v12a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V8H3a1 1 0 1 1 0-2h5zM6 8v12h12V8H6zm8-2V4h-4v2h4zm-4 4a1 1 0 0 1 1 1v6a1 1 0 0 1-2 0v-6a1 1 0 0 1 1-1zm4 0a1 1 0 0 1 1 1v6a1 1 0 0 1-2 0v-6a1 1 0 0 1 1-1z"></path></svg></div> Finishing the component The hard part’s over, now it’s just a matter of slapping on a prop to pass in the icon name and calling it a day. SvgIcon.vue <template> <div v-html="require(`./../../svg/icon-${icon}.svg`)"></div> </template> <script> export default { props: ['icon'] } </script> Usage <svg-icon icon="trash"></svg-icon> Viola! Now I have a handy Vue component to use inline SVGs effortlessly in my single file components. For some, this may be enough. If that’s the case, you can stop reading now and go implement this for yourself! For the rest of us, we need to color and size these babies. (out of the box, the SVGs are a fixed size and color) Screenshot of what I have so far Making SVGs colorful Disclaimer: my SVG knowledge is super fragmented. I’ve wrestled with them here and there, but am by no means a master. When you inevitably see me making something way more complex than it needs to be, please tweet at me @calebprozio . To my knowledge, you can’t just slap on a color: blue to an <svg> tag. SVGs use the fill attribute for this sort of thing. If you have the colors ready to go, it should be no problem to just create a prop in your new component for a fill attribute: <template> <div v-html="require(`./../../svg/icon-${icon}.svg`)"></div> </template> <script> export default { props: ['icon', 'fill'], mounted() { this.$el.firstChild.setAttribute('fill', this.fill); } </script> For me, this is no good. I’ve been relying on Tailwind’s built in colors and definitely don’t want to start hard-coding colors around my javascript. At the end of the day, I really want to be able to add a class like text-green (which sets color: ... for an element in Tailwind) to the component and have the SVG automatically inherit that color. After writing a crazy hack to achieve this functionality I discover SVG offers this functionality out of the box with a property called: fill: currentColor . To add to the spoils, Tailwind offers a CSS class called fill-current . After deleting a bunch of crazy code that listens for changes to parent classes, get’s the computed color style and sets the fill of the SVG, I simply add this fill-current class and we are off to the races! The usage <svg-icon icon="trash" class="text-green"></svg-icon> The implementation <template> <div v-html="require(`./../../svg/icon-${icon}.svg`)"></div> </template> <script> export default { props: ['icon'], mounted() { this.$el.firstChild.classList.add('fill-current') } } </script> Great, now that our SVGs are easily colorable, it’s time to tackle sizing and spacing. Screenshot with colors! Sizing the SVGs Apparently, sizing SVGs is a rabbit hole (see this CSS Tricks article to go down it). For now, I just need to get up and running with the basics: display the SVG inline and set the size according to the font-size. Later, I may want to size them explicitly and behave more like a block , but for now, this will do just fine. Out of the box, each SVG from Steve’s Heroicon UI pack is set to 24px width and 24px height. My first order of business is to strip the svg tag of these attributes. this.$el.firstChild.removeAttribute('height') this.$el.firstChild.removeAttribute('width') After banging my head against my laptop stand, I came up with the following styles that will need to be applied to the <svg> tag for the desired behavior: fill: currentColor; height: 1em; margin-top: -4px; vertical-align: middle; width: 1em; I could set these properties individually in the mounted hook using javascript like this.$el.firstChild.style.height = ‘1em’ , but I’d rather not do that for a bunch of reasons that don’t actually matter (some vague sense of Right™️, syntax highlighting, others). For this, I choose to leverage Vue’s SFC <style> tag. Choosing a selector So I know I want these styles in the <style> tag, but now I’m left with a new decision to make: what’s going to be my selector? Before we explore selectors let’s first review the DOM structure of this component. It’s basically an <svg> tag inside a <div> tag. <div> <svg> </svg> </div> Remembering I can't just add a class to the svg tag, the easiest way to apply these styles is to either use javascript to add a class to the SVG tag or to add a class to the <div> like .svg-icon and use a nested selector like the following: .svg-icon svg . My issue with this approach is that it forces me to think of a name. I’d rather explore options that avoid introducing a new name into the component. My first idea is to use a nice clean svg selector and keep it from affecting the global styles with a scoped attribute like so: <style scoped> svg { fill: currentColor; height: 1em; margin-top: -4px; vertical-align: middle; width: 1em; } </style> Turns out the scoped attribute won’t apply to elements generated by the v-html directive. Luckily, I remember seeing this in the Vue docs and don’t have to bang my head against the monitor for too long. After visiting the docs for alternatives, I read about a new Vue style tag option I’ve never seen before: module . Apparently, if you add a module attribute to your <style> tag it will generate a unique selector for you and you can apply it to your DOM programmatically (using this fancy syntax: this.$style.{your-class-name} ). This seems like a good enough option, a little complex, but well documented and gives me that clean, Solid™️ feeling I’m after. Here is the code: // Style portion <style module> .svg { fill: currentColor; height: 1em; // This margin makes me sooo saadddd // Someone please tell me why I need it or how I can get rid of it! margin-top: -4px; vertical-align: middle; width: 1em; } </style> // In my mounted() hook: this.$el.firstChild.classList.add(this.$style.svg) Also, I want these SVGs to be inline by default, so I add the inline-block class to the root div: <template> <div class="inline-block" v-html="require(`./../../svg/icon-${icon}.svg`)"></div> </template> Screenshot with proper sizing! The finish line! Awesome, I’m satisfied. I have a fairly clean Vue component for using inline SVGs that’s easily colorable and automatically scales to its context - what more could a guy ask for. I think I’m finally ready to say farewell to that Font-awesome @import and usher in the new era of doing icons Right™️. For your viewing pleasure here is the final Vue component ( here is a Github Gist too ) Usage <h1 class="text-green"> <svg-icon icon="announcement"></svg-icon> Some Announcement! </h1> SvgIcon.vue <template> <div class="inline-block" v-html="require('icon-' + this.icon + '.svg')"></div> </template> <style module> .svg { fill: currentColor; height: 1em; margin-top: -4px; vertical-align: middle; width: 1em; } </style> <script> export default { props: ['icon'], mounted() { this.$el.firstChild.classList.add(this.$style.svg) this.$el.firstChild.removeAttribute('height') this.$el.firstChild.removeAttribute('width') } } </script> If you read this far, tweet at me ( @calebprozio ) and let me know if you like this kind of storytelling format. I thought I’d try something new,and I think you can learn a lot more sometimes seeing the process than just seeing the end result. Thanks for tuning in, happy SVGing! 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https://docs.python.org/3/tutorial/controlflow.html#function-annotations | 4. More Control Flow Tools — Python 3.14.2 documentation Theme Auto Light Dark Table of Contents 4. More Control Flow Tools 4.1. if Statements 4.2. for Statements 4.3. The range() Function 4.4. break and continue Statements 4.5. else Clauses on Loops 4.6. pass Statements 4.7. match Statements 4.8. Defining Functions 4.9. More on Defining Functions 4.9.1. Default Argument Values 4.9.2. Keyword Arguments 4.9.3. Special parameters 4.9.3.1. Positional-or-Keyword Arguments 4.9.3.2. Positional-Only Parameters 4.9.3.3. Keyword-Only Arguments 4.9.3.4. Function Examples 4.9.3.5. Recap 4.9.4. Arbitrary Argument Lists 4.9.5. Unpacking Argument Lists 4.9.6. Lambda Expressions 4.9.7. Documentation Strings 4.9.8. Function Annotations 4.10. Intermezzo: Coding Style Previous topic 3. An Informal Introduction to Python Next topic 5. Data Structures This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Tutorial » 4. More Control Flow Tools | Theme Auto Light Dark | 4. More Control Flow Tools ¶ As well as the while statement just introduced, Python uses a few more that we will encounter in this chapter. 4.1. if Statements ¶ Perhaps the most well-known statement type is the if statement. For example: >>> x = int ( input ( "Please enter an integer: " )) Please enter an integer: 42 >>> if x < 0 : ... x = 0 ... print ( 'Negative changed to zero' ) ... elif x == 0 : ... print ( 'Zero' ) ... elif x == 1 : ... print ( 'Single' ) ... else : ... print ( 'More' ) ... More There can be zero or more elif parts, and the else part is optional. The keyword ‘ elif ’ is short for ‘else if’, and is useful to avoid excessive indentation. An if … elif … elif … sequence is a substitute for the switch or case statements found in other languages. If you’re comparing the same value to several constants, or checking for specific types or attributes, you may also find the match statement useful. For more details see match Statements . 4.2. for Statements ¶ The for statement in Python differs a bit from what you may be used to in C or Pascal. Rather than always iterating over an arithmetic progression of numbers (like in Pascal), or giving the user the ability to define both the iteration step and halting condition (as C), Python’s for statement iterates over the items of any sequence (a list or a string), in the order that they appear in the sequence. For example (no pun intended): >>> # Measure some strings: >>> words = [ 'cat' , 'window' , 'defenestrate' ] >>> for w in words : ... print ( w , len ( w )) ... cat 3 window 6 defenestrate 12 Code that modifies a collection while iterating over that same collection can be tricky to get right. Instead, it is usually more straight-forward to loop over a copy of the collection or to create a new collection: # Create a sample collection users = { 'Hans' : 'active' , 'Éléonore' : 'inactive' , '景太郎' : 'active' } # Strategy: Iterate over a copy for user , status in users . copy () . items (): if status == 'inactive' : del users [ user ] # Strategy: Create a new collection active_users = {} for user , status in users . items (): if status == 'active' : active_users [ user ] = status 4.3. The range() Function ¶ If you do need to iterate over a sequence of numbers, the built-in function range() comes in handy. It generates arithmetic progressions: >>> for i in range ( 5 ): ... print ( i ) ... 0 1 2 3 4 The given end point is never part of the generated sequence; range(10) generates 10 values, the legal indices for items of a sequence of length 10. It is possible to let the range start at another number, or to specify a different increment (even negative; sometimes this is called the ‘step’): >>> list ( range ( 5 , 10 )) [5, 6, 7, 8, 9] >>> list ( range ( 0 , 10 , 3 )) [0, 3, 6, 9] >>> list ( range ( - 10 , - 100 , - 30 )) [-10, -40, -70] To iterate over the indices of a sequence, you can combine range() and len() as follows: >>> a = [ 'Mary' , 'had' , 'a' , 'little' , 'lamb' ] >>> for i in range ( len ( a )): ... print ( i , a [ i ]) ... 0 Mary 1 had 2 a 3 little 4 lamb In most such cases, however, it is convenient to use the enumerate() function, see Looping Techniques . A strange thing happens if you just print a range: >>> range ( 10 ) range(0, 10) In many ways the object returned by range() behaves as if it is a list, but in fact it isn’t. It is an object which returns the successive items of the desired sequence when you iterate over it, but it doesn’t really make the list, thus saving space. We say such an object is iterable , that is, suitable as a target for functions and constructs that expect something from which they can obtain successive items until the supply is exhausted. We have seen that the for statement is such a construct, while an example of a function that takes an iterable is sum() : >>> sum ( range ( 4 )) # 0 + 1 + 2 + 3 6 Later we will see more functions that return iterables and take iterables as arguments. In chapter Data Structures , we will discuss in more detail about list() . 4.4. break and continue Statements ¶ The break statement breaks out of the innermost enclosing for or while loop: >>> for n in range ( 2 , 10 ): ... for x in range ( 2 , n ): ... if n % x == 0 : ... print ( f " { n } equals { x } * { n // x } " ) ... break ... 4 equals 2 * 2 6 equals 2 * 3 8 equals 2 * 4 9 equals 3 * 3 The continue statement continues with the next iteration of the loop: >>> for num in range ( 2 , 10 ): ... if num % 2 == 0 : ... print ( f "Found an even number { num } " ) ... continue ... print ( f "Found an odd number { num } " ) ... Found an even number 2 Found an odd number 3 Found an even number 4 Found an odd number 5 Found an even number 6 Found an odd number 7 Found an even number 8 Found an odd number 9 4.5. else Clauses on Loops ¶ In a for or while loop the break statement may be paired with an else clause. If the loop finishes without executing the break , the else clause executes. In a for loop, the else clause is executed after the loop finishes its final iteration, that is, if no break occurred. In a while loop, it’s executed after the loop’s condition becomes false. In either kind of loop, the else clause is not executed if the loop was terminated by a break . Of course, other ways of ending the loop early, such as a return or a raised exception, will also skip execution of the else clause. This is exemplified in the following for loop, which searches for prime numbers: >>> for n in range ( 2 , 10 ): ... for x in range ( 2 , n ): ... if n % x == 0 : ... print ( n , 'equals' , x , '*' , n // x ) ... break ... else : ... # loop fell through without finding a factor ... print ( n , 'is a prime number' ) ... 2 is a prime number 3 is a prime number 4 equals 2 * 2 5 is a prime number 6 equals 2 * 3 7 is a prime number 8 equals 2 * 4 9 equals 3 * 3 (Yes, this is the correct code. Look closely: the else clause belongs to the for loop, not the if statement.) One way to think of the else clause is to imagine it paired with the if inside the loop. As the loop executes, it will run a sequence like if/if/if/else. The if is inside the loop, encountered a number of times. If the condition is ever true, a break will happen. If the condition is never true, the else clause outside the loop will execute. When used with a loop, the else clause has more in common with the else clause of a try statement than it does with that of if statements: a try statement’s else clause runs when no exception occurs, and a loop’s else clause runs when no break occurs. For more on the try statement and exceptions, see Handling Exceptions . 4.6. pass Statements ¶ The pass statement does nothing. It can be used when a statement is required syntactically but the program requires no action. For example: >>> while True : ... pass # Busy-wait for keyboard interrupt (Ctrl+C) ... This is commonly used for creating minimal classes: >>> class MyEmptyClass : ... pass ... Another place pass can be used is as a place-holder for a function or conditional body when you are working on new code, allowing you to keep thinking at a more abstract level. The pass is silently ignored: >>> def initlog ( * args ): ... pass # Remember to implement this! ... For this last case, many people use the ellipsis literal ... instead of pass . This use has no special meaning to Python, and is not part of the language definition (you could use any constant expression here), but ... is used conventionally as a placeholder body as well. See The Ellipsis Object . 4.7. match Statements ¶ A match statement takes an expression and compares its value to successive patterns given as one or more case blocks. This is superficially similar to a switch statement in C, Java or JavaScript (and many other languages), but it’s more similar to pattern matching in languages like Rust or Haskell. Only the first pattern that matches gets executed and it can also extract components (sequence elements or object attributes) from the value into variables. If no case matches, none of the branches is executed. The simplest form compares a subject value against one or more literals: def http_error ( status ): match status : case 400 : return "Bad request" case 404 : return "Not found" case 418 : return "I'm a teapot" case _ : return "Something's wrong with the internet" Note the last block: the “variable name” _ acts as a wildcard and never fails to match. You can combine several literals in a single pattern using | (“or”): case 401 | 403 | 404 : return "Not allowed" Patterns can look like unpacking assignments, and can be used to bind variables: # point is an (x, y) tuple match point : case ( 0 , 0 ): print ( "Origin" ) case ( 0 , y ): print ( f "Y= { y } " ) case ( x , 0 ): print ( f "X= { x } " ) case ( x , y ): print ( f "X= { x } , Y= { y } " ) case _ : raise ValueError ( "Not a point" ) Study that one carefully! The first pattern has two literals, and can be thought of as an extension of the literal pattern shown above. But the next two patterns combine a literal and a variable, and the variable binds a value from the subject ( point ). The fourth pattern captures two values, which makes it conceptually similar to the unpacking assignment (x, y) = point . If you are using classes to structure your data you can use the class name followed by an argument list resembling a constructor, but with the ability to capture attributes into variables: class Point : def __init__ ( self , x , y ): self . x = x self . y = y def where_is ( point ): match point : case Point ( x = 0 , y = 0 ): print ( "Origin" ) case Point ( x = 0 , y = y ): print ( f "Y= { y } " ) case Point ( x = x , y = 0 ): print ( f "X= { x } " ) case Point (): print ( "Somewhere else" ) case _ : print ( "Not a point" ) You can use positional parameters with some builtin classes that provide an ordering for their attributes (e.g. dataclasses). You can also define a specific position for attributes in patterns by setting the __match_args__ special attribute in your classes. If it’s set to (“x”, “y”), the following patterns are all equivalent (and all bind the y attribute to the var variable): Point ( 1 , var ) Point ( 1 , y = var ) Point ( x = 1 , y = var ) Point ( y = var , x = 1 ) A recommended way to read patterns is to look at them as an extended form of what you would put on the left of an assignment, to understand which variables would be set to what. Only the standalone names (like var above) are assigned to by a match statement. Dotted names (like foo.bar ), attribute names (the x= and y= above) or class names (recognized by the “(…)” next to them like Point above) are never assigned to. Patterns can be arbitrarily nested. For example, if we have a short list of Points, with __match_args__ added, we could match it like this: class Point : __match_args__ = ( 'x' , 'y' ) def __init__ ( self , x , y ): self . x = x self . y = y match points : case []: print ( "No points" ) case [ Point ( 0 , 0 )]: print ( "The origin" ) case [ Point ( x , y )]: print ( f "Single point { x } , { y } " ) case [ Point ( 0 , y1 ), Point ( 0 , y2 )]: print ( f "Two on the Y axis at { y1 } , { y2 } " ) case _ : print ( "Something else" ) We can add an if clause to a pattern, known as a “guard”. If the guard is false, match goes on to try the next case block. Note that value capture happens before the guard is evaluated: match point : case Point ( x , y ) if x == y : print ( f "Y=X at { x } " ) case Point ( x , y ): print ( f "Not on the diagonal" ) Several other key features of this statement: Like unpacking assignments, tuple and list patterns have exactly the same meaning and actually match arbitrary sequences. An important exception is that they don’t match iterators or strings. Sequence patterns support extended unpacking: [x, y, *rest] and (x, y, *rest) work similar to unpacking assignments. The name after * may also be _ , so (x, y, *_) matches a sequence of at least two items without binding the remaining items. Mapping patterns: {"bandwidth": b, "latency": l} captures the "bandwidth" and "latency" values from a dictionary. Unlike sequence patterns, extra keys are ignored. An unpacking like **rest is also supported. (But **_ would be redundant, so it is not allowed.) Subpatterns may be captured using the as keyword: case ( Point ( x1 , y1 ), Point ( x2 , y2 ) as p2 ): ... will capture the second element of the input as p2 (as long as the input is a sequence of two points) Most literals are compared by equality, however the singletons True , False and None are compared by identity. Patterns may use named constants. These must be dotted names to prevent them from being interpreted as capture variable: from enum import Enum class Color ( Enum ): RED = 'red' GREEN = 'green' BLUE = 'blue' color = Color ( input ( "Enter your choice of 'red', 'blue' or 'green': " )) match color : case Color . RED : print ( "I see red!" ) case Color . GREEN : print ( "Grass is green" ) case Color . BLUE : print ( "I'm feeling the blues :(" ) For a more detailed explanation and additional examples, you can look into PEP 636 which is written in a tutorial format. 4.8. Defining Functions ¶ We can create a function that writes the Fibonacci series to an arbitrary boundary: >>> def fib ( n ): # write Fibonacci series less than n ... """Print a Fibonacci series less than n.""" ... a , b = 0 , 1 ... while a < n : ... print ( a , end = ' ' ) ... a , b = b , a + b ... print () ... >>> # Now call the function we just defined: >>> fib ( 2000 ) 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597 The keyword def introduces a function definition . It must be followed by the function name and the parenthesized list of formal parameters. The statements that form the body of the function start at the next line, and must be indented. The first statement of the function body can optionally be a string literal; this string literal is the function’s documentation string, or docstring . (More about docstrings can be found in the section Documentation Strings .) There are tools which use docstrings to automatically produce online or printed documentation, or to let the user interactively browse through code; it’s good practice to include docstrings in code that you write, so make a habit of it. The execution of a function introduces a new symbol table used for the local variables of the function. More precisely, all variable assignments in a function store the value in the local symbol table; whereas variable references first look in the local symbol table, then in the local symbol tables of enclosing functions, then in the global symbol table, and finally in the table of built-in names. Thus, global variables and variables of enclosing functions cannot be directly assigned a value within a function (unless, for global variables, named in a global statement, or, for variables of enclosing functions, named in a nonlocal statement), although they may be referenced. The actual parameters (arguments) to a function call are introduced in the local symbol table of the called function when it is called; thus, arguments are passed using call by value (where the value is always an object reference , not the value of the object). [ 1 ] When a function calls another function, or calls itself recursively, a new local symbol table is created for that call. A function definition associates the function name with the function object in the current symbol table. The interpreter recognizes the object pointed to by that name as a user-defined function. Other names can also point to that same function object and can also be used to access the function: >>> fib <function fib at 10042ed0> >>> f = fib >>> f ( 100 ) 0 1 1 2 3 5 8 13 21 34 55 89 Coming from other languages, you might object that fib is not a function but a procedure since it doesn’t return a value. In fact, even functions without a return statement do return a value, albeit a rather boring one. This value is called None (it’s a built-in name). Writing the value None is normally suppressed by the interpreter if it would be the only value written. You can see it if you really want to using print() : >>> fib ( 0 ) >>> print ( fib ( 0 )) None It is simple to write a function that returns a list of the numbers of the Fibonacci series, instead of printing it: >>> def fib2 ( n ): # return Fibonacci series up to n ... """Return a list containing the Fibonacci series up to n.""" ... result = [] ... a , b = 0 , 1 ... while a < n : ... result . append ( a ) # see below ... a , b = b , a + b ... return result ... >>> f100 = fib2 ( 100 ) # call it >>> f100 # write the result [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89] This example, as usual, demonstrates some new Python features: The return statement returns with a value from a function. return without an expression argument returns None . Falling off the end of a function also returns None . The statement result.append(a) calls a method of the list object result . A method is a function that ‘belongs’ to an object and is named obj.methodname , where obj is some object (this may be an expression), and methodname is the name of a method that is defined by the object’s type. Different types define different methods. Methods of different types may have the same name without causing ambiguity. (It is possible to define your own object types and methods, using classes , see Classes ) The method append() shown in the example is defined for list objects; it adds a new element at the end of the list. In this example it is equivalent to result = result + [a] , but more efficient. 4.9. More on Defining Functions ¶ It is also possible to define functions with a variable number of arguments. There are three forms, which can be combined. 4.9.1. Default Argument Values ¶ The most useful form is to specify a default value for one or more arguments. This creates a function that can be called with fewer arguments than it is defined to allow. For example: def ask_ok ( prompt , retries = 4 , reminder = 'Please try again!' ): while True : reply = input ( prompt ) if reply in { 'y' , 'ye' , 'yes' }: return True if reply in { 'n' , 'no' , 'nop' , 'nope' }: return False retries = retries - 1 if retries < 0 : raise ValueError ( 'invalid user response' ) print ( reminder ) This function can be called in several ways: giving only the mandatory argument: ask_ok('Do you really want to quit?') giving one of the optional arguments: ask_ok('OK to overwrite the file?', 2) or even giving all arguments: ask_ok('OK to overwrite the file?', 2, 'Come on, only yes or no!') This example also introduces the in keyword. This tests whether or not a sequence contains a certain value. The default values are evaluated at the point of function definition in the defining scope, so that i = 5 def f ( arg = i ): print ( arg ) i = 6 f () will print 5 . Important warning: The default value is evaluated only once. This makes a difference when the default is a mutable object such as a list, dictionary, or instances of most classes. For example, the following function accumulates the arguments passed to it on subsequent calls: def f ( a , L = []): L . append ( a ) return L print ( f ( 1 )) print ( f ( 2 )) print ( f ( 3 )) This will print [ 1 ] [ 1 , 2 ] [ 1 , 2 , 3 ] If you don’t want the default to be shared between subsequent calls, you can write the function like this instead: def f ( a , L = None ): if L is None : L = [] L . append ( a ) return L 4.9.2. Keyword Arguments ¶ Functions can also be called using keyword arguments of the form kwarg=value . For instance, the following function: def parrot ( voltage , state = 'a stiff' , action = 'voom' , type = 'Norwegian Blue' ): print ( "-- This parrot wouldn't" , action , end = ' ' ) print ( "if you put" , voltage , "volts through it." ) print ( "-- Lovely plumage, the" , type ) print ( "-- It's" , state , "!" ) accepts one required argument ( voltage ) and three optional arguments ( state , action , and type ). This function can be called in any of the following ways: parrot ( 1000 ) # 1 positional argument parrot ( voltage = 1000 ) # 1 keyword argument parrot ( voltage = 1000000 , action = 'VOOOOOM' ) # 2 keyword arguments parrot ( action = 'VOOOOOM' , voltage = 1000000 ) # 2 keyword arguments parrot ( 'a million' , 'bereft of life' , 'jump' ) # 3 positional arguments parrot ( 'a thousand' , state = 'pushing up the daisies' ) # 1 positional, 1 keyword but all the following calls would be invalid: parrot () # required argument missing parrot ( voltage = 5.0 , 'dead' ) # non-keyword argument after a keyword argument parrot ( 110 , voltage = 220 ) # duplicate value for the same argument parrot ( actor = 'John Cleese' ) # unknown keyword argument In a function call, keyword arguments must follow positional arguments. All the keyword arguments passed must match one of the arguments accepted by the function (e.g. actor is not a valid argument for the parrot function), and their order is not important. This also includes non-optional arguments (e.g. parrot(voltage=1000) is valid too). No argument may receive a value more than once. Here’s an example that fails due to this restriction: >>> def function ( a ): ... pass ... >>> function ( 0 , a = 0 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : function() got multiple values for argument 'a' When a final formal parameter of the form **name is present, it receives a dictionary (see Mapping Types — dict ) containing all keyword arguments except for those corresponding to a formal parameter. This may be combined with a formal parameter of the form *name (described in the next subsection) which receives a tuple containing the positional arguments beyond the formal parameter list. ( *name must occur before **name .) For example, if we define a function like this: def cheeseshop ( kind , * arguments , ** keywords ): print ( "-- Do you have any" , kind , "?" ) print ( "-- I'm sorry, we're all out of" , kind ) for arg in arguments : print ( arg ) print ( "-" * 40 ) for kw in keywords : print ( kw , ":" , keywords [ kw ]) It could be called like this: cheeseshop ( "Limburger" , "It's very runny, sir." , "It's really very, VERY runny, sir." , shopkeeper = "Michael Palin" , client = "John Cleese" , sketch = "Cheese Shop Sketch" ) and of course it would print: -- Do you have any Limburger ? -- I'm sorry, we're all out of Limburger It's very runny, sir. It's really very, VERY runny, sir. ---------------------------------------- shopkeeper : Michael Palin client : John Cleese sketch : Cheese Shop Sketch Note that the order in which the keyword arguments are printed is guaranteed to match the order in which they were provided in the function call. 4.9.3. Special parameters ¶ By default, arguments may be passed to a Python function either by position or explicitly by keyword. For readability and performance, it makes sense to restrict the way arguments can be passed so that a developer need only look at the function definition to determine if items are passed by position, by position or keyword, or by keyword. A function definition may look like: def f(pos1, pos2, /, pos_or_kwd, *, kwd1, kwd2): ----------- ---------- ---------- | | | | Positional or keyword | | - Keyword only -- Positional only where / and * are optional. If used, these symbols indicate the kind of parameter by how the arguments may be passed to the function: positional-only, positional-or-keyword, and keyword-only. Keyword parameters are also referred to as named parameters. 4.9.3.1. Positional-or-Keyword Arguments ¶ If / and * are not present in the function definition, arguments may be passed to a function by position or by keyword. 4.9.3.2. Positional-Only Parameters ¶ Looking at this in a bit more detail, it is possible to mark certain parameters as positional-only . If positional-only , the parameters’ order matters, and the parameters cannot be passed by keyword. Positional-only parameters are placed before a / (forward-slash). The / is used to logically separate the positional-only parameters from the rest of the parameters. If there is no / in the function definition, there are no positional-only parameters. Parameters following the / may be positional-or-keyword or keyword-only . 4.9.3.3. Keyword-Only Arguments ¶ To mark parameters as keyword-only , indicating the parameters must be passed by keyword argument, place an * in the arguments list just before the first keyword-only parameter. 4.9.3.4. Function Examples ¶ Consider the following example function definitions paying close attention to the markers / and * : >>> def standard_arg ( arg ): ... print ( arg ) ... >>> def pos_only_arg ( arg , / ): ... print ( arg ) ... >>> def kwd_only_arg ( * , arg ): ... print ( arg ) ... >>> def combined_example ( pos_only , / , standard , * , kwd_only ): ... print ( pos_only , standard , kwd_only ) The first function definition, standard_arg , the most familiar form, places no restrictions on the calling convention and arguments may be passed by position or keyword: >>> standard_arg ( 2 ) 2 >>> standard_arg ( arg = 2 ) 2 The second function pos_only_arg is restricted to only use positional parameters as there is a / in the function definition: >>> pos_only_arg ( 1 ) 1 >>> pos_only_arg ( arg = 1 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : pos_only_arg() got some positional-only arguments passed as keyword arguments: 'arg' The third function kwd_only_arg only allows keyword arguments as indicated by a * in the function definition: >>> kwd_only_arg ( 3 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : kwd_only_arg() takes 0 positional arguments but 1 was given >>> kwd_only_arg ( arg = 3 ) 3 And the last uses all three calling conventions in the same function definition: >>> combined_example ( 1 , 2 , 3 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : combined_example() takes 2 positional arguments but 3 were given >>> combined_example ( 1 , 2 , kwd_only = 3 ) 1 2 3 >>> combined_example ( 1 , standard = 2 , kwd_only = 3 ) 1 2 3 >>> combined_example ( pos_only = 1 , standard = 2 , kwd_only = 3 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : combined_example() got some positional-only arguments passed as keyword arguments: 'pos_only' Finally, consider this function definition which has a potential collision between the positional argument name and **kwds which has name as a key: def foo ( name , ** kwds ): return 'name' in kwds There is no possible call that will make it return True as the keyword 'name' will always bind to the first parameter. For example: >>> foo ( 1 , ** { 'name' : 2 }) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : foo() got multiple values for argument 'name' >>> But using / (positional only arguments), it is possible since it allows name as a positional argument and 'name' as a key in the keyword arguments: >>> def foo ( name , / , ** kwds ): ... return 'name' in kwds ... >>> foo ( 1 , ** { 'name' : 2 }) True In other words, the names of positional-only parameters can be used in **kwds without ambiguity. 4.9.3.5. Recap ¶ The use case will determine which parameters to use in the function definition: def f ( pos1 , pos2 , / , pos_or_kwd , * , kwd1 , kwd2 ): As guidance: Use positional-only if you want the name of the parameters to not be available to the user. This is useful when parameter names have no real meaning, if you want to enforce the order of the arguments when the function is called or if you need to take some positional parameters and arbitrary keywords. Use keyword-only when names have meaning and the function definition is more understandable by being explicit with names or you want to prevent users relying on the position of the argument being passed. For an API, use positional-only to prevent breaking API changes if the parameter’s name is modified in the future. 4.9.4. Arbitrary Argument Lists ¶ Finally, the least frequently used option is to specify that a function can be called with an arbitrary number of arguments. These arguments will be wrapped up in a tuple (see Tuples and Sequences ). Before the variable number of arguments, zero or more normal arguments may occur. def write_multiple_items ( file , separator , * args ): file . write ( separator . join ( args )) Normally, these variadic arguments will be last in the list of formal parameters, because they scoop up all remaining input arguments that are passed to the function. Any formal parameters which occur after the *args parameter are ‘keyword-only’ arguments, meaning that they can only be used as keywords rather than positional arguments. >>> def concat ( * args , sep = "/" ): ... return sep . join ( args ) ... >>> concat ( "earth" , "mars" , "venus" ) 'earth/mars/venus' >>> concat ( "earth" , "mars" , "venus" , sep = "." ) 'earth.mars.venus' 4.9.5. Unpacking Argument Lists ¶ The reverse situation occurs when the arguments are already in a list or tuple but need to be unpacked for a function call requiring separate positional arguments. For instance, the built-in range() function expects separate start and stop arguments. If they are not available separately, write the function call with the * -operator to unpack the arguments out of a list or tuple: >>> list ( range ( 3 , 6 )) # normal call with separate arguments [3, 4, 5] >>> args = [ 3 , 6 ] >>> list ( range ( * args )) # call with arguments unpacked from a list [3, 4, 5] In the same fashion, dictionaries can deliver keyword arguments with the ** -operator: >>> def parrot ( voltage , state = 'a stiff' , action = 'voom' ): ... print ( "-- This parrot wouldn't" , action , end = ' ' ) ... print ( "if you put" , voltage , "volts through it." , end = ' ' ) ... print ( "E's" , state , "!" ) ... >>> d = { "voltage" : "four million" , "state" : "bleedin' demised" , "action" : "VOOM" } >>> parrot ( ** d ) -- This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised ! 4.9.6. Lambda Expressions ¶ Small anonymous functions can be created with the lambda keyword. This function returns the sum of its two arguments: lambda a, b: a+b . Lambda functions can be used wherever function objects are required. They are syntactically restricted to a single expression. Semantically, they are just syntactic sugar for a normal function definition. Like nested function definitions, lambda functions can reference variables from the containing scope: >>> def make_incrementor ( n ): ... return lambda x : x + n ... >>> f = make_incrementor ( 42 ) >>> f ( 0 ) 42 >>> f ( 1 ) 43 The above example uses a lambda expression to return a function. Another use is to pass a small function as an argument. For instance, list.sort() takes a sorting key function key which can be a lambda function: >>> pairs = [( 1 , 'one' ), ( 2 , 'two' ), ( 3 , 'three' ), ( 4 , 'four' )] >>> pairs . sort ( key = lambda pair : pair [ 1 ]) >>> pairs [(4, 'four'), (1, 'one'), (3, 'three'), (2, 'two')] 4.9.7. Documentation Strings ¶ Here are some conventions about the content and formatting of documentation strings. The first line should always be a short, concise summary of the object’s purpose. For brevity, it should not explicitly state the object’s name or type, since these are available by other means (except if the name happens to be a verb describing a function’s operation). This line should begin with a capital letter and end with a period. If there are more lines in the documentation string, the second line should be blank, visually separating the summary from the rest of the description. The following lines should be one or more paragraphs describing the object’s calling conventions, its side effects, etc. The Python parser strips indentation from multi-line string literals when they serve as module, class, or function docstrings. Here is an example of a multi-line docstring: >>> def my_function (): ... """Do nothing, but document it. ... ... No, really, it doesn't do anything: ... ... >>> my_function() ... >>> ... """ ... pass ... >>> print ( my_function . __doc__ ) Do nothing, but document it. No, really, it doesn't do anything: >>> my_function() >>> 4.9.8. Function Annotations ¶ Function annotations are completely optional metadata information about the types used by user-defined functions (see PEP 3107 and PEP 484 for more information). Annotations are stored in the __annotations__ attribute of the function as a dictionary and have no effect on any other part of the function. Parameter annotations are defined by a colon after the parameter name, followed by an expression evaluating to the value of the annotation. Return annotations are defined by a literal -> , followed by an expression, between the parameter list and the colon denoting the end of the def statement. The following example has a required argument, an optional argument, and the return value annotated: >>> def f ( ham : str , eggs : str = 'eggs' ) -> str : ... print ( "Annotations:" , f . __annotations__ ) ... print ( "Arguments:" , ham , eggs ) ... return ham + ' and ' + eggs ... >>> f ( 'spam' ) Annotations: {'ham': <class 'str'>, 'return': <class 'str'>, 'eggs': <class 'str'>} Arguments: spam eggs 'spam and eggs' 4.10. Intermezzo: Coding Style ¶ Now that you are about to write longer, more complex pieces of Python, it is a good time to talk about coding style . Most languages can be written (or more concise, formatted ) in different styles; some are more readable than others. Making it easy for others to read your code is always a good idea, and adopting a nice coding style helps tremendously for that. For Python, PEP 8 has emerged as the style guide that most projects adhere to; it promotes a very readable and eye-pleasing coding style. Every Python developer should read it at some point; here are the most important points extracted for you: Use 4-space indentation, and no tabs. 4 spaces are a good compromise between small indentation (allows greater nesting depth) and large indentation (easier to read). Tabs introduce confusion, and are best left out. Wrap lines so that they don’t exceed 79 characters. This helps users with small displays and makes it possible to have several code files side-by-side on larger displays. Use blank lines to separate functions and classes, and larger blocks of code inside functions. When possible, put comments on a line of their own. Use docstrings. Use spaces around operators and after commas, but not directly inside bracketing constructs: a = f(1, 2) + g(3, 4) . Name your classes and functions consistently; the convention is to use UpperCamelCase for classes and lowercase_with_underscores for functions and methods. Always use self as the name for the first method argument (see A First Look at Classes for more on classes and methods). Don’t use fancy encodings if your code is meant to be used in international environments. Python’s default, UTF-8, or even plain ASCII work best in any case. Likewise, don’t use non-ASCII characters in identifiers if there is only the slightest chance people speaking a different language will read or maintain the code. Footnotes [ 1 ] Actually, call by object reference would be a better description, since if a mutable object is passed, the caller will see any changes the callee makes to it (items inserted into a list). Table of Contents 4. More Control Flow Tools 4.1. if Statements 4.2. for Statements 4.3. The range() Function 4.4. break and continue Statements 4.5. else Clauses on Loops 4.6. pass Statements 4.7. match Statements 4.8. Defining Functions 4.9. More on Defining Functions 4.9.1. Default Argument Values 4.9.2. Keyword Arguments 4.9.3. Special parameters 4.9.3.1. Positional-or-Keyword Arguments 4.9.3.2. Positional-Only Parameters 4.9.3.3. Keyword-Only Arguments 4.9.3.4. Function Examples 4.9.3.5. Recap 4.9.4. Arbitrary Argument Lists 4.9.5. Unpacking Argument Lists 4.9.6. Lambda Expressions 4.9.7. Documentation Strings 4.9.8. Function Annotations 4.10. Intermezzo: Coding Style Previous topic 3. An Informal Introduction to Python Next topic 5. Data Structures This page Report a bug Show source « Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Tutorial » 4. More Control Flow Tools | Theme Auto Light Dark | © Copyright 2001 Python Software Foundation. This page is licensed under the Python Software Foundation License Version 2. Examples, recipes, and other code in the documentation are additionally licensed under the Zero Clause BSD License. See History and License for more information. The Python Software Foundation is a non-profit corporation. Please donate. 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Navigation Python SDK Trigger Workflow from API Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog Python SDK Trigger Workflow from API OpenAI Open in ChatGPT Learn how to trigger workflows using direct workflow API, with code snippets and examples. OpenAI Open in ChatGPT It is a unified API to trigger workflow and doesn’t require user creation before hand to trigger notification. Recommended for platforms transitioning their existing notifications to SuprSend. If you are using our frontend SDKs to configure notifications and passing events and user properties from third-party data platforms like Segment, then event-based trigger would be a better choice. 📘 Available in SDK version >= v0.11.0 Payload Schema Sample Payload Response Copy Ask AI from suprsend import Event from suprsend import WorkflowTriggerRequest supr_client = Suprsend( "_workspace_key_" , "_workspace_secret_" ) # Prepare workflow payload w1 = WorkflowTriggerRequest( body = { "workflow" : "_workflow_slug_" , "actor" : { "distinct_id" : "0fxxx8f74-xxxx-41c5-8752-xxxcb6911fb08" , "name" : "actor_1" , "$skip_create" : true, }, "recipients" : [ # notify user { "distinct_id" : "0gxxx9f14-xxxx-23c5-1902-xxxcb6912ab09" , "$email" : [ " [email protected] " ], "name" : "recipient_1" , "$preferred_language" : "en" , "$timezone" : "America/New_York" , "$skip_create" : true, }, # notify object { "object_type" : "teams" , "id" : "finance" , "$skip_create" : true}, ], "data" : { "first_name" : "User" , "invoice_amount" : "$5000" , "invoice_id" : "Invoice-1234" , }, }, tenant_id = "tenant_id1" , idempotency_key = "_unique_identifier_of_the_request_" , ) # Trigger workflow response = supr_client.workflows.trigger(w1) print (response) To prevent automatic creation of an actor, or recipient (user/object) in SuprSend (the case where they already exist in your system), you can use the "$skip_create": true flag. This can be applied inside the actor, individual user recipient objects, or object recipient objects. Once your request is accepted, you can check the status of your request on SuprSend Logs page. Property Type Description workflow string Slug of the designed workflow on the SuprSend dashboard. You’ll get the slug from workflow settings. actor (optional) string / object Includes distinct_id and properties of the user who performed the action. Used for cross-user notifications , where you need to include actor properties in the notification template. Actor properties can be added as $actor.<prop> . recipients array of string / array of objects List of users who need to be notified. You can add up to 100 recipients in a workflow trigger. Recipients can be passed as an array of distinct_ID (if the user is pre-synced in the SuprSend database) or defined inline . data object Variable data required to render dynamic template content or workflow properties such as dynamic delay or channel override in the send node. tenant_id string Unique identifier of the brand / tenant . idempotency_key string Unique identifier of the request. It will be returned in the outbound webhook response . You can use it to map notification statuses and replies in your system. recipients[].$timezone string Used to set the recipient’s timezone. Allows sending notifications in the user’s local timezone. Pass the timezone in IANA (TZ identifier) format. recipients[].$preferred_language string Used to set the recipient’s preferred language. Sending notification to multiple recipients Recipients in workflow call is an array of distinct_ids or recipient objects. You can pass up to 100 recipients in a single workflow trigger. SuprSend will internally convert it into multiple workflow triggers, one for each recipient in the array. json Copy Ask AI "recipients" : [ { "distinct_id" : "id1" , "$email" :[ " [email protected] " ], "name" : "recipient_1" }, { "distinct_id" : "id1" , "$email" :[ " [email protected] " ], "name" : "recipient_2" } ] ---- OR ------ "recipients" : [ "id1" , "id2" ] 📘 Use lists to broadcast to a large list of users: We recommend you to use lists and broadcasts to send notifications to a user list larger than 1000 users. This approach allows for bulk processing within SuprSend, resulting in significantly faster delivery compared to individual workflow calls. Sending individual workflows to a large set of users may introduce delays in your notification queue and is not an optimized way of handling bulk trigger. Identifying recipients inline One of the benefits of using direct workflow trigger is that you can identify recipients inline. You can include recipient channel information, their channel preferences, and their user properties along with the workflow trigger. Upon triggering the workflow, the recipient will be automatically created in the SuprSend database in the background. This facilitates dynamic synchronization of your user data within SuprSend and eliminates the need for any migration efforts on your end to start sending notifications from SuprSend. You can also use recipient properties in your template as $recipient.<property> . This is how the complete recipient object with look like json Copy Ask AI { "distinct_id" : "0gxxx9f14-xxxx-23c5-1902-xxxcb6912ab09" , "$email" :[ " [email protected] " ], "$channels" :[ "email" , "inbox" ], "user_prop1" : "value_1" , "$preferred_language" : "en" , "$timezone" : "America/New_York" } Property Type Description distinct_id string Unique identifier of the user to be notified. $<channel> (e.g. $sms ) array of string / objects You can pass user channel information using $<channel> key. The channel info will be updated in the user profile in the background. For this workflow, only channel values specified in this key will be used for sending notifications (instead of all channel values present in the user profile). Refer to how different communication channels can be passed here . $channels array of string Use it to pass the user’s channel preference in the payload. You can always use our in-built preference APIs to maintain user notification preferences. Preferences defined within SuprSend will automatically apply with the workflow trigger. By default, notifications will be sent to all channels defined in the workflow delivery node. However, if the user has a specific channel preference for a notification (e.g. only wants to receive payment reminders via email), you can include that preference in the workflow payload. This ensures notifications are sent only to the channels specified in the $channels key. Supported channel values: email, sms, whatsapp, androidpush, iospush, slack, webpush, ms_teams . $preferred_language string To set the recipient’s preferred language. This supports localization in notification content. Pass the language in ISO 639-1 2-letter format. Refer to all language codes here . $timezone string To set the recipient’s timezone. Used to send notifications in the user’s local timezone. Pass the timezone in IANA (TZ identifier) format. * key-value pair You can pass other user properties to render dynamic template content in key-value pairs like "user_prop1": "value1" . Extra properties will be set in the subscriber profile (as subscriber properties), which can then be used in the template as $recipient.<property> . Add user communication channel json Copy Ask AI "$email" :[ " [email protected] " ], "$whatsapp" :[ "+15555555555" ], "$sms" :[ "+15555555555" ], "$androidpush" : [{ "token" : "__android_push_token__" , "provider" : "fcm" , "device_id" : "" }], "$iospush" :[{ "token" : "__ios_push_token__" , "provider" : "apns" , "device_id" : "" }], "$slack" : [{ "email" : " [email protected] " , "access_token" : "xoxb-XXXXXXXX" }] // slack using email "$slack" : [{ "user_id" : "U/WXXXXXXXX" , "access_token" : "xoxb-XXXXXX" }] // slack using member_id "$slack" : [{ "channel" : "CXXXXXXXX" , "access_token" : "xoxb-XXXXXX" }] // slack channel "$slack" : [{ "incoming_webhook" : { "url" : "https://hooks.slack.com/services/TXXXX/BXXXX/XXXXXXX" } }] // slack incoming webhook "$ms_teams" : [{ "tenant_id" : "c1981ab2-9aaf-xxxx-xxxx" , "service_url" : "https://smba.trafficmanager.net/amer" , "conversation_id" : "19:c1524d7c-a06f-456f-8abe-xxxx" }] // MS teams user or channel using conversation_id "$ms_teams" : [{ "tenant_id" : "c1981ab2-9aaf-xxxx-xxxx" , "service_url" : "https://smba.trafficmanager.net/amer" , "user_id" : "29:1nsLcmJ2RKtYH6Cxxxx-xxxx" }] // MS teams user using user_id "$ms_teams" : [{ "incoming_webhook" : { "url" : "https://wnk1z.webhook.office.com/webhookb2/XXXXXXXXX" } }] // MS teams incoming webhook Sending cross-user notifications In scenarios where you need to notify a group of users based on another user’s action, such as sending a notification to the document owner when someone comments on it, you can specify the actor in your workflow call. This allows you to use actor’s name or other properties in your notification template. Actor properties can be included in the template as $actor.<property> . Sample template with actor and recipient properties: text Copy Ask AI //handlebar template Hi {{$recipient.name}}, {{$actor.name}} added {{length comments}} new comments on the {{doc_name}}. //Rendered content Hi recipient_1, actor_1 added 2 new comments on the annual IT report. Sample workflow body Copy Ask AI { "workflow" : "new_comment" , "actor" : { "distinct_id" : "0fxxx8f74-xxxx-41c5-8752-xxxcb6911fb08" , "name" : "actor_1" }, "recipients" : [ { "distinct_id" : "0gxxx9f14-xxxx-23c5-1902-xxxcb6912ab09" , "$email" :[ " [email protected] ""], " name ":" recipient_ 1 " } ], " data ":{ " doc_name ": " annual IT report ", " date ": " 2024-01-01 ", " comments ":[" change the date "," rest looks good "] } } Sending notification to anonymous user You can send notifications to anonymous users by passing "is_transient": True in your recipient object. This approach is recommended for scenarios where you need to send notifications to unregistered users without creating them in the SuprSend platform. The same way, you can pass "is_transient": True in your actor object to use actor properties in template without creating user profile. Request Copy Ask AI from suprsend import Event from suprsend import WorkflowTriggerRequest supr_client = Suprsend( "_workspace_key_" , "_workspace_secret_" ) # Prepare workflow payload w1 = WorkflowTriggerRequest( body = { "workflow" : "_workflow_slug_" , "actor" : { "is_transient" : True , "name" : "actor_1" }, "recipients" : [ { "is_transient" : True , "$email" :[ " [email protected] " ], "name" : "recipient_1" } ], "data" :{ "first_name" : "User" , "invoice_amount" : "$5000" , "invoice_id" : "Invoice-1234" } }, tenant_id = "tenant_id1" , idempotency_key = "_unique_identifier_of_the_request_" ) # Trigger workflow response = supr_client.workflows.trigger(w1) print (response) Multi-tenant notifications For use cases where you want to send notifications to your enterprise customers’ end users, pass the tenant_id in your workflow instance. You can use this to dynamically manage tenant level notification customizations . This includes the ability to customize template design or content and route notifications via tenant vendors. Request Copy Ask AI from suprsend import Event from suprsend import WorkflowTriggerRequest supr_client = Suprsend( "_workspace_key_" , "_workspace_secret_" ) # Prepare workflow payload w1 = WorkflowTriggerRequest( body = { ... }, tenant_id = "tenant_id1" , idempotency_key = "_unique_identifier_of_the_request_" ) # Trigger workflow response = supr_client.workflows.trigger(w1) print (response) Idempotent requests SuprSend supports idempotency to ensure that requests can be retried safely without duplicate processing. If Suprsend receives and processes a request with an idempotency_key, it will skip processing requests with same idempotency_key for next 24 hours. Idempotency key should be uniquely generated for each request (max 255 characters allowed). Spaces in start and end of the key will be trimmed. Here are some common approaches for generating idempotency keys: Generate a random UUID for each request. Construct the idempotency key by combining relevant information about the request . This can include parameters, identifiers, or specific contextual details that are meaningful within your application. e.g., you could concatenate the user ID, action, and timestamp to form an idempotency key like user147-new-comment-1687437670 Request-specific Identifier : If your request already contains a unique identifier, such as an order ID or a job ID, you can use that identifier directly as the idempotency key. Bulk trigger multiple workflows Bulk API allows you to send multiple workflow requests in a single call. There isn’t any limit on number-of-records that can be added to bulk_workflows instance. Use .append() on workflows.bulk_trigger_instance() instance to add however-many-records to call in bulk. Request Response Copy Ask AI from suprsend import Event from suprsend import WorkflowTriggerRequest supr_client = Suprsend( "_workspace_key_" , "_workspace_secret_" ) # Workflow: 1 w1 = WorkflowTriggerRequest( body = { ... }, tenant_id = "tenant_id1" , idempotency_key = "_unique_identifier_of_the_request_" ) # Workflow: 2 w2 = WorkflowTriggerRequest( body = { ... } ) # ...... Add as many Workflow records as required. bulk_ins = supr_client.workflows.bulk_trigger_instance() bulk_ins.append(w1,w2) # Trigger workflow response = bulk_ins.trigger() print (response) Add file attachment in email To add one or more Attachments to a Notification (viz. Email), call wf_instance.add_attachment() for each file with local-path. Ensure that file_path is proper, otherwise it will raise FileNotFoundError. Request Copy Ask AI from suprsend import Workflow workflow_body = { ... } wf_instance = Workflow( body = workflow_body) # this snippet can be used to add attachment to workflow file_path = "/home/user/billing.pdf" wf_instance.add_attachment(file_path) A single workflow body size (including attachment) must not exceed 800KB (800 x 1024 bytes). Dynamic workflow trigger You can trigger workflow from python SDK using supr_client.trigger_workflow method. The SDK internally makes an HTTP call to SuprSend Platform to register this request, and you’ll immediately receive a response indicating the acceptance status. Note: The actual processing/execution of workflow happens asynchronously. Once your request is accepted, you can check the status of your request in the ’ SuprSend Logs ’ section. Request Response Copy Ask AI from suprsend import Workflow # Prepare Workflow body workflow_body = { "name" : "workflow_name" , "template" : "template_slug" , "notification_category" : "notification_category" , # notification category transactional/promotional/system "delay" : "time_delay" , # time delay after which the first notification will be sent "trigger_at" : "date string in ISO 8601" , #to trigger scheduled notifications "users" : [ { "distinct_id" : "distinct_id" , # unique identifier of the user # if $channels is present, communication will be triggered on mentioned channels only. # "$channels": ["email"], # User communication channel can be added as [optional]: # "$email":[" [email protected] "], # "$whatsapp":["+15555555555"], # "$sms":["+15555555555"], # "$androidpush": [{"token": "__android_push_token__", "provider": "fcm", "device_id": ""}], # "$iospush":[{"token": "__ios_push_token__", "provider": "apns", "device_id": ""}], # "$slack": { # "email": " [email protected] ", # "access_token": "xoxb-XXXXXXXX" #} --- slack using email # "$slack": { # "user_id": "U/WXXXXXXXX", # "access_token": "xoxb-XXXXXX" #} --- slack using member_id # "$slack": { # "channel": "CXXXXXXXX", # "access_token": "xoxb-XXXXXX" #} --- slack channel # "$slack": { # "incoming_webhook": { # "url": "https://hooks.slack.com/services/TXXXX/BXXXX/XXXXXXX" # } #} --- slack incoming webhook # "$ms_teams": { #"tenant_id": "c1981ab2-9aaf-xxxx-xxxx", #"service_url": "https://smba.trafficmanager.net/amer", #"conversation_id": "19:c1524d7c-a06f-456f-8abe-xxxx" #} --- MS teams user or channel using conversation_id # "$ms_teams": { #"tenant_id": "c1981ab2-9aaf-xxxx-xxxx", #"service_url": "https://smba.trafficmanager.net/amer", #"user_id": "29:1nsLcmJ2RKtYH6Cxxxx-xxxx" #} --- MS teams user using user_id # "$ms_teams": { # "incoming_webhook": { # "url": "https://wnk1z.webhook.office.com/webhookb2/XXXXXXXXX" # } #} --- MS teams incoming webhook } ], # delivery instruction [optional]. how should notifications be sent, and whats the success metric "delivery" : { "smart" : < boolean_value > , "success" : "success_metric" , "time_to_live" : "TTL duration" , # will be applicable for smart = TRUE "mandatory_channels" : [] # list of mandatory channels e.g ["email"], will be applicable for smart = TRUE }, # data can be any json / serializable python-dictionary "data" : { "key" : "value" , "nested_key" : { "nested_key1" : "some_value_1" , "nested_key2" : { "nested_key3" : "some_value_3" , }, } } } wf = Workflow( body = workflow_body, idempotency_key = "__uniq_request_id__" , brand_id = "default" ) # Trigger workflow response = supr_client.trigger_workflow(wf) print (response) For configuring a workflow from backend, you can pass following properties in your method Parameter Description Format Obligation name It is the unique name of the workflow. You can see workflow-related analytics on the workflow page (how many notifications were sent, delivered, clicked, or interacted). The workflow name should be easily identifiable for your reference at a later stage. text Mandatory template It is the unique slug of the template created on the SuprSend platform. You can get this slug by clicking on the clipboard icon next to the Template name on the SuprSend templates page. It is the same for all channels. slug name Mandatory notification_category You can understand more about them in the Notification Category documentation. system / transactional / promotional Mandatory delay Workflow will be halted for the time mentioned in delay and becomes active once the delay period is over. **XX**d**XX**h**XX**m**XX**s or if it’s a number ( n ), then delay is in seconds ( n ). Optional trigger_at Trigger workflow on a specific date-time. Date string in ISO 8601 format e.g. "2021-08-27T20:14:51.643Z" Optional users Array object of target users. At least 1 user mandatory. distinct_id for each user is mandatory. You can pass up to 100 entries in the users array. Channel information is non-mandatory. If you pass channel information here, then these channels will be used for sending notifications; otherwise, channels will be picked from the user profile. json"users": [ { "distinct_id": "value", "$channels": [], channel_information_dict #(optional) } ] Mandatory delivery Delivery instructions for the workflow. You can enable smart delivery by setting "smart": True .By default, the delivery instruction will be: json"delivery": { "smart": False, "success": "seen" } Further details are given in the below section . json"delivery": { "smart": True/False, "success": "delivered/seen/interaction/<some-user-defined-success-event>", "time_to_live": "<TTL duration>", "mandatory_channels": [] } Optional data JSON. To replace variables in the template, templates use the handlebars language. json "data": { "key": { "key": "value", "key": "value" } } Optional brand_id Brand_id of the tenant to trigger a notification on behalf of your tenants. string Optional idempotency_key Unique key in the request call for idempotent requests . string Optional +CountryCode Required for SMS and Whatsapp: For setting $sms and $whatsapp , +<countrycode> is mandatory to send along with phone number. Eg: +1 for US To find the template slug name on SuprSend platform, click on the clipboard icon on Templates page. Templates > Template Details Page Bulk API for triggering multiple workflows Bulk API allows you to send multiple workflow requests in a single call. There isn’t any limit on number-of-records that can be added to bulk_workflows instance. Use .append() on bulk_workflows instance to add however-many-records to call in bulk. Request Response Copy Ask AI from suprsend import Workflow bulk_ins = supr_client.bulk_workflows.new_instance() # one or more workflow instances workflow1 = Workflow( body = { ... }) # body must be a proper workflow request json/dict workflow2 = Workflow( body = { ... }) # body must be a proper workflow request json/dict # --- use .append on bulk instance to add one or more records bulk_ins.append(workflow1) bulk_ins.append(workflow2) # OR bulk_ins.append(workflow1, workflow2) # ------- response = bulk_ins.trigger() print (response) Was this page helpful? Yes No Suggest edits Raise issue Previous Tenants Learn how to create, update, fetch, & list tenants using Python SDK. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Beginners Follow Hide "A journey of a thousand miles begins with a single step." -Chinese Proverb Create Post submission guidelines UPDATED AUGUST 2, 2019 This tag is dedicated to beginners to programming, development, networking, or to a particular language. Everything should be geared towards that! For Questions... Consider using this tag along with #help, if... You are new to a language, or to programming in general, You want an explanation with NO prerequisite knowledge required. You want insight from more experienced developers. Please do not use this tag if you are merely new to a tool, library, or framework. See also, #explainlikeimfive For Articles... Posts should be specifically geared towards true beginners (experience level 0-2 out of 10). 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Right menu You Know Python Basics—Now Let's Build Something Real Samuel Ochaba Samuel Ochaba Samuel Ochaba Follow Jan 8 You Know Python Basics—Now Let's Build Something Real # python # beginners # gamedev # programming Comments Add Comment 3 min read Understanding if, elif, and else in Python with Simple Examples Shahrouz Nikseresht Shahrouz Nikseresht Shahrouz Nikseresht Follow Jan 8 Understanding if, elif, and else in Python with Simple Examples # python # beginners # tutorial # programming Comments Add Comment 2 min read Build Your Own Local AI Agent (Part 4): The PII Scrubber 🧼 Harish Kotra (he/him) Harish Kotra (he/him) Harish Kotra (he/him) Follow Jan 8 Build Your Own Local AI Agent (Part 4): The PII Scrubber 🧼 # programming # ai # beginners # opensource Comments Add Comment 1 min read I finally Deployed on AWS Olamide Olanrewaju Olamide Olanrewaju Olamide Olanrewaju Follow Jan 8 I finally Deployed on AWS # aws # beginners # devjournal Comments Add Comment 3 min read System Design Intro #Day-1 VINAY TEJA ARUKALA VINAY TEJA ARUKALA VINAY TEJA ARUKALA Follow Jan 9 System Design Intro #Day-1 # systemdesign # beginners # computerscience # interview Comments Add Comment 2 min read Day 12: Understanding Constructors in Java Karthick Narayanan Karthick Narayanan Karthick Narayanan Follow Jan 8 Day 12: Understanding Constructors in Java # java # programming # beginners # tutorial Comments Add Comment 2 min read 7 Essential Rust Libraries for Building High-Performance Backends James Miller James Miller James Miller Follow Jan 8 7 Essential Rust Libraries for Building High-Performance Backends # rust # programming # webdev # beginners 1 reaction Comments Add Comment 6 min read Day 11: Understanding `break` and `continue` Statements in Java Karthick Narayanan Karthick Narayanan Karthick Narayanan Follow Jan 8 Day 11: Understanding `break` and `continue` Statements in Java # beginners # java # programming # tutorial Comments Add Comment 2 min read Introdução ao Deploy Yuri Peixinho Yuri Peixinho Yuri Peixinho Follow Jan 8 Introdução ao Deploy # beginners # devops # webdev Comments Add Comment 2 min read Scrapy Cookie Handling: Master Sessions Like a Pro Muhammad Ikramullah Khan Muhammad Ikramullah Khan Muhammad Ikramullah Khan Follow Jan 8 Scrapy Cookie Handling: Master Sessions Like a Pro # webdev # programming # python # beginners Comments Add Comment 7 min read Gear Up for React: Mastering the Modern Frontend Toolkit! (Day 3 – Pre-React Article 3) Vasu Ghanta Vasu Ghanta Vasu Ghanta Follow Jan 8 Gear Up for React: Mastering the Modern Frontend Toolkit! (Day 3 – Pre-React Article 3) # webdev # frontend # react # beginners Comments Add Comment 7 min read Day 9 of 100 Palak Hirave Palak Hirave Palak Hirave Follow Jan 8 Day 9 of 100 # challenge # programming # python # beginners Comments Add Comment 2 min read Why Version Control Exists: The Pendrive Problem Debashis Das Debashis Das Debashis Das Follow Jan 8 Why Version Control Exists: The Pendrive Problem # beginners # git # softwaredevelopment Comments Add Comment 3 min read System Design 101: A Clear & Simple Introduction (With a Real-World Analogy) Vishwark Vishwark Vishwark Follow Jan 8 System Design 101: A Clear & Simple Introduction (With a Real-World Analogy) # systemdesign # architecture # beginners # careerdevelopment Comments Add Comment 3 min read Learning the Foliage Tool in Unreal Engine (Day 13) Dinesh Dinesh Dinesh Follow Jan 8 Learning the Foliage Tool in Unreal Engine (Day 13) # gamedev # unrealengine # beginners # learning Comments Add Comment 2 min read Boot Process & Init Systems Shivakumar Shivakumar Shivakumar Follow Jan 8 Boot Process & Init Systems # architecture # beginners # linux Comments Add Comment 6 min read You Probably Already Know What a Monad Is Christian Ekrem Christian Ekrem Christian Ekrem Follow Jan 8 You Probably Already Know What a Monad Is # programming # frontend # functional # beginners Comments Add Comment 1 min read Course Launch: Writing Is an Important Part of Coding Prasoon Jadon Prasoon Jadon Prasoon Jadon Follow Jan 8 Course Launch: Writing Is an Important Part of Coding # programming # learning # tutorial # beginners 1 reaction Comments Add Comment 2 min read I built a permanent text wall with Next.js and Supabase. Users are already fighting. ZenomHunter123 ZenomHunter123 ZenomHunter123 Follow Jan 8 I built a permanent text wall with Next.js and Supabase. Users are already fighting. # showdev # javascript # webdev # beginners Comments Add Comment 1 min read 🎬 Build a Relax Video Generator (Images + MP3 MP4) with Python & Tkinter Mate Technologies Mate Technologies Mate Technologies Follow Jan 11 🎬 Build a Relax Video Generator (Images + MP3 MP4) with Python & Tkinter # python # desktopapp # automation # beginners 1 reaction Comments Add Comment 3 min read Code Hike in 100 Seconds Fabian Frank Werner Fabian Frank Werner Fabian Frank Werner Follow Jan 11 Code Hike in 100 Seconds # webdev # programming # javascript # beginners 12 reactions Comments Add Comment 2 min read Sliding window (Fixed length) Jayaprasanna Roddam Jayaprasanna Roddam Jayaprasanna Roddam Follow Jan 6 Sliding window (Fixed length) # programming # beginners # tutorial # learning Comments Add Comment 2 min read How To Replace Over-Complicated NgRx Stores With Angular Signals — Without Losing Control kafeel ahmad kafeel ahmad kafeel ahmad Follow Jan 7 How To Replace Over-Complicated NgRx Stores With Angular Signals — Without Losing Control # webdev # javascript # beginners # angular Comments Add Comment 27 min read AI Automation vs AI Agents: What’s the Real Difference (Explained with Real-Life Examples) Viveka Sharma Viveka Sharma Viveka Sharma Follow Jan 8 AI Automation vs AI Agents: What’s the Real Difference (Explained with Real-Life Examples) # agents # tutorial # beginners # ai 1 reaction Comments 1 comment 3 min read Why I rescheduled my AWS exam today Ali-Funk Ali-Funk Ali-Funk Follow Jan 7 Why I rescheduled my AWS exam today # aws # beginners # cloud # career Comments Add Comment 2 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close # documentation Follow Hide Improving and writing documentation Create Post Older #documentation posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu How I Turned Slack Messages Into Documentation Daisy Auma Daisy Auma Daisy Auma Follow Jan 13 How I Turned Slack Messages Into Documentation # devrel # documentation Comments Add Comment 5 min read Mother CLAUDE: How We Built a Documentation System That Makes LLMs Productive Immediately Dorothy J Aubrey Dorothy J Aubrey Dorothy J Aubrey Follow Jan 10 Mother CLAUDE: How We Built a Documentation System That Makes LLMs Productive Immediately # ai # productivity # documentation # devrel 6 reactions Comments 1 comment 8 min read Better Docs, Less Effort: Using The Continue MCP Cookbook Anita Ihuman 🌼 Anita Ihuman 🌼 Anita Ihuman 🌼 Follow Jan 12 Better Docs, Less Effort: Using The Continue MCP Cookbook # ai # documentation # opensource Comments Add Comment 5 min read Five Patterns for Building Self-Updating Documentation Stella Achar Oiro Stella Achar Oiro Stella Achar Oiro Follow Jan 12 Five Patterns for Building Self-Updating Documentation # architecture # automation # devops # documentation Comments Add Comment 6 min read Making Retype Docs AI-Ready with llms.txt Automation zakaria chahboun zakaria chahboun zakaria chahboun Follow Jan 10 Making Retype Docs AI-Ready with llms.txt Automation # documentation # githubactions # markdown # devops Comments Add Comment 2 min read LINE Bot Developer Guide: Other Related Features Evan Lin Evan Lin Evan Lin Follow Jan 11 LINE Bot Developer Guide: Other Related Features # documentation # tutorial # api # programming Comments Add Comment 7 min read Anyone else feel like they spend more time finding information than writing code? Kumar Kislay Kumar Kislay Kumar Kislay Follow Jan 11 Anyone else feel like they spend more time finding information than writing code? # discuss # documentation # career # productivity Comments Add Comment 1 min read I Got Tired of Outdated DB Diagrams, So I Built a Tool That Understands Schemas Instead Rushikesh Bodakhe Rushikesh Bodakhe Rushikesh Bodakhe Follow Jan 12 I Got Tired of Outdated DB Diagrams, So I Built a Tool That Understands Schemas Instead # showdev # database # documentation # tooling 1 reaction Comments Add Comment 2 min read Kong's 7% AI Accuracy Gain Didn't Come From Better Models jedrzejdocs jedrzejdocs jedrzejdocs Follow Jan 9 Kong's 7% AI Accuracy Gain Didn't Come From Better Models # documentation # ai # devtools # techwriting 5 reactions Comments Add Comment 4 min read How do you keep engineering context alive when requirements change? Post: Kumar Kislay Kumar Kislay Kumar Kislay Follow Jan 11 How do you keep engineering context alive when requirements change? Post: # discuss # documentation # productivity 1 reaction Comments Add Comment 1 min read 📘 Adopting a Documentation Framework: A Practical Guide for Tech Teams Nassbin Nassbin Nassbin Follow Jan 9 📘 Adopting a Documentation Framework: A Practical Guide for Tech Teams # documentation # diataxis # teams Comments Add Comment 3 min read Digital Twin Documentation Doesn't Scale - Here's Why Ronny Elsner Ronny Elsner Ronny Elsner Follow Jan 8 Digital Twin Documentation Doesn't Scale - Here's Why # discuss # automation # documentation Comments Add Comment 5 min read How to Make AI Reconstruct Context Without Memory synthaicode synthaicode synthaicode Follow Jan 6 How to Make AI Reconstruct Context Without Memory # documentation # ai # productivity Comments Add Comment 3 min read # Why I Chose Mintlify (And What I Wish I Knew Earlier) Daisy Auma Daisy Auma Daisy Auma Follow Jan 5 # Why I Chose Mintlify (And What I Wish I Knew Earlier) # discuss # documentation # tooling Comments Add Comment 5 min read How I Can Still Consult AI About Decisions Made Two Months Ago synthaicode synthaicode synthaicode Follow Jan 5 How I Can Still Consult AI About Decisions Made Two Months Ago # ai # productivity # programming # documentation Comments Add Comment 3 min read Translating a Complex Object Detection Model for Sales Teams: An AI Documentation Case Study Ebikara Spiff ᴀɪᴄᴍᴄ Ebikara Spiff ᴀɪᴄᴍᴄ Ebikara Spiff ᴀɪᴄᴍᴄ Follow Jan 5 Translating a Complex Object Detection Model for Sales Teams: An AI Documentation Case Study # ai # writing # documentation # webdev 5 reactions Comments Add Comment 2 min read Docs-as-Code: Why Your Team Needs a Markdown CMS Val Val Val Follow Jan 5 Docs-as-Code: Why Your Team Needs a Markdown CMS # webdev # programming # markdown # documentation Comments Add Comment 5 min read Why I Don’t Keep Session Logs for AI Collaboration synthaicode synthaicode synthaicode Follow Jan 4 Why I Don’t Keep Session Logs for AI Collaboration # documentation # ai # productivity Comments Add Comment 3 min read An award-winning devportal is more than words Naomi Pentrel Naomi Pentrel Naomi Pentrel Follow Jan 7 An award-winning devportal is more than words # career # devjournal # documentation # writing Comments Add Comment 5 min read Learning Markdown & Docs-as-Code tuezarova tuezarova tuezarova Follow Jan 4 Learning Markdown & Docs-as-Code # discuss # beginners # documentation # writing Comments Add Comment 1 min read Documentation is a productivity problem (and AI made it visible) synthaicode synthaicode synthaicode Follow Jan 2 Documentation is a productivity problem (and AI made it visible) # documentation # productivity Comments Add Comment 4 min read 10 Proven Techniques to Master Documentation Quickly for Any Framework or Library Abu Horaira Tarif Abu Horaira Tarif Abu Horaira Tarif Follow Dec 31 '25 10 Proven Techniques to Master Documentation Quickly for Any Framework or Library # webdev # productivity # community # documentation Comments Add Comment 3 min read A New Year, an Open Source Tool Surhid Amatya Surhid Amatya Surhid Amatya Follow Jan 1 A New Year, an Open Source Tool # documentation # opensource # tooling # api Comments Add Comment 2 min read Customer Self-Service Experience Best Practices for Support Teams FreePixel FreePixel FreePixel Follow Dec 31 '25 Customer Self-Service Experience Best Practices for Support Teams # customersupport # ux # documentation # saas Comments Add Comment 4 min read Software Development Documentation and Workflow dss99911 dss99911 dss99911 Follow Dec 30 '25 Software Development Documentation and Workflow # programming # common # developmentmethodology # documentation Comments Add Comment 2 min read loading... trending guides/resources Self-Improving AI: One Prompt That Makes Claude Learn From Every Mistake How I Integrated an AI Agent into Free GitLab CI/CD Writing Docs in a World Where LLMs Are the Readers Storybook 10: Why I Chose It Over Ladle and Histoire for Component Documentation Introducing Claude Code Documentation Standards: Automated Documentation with Built-in Linting Generating Application Specific Go Documentation Using Go AST and Antora Transform Your OpenAPI Specs Into Living Documentation: The Complete Guide DAT as Code : automatiser la documentation technique avec l'IA 10 Best OpenAPI Documentation Generators: Turn Your Spec Into Developer-Friendly Docs Docfx-Plus: A template and a tool to enhance DocFx and migrate from SHFB (Sandcastle) Fumadocs for Products with Rapidly Evolving SPIs & SDKs Export Your Confluence Documentation Like a Pro: Introducing Confluence Export CLI Automate Content Quality with VectorLint GitHub Action AI-Friendly README: Stop Claude & ChatGPT Hallucinations Leafwiki v0.5.2 - is out - dark mode and Markdown improvements Top AI Tools for Documentation | Guide for 2026 How I Added Glossary Tooltip Hover to Kgateway Docs (Using Hugo Shortcodes) We built an AI that does the tasks no human likes to repeat — meet Codedoc How AI Documentation Tools Cut Onboarding Time by 80% How do you keep engineering context alive when requirements change? Post: 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:45 |
https://docs.suprsend.com/docs/web-components-integration | Integration - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection GETTING STARTED What is SuprSend? Quick Start Guide Best Practices Plan Your Integration Go-live checklist CORE CONCEPTS Templates Users Events Workflow Notification Categories Preferences Tenants Lists Broadcast Objects Translations DLT Guidelines Whatsapp Template Guidelines WORKFLOW BUILDER Design Workflow Node List Workflow Settings Trigger Workflow Validate Trigger Payload Tenant Workflows Notification Inbox Overview Multi Tabs React Javascript (Angular, Vuejs etc) Integration Customization options React Native Flutter (Headless) PREFERENCE CENTRE Embedded Preference Centre Javascript Angular React VENDOR INTEGRATION GUIDE Overview Email Integrations SMS Integrations Android Push Whatsapp Integrations iOS Push Chat Integrations Vendor Fallback Tenant Vendor INTEGRATIONS Webhook Connectors MONITORING & DEBUGGING Logs Audit Logs Error Guides MANAGE YOUR ACCOUNT Authentication Methods Contact Us Get Started SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Ask AI Contact Us Get Started Get Started Search... Navigation Javascript (Angular, Vuejs etc) Integration Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog Javascript (Angular, Vuejs etc) Integration OpenAI Open in ChatGPT How to integrate SuprSend inbox/feed components in Angular, Vue, VanillaJS, and other non-React frameworks. OpenAI Open in ChatGPT End of Support for @suprsend/web-inbox . Migrate to @suprsend/web-components We have upgraded authentication of inbox from HMAC to JWT as it is more secure. Please migrate to newer SDK if you are on old one. There are 2 ways in which you can implement inbox functionality: Drop-in components: Pre-built UI with many customizable options which require minimal effort to build. Headless implementation: For more advanced use cases where you want to build UI/UX from scratch. This guide help you integrate drop-in components in your non-react frameworks (angular, vuejs, vanillajs etc). If you want to build your own UI (headless) instead of using drop-in components please refer docs . Integration Integrate using script tag This integration is used in Vanillajs, Django, Laravel, ruby etc where npm is not used. Copy Ask AI <!-- for dropin inbox with bell --> < div id = "suprsend-inbox" ></ div > <!-- for feed without bell as a fullscreen notification etc --> < div id = "suprsend-feed" ></ div > < script > window . suprsendConfig = { distinctId: "YOUR_DISTINCT_ID" , publicApiKey: "YOUR_PUBLIC_API_KEY" , userAuthenticationHandler : ({ response }) => { console . log ( "User Authentication Response" , response ); }, }; let scriptElem = document . createElement ( "script" ); scriptElem . async = 1 ; scriptElem . src = "https://web-components.suprsend.com/v0.3.0/bundle.umd.js" ; scriptElem . onload = () => { console . log ( "SuprSend SDK loaded" , window . suprsend ); }; document . body . appendChild ( scriptElem ); </ script > Integrate as npm package This integration is used in framework based applications like angular, vuejs etc. Copy Ask AI npm install @suprsend/web-components@latest Copy Ask AI import { initSuprSend , clearSuprSend } from "@suprsend/web-components" ; // for dropin inbox with bell < div id = "suprsend-inbox" ></ div > // for feed without bell as a fullscreen notification etc < div id = "suprsend-feed" ></ div > const suprsendConfig = { distinctId: "YOUR_DISTINCT_ID" , publicApiKey: "YOUR_PUBLIC_API_KEY" , userAuthenticationHandler : ({ response }) => { console . log ( "User Authentication Response" , response ); }, }; initSuprSend ( suprsendConfig ) // for creating instance and rendering component console . log ( "Instance created but user authentication pending" , window . suprsend ) NOTE: If you are using suprsend-feed , specify height for the container for infinite scroll to work properly. Copy Ask AI const suprsendConfig = { distinctId: "YOUR_DISTINCT_ID" , publicApiKey: "YOUR_PUBLIC_API_KEY" , feed: { theme: { notificationsContainer: { container: { height: "100vh" } } }, // add this to specify height }, }; Removing instance Components will be removed automatically if you navigate away from the page (on unmounting). If you want to remove them manually, you can use below methods. Using script tag Using npm package Copy Ask AI window . suprsend . clearSuprSend (); // clears instance and remove all components window . suprsend . clearSuprSendInbox (); // unmount only inbox component window . suprsend . clearSuprSendFeed (); // unmount only feed component Updating configuration dynamically Copy Ask AI window . suprsend . updateSuprSendConfig ( config : IUpdateSuprSendConfigOptions ); // refresh userToken, change locale, translations dymanically window . suprsend . updateInboxConfig ( config : IInbox ); window . suprsend . updateFeedConfig ( config : IFeed ); window . suprsend . updateToastConfig ( config : IToastNotificationProps ); Accessing other instance methods SDK internally calls new SuprSend() when you call initSuprSend() then you can access instance using window.suprsend.client . This instance has methods like preferences , webpush , event and user updates . Copy Ask AI // example methods window . suprsend . client . isIdentified (); window . suprsend . client . user . addEmail ( email : string ); window . suprsend . client . track ( event : string , properties ?: Dictionary ) window . suprsend . client . webpush . registerPush (); window . suprsend . client . user . preferences . getPreferences ( args ?: {tenantId? : string }); Config options To customise SuprSend components you can pass config object. Config Options Inbox Config Options Feed Config Options Toast Config Options Copy Ask AI interface ConfigProps { publicApiKey : string ; distinctId ? : unknown ; userToken ? : string ; host ? : string ; initOnLoad ? : boolean ; // pass false if you don't want to initialise instance just after loading script refreshUserToken ? : ( oldUserToken : string , tokenPayload : Dictionary ) => Promise < string > ; vapidKey ? : string ; swFileName ? : string ; userAuthenticationHandler ? : ({ response : ApiResponse }) => void ; inbox ? : IInbox ; // inbox config options feed ? : IFeed ; // feed config options toast ? : IToastNotificationProps ; // toast config options shadowRoot ?: ShadowRoot ; //shadowRoot reference } Parameter Description publicApiKey Public API Key is mandatory field without which error will be thrown by SuprSendProvider. You can get this from SuprSend Dashboard . distinctId Unique identifier to identify a user across platform. If a value is passed SDK will create user and authenticate user. If null value is passed authenticated user’s instance data will be cleared in your application, kind of logout. userToken Mandatory when enhanced security mode is on. This is ES256 JWT token generated in your server-side. Refer docs to create userToken. refreshUserToken This function is called by SDK internally to get new userToken before existing token is expired. The returned JWT token string is used as the new userToken. userAuthenticationHandler This callback will be called after authenticating user internally when you pass distinctId field to give you back the response of user creation API call. host Customise the host url. vapidKey This key is needed only if you are implementing WebPush notifications. You can get it in SuprSend Dashboard —> Vendors —> WebPush swFileName This key is needed only if you are implementing WebPush notifications and want to customise default serviceworker.js file name with your own service worker file name. shadowRoot Shadow root reference to render components inside shadow dom For further component specific customisations please refer to the docs . Was this page helpful? Yes No Suggest edits Raise issue Previous Customization options How to customize the styling, CSS, and layout of the Inbox Feed to match your product’s design in non-React websites. Next ⌘ I x github linkedin youtube Powered by On this page Integration Integrate using script tag Integrate as npm package Removing instance Updating configuration dynamically Accessing other instance methods Config options | 2026-01-13T08:48:45 |
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https://nextjs.org | Next.js by Vercel - The React Framework Skip to content Search documentation... Search... ⌘K Showcase Docs Blog Templates Enterprise Search documentation... Search... ⌘K Deploy Learn The React Framework for the Web Used by some of the world's largest companies, Next.js enables you to create high-quality web applications with the power of React components. Get Started Learn Next.js ▲ ~ npx create-next-app@latest What's in Next.js? Everything you need to build great products on the web. Data Fetching Make your React component async and await your data. Next.js supports both server and client data fetching. Server Actions Run server code by calling a function. Skip the API. Then, easily revalidate cached data and update your UI in one network roundtrip. Advanced Routing & Nested Layouts Create routes using the file system, including support for more advanced routing patterns and UI layouts. CSS Support Style your application with your favorite tools, including support for CSS Modules, Tailwind CSS, and popular community libraries. Route Handlers Build API endpoints to securely connect with third-party services for handling auth or listening for webhooks. Middleware Take control of the incoming request. Use code to define routing and access rules for authentication, experimentation, and internationalization. React Server Components Add components without sending additional client-side JavaScript. Built on the latest React features. Client and Server Rendering Flexible rendering and caching options, including Incremental Static Regeneration (ISR), on a per-page level. React Server Components Add components without sending additional client-side JavaScript. Built on the latest React features. Data Fetching Make your React component async and await your data. Next.js supports both server and client data fetching. Server Actions Run server code by calling a function. 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Next.js supports both server and client data fetching. Server Actions Run server code by calling a function. Skip the API. Then, easily revalidate cached data and update your UI in one network roundtrip. Advanced Routing & Nested Layouts Create routes using the file system, including support for more advanced routing patterns and UI layouts. CSS Support Style your application with your favorite tools, including support for CSS Modules, Tailwind CSS, and popular community libraries. Route Handlers Build API endpoints to securely connect with third-party services for handling auth or listening for webhooks. Middleware Take control of the incoming request. Use code to define routing and access rules for authentication, experimentation, and internationalization. Client and Server Rendering Flexible rendering and caching options, including Incremental Static Regeneration (ISR), on a per-page level. Next.js 16 The power of full-stack to the frontend. Read the release notes. 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Dynamic HTML Streaming Instantly stream UI from the server, integrated with the App Router and React Suspense. Next.js 16 The power of full-stack to the frontend. Read the release notes. Built-in Optimizations Automatic Image, Font, and Script Optimizations for improved UX and Core Web Vitals. Dynamic HTML Streaming Instantly stream UI from the server, integrated with the App Router and React Suspense. | 2026-01-13T08:48:45 |
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https://dev.to/t/beginners/page/3#main-content | Beginners Page 3 - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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https://docs.python.org/3/glossary.html#term-mutable | Glossary — Python 3.14.2 documentation Theme Auto Light Dark Previous topic Deprecations Next topic About this documentation This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » Glossary | Theme Auto Light Dark | Glossary ¶ >>> ¶ The default Python prompt of the interactive shell. Often seen for code examples which can be executed interactively in the interpreter. ... ¶ Can refer to: The default Python prompt of the interactive shell when entering the code for an indented code block, when within a pair of matching left and right delimiters (parentheses, square brackets, curly braces or triple quotes), or after specifying a decorator. The three dots form of the Ellipsis object. abstract base class ¶ Abstract base classes complement duck-typing by providing a way to define interfaces when other techniques like hasattr() would be clumsy or subtly wrong (for example with magic methods ). ABCs introduce virtual subclasses, which are classes that don’t inherit from a class but are still recognized by isinstance() and issubclass() ; see the abc module documentation. Python comes with many built-in ABCs for data structures (in the collections.abc module), numbers (in the numbers module), streams (in the io module), import finders and loaders (in the importlib.abc module). You can create your own ABCs with the abc module. annotate function ¶ A function that can be called to retrieve the annotations of an object. This function is accessible as the __annotate__ attribute of functions, classes, and modules. Annotate functions are a subset of evaluate functions . annotation ¶ A label associated with a variable, a class attribute or a function parameter or return value, used by convention as a type hint . Annotations of local variables cannot be accessed at runtime, but annotations of global variables, class attributes, and functions can be retrieved by calling annotationlib.get_annotations() on modules, classes, and functions, respectively. See variable annotation , function annotation , PEP 484 , PEP 526 , and PEP 649 , which describe this functionality. Also see Annotations Best Practices for best practices on working with annotations. argument ¶ A value passed to a function (or method ) when calling the function. There are two kinds of argument: keyword argument : an argument preceded by an identifier (e.g. name= ) in a function call or passed as a value in a dictionary preceded by ** . For example, 3 and 5 are both keyword arguments in the following calls to complex() : complex ( real = 3 , imag = 5 ) complex ( ** { 'real' : 3 , 'imag' : 5 }) positional argument : an argument that is not a keyword argument. Positional arguments can appear at the beginning of an argument list and/or be passed as elements of an iterable preceded by * . For example, 3 and 5 are both positional arguments in the following calls: complex ( 3 , 5 ) complex ( * ( 3 , 5 )) Arguments are assigned to the named local variables in a function body. See the Calls section for the rules governing this assignment. Syntactically, any expression can be used to represent an argument; the evaluated value is assigned to the local variable. See also the parameter glossary entry, the FAQ question on the difference between arguments and parameters , and PEP 362 . asynchronous context manager ¶ An object which controls the environment seen in an async with statement by defining __aenter__() and __aexit__() methods. Introduced by PEP 492 . asynchronous generator ¶ A function which returns an asynchronous generator iterator . It looks like a coroutine function defined with async def except that it contains yield expressions for producing a series of values usable in an async for loop. Usually refers to an asynchronous generator function, but may refer to an asynchronous generator iterator in some contexts. In cases where the intended meaning isn’t clear, using the full terms avoids ambiguity. An asynchronous generator function may contain await expressions as well as async for , and async with statements. asynchronous generator iterator ¶ An object created by an asynchronous generator function. This is an asynchronous iterator which when called using the __anext__() method returns an awaitable object which will execute the body of the asynchronous generator function until the next yield expression. Each yield temporarily suspends processing, remembering the execution state (including local variables and pending try-statements). When the asynchronous generator iterator effectively resumes with another awaitable returned by __anext__() , it picks up where it left off. See PEP 492 and PEP 525 . asynchronous iterable ¶ An object, that can be used in an async for statement. Must return an asynchronous iterator from its __aiter__() method. Introduced by PEP 492 . asynchronous iterator ¶ An object that implements the __aiter__() and __anext__() methods. __anext__() must return an awaitable object. async for resolves the awaitables returned by an asynchronous iterator’s __anext__() method until it raises a StopAsyncIteration exception. Introduced by PEP 492 . atomic operation ¶ An operation that appears to execute as a single, indivisible step: no other thread can observe it half-done, and its effects become visible all at once. Python does not guarantee that high-level statements are atomic (for example, x += 1 performs multiple bytecode operations and is not atomic). Atomicity is only guaranteed where explicitly documented. See also race condition and data race . attached thread state ¶ A thread state that is active for the current OS thread. When a thread state is attached, the OS thread has access to the full Python C API and can safely invoke the bytecode interpreter. Unless a function explicitly notes otherwise, attempting to call the C API without an attached thread state will result in a fatal error or undefined behavior. A thread state can be attached and detached explicitly by the user through the C API, or implicitly by the runtime, including during blocking C calls and by the bytecode interpreter in between calls. On most builds of Python, having an attached thread state implies that the caller holds the GIL for the current interpreter, so only one OS thread can have an attached thread state at a given moment. In free-threaded builds of Python, threads can concurrently hold an attached thread state, allowing for true parallelism of the bytecode interpreter. attribute ¶ A value associated with an object which is usually referenced by name using dotted expressions. For example, if an object o has an attribute a it would be referenced as o.a . It is possible to give an object an attribute whose name is not an identifier as defined by Names (identifiers and keywords) , for example using setattr() , if the object allows it. Such an attribute will not be accessible using a dotted expression, and would instead need to be retrieved with getattr() . awaitable ¶ An object that can be used in an await expression. Can be a coroutine or an object with an __await__() method. See also PEP 492 . BDFL ¶ Benevolent Dictator For Life, a.k.a. Guido van Rossum , Python’s creator. binary file ¶ A file object able to read and write bytes-like objects . Examples of binary files are files opened in binary mode ( 'rb' , 'wb' or 'rb+' ), sys.stdin.buffer , sys.stdout.buffer , and instances of io.BytesIO and gzip.GzipFile . See also text file for a file object able to read and write str objects. borrowed reference ¶ In Python’s C API, a borrowed reference is a reference to an object, where the code using the object does not own the reference. It becomes a dangling pointer if the object is destroyed. For example, a garbage collection can remove the last strong reference to the object and so destroy it. Calling Py_INCREF() on the borrowed reference is recommended to convert it to a strong reference in-place, except when the object cannot be destroyed before the last usage of the borrowed reference. The Py_NewRef() function can be used to create a new strong reference . bytes-like object ¶ An object that supports the Buffer Protocol and can export a C- contiguous buffer. This includes all bytes , bytearray , and array.array objects, as well as many common memoryview objects. Bytes-like objects can be used for various operations that work with binary data; these include compression, saving to a binary file, and sending over a socket. Some operations need the binary data to be mutable. The documentation often refers to these as “read-write bytes-like objects”. Example mutable buffer objects include bytearray and a memoryview of a bytearray . Other operations require the binary data to be stored in immutable objects (“read-only bytes-like objects”); examples of these include bytes and a memoryview of a bytes object. bytecode ¶ Python source code is compiled into bytecode, the internal representation of a Python program in the CPython interpreter. The bytecode is also cached in .pyc files so that executing the same file is faster the second time (recompilation from source to bytecode can be avoided). This “intermediate language” is said to run on a virtual machine that executes the machine code corresponding to each bytecode. Do note that bytecodes are not expected to work between different Python virtual machines, nor to be stable between Python releases. A list of bytecode instructions can be found in the documentation for the dis module . callable ¶ A callable is an object that can be called, possibly with a set of arguments (see argument ), with the following syntax: callable ( argument1 , argument2 , argumentN ) A function , and by extension a method , is a callable. An instance of a class that implements the __call__() method is also a callable. callback ¶ A subroutine function which is passed as an argument to be executed at some point in the future. class ¶ A template for creating user-defined objects. Class definitions normally contain method definitions which operate on instances of the class. class variable ¶ A variable defined in a class and intended to be modified only at class level (i.e., not in an instance of the class). closure variable ¶ A free variable referenced from a nested scope that is defined in an outer scope rather than being resolved at runtime from the globals or builtin namespaces. May be explicitly defined with the nonlocal keyword to allow write access, or implicitly defined if the variable is only being read. For example, in the inner function in the following code, both x and print are free variables , but only x is a closure variable : def outer (): x = 0 def inner (): nonlocal x x += 1 print ( x ) return inner Due to the codeobject.co_freevars attribute (which, despite its name, only includes the names of closure variables rather than listing all referenced free variables), the more general free variable term is sometimes used even when the intended meaning is to refer specifically to closure variables. complex number ¶ An extension of the familiar real number system in which all numbers are expressed as a sum of a real part and an imaginary part. Imaginary numbers are real multiples of the imaginary unit (the square root of -1 ), often written i in mathematics or j in engineering. Python has built-in support for complex numbers, which are written with this latter notation; the imaginary part is written with a j suffix, e.g., 3+1j . To get access to complex equivalents of the math module, use cmath . Use of complex numbers is a fairly advanced mathematical feature. If you’re not aware of a need for them, it’s almost certain you can safely ignore them. concurrency ¶ The ability of a computer program to perform multiple tasks at the same time. Python provides libraries for writing programs that make use of different forms of concurrency. asyncio is a library for dealing with asynchronous tasks and coroutines. threading provides access to operating system threads and multiprocessing to operating system processes. Multi-core processors can execute threads and processes on different CPU cores at the same time (see parallelism ). concurrent modification ¶ When multiple threads modify shared data at the same time. Concurrent modification without proper synchronization can cause race conditions , and might also trigger a data race , data corruption, or both. context ¶ This term has different meanings depending on where and how it is used. Some common meanings: The temporary state or environment established by a context manager via a with statement. The collection of keyvalue bindings associated with a particular contextvars.Context object and accessed via ContextVar objects. Also see context variable . A contextvars.Context object. Also see current context . context management protocol ¶ The __enter__() and __exit__() methods called by the with statement. See PEP 343 . context manager ¶ An object which implements the context management protocol and controls the environment seen in a with statement. See PEP 343 . context variable ¶ A variable whose value depends on which context is the current context . Values are accessed via contextvars.ContextVar objects. Context variables are primarily used to isolate state between concurrent asynchronous tasks. contiguous ¶ A buffer is considered contiguous exactly if it is either C-contiguous or Fortran contiguous . Zero-dimensional buffers are C and Fortran contiguous. In one-dimensional arrays, the items must be laid out in memory next to each other, in order of increasing indexes starting from zero. In multidimensional C-contiguous arrays, the last index varies the fastest when visiting items in order of memory address. However, in Fortran contiguous arrays, the first index varies the fastest. coroutine ¶ Coroutines are a more generalized form of subroutines. Subroutines are entered at one point and exited at another point. Coroutines can be entered, exited, and resumed at many different points. They can be implemented with the async def statement. See also PEP 492 . coroutine function ¶ A function which returns a coroutine object. A coroutine function may be defined with the async def statement, and may contain await , async for , and async with keywords. These were introduced by PEP 492 . CPython ¶ The canonical implementation of the Python programming language, as distributed on python.org . The term “CPython” is used when necessary to distinguish this implementation from others such as Jython or IronPython. current context ¶ The context ( contextvars.Context object) that is currently used by ContextVar objects to access (get or set) the values of context variables . Each thread has its own current context. Frameworks for executing asynchronous tasks (see asyncio ) associate each task with a context which becomes the current context whenever the task starts or resumes execution. cyclic isolate ¶ A subgroup of one or more objects that reference each other in a reference cycle, but are not referenced by objects outside the group. The goal of the cyclic garbage collector is to identify these groups and break the reference cycles so that the memory can be reclaimed. data race ¶ A situation where multiple threads access the same memory location concurrently, at least one of the accesses is a write, and the threads do not use any synchronization to control their access. Data races lead to non-deterministic behavior and can cause data corruption. Proper use of locks and other synchronization primitives prevents data races. Note that data races can only happen in native code, but that native code might be exposed in a Python API. See also race condition and thread-safe . deadlock ¶ A situation in which two or more tasks (threads, processes, or coroutines) wait indefinitely for each other to release resources or complete actions, preventing any from making progress. For example, if thread A holds lock 1 and waits for lock 2, while thread B holds lock 2 and waits for lock 1, both threads will wait indefinitely. In Python this often arises from acquiring multiple locks in conflicting orders or from circular join/await dependencies. Deadlocks can be avoided by always acquiring multiple locks in a consistent order. See also lock and reentrant . decorator ¶ A function returning another function, usually applied as a function transformation using the @wrapper syntax. Common examples for decorators are classmethod() and staticmethod() . The decorator syntax is merely syntactic sugar, the following two function definitions are semantically equivalent: def f ( arg ): ... f = staticmethod ( f ) @staticmethod def f ( arg ): ... The same concept exists for classes, but is less commonly used there. See the documentation for function definitions and class definitions for more about decorators. descriptor ¶ Any object which defines the methods __get__() , __set__() , or __delete__() . When a class attribute is a descriptor, its special binding behavior is triggered upon attribute lookup. Normally, using a.b to get, set or delete an attribute looks up the object named b in the class dictionary for a , but if b is a descriptor, the respective descriptor method gets called. Understanding descriptors is a key to a deep understanding of Python because they are the basis for many features including functions, methods, properties, class methods, static methods, and reference to super classes. For more information about descriptors’ methods, see Implementing Descriptors or the Descriptor How To Guide . dictionary ¶ An associative array, where arbitrary keys are mapped to values. The keys can be any object with __hash__() and __eq__() methods. Called a hash in Perl. dictionary comprehension ¶ A compact way to process all or part of the elements in an iterable and return a dictionary with the results. results = {n: n ** 2 for n in range(10)} generates a dictionary containing key n mapped to value n ** 2 . See Displays for lists, sets and dictionaries . dictionary view ¶ The objects returned from dict.keys() , dict.values() , and dict.items() are called dictionary views. They provide a dynamic view on the dictionary’s entries, which means that when the dictionary changes, the view reflects these changes. To force the dictionary view to become a full list use list(dictview) . See Dictionary view objects . docstring ¶ A string literal which appears as the first expression in a class, function or module. While ignored when the suite is executed, it is recognized by the compiler and put into the __doc__ attribute of the enclosing class, function or module. Since it is available via introspection, it is the canonical place for documentation of the object. duck-typing ¶ A programming style which does not look at an object’s type to determine if it has the right interface; instead, the method or attribute is simply called or used (“If it looks like a duck and quacks like a duck, it must be a duck.”) By emphasizing interfaces rather than specific types, well-designed code improves its flexibility by allowing polymorphic substitution. Duck-typing avoids tests using type() or isinstance() . (Note, however, that duck-typing can be complemented with abstract base classes .) Instead, it typically employs hasattr() tests or EAFP programming. dunder ¶ An informal short-hand for “double underscore”, used when talking about a special method . For example, __init__ is often pronounced “dunder init”. EAFP ¶ Easier to ask for forgiveness than permission. This common Python coding style assumes the existence of valid keys or attributes and catches exceptions if the assumption proves false. This clean and fast style is characterized by the presence of many try and except statements. The technique contrasts with the LBYL style common to many other languages such as C. evaluate function ¶ A function that can be called to evaluate a lazily evaluated attribute of an object, such as the value of type aliases created with the type statement. expression ¶ A piece of syntax which can be evaluated to some value. In other words, an expression is an accumulation of expression elements like literals, names, attribute access, operators or function calls which all return a value. In contrast to many other languages, not all language constructs are expressions. There are also statement s which cannot be used as expressions, such as while . Assignments are also statements, not expressions. extension module ¶ A module written in C or C++, using Python’s C API to interact with the core and with user code. f-string ¶ f-strings ¶ String literals prefixed with f or F are commonly called “f-strings” which is short for formatted string literals . See also PEP 498 . file object ¶ An object exposing a file-oriented API (with methods such as read() or write() ) to an underlying resource. Depending on the way it was created, a file object can mediate access to a real on-disk file or to another type of storage or communication device (for example standard input/output, in-memory buffers, sockets, pipes, etc.). File objects are also called file-like objects or streams . There are actually three categories of file objects: raw binary files , buffered binary files and text files . Their interfaces are defined in the io module. The canonical way to create a file object is by using the open() function. file-like object ¶ A synonym for file object . filesystem encoding and error handler ¶ Encoding and error handler used by Python to decode bytes from the operating system and encode Unicode to the operating system. The filesystem encoding must guarantee to successfully decode all bytes below 128. If the file system encoding fails to provide this guarantee, API functions can raise UnicodeError . The sys.getfilesystemencoding() and sys.getfilesystemencodeerrors() functions can be used to get the filesystem encoding and error handler. The filesystem encoding and error handler are configured at Python startup by the PyConfig_Read() function: see filesystem_encoding and filesystem_errors members of PyConfig . See also the locale encoding . finder ¶ An object that tries to find the loader for a module that is being imported. There are two types of finder: meta path finders for use with sys.meta_path , and path entry finders for use with sys.path_hooks . See Finders and loaders and importlib for much more detail. floor division ¶ Mathematical division that rounds down to nearest integer. The floor division operator is // . For example, the expression 11 // 4 evaluates to 2 in contrast to the 2.75 returned by float true division. Note that (-11) // 4 is -3 because that is -2.75 rounded downward . See PEP 238 . free threading ¶ A threading model where multiple threads can run Python bytecode simultaneously within the same interpreter. This is in contrast to the global interpreter lock which allows only one thread to execute Python bytecode at a time. See PEP 703 . free variable ¶ Formally, as defined in the language execution model , a free variable is any variable used in a namespace which is not a local variable in that namespace. See closure variable for an example. Pragmatically, due to the name of the codeobject.co_freevars attribute, the term is also sometimes used as a synonym for closure variable . function ¶ A series of statements which returns some value to a caller. It can also be passed zero or more arguments which may be used in the execution of the body. See also parameter , method , and the Function definitions section. function annotation ¶ An annotation of a function parameter or return value. Function annotations are usually used for type hints : for example, this function is expected to take two int arguments and is also expected to have an int return value: def sum_two_numbers ( a : int , b : int ) -> int : return a + b Function annotation syntax is explained in section Function definitions . See variable annotation and PEP 484 , which describe this functionality. Also see Annotations Best Practices for best practices on working with annotations. __future__ ¶ A future statement , from __future__ import <feature> , directs the compiler to compile the current module using syntax or semantics that will become standard in a future release of Python. The __future__ module documents the possible values of feature . By importing this module and evaluating its variables, you can see when a new feature was first added to the language and when it will (or did) become the default: >>> import __future__ >>> __future__ . division _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192) garbage collection ¶ The process of freeing memory when it is not used anymore. Python performs garbage collection via reference counting and a cyclic garbage collector that is able to detect and break reference cycles. The garbage collector can be controlled using the gc module. generator ¶ A function which returns a generator iterator . It looks like a normal function except that it contains yield expressions for producing a series of values usable in a for-loop or that can be retrieved one at a time with the next() function. Usually refers to a generator function, but may refer to a generator iterator in some contexts. In cases where the intended meaning isn’t clear, using the full terms avoids ambiguity. generator iterator ¶ An object created by a generator function. Each yield temporarily suspends processing, remembering the execution state (including local variables and pending try-statements). When the generator iterator resumes, it picks up where it left off (in contrast to functions which start fresh on every invocation). generator expression ¶ An expression that returns an iterator . It looks like a normal expression followed by a for clause defining a loop variable, range, and an optional if clause. The combined expression generates values for an enclosing function: >>> sum ( i * i for i in range ( 10 )) # sum of squares 0, 1, 4, ... 81 285 generic function ¶ A function composed of multiple functions implementing the same operation for different types. Which implementation should be used during a call is determined by the dispatch algorithm. See also the single dispatch glossary entry, the functools.singledispatch() decorator, and PEP 443 . generic type ¶ A type that can be parameterized; typically a container class such as list or dict . Used for type hints and annotations . For more details, see generic alias types , PEP 483 , PEP 484 , PEP 585 , and the typing module. GIL ¶ See global interpreter lock . global interpreter lock ¶ The mechanism used by the CPython interpreter to assure that only one thread executes Python bytecode at a time. This simplifies the CPython implementation by making the object model (including critical built-in types such as dict ) implicitly safe against concurrent access. Locking the entire interpreter makes it easier for the interpreter to be multi-threaded, at the expense of much of the parallelism afforded by multi-processor machines. However, some extension modules, either standard or third-party, are designed so as to release the GIL when doing computationally intensive tasks such as compression or hashing. Also, the GIL is always released when doing I/O. As of Python 3.13, the GIL can be disabled using the --disable-gil build configuration. After building Python with this option, code must be run with -X gil=0 or after setting the PYTHON_GIL=0 environment variable. This feature enables improved performance for multi-threaded applications and makes it easier to use multi-core CPUs efficiently. For more details, see PEP 703 . In prior versions of Python’s C API, a function might declare that it requires the GIL to be held in order to use it. This refers to having an attached thread state . global state ¶ Data that is accessible throughout a program, such as module-level variables, class variables, or C static variables in extension modules . In multi-threaded programs, global state shared between threads typically requires synchronization to avoid race conditions and data races . hash-based pyc ¶ A bytecode cache file that uses the hash rather than the last-modified time of the corresponding source file to determine its validity. See Cached bytecode invalidation . hashable ¶ An object is hashable if it has a hash value which never changes during its lifetime (it needs a __hash__() method), and can be compared to other objects (it needs an __eq__() method). Hashable objects which compare equal must have the same hash value. Hashability makes an object usable as a dictionary key and a set member, because these data structures use the hash value internally. Most of Python’s immutable built-in objects are hashable; mutable containers (such as lists or dictionaries) are not; immutable containers (such as tuples and frozensets) are only hashable if their elements are hashable. Objects which are instances of user-defined classes are hashable by default. They all compare unequal (except with themselves), and their hash value is derived from their id() . IDLE ¶ An Integrated Development and Learning Environment for Python. IDLE — Python editor and shell is a basic editor and interpreter environment which ships with the standard distribution of Python. immortal ¶ Immortal objects are a CPython implementation detail introduced in PEP 683 . If an object is immortal, its reference count is never modified, and therefore it is never deallocated while the interpreter is running. For example, True and None are immortal in CPython. Immortal objects can be identified via sys._is_immortal() , or via PyUnstable_IsImmortal() in the C API. immutable ¶ An object with a fixed value. Immutable objects include numbers, strings and tuples. Such an object cannot be altered. A new object has to be created if a different value has to be stored. They play an important role in places where a constant hash value is needed, for example as a key in a dictionary. Immutable objects are inherently thread-safe because their state cannot be modified after creation, eliminating concerns about improperly synchronized concurrent modification . import path ¶ A list of locations (or path entries ) that are searched by the path based finder for modules to import. During import, this list of locations usually comes from sys.path , but for subpackages it may also come from the parent package’s __path__ attribute. importing ¶ The process by which Python code in one module is made available to Python code in another module. importer ¶ An object that both finds and loads a module; both a finder and loader object. interactive ¶ Python has an interactive interpreter which means you can enter statements and expressions at the interpreter prompt, immediately execute them and see their results. Just launch python with no arguments (possibly by selecting it from your computer’s main menu). It is a very powerful way to test out new ideas or inspect modules and packages (remember help(x) ). For more on interactive mode, see Interactive Mode . interpreted ¶ Python is an interpreted language, as opposed to a compiled one, though the distinction can be blurry because of the presence of the bytecode compiler. This means that source files can be run directly without explicitly creating an executable which is then run. Interpreted languages typically have a shorter development/debug cycle than compiled ones, though their programs generally also run more slowly. See also interactive . interpreter shutdown ¶ When asked to shut down, the Python interpreter enters a special phase where it gradually releases all allocated resources, such as modules and various critical internal structures. It also makes several calls to the garbage collector . This can trigger the execution of code in user-defined destructors or weakref callbacks. Code executed during the shutdown phase can encounter various exceptions as the resources it relies on may not function anymore (common examples are library modules or the warnings machinery). The main reason for interpreter shutdown is that the __main__ module or the script being run has finished executing. iterable ¶ An object capable of returning its members one at a time. Examples of iterables include all sequence types (such as list , str , and tuple ) and some non-sequence types like dict , file objects , and objects of any classes you define with an __iter__() method or with a __getitem__() method that implements sequence semantics. Iterables can be used in a for loop and in many other places where a sequence is needed ( zip() , map() , …). When an iterable object is passed as an argument to the built-in function iter() , it returns an iterator for the object. This iterator is good for one pass over the set of values. When using iterables, it is usually not necessary to call iter() or deal with iterator objects yourself. The for statement does that automatically for you, creating a temporary unnamed variable to hold the iterator for the duration of the loop. See also iterator , sequence , and generator . iterator ¶ An object representing a stream of data. Repeated calls to the iterator’s __next__() method (or passing it to the built-in function next() ) return successive items in the stream. When no more data are available a StopIteration exception is raised instead. At this point, the iterator object is exhausted and any further calls to its __next__() method just raise StopIteration again. Iterators are required to have an __iter__() method that returns the iterator object itself so every iterator is also iterable and may be used in most places where other iterables are accepted. One notable exception is code which attempts multiple iteration passes. A container object (such as a list ) produces a fresh new iterator each time you pass it to the iter() function or use it in a for loop. Attempting this with an iterator will just return the same exhausted iterator object used in the previous iteration pass, making it appear like an empty container. More information can be found in Iterator Types . CPython implementation detail: CPython does not consistently apply the requirement that an iterator define __iter__() . And also please note that free-threaded CPython does not guarantee thread-safe behavior of iterator operations. key function ¶ A key function or collation function is a callable that returns a value used for sorting or ordering. For example, locale.strxfrm() is used to produce a sort key that is aware of locale specific sort conventions. A number of tools in Python accept key functions to control how elements are ordered or grouped. They include min() , max() , sorted() , list.sort() , heapq.merge() , heapq.nsmallest() , heapq.nlargest() , and itertools.groupby() . There are several ways to create a key function. For example. the str.casefold() method can serve as a key function for case insensitive sorts. Alternatively, a key function can be built from a lambda expression such as lambda r: (r[0], r[2]) . Also, operator.attrgetter() , operator.itemgetter() , and operator.methodcaller() are three key function constructors. See the Sorting HOW TO for examples of how to create and use key functions. keyword argument ¶ See argument . lambda ¶ An anonymous inline function consisting of a single expression which is evaluated when the function is called. The syntax to create a lambda function is lambda [parameters]: expression LBYL ¶ Look before you leap. This coding style explicitly tests for pre-conditions before making calls or lookups. This style contrasts with the EAFP approach and is characterized by the presence of many if statements. In a multi-threaded environment, the LBYL approach can risk introducing a race condition between “the looking” and “the leaping”. For example, the code, if key in mapping: return mapping[key] can fail if another thread removes key from mapping after the test, but before the lookup. This issue can be solved with locks or by using the EAFP approach. See also thread-safe . lexical analyzer ¶ Formal name for the tokenizer ; see token . list ¶ A built-in Python sequence . Despite its name it is more akin to an array in other languages than to a linked list since access to elements is O (1). list comprehension ¶ A compact way to process all or part of the elements in a sequence and return a list with the results. result = ['{:#04x}'.format(x) for x in range(256) if x % 2 == 0] generates a list of strings containing even hex numbers (0x..) in the range from 0 to 255. The if clause is optional. If omitted, all elements in range(256) are processed. lock ¶ A synchronization primitive that allows only one thread at a time to access a shared resource. A thread must acquire a lock before accessing the protected resource and release it afterward. If a thread attempts to acquire a lock that is already held by another thread, it will block until the lock becomes available. Python’s threading module provides Lock (a basic lock) and RLock (a reentrant lock). Locks are used to prevent race conditions and ensure thread-safe access to shared data. Alternative design patterns to locks exist such as queues, producer/consumer patterns, and thread-local state. See also deadlock , and reentrant . loader ¶ An object that loads a module. It must define the exec_module() and create_module() methods to implement the Loader interface. A loader is typically returned by a finder . See also: Finders and loaders importlib.abc.Loader PEP 302 locale encoding ¶ On Unix, it is the encoding of the LC_CTYPE locale. It can be set with locale.setlocale(locale.LC_CTYPE, new_locale) . On Windows, it is the ANSI code page (ex: "cp1252" ). On Android and VxWorks, Python uses "utf-8" as the locale encoding. locale.getencoding() can be used to get the locale encoding. See also the filesystem encoding and error handler . magic method ¶ An informal synonym for special method . mapping ¶ A container object that supports arbitrary key lookups and implements the methods specified in the collections.abc.Mapping or collections.abc.MutableMapping abstract base classes . Examples include dict , collections.defaultdict , collections.OrderedDict and collections.Counter . meta path finder ¶ A finder returned by a search of sys.meta_path . Meta path finders are related to, but different from path entry finders . See importlib.abc.MetaPathFinder for the methods that meta path finders implement. metaclass ¶ The class of a class. Class definitions create a class name, a class dictionary, and a list of base classes. The metaclass is responsible for taking those three arguments and creating the class. Most object oriented programming languages provide a default implementation. What makes Python special is that it is possible to create custom metaclasses. Most users never need this tool, but when the need arises, metaclasses can provide powerful, elegant solutions. They have been used for logging attribute access, adding thread-safety, tracking object creation, implementing singletons, and many other tasks. More information can be found in Metaclasses . method ¶ A function which is defined inside a class body. If called as an attribute of an instance of that class, the method will get the instance object as its first argument (which is usually called self ). See function and nested scope . method resolution order ¶ Method Resolution Order is the order in which base classes are searched for a member during lookup. See The Python 2.3 Method Resolution Order for details of the algorithm used by the Python interpreter since the 2.3 release. module ¶ An object that serves as an organizational unit of Python code. Modules have a namespace containing arbitrary Python objects. Modules are loaded into Python by the process of importing . See also package . module spec ¶ A namespace containing the import-related information used to load a module. An instance of importlib.machinery.ModuleSpec . See also Module specs . MRO ¶ See method resolution order . mutable ¶ An object with state that is allowed to change during the course of the program. In multi-threaded programs, mutable objects that are shared between threads require careful synchronization to avoid race conditions . See also immutable , thread-safe , and concurrent modification . named tuple ¶ The term “named tuple” applies to any type or class that inherits from tuple and whose indexable elements are also accessible using named attributes. The type or class may have other features as well. Several built-in types are named tuples, including the values returned by time.localtime() and os.stat() . Another example is sys.float_info : >>> sys . float_info [ 1 ] # indexed access 1024 >>> sys . float_info . max_exp # named field access 1024 >>> isinstance ( sys . float_info , tuple ) # kind of tuple True Some named tuples are built-in types (such as the above examples). Alternatively, a named tuple can be created from a regular class definition that inherits from tuple and that defines named fields. Such a class can be written by hand, or it can be created by inheriting typing.NamedTuple , or with the factory function collections.namedtuple() . The latter techniques also add some extra methods that may not be found in hand-written or built-in named tuples. namespace ¶ The place where a variable is stored. Namespaces are implemented as dictionaries. There are the local, global and built-in namespaces as well as nested namespaces in objects (in methods). Namespaces support modularity by preventing naming conflicts. For instance, the functions builtins.open and os.open() are distinguished by their namespaces. Namespaces also aid readability and maintainability by making it clear which module implements a function. For instance, writing random.seed() or itertools.islice() makes it clear that those functions are implemented by the random and itertools modules, respectively. namespace package ¶ A package which serves only as a container for subpackages. Namespace packages may have no physical representation, and specifically are not like a regular package because they have no __init__.py file. Namespace packages allow several individually installable packages to have a common parent package. Otherwise, it is recommended to use a regular package . For more information, see PEP 420 and Namespace packages . See also module . native code ¶ Code that is compiled to machine instructions and runs directly on the processor, as opposed to code that is interpreted or runs in a virtual machine. In the context of Python, native code typically refers to C, C++, Rust or Fortran code in extension modules that can be called from Python. See also extension module . nested scope ¶ The ability to refer to a variable in an enclosing definition. For instance, a function defined inside another function can refer to variables in the outer function. Note that nested scopes by default work only for reference and not for assignment. Local variables both read and write in the innermost scope. Likewise, global variables read and write to the global namespace. The nonlocal allows writing to outer scopes. new-style class ¶ Old name for the flavor of classes now used for all class objects. In earlier Python versions, only new-style classes could use Python’s newer, versatile features like __slots__ , descriptors, properties, __getattribute__() , class methods, and static methods. non-deterministic ¶ Behavior where the outcome of a program can vary between executions with the same inputs. In multi-threaded programs, non-deterministic behavior often results from race conditions where the relative timing or interleaving of threads affects the result. Proper synchronization using locks and other synchronization primitives helps ensure deterministic behavior. object ¶ Any data with state (attributes or value) and defined behavior (methods). Also the ultimate base class of any new-style class . optimized scope ¶ A scope where target local variable names are reliably known to the compiler when the code is compiled, allowing optimization of read and write access to these names. The local namespaces for functions, generators, coroutines, comprehensions, and generator expressions are optimized in this fashion. Note: most interpreter optimizations are applied to all scopes, only those relying on a known set of local and nonlocal variable names are restricted to optimized scopes. optional module ¶ An extension module that is part of the standard library , but may be absent in some builds of CPython , usually due to missing third-party libraries or because the module is not available for a given platform. See Requirements for optional modules for a list of optional modules that require third-party libraries. package ¶ A Python module which can contain submodules or recursively, subpackages. Technically, a package is a Python module with a __path__ attribute. See also regular package and namespace package . parallelism ¶ Executing multiple operations at the same time (e.g. on multiple CPU cores). In Python builds with the global interpreter lock (GIL) , only one thread runs Python bytecode at a time, so taking advantage of multiple CPU cores typically involves multiple processes (e.g. multiprocessing ) or native extensions that release the GIL. In free-threaded Python, multiple Python threads can run Python code simultaneously on different cores. parameter ¶ A named entity in a function (or method) definition that specifies an argument (or in some cases, arguments) that the function can accept. There are five kinds of parameter: positional-or-keyword : specifies an argument that can be passed either positionally or as a keyword argument . This is the default kind of parameter, for example foo and bar in the following: def func ( foo , bar = None ): ... positional-only : specifies an argument that can be supplied only by position. Positional-only parameters can be defined by including a / character in the parameter list of the function definition after them, for example posonly1 and posonly2 in the following: def func ( posonly1 , posonly2 , / , positional_or_keyword ): ... keyword-only : specifies an argument that can be supplied only by keyword. Keyword-only parameters can be defined by including a single var-positional parameter or bare * in the parameter list of the function definition before them, for example kw_only1 and kw_only2 in the following: def func ( arg , * , kw_only1 , kw_only2 ): ... var-positional : specifies that an arbitrary sequence of positional arguments can be provided (in addition to any positional arguments already accepted by other parameters). Such a parameter can be defined by prepending the parameter name with * , for example args in the following: def func ( * args , ** kwargs ): ... var-keyword : specifies that arbitrarily many keyword arguments can be provided (in addition to any keyword arguments already accepted by other parameters). Such a parameter can be defined by prepending the parameter name with ** , for example kwargs in the example above. Parameters can specify both optional and required arguments, as well as default values for some optional arguments. See also the argument glossary entry, the FAQ question on the difference between arguments and parameters , the inspect.Parameter class, the Function definitions section, and PEP 362 . path entry ¶ A single location on the import path which the path based finder consults to find modules for importing. path entry finder ¶ A finder returned by a callable on sys.path_hooks (i.e. a path entry hook ) which knows how to locate modules given a path entry . See importlib.abc.PathEntryFinder for the methods that path entry finders implement. path entry hook ¶ A callable on the sys.path_hooks list which returns a path entry finder if it knows how to find modules on a specific path entry . path based finder ¶ One of the default meta path finders which searches an import path for modules. path-like object ¶ An object representing a file system path. A path-like object is either a str or bytes object representing a path, or an object implementing the os.PathLike protocol. An object that supports the os.PathLike protocol can be converted to a str or bytes file system path by calling the os.fspath() function; os.fsdecode() and os.fsencode() can be used to guarantee a str or bytes result instead, respectively. Introduced by PEP 519 . PEP ¶ Python Enhancement Proposal. A PEP is a design document providing information to the Python community, or describing a new feature for Python or its processes or environment. PEPs should provide a concise technical specification and a rationale for proposed features. PEPs are intended to be the primary mechanisms for proposing major new features, for collecting community input on an issue, and for documenting the design decisions that have gone into Python. The PEP author is responsible for building consensus within the community and documenting dissenting opinions. See PEP 1 . portion ¶ A set of files in a single directory (possibly stored in a zip file) that contribute to a namespace package, as defined in PEP 420 . positional argument ¶ See argument . provisional API ¶ A provisional API is one which has been deliberately excluded from the standard library’s backwards compatibility guarantees. While major changes to such interfaces are not expected, as long as they are marked provisional, backwards incompatible changes (up to and including removal of the interface) may occur if deemed necessary by core developers. Such changes will not be made | 2026-01-13T08:48:45 |
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https://porkbun.com/about | porkbun.com | About Us Toggle navigation porkbun $0.00 (0) products Domains Transfers Local Marketplace Local Auctions 3rd Party Aftermarket Web Hosting All Web Hosting Options Easy WordPress Link In Bio Articulation Sitebuilder Cloud WordPress Shared cPanel Hosting Static Hosting Website Builder Easy PHP Email Hosting All Email Hosting Options Proton Mail Porkbun Email Free Email Forwarding Marketing Tools Textla - SMS Marketing Free WHOIS Privacy Free SSL Certificates Free URL Forwarding transfer Free WordPress SALE! .COM SALE! About --> About Who We Are Why Choose Porkbun Porkbun vs Cloudflare FAQs Resources Knowledge Base Porkbun Blog Service Status Help $0.00 (0) sign in About Us What We Are DOMAIN NAME REGISTRAR Porkbun is an amazingly awesome ICANN accredited domain name registrar based out of the Pacific Northwest. We're different, we're easy, and we're affordable. Use us, you won't be sorry. If you don't use us we'll be sad, but we'll still love you. What People Are Saying About Us WHY FOLKS LOVE PORKBUN The people have spoken and shared their love for the Bun! We’re super proud to have been named the #1 domain registrar by USA Today for 2023 through 2025 — that's three year's running. It’s an incredible honor and reflects our dedication to our customers. We’ve also got more 5-star reviews on Trustpilot from real customers sharing their positive experience with Porkbun! While we love hearing the good stuff, we also pay attention to where we can improve. We use your feedback to look for ways to make the experience even better for each and every one of our customers. At the end of the day, our success is based on putting our customers first. So keep those reviews coming in and let us know how we’re doing! We’re listening, learning, and working hard to be the domain registrar you deserve. What Makes Us Different? WHY PORKBUN IS THE BEST REGISTRAR We believe we are the best domain registrar in the world. Many folks that find us are looking for a good deal, and we certainly are competitive on price. However, we don't simply aim to be cheap — we aim to be awesome! We offer great prices & deals to save you money. We sell you things you want and need, and nothing that you don't. Our support department is available 365 days a year. We value feedback and do not take your business for granted. We think we’re hooves-down the best domain registrar in the world! Why? Sure, we’ve got low, competitive prices on domain names, powerful web hosting solutions, email hosting, and more (who doesn’t love a good deal?), but what it’s really all about is you — our customers. YOU’RE THE BEST! At Porkbun, we think you’re the important part of the story and the center of our work. It’s why we’re always striving to give you an amazing experience. It’s about giving you personalized support 365 days a year and helping you get the most from the products and services you need. It’s about offering what you actually want and need, without trying to constantly upsell you on a bunch of stuff you don’t. It’s about listening to your feedback, valuing your business, and continuing to grow in a way that honors our earliest supporters and newest customers alike. At Porkbun, it’s about you — our customers. We think you’re the best, and we’re always striving to give you the best experience possible. How Porkbun Keeps Prices Low THE PORKBUN PRICING APPROACH Here’s the deal: every domain registrar pays a fixed cost to the registry (the folks who own the extensions like .com or .org). They’re the wholesalers, while we represent the retail side of the industry, where you can register a domain name. At Porkbun, we sell most domains at our cost (wholesale + ICANN + credit card fees) — even on our most popular extensions like .com and .org. We also pass on any discounts we get from the registry to you in full, now that's oinking it forward! 📦 .com Wholesale $10.26 🌐 ICANN Fee $0.20 💳 Credit Card Fees $0.64 👻 Hidden Fees NONE 🛒 Total $11.08 Transparent pricing. Zero markup. Now that's Oddly Satisfying. Updated July 1, 2025. Speaking of gimmicks, you’ve probably seen those “free domain” or super low first-year offers at other domain registrars (you know the ones). Spoiler alert: they’re not really free. Those registrars are making it back somewhere else (probably your renewal rate, the amount you’re paying for year two, three, and onward). When shopping for domains, pay attention to those steep first year discounts and "free" domain offers. A free .com domain doesn't exist Free.com — your provider simply is paying for the name and making enough money off you elsewhere to write it off. At Porkbun, we’ll always pass on first-year savings when we can get a sweet deal from a registry, and our renewal prices are kept as low as we can to give you the most value for your investment. No surprises, no tricks — just pricing transparency offering a great value year after year. We also offer some steep discounts in the FIRST YEAR . If we can get a good deal from a registry partner, we want to pass it on to you! When you compare our renewal prices against the competition, we are consistently a better deal Why do we do all that? Because we’d rather grow our business by making you happy instead of drastically increasing renewal prices or having hidden fees. Our focus is on providing you the best service and support, not lining our pockets with a high markup on domain names. Our business grows because our happy customers tell their friends. We use that growth to expand our products and services. There’s no better way to earn your continued business than by delivering a mindblowing experience. Why We Give Things Away For Free PORKBUN FREE DOMAIN NAME FEATURES Everyone loves freebies! Here at Porkbun, we believe that part of being the best domain registrar includes giving you more for your money. That’s why every domain name from Porkbun comes with free domain name features like WHOIS Privacy, SSL certificates, email and web hosting trials, and so much more. The way we see it, why pay for things that should be free? We were the first to offer free Whois Privacy — protecting your contact info from being plastered all over the internet (unless you opt out or the domain extension doesn’t allow it). It’s the right thing to do. Period. We were also the first registrar to use Let’s Encrypt to offer free SSL certificates. These certificates keep your site secure, boost your search rankings, and show visitors you’re the real deal. If you’re using our DNS, your Let’s Encrypt SSL certificate will renew automatically. If you’re using our web hosting you’ll have the most seamless experience as it’ll renew and install automatically without you having to do a thing! We’re all about making your life easier. Other domain registrars may charge extra for these basics, but not us. Privacy and security shouldn’t be an added cost — they should come standard. Since we’ve never charged for these, we’re not subject to the same revenue pressure they are, so you’re getting more for your money at Porkbun. Why We're Here OUR CORE VALUES Everything we do at Porkbun follows our core values to give you the best experience possible. We’re not just about domain names — we’re about creating something extraordinary. Our core values guide everything we do, from how we treat our customers to how we operate as a team. Here at Porkbun, we want to: Deliver a mind-blowing experience: We don’t just meet expectations — we aim to blow them out of the water! Be thoughtful: We listen, we care, and we prioritize what matters most to you. Infuse the world with fun: From our Porkbun pig logo to the way we communicate, we believe everything’s better with a bit of fun. Stand behind each other: We’re a team, and we support our team members — and we want you on our team, too! Whether you’re a first-time buyer or a domain pro, we’ve got your back. Our core values are the cornerstone of our approach as a domain name registrar and what we attribute to our continued growth. Why Use Porkbun? WHY PEOPLE CHOOSE PORKBUN We’re confident if you take a look, you’ll see why Porkbun is the best domain name registrar out there. Whether you choose us or not, we want you to feel informed about your decision. When you compare domain registrars like GoDaddy vs Porkbun , make sure you’re looking beyond the flashy deals. Check out their renewal prices, any possible fees for domain features like WHOIS Privacy and SSL certificates, and how they handle customer support. Our incredible support team is available to you 365 days a year by email, phone, and chat to make sure you’re getting the best experience possible.. Lastly, check out our pig butt logo. We’re fun, friendly, and seriously good at what we do. Now you’ll understand why we had no problem calling ourselves the best domain registrar in the world! Let’s do something awesome together. 🐷 Who We Are WORLD'S GREATEST DOMAIN TEAM While we consider the Pacific Northwest our home, our team comes from all over to provide you with the best domains experience!. Cause in the sty, we all fam! Porkbun Master of Oinks Don't ever tell her "that'll do, pig". Just don't. Raymond King of Porkbun This man owns a lot of goats. Peter Head Bean Counter Loves tennis and Brazilian churrascaria. Andrew Good Cop 👼 Beyonce's biggest fan. Owen Janitor May or may not have a bunker. Kimberly The Enforcer Everyone in her hometown owns a giant panda. Just kidding! Summer Partnership Manager Chinese business guru and coolest name in the office. Ross Director of Operations Resident knitting and bread enthusiast. Nikki Design Director Makes things pretty because the rest of us are a mess. Sarah The Saint She's from Idaho, so something about potatoes. Phillip El Jefe He's learning Spanish so his cat can ignore him in two languages. Christopher Porkbun Wizard Probably our best bowler. Danielle Campaign Captain A swiftie. David Marketing Content Specialist Best beard in company now. Also does wicked stuff on vinyl. Lindsay Marketing Content Specialist She hasn't killed Steve! --> Steve The Devourer of Souls and Sinuses Has really wonderful growth potential. Eddie Andrew's Future Boss His real title is over 20 words long and cannot be spoken by mere mortals. Dylan Support Guru Dylan once left Portland and Portland ceased to exist. Alex The Gator 🐊 He's our very own Florida man! Won't admit it but has probably wrastled a gator. Andy DNS Detangler He's close to the other Portland. Migrated to California. Wound up getting stuck in Texas. Chris Support Guru He's been everywhere, man. Jeremy Porkbun Wordsmith Will make you feel bad about how few books you read. Dakota Moderating Magician Careful, she'll convince you that you need a Labradoodle. Isaac Certified Porklift Operator Also from Idaho, so something else about potatoes. Morgan Meme Queen Knows more about Spiderman than Spiderman knows about himself. Will Support Guru Where there's a Will, there's a way. India Cosmic Pixel Pusher Computing funny blurb... Trevor DNS Whisperer Yet another Idahoan, but we're all out of potato jokes. Maggie Empress of the Void Sione Support Guru She'll be in her shed, if she didn't lock herself out. Zeek The Raccoon 🦝 Totally not a raccoon. Kevin Late Night DJ He wont be impressed by technology until he can download food. --> Richard Pork-Propagation Specialist Is fluent in over seventeen amphibian dialects. Also, Rock Lobstah! 🦞 Tucker Homelab Renovator Doesn't know how to take a selfie. Steven strADegist Was going to tease him about watching infomercials for fun, but he knows Jiu Jitsu. Edgardo Unlicensed DNS Therapist [FUNNY TEXT PLACEHOLDER] Claire Emoji Curator Has a collection of the world's greatest custom emojis. Kaku Customer Appreciation Technician Meow meow, meow meow meow meow — meow! Michelle Kung-Fu Communicator Earned a black belt in Speech and Debate. --> Sara Bean Sprout Unlike the Dodo, Doudou will never go extinct! Jenny Professional Juggler Juggling is a sport, not a hobby. Calista Domain Tuner 432hz > 440hz. Ina Auxilium Architectus They know Latin, but do they know Pig Latin?. Amelia Fishing and Inter-Net Navigator Has never seen a panda. Calvin Support Raid Leader [Calvin has entered chat] [Roll for Initiative] Jay Paladin of the Phone Line 🔥🗡️ Brenton Wallfacer First he's (re)learning unicycle. Next it'll be bagpipes and fencing. I'm sure there's a way to combine all three too. RuiRui DNS-Pop Superstar I assume four of her cats are named Jisoo, Jennie, Rosé, and Lisa, but what's the fifth cat's name? Steve? Will Goth Dad Now we need to hire someone named "Wei." Porkbun Porkbun lived on a farm before becoming our Master of Oinks and overall doer of awesomeness. It was a happy life, but boring. She was a dreamer. All the other pigs were content to root for truffles in the mud, but not Porkbun. She wanted to travel the world, see the sights, have adventures and start her own business. The other animals made fun of her and called her a silly little pig, but she didn't listen. She packed up her stuff and moved to the city. She never did start that business though. Instead, she took over ours! When not knee deep in the day to day of running the best domain name registrar in the Orion Arm of the Milky Way; Porkbun loves to spend her free time sipping fine wine, racing monster trucks, and reproducing early American pioneer era patchwork quilts. Raymond Raymond, or Ray, has been a noted innovator and entrepreneur since he started a company while still in high school. His next project, Semaphore, Inc., was created during his sophomore year at M.I.T., and began as a project management software package. By 1990, it was rated #1 in its space by ARCHITECTURE magazine, and grew to over 100 employees, serving 2,500+ clients. Ray went on to co-found SnapNames.com. It was his first major role in the domain name space and they invented several new ways for people to acquire domain names; it grew to more than $49 million in annual revenue by 2006. Ray has had a personal passion for wikis for years, which even led him to found ICANNWiki, a vibrant wiki resource that links together the ICANN ecosystem. He is a native and long-time resident of New York City, but has been in Portland Ore. since co-founding SnapNames.com – his current farm outside the city, complete with tractor and goats, is a definite but welcome departure from his days in Manhattan. Peter Peter has over 22 years of experience in starting, investing and managing new companies within the healthcare, auto, loan, entertainment and technology sectors. He is the Chairman of HomeNurse, Inc., a leading provider of home care in the state of Georgia, with over 1,000 employees. Prior to HomeNurse, Peter was the COO of Liberty Home Health, Inc. and led the sale of the company to Georgia Baptist Hospital, now known as Tenet Healthcare (NYSE:THC). Peter was nominated for the Merrill Lynch/Ernst Young Entrepreneur Award in 1996. He holds a BS in Engineering from the United States Military Academy at West Point and earned an MBA from the JL Kellogg Graduate School of Management at Northwestern University. Peter served in the U.S. Army infantry where he attained the rank of Captain and earned airborne, air assault and ranger qualifications. Peter is an Endowment Guardian with the Boys and Girls Club of Nassau County Foundation, Florida and a founding member of the Georgia Aquarium in Atlanta, Georgia. Andrew Andrew's knowledge of ICANN and the DNS industry comes from years with ICANNWiki, where he managed the site, including its fundraising and content, and represented the project at every ICANN meeting since 2011. While still active in ICANN policy development, he now leads corporate and TLD specific strategies. He is in awe of the Internet and values the chance to contribute to its continued development. Andrew is a native New Mexican; even if he was born in California and spent much of his young life in Minnesota. He has studied and lived abroad in Italy, East Africa, and Panamá, and he graduated from Lewis and Clark College in Portland with a B.A. in Religious Studies. He speaks both Italian and Spanish, though, more often than not, a somewhat intelligible hybrid of the two. Andrew also still remembers enough Kiswahili to surprise the East African delegation at ICANN meetings. Owen Owen is a long time veteran of the domain name industry. Starting in 1999 at Dotster.com as one of their first employees, he engineered and built their NameWinner domain backordering platform before eventually moving on to SnapNames.com where he continued work on backorder technology. In 2003 he went to work building and maintaining the domain registrar DomainSite which eventually became Name.com. He spent the next ten years there, holding many different technology related rolls before departing after its sell to Demand Media. Owen is a product of a small town in Washington state but has lived in Portland, Oregon and Denver, Colorado while pursuing his career. He's now back in his home state where he enjoys being outdoors, most notably sailing the high seas of the Pacific Northwest, and traveling with his wife and four children. He speaks a bit of Brazilian Portuguese and prior to stumbling upon his calling of developing sweet online products and services he held such prestigious positions as dump truck driver and auto parts store manager. Ross Ross began his career in tech support as a high school intern. He's been honing those skills ever since, and leapt at the opportunity to bring that experience to Porkbun. In his spare time, Ross loves to sing, play the guitar, and code. His favorite Portland Vietnamese restaurant is Phở Hung, although he admits Hà VL is pretty dang good, too. Sarah Sarah relocated to Oregon from Boise, Idaho. She has extensive IT / customer support experience and is excited to use those skills to support Porkbun customers. She has spent some time traveling and loves spending her free time eating her way through Portland. Phillip Phillip moved back to Portland in 2018 from his hometown of Milton-Freewater, Oregon. He began his career in IT as a student worker at the Office of Information Technology at Portland State University. Prior to Porkbun, Phillip spent 3 years providing awesome support with Vivio Technologies in Walla Walla, WA. In his free time Phillip enjoys playing video games, going on nature hikes and volunteering his time to noble causes. He is also a skilled cat whisperer and photographer of feline friends. Christopher Christopher started off his IT career with Godaddy in Gilbert, AZ. He started in tech support/sales support with Godaddy, then moved on to hosting support before relocating back to the NW. Most recently, Christopher was the support manager for canvashost.com, a local web hosting provider here in downtown Portland. Christopher enjoys spending time with his wife and two children. Christopher is an avid golfer and bowler as well. Kimberly Qi (Kimberly) is from Sichuan, China, which is famous for the giant panda and spicy hotpot. She studied at San Francisco State University as an international business major and has years of online marketing experience in the software industry. Before she joined the Pokbun side of the business, she was with Top Level Design (the registry) for many years. She is really good at numbers and is ready to bring her expertise to her new role at Porkbun. Sichuanese love spicy food, and Kimberly is no exception. She lives in Beijing with her husband, two lovely cats and a cute dog. She keeps hunting spicy food in her local area. Danielle Danielle is from Tujunga CA, a mountain town north of Los Angeles, a place where nature meets the big city. After getting her bachelor's degree in Marketing from San Diego State University, she went back to Los Angeles and began her career in marketing. She now has over a decade of experience in both traditional and contemporary marketing strategies and has worked in a variety of creative industries. From the music industry to health and wellness companies, she has a vast array of marketing knowledge and experience. She is ready to bring her balance of creativity and brand building strategies to Top Level Design. Danielle currently lives in Portland with her husband and her beloved parrot, Pete. She loves being in nature, exploring new neighborhoods, seeing live music, and would one day love to learn a new skill such as painting or playing a musical instrument. David David is a language engineer with an eye for design and an ear for the unordinary. He earned his bachelor's from Colby College (where he focused on music and German language/culture) but his story really began when he moved to San Francisco and found his place among the Bay Area's vibrant queer and creative communities. The search for sustainability led him to Portland, and after several years at a social justice nonprofit, David joined Top Level Design to develop creative strategies for making the internet a more expressive and inclusive space. David is a DJ, a vinyl collector, a synthesizer enthusiast, and a burgeoning plant daddy. He is passionate about enriching people's lives through music, art, design, poetry, literature, and advocacy for education, health care, the environment, and civil rights. He believes in the power of mindfulness and compassion to make the world a better place. Lindsay Lindsay's passion for language and literature continually drives her work. After completing her bachelor's in Writing, Art, and Women's Studies from Portland State University, she returned to Los Angeles and gained a breadth of experience at a digital marketing agency, working across a diverse range of industries. After her fill of sunshine and tacos, she settled back into Portland's vibrant queer community, where she seldom identifies as one of those notorious Californian transplants. Compelled by a commitment to connective storytelling, Lindsay joined the Top Level Design team to further cultivate her creativity and community engagement. As an artist, Lindsay is usually bouncing between too many things—sometimes huddled in with a good read (most likely a theoretical feminist manifesto, or two), more often starting a creative project to add to her increasingly over-crowded walls. On welcome sunny days, she's out in her kayak, soaking up the gems of the PNW. --> Steve When Steve was a young sprout she longed for a day where lounging around in some office window sill was all she had to worry about. After spending a bit of time being sent from greenhouse to greenhouse she eventually found her spot in the Porkbun office. As a plant Steve mostly just sits there and creates oxygen. She does enjoy a cool sip of water from time to time and listening to some good tunes but mostly she just photosynthesizes. Eddie Eddie originally is a classically trained singer and musician, proficient in opera and musical performance. Their years at Lewis & Clark College though were mostly spent working in the library basement, where he maintained a lab of Mac Pros for students to use for editing, along with four large format printers that needed constant care. He has since moved out of the basement and spent many years doing marketing in the produce and food industry before landing at Porkbun. They were born and raised in Oregon where he still resides. He enjoys exploring the vast lands of Skyrim and the greater Pacific North West, cooking over an open flame, and spending time with his loving partner and their multiple fur babies, clumsy bearded dragon, and many, many plants. Dylan Born and raised in Portland, OR, Dylan has lived in the Pacific Northwest their whole life. Like any good Portlander, they love the great outdoors, a good cup of coffee, and kale. Beyond being a proud Portland stereotype, Dylan has had a passion for punk rock and the local music scene, going to shows since they could barely see over the stage. Professionally, Dylan worked several years in social services and at social justice organizations. Looking for a new challenge, Dylan found a place in technology, working various technical support roles and eventually going to school for website design and development. When not programming, drinking coffee, or at a show, Dylan can be found hanging out with their partner and two cats, Wasabi and Char Siu. Alex Originally from the PNW, Alex ran far, far away to the often news-worthy state of Florida. He currently resides in Palm Beach county, about 60 miles north of Miami. Naturally, his mother worries about the hurricanes for him, freeing up Alex to enjoy life in the sunshine state, nonchalantly. He attended college in the Midwest and Southeastern United States, studying Computer Information Systems, while also working for several financial and technological organizations. He found his calling when he realized that problem-solving was enjoyable and fulfilling. All his life he had been studying the art of, “This thing isn't working, can you fix it?” only to discover that companies were willing to hire him for this skill. When Alex isn't problem-solving he savors beaches, brunches, brews, wandering the wastelands of the Fallout series, and balmy breezes through emerald palms. Andy Andy has loved technology since being enthralled by the Mac-powered escapades in 1994's childhood tech thriller Blank Check , filmed in Austin near Andy's Central Texas home. After spending time at Baylor University, Andy worked in a variety of technical roles (and moved to Maine), gaining exposure to a variety of technology, climates and customers. Beyond his technological interests (including a large public domain photography collection), Andy is an avid college sports fan (Sic ‘Em Bears!) and loves the leisurely side of enjoying the outdoors, having recently taken an interest in e-bikes. Chris Hailing from the midwest dontcha know, Christopher has lived and traversed all over the states. From Alaska to Florida, the unforgivingly sunny SoCal, and up the ever drizzling PNW, he has lived just about everywhere before nestling into the mountainous lands of Denver. While waiting for the bubble to burst in real estate, Christopher can be found in the mountains with his puppies, getting into shenanigans under the stars with a tent and backpack, or slowly wasting away in a CrossFit class sweating and questioning his life choices. Whether writing his next novel, enjoying the cherry blossoms in Tokyo, solving someone's DNS issues, or drinking one too many energy drinks (not fit for human consumption may just be a warning and not a fact), Christopher is on the case with whatever you may need! Jeremy Originally from Louisville, KY and now living in Los Angeles, Jeremy started his career in marketing and quickly launched his own company. Interested in a more collaborative dynamic, he's excited to bring his love for creativity and strategy to the Porkbun team. Trained as an actor, he enjoys any sort of creative outlet. In his spare time, he loves cooking beautiful meals for friends and family, reading, making floral arrangements, and traveling (Paris is like a second home). He also has a passion for cars and likes playing video games (anything Final Fantasy!). Dakota Dakota's educational adventure took her from earning a Bachelor of Arts in Sociology and Religion at Wheaton College (MA) to achieving a Masters of Science in Communications from Northwestern University. Hailing from the picturesque Pacific Northwest, she finds "pawsitive vibes" in her backyard, accompanied by her three labradoodles: Arrow, May May, and Cherry Sue! They're not just her "fur-endly" companions but also her "bark-tastic" partners in outdoor adventures. When she's "pawsing" to appreciate nature, Dakota fully embraces the joy of the outdoors with her furry pals and her husband, "unleashing" unforgettable moments amidst nature's beauty. Isaac Isaac was born and raised in Boise, Idaho, where he lives with his fiancé, cat, and dog. He recently changed career paths after 15 years in the health food retail industry. In his free time Isaac enjoys playing RPGs and strategy games, cooking, biking around town, and sipping on beers at any of Boise's many breweries. Morgan Morgan started using computers behind her parent's back when she was six years old and has loved technology ever since. She studied theatre in high school and college, where she focused on audio engineering and design. While studying she was also employed by her university's IT department, so she is used to troubleshooting issues from simple to persistent. She is a current Texan that was born and raised in Chicago, so she is unfortunately still a fan of sports teams that disappoint her. Her personality centers around her cat Frank, her obsession with Spider-Man, and the movie Shrek 2. Will Originally from God's Country (New Jersey), Will can play six degrees of separation with both Bon Jovi and Bruce Springsteen. You can usually find them hanging with their dog Young Man or contemplating the nature of existence. They have worked in the domain and tech support fields for over a decade and are stoked to bring that experience to Porkbun. India India was born on the east coast where she earned a degree in Computer Science and Psychology. She has transformed that knowledge into a 9+ year Information Technology career that spans from Technician, Design, and Support work to teaching volunteer computer classes. She has diversified professional experience having also spent significant time in Business Logistics Management and Human Resources. India is a lifelong learner and loves reading about, trying, and experiencing new things that interest her. Trevor Born in sunny Las Vegas and currently living in Boise, Idaho, Trevor's battle with dry skin is ongoing. When he's not moisturizing, you can find him hanging out with his cat (an orange tabby/menace to society named Duchess Jellybean), learning video game design, and watching Scottish Parliamentary proceedings after they get uploaded to the internet. He dreams of one day creating the perfect bowl of ramen. Maggie After many years of deliberation and working for Gaming retail companies, Maggie finally decided to follow in her father's footsteps and get into the tech scene. She's always been fond of helping people and solving issues regarding tech and decided to make the big step to continue that legacy her father left. When she's not helping out she likes to spend her time playing games and drawing (and maybe the occasional escape room). If you need any game recommendations let her know! Sione Sione was born in New Orleans, Louisiana but has since relocated to Dallas where she spends her days creating things in her craft shed. With a lifelong love for activities that spark both the creative and analytical centers of the brain, her career in technology was a surprise to no one. When she isn't eye to eye with a computer screen, she plays an almost concerning amount of tabletop games, cooks ridiculously tasty meals, and writes almost twice as much as she reads (which is a lot). Zeek Zeek has been providing nothing short of the most epic customer support ever for over 12 years with a specific focus in the video game industry. When this raccoon in disguise isn't spamming terminal commands, he secretly aspires to be a self-published author following in the steps of great writers like Brian Jacques and H.P. Lovecraft. He also enjoys exploring the many different variations of vegan cuisine and hanging out with his Shiba Inu, Cheems. Just don't ever ask Zeek to finish the game he's working on -- 'cuz then it'll really never get done. Kevin Born and raised in Los Angeles, CA Kevin has been in the industry since 2016. Prior to joining the Porkbun team Kevin worked at GoDaddy for over 8 years as a Support Specialist. He is an avid traveler who has visited more than 20 countries and likes to spend his free time near large bodies of water and hanging out with friends and family. He enjoys finding new restaurants to try and holds sampler platters, be it food or beer, in the highest regard. His hot-take is that cats are superior to dogs as pets. Richard Richard's tech journey started as a young boy with his first love—his Coleco Adam home computer, which transformed him into a full-fledged gaming addict and computer geek. From the blazing deserts of California, he pursued an education in computer science and mathematics, all while dreaming of one day merging with technology to become the ultimate human-computer hybrid (think V'ger from Star Trek). Until then, he's happy solving tech puzzles and embracing the digital world with both claws forward. Tucker Totally not generated using AI: What can we say about Tucker? Not much, since we're still waiting on their official bio... which was due several weeks (or was it months?) ago. But that just makes them all the more intriguing. Some say they're a master of quiet observation, others believe they've unlocked the secrets of office microwave etiquette. What we do know is this: they show up, get the job done, and somehow avoid being in group photos. Rumors abound—did Tucker once backpack through the Andes with only a spork and a dream? Have they really trained a pigeon to deliver their emails? We may never know. Until their bio miraculously arrives, Tucker remains an elusive figure in our office lore, quietly building a legacy of intrigue. One day we'll have the full story... but today is not that day. Steven Steven is born and raised in Nike Town, Oregon. Enjoys all physical challenges – marathon running (retired), spartan races, brazilian jiu jitsu, weight lifting with a focus in bodybuilding + olympic lifting, and a special PhD in Broscience from YouTube University! Also plays board and video games, anything that connects friends and family. Reading in his spare time a mix of dystopian fantasy fiction and self development books. Finally a hot take that book clubs need a comeback to be more mainstream. After discovering an interest in marketing, like tier-listing superbowl commercials, went on to study at Oregon State University for a B.S. in Marketing & Management. This sparked a career in advertising platforms in the tech and healthcare industries. Now blending data with business acumen, he strives to serve customers with the right product-service offering through ads. Edgardo Edgardo was born and raised in Los Angeles, CA. His love for technology began at an early age, sparked by an incident where he accidentally crashed his home computer while downloading music. He attended Cal State Northridge, where he further developed his skills and passion for technology. Outside of work, he lives with his wife and two dogs — a Shih Tzu and a Schnauzer. When he's not working, you'll find him playing video games, watching football, basketball, and soccer, hiking, hitting the beach, and exploring new restaurants. A firm believer in learning through resources like YouTube University, he's always looking for ways to stay current with the latest tech trends. Claire Meet Claire, a super friendly and problem-solving enthusiast from Henan, China. Fun fact: her real name is Purple Wild Googe (yes, it's a bit quirky in English, but she loves it!). Claire also goes by Claire Pritchett, inspired by her favorite TV character. And here's a joke — every 14 Chinese people, one is from Henan, so she's in good company! Before joining Porkbun, Claire worked for a solar company, always enjoying helping people and tackling challenges. But here's the little secret—Claire might have chosen to join Porkbun because she's a big fan of pork buns, especially for breakfast! Kaku Kaku loves spending her days making sure people feel heard and understood — whether in person, over the phone, or through a screen. She has a thing for languages and communication, though her toughest challenge yet is trying to hold a proper conversation with her two cats (so far, they're winning). Fluent in English, Japanese, Chinese, and a bit more, Kaku is endlessly curious about different cultures and creative ways to connect with people. When she's not working, she's probably lost in an anime marathon, on a mission to find the perfect dessert café, or locked in a heated debate with her cats over who actually owns the couch. She's always up for a challenge — especially if it involves learning something new, great conversations, or just a little fun along the way! Michelle Michelle was born in Henan province in China, a region famous for its Hulatang (Spicy Pepper Soup), Huimian (Henan Braised Noodles in Savory Broth), and, of course, the renowned Shaolin Temple, that's where you can learn the Chinese Kungfu! Michelle has always been the kind of person who's energized by meeting new people and love to travel around. She is drawn to the experience of immersing herself in different cultures, meeting people from all walks of life, and truly living as the locals do. She believes that travel isn't just about sightseeing—it's about understanding different ways of life and broadening her perspective. Besides traveling, she enjoys the simple pleasures of life, like hanging out with friends or taking a walk in the park. Whether it's a lively conversation over coffee or a quiet moment surrounded by nature, these small joys help her recharge and stay inspired. Her love for languages started early, which is why she decided to major in English at university and pursue a master's degree in interpretation and translation. While many might have settled into a career as a translator or teacher, Michelle had other plans. After years of learning English, she decided it was time to step outside her comfort zone. Why stick with what you know when there's a whole world of knowledge waiting to be explored? Joining Porkbun is not the most obvious choice for someone with her background, but that's exactly why she's excited about it. It's a completely new industry, a chance to dive headfirst into the tech world and learn something completely different. And if there's one thing Michelle loves, it's challenges—so she's ready for this next adventure. Amelia Amelia was born in Henan—a place with no panda in sight, but she's counting on Kimberly to get her one eventually. She brings her boundless energy, quick wit, and sunny spirit to the Porkbun team, always ready to support our customers with a smile. When she's isn't helping customers untangle tricky domain questions, she's scaling mountains and hiking through nature with a fishing rod in hand. That is… until one life-changing moment when the fish wouldn't bite and she discovered the true power of the net. Ever since then, she's proudly embraced her identity as a mountain-stream net fisher. Efficiency matters. She cares for her aquarium fish, tends lovingly to her houseplants, and her cat Mimi thinks flowers are salad and fish tank is drinking fountain. Meet the apex predator of the ecosystem—Mimi the Great! Despite the chaos, the kitty loves Amelia so much (she insists). Sara My last name is Dou, which means "bean" in English — so my friends affectionately call me Doudou, and the nickname has stuck ever since! I'm from Huaiyang, Henan, a small town in China that's known as the birthplace of the First Ancestor of Chinese Civilization. One of the most unique cultural traditions in my hometown is a folk art called “Nini Dog” — an intangible cultural heritage where people handcraft small clay figures with distinctive designs. I had the chance to work in the Middle East for three years, and it was a truly eye-opening experience that broadened my view of the world. In my free time, I enjoy drinking tea — especially Chinese tea — and I love jogging to stay healthy and clear my mind. I'm excited about the future and look forward to traveling to new places and meeting friends from all around the world! Ina Ina grew up in a sepia-toned and crowded childhood, where colors first flickered through the pixels of Microsoft Windows. They've always loved listening to people talk about their dreams, especially the kind that try to reach beyond the screen. With a background in tutoring and education, Ina remains skeptical of “talent” as defined by the systems that benefit from it. Their work is shaped by a belief in making room for quiet voices, and finding ways to bridge ideas and reality. The same instinct led them to Porkbun, where naming a dream is often the first step toward building it. Beyond working hours, they love wandering through cities (especially the parts you're not supposed to explore), deciphering Latin, and crafting perfumes from botanical tinctures. Somewhere in the patch notes of the universe, it says: if you prepare a hard drive with Yume Nikki, Machinarium, Year Walk, and a slice of tiramisu… Ina appears. People say it's only a myth. But check your friend requests, just in case. Calista Calista is the Zhengzhou-born domain specialist at Porkbun who configures DNS records to the rhythm of Jay Chou's "Sunny Day." From her academic days near Niagara Falls to becoming a domain expert, she approaches technology with a musician's ear, turning complex systems into solutions that feel as natural as humming a favorite song. At her workspace, the aroma of pour-over coffee blends with focused problem-solving. While crafting solutions for .pork domains, she adds playful charm to her work: "This domain deserves center stage!" or "Let's fine-tune your online presence like a perfect melody." Whether she's syncing DNS records to a beat or troubleshooting with the precision of a metronome, Calista proves that, in the right hands, even technology can hit all the right notes - especially when coffee is involved. Jenny Jenny once spent years managing software localization projects across teams, tools, and time zones — now she wrangles DNS records with equal finesse. She brings calm, pragmatic energy to every support request, probably shaped by raising a ten-year-old (and previously, a dog). Based in Zhengzhou, Henan, she juggles support tickets, spicy snacks, and a child with more energy than the entire engineering team. When she's not solving domain mysteries, she's binge-watching crime dramas until 2 a.m., dreaming of her next street food adventure, or quietly judging email headers like they're plot twists on Netflix. Calvin Calvin didn’t join Porkbun in a normal way—he basically fast-traveled here. Before joining the herd, he ran go-karts, VR arenas, and chaotic vacation energy on cruise ships, proving that if you can manage tourists racing tiny cars on a moving ocean, you can definitely handle DNS on solid land. Born in Henan and powered by coffee, Calvin treats every support ticket like a co-op raid: read the mechanics, find the weak spot, and help the whole party clear the dungeon with better loot (and working email). He’s specced heavily into empathy, curiosity, and “I’ll explain this without making your brain crash.” Off the clock, Calvin dives headfirst into the future—AI copilots, neural link headsets, full-dive VR rigs, AR contact lenses, and any other technology that sounds like it was patched in from another timeline. His long-term dream is to resolve tickets via direct brain ping and call it “latency-free support.” At home, he serves as a humble NPC to four opinionated cats who firmly believe keyboards were invented for them. If your domain ever feels stuck in another dimension, chances are Calvin is somewhere nearby, calmly patching reality—one support ticket at a time. Jay Jay is a hardcore gamer, Dark Souls veteran, and proud Chinese food enthusiast. Jay learns quickly and loves a good challenge—whether it's taking down a boss with a door handle or perfecting his stir-fry technique. When not farming souls, he is in the kitchen cooking up some of the best Chinese dishes you'll ever taste (no, really, he's got it down to a science). He went to high school in Atlanta, and not much was going on—what was he supposed to do, learn American high school math as a Chinese kid? Honestly, the only thing hard was explaining to his teachers that he didn't need help with algebra—he just needed help with English. Therefore, he got a lot of free time and developed a lot of habits there. He lived with a Christian family that was all about caring for others, and he thinks he picked up their compassion. That's why he loves helping people—because why not bring a little kindness into every side quest? Dark Souls taught him patience... and cooking taught him how to handle a knife (for non-boss reasons). ⚔️🍜 Brenton Brenton grew up in Washington state and still calls it home. He found his way into the web hosting world after college and still enjoys it. Before joining Porkbun, he spent 14 years at Vivio Technologies where he worked as a Server Administrator and Support Manager. Off the clock, Brenton enjoys spending time with his wife and two kids, reading books(mostly sci-fi and fantasy), playing computer games, catching up on TV shows, camping, and has recently picked up riding a unicycle again. He is a hoarder of computer parts because he "might need them one day". Ask him about the book he is currently reading and you'll probably get a longer answer than you bargained for. Rui Yes, I hugged Jennie from BLACKPINK. I’m someone who finds joy in quiet curiosity—whether I’m reading a good book, watching documentaries, or flowing through yoga or pilates. I’m currently working toward my Pilates instructor certificate, slowly building the kind of strength and balance I want in life. My dream life is simple: cooking spicy food in a cozy kitchen, living near the sea, riding my bicycle whenever I can, keeping a fit and healthy body, and spending my days doing the things that genuinely light me up, which I’m creating step by step. Will Will likes computers. No surprise, since he's been on them since he was five years old. He's spent most of his adult life fixing tech problems and solving complicated issues on almost anything with a circuit board. Will brings his unique attitude and worldview to Porkbun on a mission to solve current problems and set customers up for the future. Will can usually be found gaming, reading, or hanging out at the many goth clubs in his hometown of Portland. He listens to music throughout every day, and his preferred playlist currently clocks in at over 17 hours. Other interests include retro gaming, cooking, baseball, and the works of David Lynch. × Modal Title Close Close × Modal Title Close porkbun Porkbun is an amazingly awesome ICANN accredited domain name registrar based out of the Pacific Northwest. We're different, we're easy, and we're affordable. Use us, you won't be sorry. If you don't use us we'll be sad, but we'll still love you. Get Pork-Puns In Your Inbox Stay in the loop on all things Porkbun by signing up for our newsletter! 21370 SW Langer Farms Parkway, Suite 142-429 Sherwood, OR 97140, US If you're looking for support, you might be able to answer your own question using our Knowledge Base . Support Hours Impacted From January 3rd to January 11th we will be holding our annual company summit which will impact live and after hours support. Our goal is to provide you with an excellent domain registration experience and support and we all appreciate your patience as the whole company works together to make Porkbun even better. Thank you. Reach our USA-Based phone support team: 1.855.PORKBUN (1.855.767.5286) 9AM - 5PM Pacific Time Other Hours: Your mileage may vary, but give it a whirl support@porkbun.com 24 / 7 Email Support Chat Support Hours Vary Your browser does not support the audio element. This plays a little Porkbun jingle. Stay up to date with Porkbun. Sign up for our cool newsletter and we'll keep you up to date with sweet deals, amazing info, and maybe even the occasional limerick or sonnet. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close # development Follow Hide Tracking and discussing physical and cognitive milestones. Create Post Older #development posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Why Repetition Strengthens Knowledge Memory Rush Memory Rush Memory Rush Follow Jan 5 Why Repetition Strengthens Knowledge # requestforpost # learning # science # development Comments Add Comment 2 min read How Learning Develops Over Time Memory Rush Memory Rush Memory Rush Follow Jan 5 How Learning Develops Over Time # memory # development # learning # requestforpost Comments Add Comment 2 min read The silent revolution in Linux? Historical maintainer analysis shows Nix +264%, AUR +100%, while Debian barely grows (+2.3%) Metehan Yurtseven Metehan Yurtseven Metehan Yurtseven Follow Jan 3 The silent revolution in Linux? Historical maintainer analysis shows Nix +264%, AUR +100%, while Debian barely grows (+2.3%) # discuss # linux # opensource # development Comments Add Comment 1 min read Privacy vs. Convenience: The Hidden Cost of Always-On Tracking 🔍📱 Willie Harris Willie Harris Willie Harris Follow Jan 3 Privacy vs. Convenience: The Hidden Cost of Always-On Tracking 🔍📱 # privacy # development # technology Comments Add Comment 5 min read Designing Secure Plugin Architectures for Desktop Applications Emanuele Balsamo Emanuele Balsamo Emanuele Balsamo Follow for CyberPath Jan 2 Designing Secure Plugin Architectures for Desktop Applications # architecture # plugins # security # development Comments Add Comment 12 min read I built wordle for desktop but using my own GUI library! Scriptor Scriptor Scriptor Follow Jan 2 I built wordle for desktop but using my own GUI library! # showdev # opensource # testing # development Comments Add Comment 2 min read Deep Dive into Zero-Day Exploits: Part 1 Emanuele Balsamo Emanuele Balsamo Emanuele Balsamo Follow for CyberPath Jan 2 Deep Dive into Zero-Day Exploits: Part 1 # zeroday # exploit # development # vulnerability Comments Add Comment 9 min read Docker Network Commands Megha Sharma Megha Sharma Megha Sharma Follow Jan 2 Docker Network Commands # devops # docker # opensource # development Comments Add Comment 8 min read Get Hit By Performance Bottleneck In Canvas Ikhwan A Latif Ikhwan A Latif Ikhwan A Latif Follow Jan 2 Get Hit By Performance Bottleneck In Canvas # learning # development # programming # performance Comments Add Comment 4 min read Why Learning Feels Slow at First Memory Rush Memory Rush Memory Rush Follow Jan 3 Why Learning Feels Slow at First # learning # deved # development Comments Add Comment 3 min read Designing High-Performance RTP Media Infrastructure at Massive Scale Ecosmob Technologies Ecosmob Technologies Ecosmob Technologies Follow Jan 2 Designing High-Performance RTP Media Infrastructure at Massive Scale # news # development # rtpmedia Comments Add Comment 4 min read Building a Trustworthy Online IQ Test as a Developer Whats Your IQ Whats Your IQ Whats Your IQ Follow Jan 3 Building a Trustworthy Online IQ Test as a Developer # showdev # iqtest # freeiqtest # development 1 reaction Comments Add Comment 5 min read AI Should Be "Blind" (And That's a Good Thing) Dexmac Dexmac Dexmac Follow Jan 4 AI Should Be "Blind" (And That's a Good Thing) # ai # programming # development Comments Add Comment 6 min read What Happens When Mobile Apps Compete for CPU Time? Raul Smith Raul Smith Raul Smith Follow Dec 31 '25 What Happens When Mobile Apps Compete for CPU Time? # appdev # development # mobileapp Comments Add Comment 4 min read What is UML? Aniket Vaishnav Aniket Vaishnav Aniket Vaishnav Follow Dec 31 '25 What is UML? # programming # development Comments Add Comment 1 min read Why I decided to give away my UI library for free (and just sell the boilerplate) Raman Mohammed Raman Mohammed Raman Mohammed Follow Jan 5 Why I decided to give away my UI library for free (and just sell the boilerplate) # development # webdev # saas # productivity 2 reactions Comments 1 comment 1 min read Introduce Parameter Object: A Refactoring Pattern That Scales CodeCraft Diary CodeCraft Diary CodeCraft Diary Follow Dec 29 '25 Introduce Parameter Object: A Refactoring Pattern That Scales # php # cleancode # programming # development Comments Add Comment 4 min read React Native 0.83 for Production Teams: Better DevTools, Better Tracing, Less Risk Alisson Goulart Alisson Goulart Alisson Goulart Follow Dec 29 '25 React Native 0.83 for Production Teams: Better DevTools, Better Tracing, Less Risk # mobile # typescript # development # product Comments Add Comment 5 min read Artificial Intelligence in Mobile App Development Today Devang Panchal Devang Panchal Devang Panchal Follow Dec 30 '25 Artificial Intelligence in Mobile App Development Today # ai # app # development 15 reactions Comments 2 comments 4 min read Giving AI Roles and Names synthaicode synthaicode synthaicode Follow Dec 28 '25 Giving AI Roles and Names # ai # system # development # productivity Comments Add Comment 3 min read MiniMax M2.1 is live in Kilo Darko from Kilo Darko from Kilo Darko from Kilo Follow Dec 29 '25 MiniMax M2.1 is live in Kilo # coding # ai # development Comments Add Comment 3 min read Day 38 of improving my Data Science skills Sylvester Promise Sylvester Promise Sylvester Promise Follow Jan 1 Day 38 of improving my Data Science skills # codenewbie # tooling # datascience # development Comments Add Comment 2 min read Advanced Context Engineering for Coding Agents Alex Metelli Alex Metelli Alex Metelli Follow Dec 28 '25 Advanced Context Engineering for Coding Agents # agents # ai # development # programming Comments Add Comment 4 min read Building Intelligent, Agentic Applications in VS Code - A Technical Deep Dive into the AI Toolkit Extension Pack Holger Imbery Holger Imbery Holger Imbery Follow Dec 27 '25 Building Intelligent, Agentic Applications in VS Code - A Technical Deep Dive into the AI Toolkit Extension Pack # agents # development # vscode # aitoolkit Comments Add Comment 12 min read Stop Fighting Context Limits: How Multi-Agent Systems Solved My Development Chaos(Part 1) Nour Mohamed Amine Nour Mohamed Amine Nour Mohamed Amine Follow Dec 28 '25 Stop Fighting Context Limits: How Multi-Agent Systems Solved My Development Chaos(Part 1) # architecture # development # productivity # ai Comments Add Comment 6 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://legacy.reactjs.org/blog/2019/02/06/react-v16.8.0.html | React v16.8: The One With Hooks – React Blog We want to hear from you! Take our 2021 Community Survey! This site is no longer updated. Go to react.dev React Docs Tutorial Blog Community v 18.2.0 Languages GitHub React v16.8: The One With Hooks February 06, 2019 by Dan Abramov This blog site has been archived. Go to react.dev/blog to see the recent posts. With React 16.8, React Hooks are available in a stable release! What Are Hooks? Hooks let you use state and other React features without writing a class. You can also build your own Hooks to share reusable stateful logic between components. If you’ve never heard of Hooks before, you might find these resources interesting: Introducing Hooks explains why we’re adding Hooks to React. Hooks at a Glance is a fast-paced overview of the built-in Hooks. Building Your Own Hooks demonstrates code reuse with custom Hooks. Making Sense of React Hooks explores the new possibilities unlocked by Hooks. useHooks.com showcases community-maintained Hooks recipes and demos. You don’t have to learn Hooks right now. Hooks have no breaking changes, and we have no plans to remove classes from React. The Hooks FAQ describes the gradual adoption strategy. No Big Rewrites We don’t recommend rewriting your existing applications to use Hooks overnight. Instead, try using Hooks in some of the new components, and let us know what you think. Code using Hooks will work side by side with existing code using classes. Can I Use Hooks Today? Yes! Starting with 16.8.0, React includes a stable implementation of React Hooks for: React DOM React DOM Server React Test Renderer React Shallow Renderer Note that to enable Hooks, all React packages need to be 16.8.0 or higher . Hooks won’t work if you forget to update, for example, React DOM. React Native will support Hooks in the 0.59 release . Tooling Support React Hooks are now supported by React DevTools. They are also supported in the latest Flow and TypeScript definitions for React. We strongly recommend enabling a new lint rule called eslint-plugin-react-hooks to enforce best practices with Hooks. It will soon be included into Create React App by default. What’s Next We described our plan for the next months in the recently published React Roadmap . Note that React Hooks don’t cover all use cases for classes yet but they’re very close . Currently, only getSnapshotBeforeUpdate() and componentDidCatch() methods don’t have equivalent Hooks APIs, and these lifecycles are relatively uncommon. If you want, you should be able to use Hooks in most of the new code you’re writing. Even while Hooks were in alpha, the React community created many interesting examples and recipes using Hooks for animations, forms, subscriptions, integrating with other libraries, and so on. We’re excited about Hooks because they make code reuse easier, helping you write your components in a simpler way and make great user experiences. We can’t wait to see what you’ll create next! Testing Hooks We have added a new API called ReactTestUtils.act() in this release. It ensures that the behavior in your tests matches what happens in the browser more closely. We recommend to wrap any code rendering and triggering updates to your components into act() calls. Testing libraries can also wrap their APIs with it (for example, react-testing-library ’s render and fireEvent utilities do this). For example, the counter example from this page can be tested like this: import React from 'react' ; import ReactDOM from 'react-dom' ; import { act } from 'react-dom/test-utils' ; import Counter from './Counter' ; let container ; beforeEach ( ( ) => { container = document . createElement ( 'div' ) ; document . body . appendChild ( container ) ; } ) ; afterEach ( ( ) => { document . body . removeChild ( container ) ; container = null ; } ) ; it ( 'can render and update a counter' , ( ) => { // Test first render and effect act ( ( ) => { ReactDOM . render ( < Counter /> , container ) ; } ) ; const button = container . querySelector ( 'button' ) ; const label = container . querySelector ( 'p' ) ; expect ( label . textContent ) . toBe ( 'You clicked 0 times' ) ; expect ( document . title ) . toBe ( 'You clicked 0 times' ) ; // Test second render and effect act ( ( ) => { button . dispatchEvent ( new MouseEvent ( 'click' , { bubbles : true } ) ) ; } ) ; expect ( label . textContent ) . toBe ( 'You clicked 1 times' ) ; expect ( document . title ) . toBe ( 'You clicked 1 times' ) ; } ) ; The calls to act() will also flush the effects inside of them. If you need to test a custom Hook, you can do so by creating a component in your test, and using your Hook from it. Then you can test the component you wrote. To reduce the boilerplate, we recommend using react-testing-library which is designed to encourage writing tests that use your components as the end users do. Thanks We’d like to thank everybody who commented on the Hooks RFC for sharing their feedback. We’ve read all of your comments and made some adjustments to the final API based on them. Installation React React v16.8.0 is available on the npm registry. To install React 16 with Yarn, run: yarn add react@^16.8.0 react-dom@^16.8.0 To install React 16 with npm, run: npm install --save react@^16.8.0 react-dom@^16.8.0 We also provide UMD builds of React via a CDN: < script crossorigin src = " https://unpkg.com/react@16/umd/react.production.min.js " > </ script > < script crossorigin src = " https://unpkg.com/react-dom@16/umd/react-dom.production.min.js " > </ script > Refer to the documentation for detailed installation instructions . ESLint Plugin for React Hooks Note As mentioned above, we strongly recommend using the eslint-plugin-react-hooks lint rule. If you’re using Create React App, instead of manually configuring ESLint you can wait for the next version of react-scripts which will come out shortly and will include this rule. Assuming you already have ESLint installed, run: # npm npm install eslint-plugin-react-hooks --save-dev # yarn yarn add eslint-plugin-react-hooks --dev Then add it to your ESLint configuration: { "plugins" : [ // ... "react-hooks" ] , "rules" : { // ... "react-hooks/rules-of-hooks" : "error" } } Changelog React Add Hooks — a way to use state and other React features without writing a class. ( @acdlite et al. in #13968 ) Improve the useReducer Hook lazy initialization API. ( @acdlite in #14723 ) React DOM Bail out of rendering on identical values for useState and useReducer Hooks. ( @acdlite in #14569 ) Don’t compare the first argument passed to useEffect / useMemo / useCallback Hooks. ( @acdlite in #14594 ) Use Object.is algorithm for comparing useState and useReducer values. ( @Jessidhia in #14752 ) Support synchronous thenables passed to React.lazy() . ( @gaearon in #14626 ) Render components with Hooks twice in Strict Mode (DEV-only) to match class behavior. ( @gaearon in #14654 ) Warn about mismatching Hook order in development. ( @threepointone in #14585 and @acdlite in #14591 ) Effect clean-up functions must return either undefined or a function. All other values, including null , are not allowed. @acdlite in #14119 React Test Renderer Support Hooks in the shallow renderer. ( @trueadm in #14567 ) Fix wrong state in shouldComponentUpdate in the presence of getDerivedStateFromProps for Shallow Renderer. ( @chenesan in #14613 ) Add ReactTestRenderer.act() and ReactTestUtils.act() for batching updates so that tests more closely match real behavior. ( @threepointone in #14744 ) ESLint Plugin: React Hooks Initial release . ( @calebmer in #13968 ) Fix reporting after encountering a loop. ( @calebmer and @Yurickh in #14661 ) Don’t consider throwing to be a rule violation. ( @sophiebits in #14040 ) Hooks Changelog Since Alpha Versions The above changelog contains all notable changes since our last stable release (16.7.0). As with all our minor releases , none of the changes break backwards compatibility. If you’re currently using Hooks from an alpha build of React, note that this release does contain some small breaking changes to Hooks. We don’t recommend depending on alphas in production code. We publish them so we can make changes in response to community feedback before the API is stable. Here are all breaking changes to Hooks that have been made since the first alpha release: Remove useMutationEffect . ( @sophiebits in #14336 ) Rename useImperativeMethods to useImperativeHandle . ( @threepointone in #14565 ) Bail out of rendering on identical values for useState and useReducer Hooks. ( @acdlite in #14569 ) Don’t compare the first argument passed to useEffect / useMemo / useCallback Hooks. ( @acdlite in #14594 ) Use Object.is algorithm for comparing useState and useReducer values. ( @Jessidhia in #14752 ) Render components with Hooks twice in Strict Mode (DEV-only). ( @gaearon in #14654 ) Improve the useReducer Hook lazy initialization API. ( @acdlite in #14723 ) Is this page useful? Edit this page Recent Posts React Labs: What We've Been Working On – June 2022 React v18.0 How to Upgrade to React 18 React Conf 2021 Recap The Plan for React 18 Introducing Zero-Bundle-Size React Server Components React v17.0 Introducing the New JSX Transform React v17.0 Release Candidate: No New Features React v16.13.0 All posts ... Docs Installation Main Concepts Advanced Guides API Reference Hooks Testing Contributing FAQ Channels GitHub Stack Overflow Discussion Forums Reactiflux Chat DEV Community Facebook Twitter Community Code of Conduct Community Resources More Tutorial Blog Acknowledgements React Native Privacy Terms Copyright © 2025 Meta Platforms, Inc. | 2026-01-13T08:48:45 |
https://docs.suprsend.com/docs/node-create-user-profile | Manage Users - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection Developer Resources Overview Updates and Versioning Versioning and Support Policy SDK Changelog Authentication API Keys and Secrets Service Token Best Practices for Key & Token Management MCP Overview BETA Quickstart Tool List Building with LLMs Security Security SDKs and APIs SDKs SDK Overview SuprSend Backend SDK Python SDK Node.js SDK Integrate Node SDK Manage Users Objects Send and Track Events Trigger Workflow from API Tenants Lists Broadcast Java SDK Go SDK SuprSend Client SDK Management API REST API Postman Collection Features Validate Trigger Payload Type Safety Testing Testing the Template Test Mode Monitoring and Logging Logs Data Out Contact Us Get Started SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Ask AI Contact Us Get Started Get Started Search... Navigation Node.js SDK Manage Users Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog Node.js SDK Manage Users OpenAI Open in ChatGPT Create, update, & manage user profiles and communication channels using NodeJS SDK methods. OpenAI Open in ChatGPT How SuprSend identifies a User SuprSend identifies users with immutable distinct_id . It’s best to map the same identifier in your DB with distinct_id in SuprSend. Do not use identifiers that can be changed like email or phone number. You can view synced users by searching distinct_id on Users page . Create User To create a new user or to update an existing user, you’ll have to fetch user instance. Call supr_client.user.get_instance to instantiate user object. Request Response Copy Ask AI const user = supr_client . user . get_instance ( "_distinct_id_" ); // create user instance // user methods mentioned in this docs can be attached to user instance if needed const response = user . save () // IMP: trigger request response . then (( res ) => console . log ( "response" , res )); Edit User To Edit user, you need to first fetch user instance, call all the update methods and save changes using user.save() method. Request Response Copy Ask AI // Fetch user instance const user = supr_client . users . get_edit_instance ( "_distinct_id_" ); // Call user update methods user . set_timezone ( "America/Los_Angeles" ); user . set ( "name" , "John Doe" ); // Save Changes const response = user . save (); // IMP: trigger request response . then (( res ) => console . log ( "response" , res )); Here’s a list of all edit methods: Add User Channels Use user.add_* method to add user channels. Request Copy Ask AI // add Email user . add_email ( " [email protected] " ) // add SMS user . add_sms ( "+15555555555" ) // add Whatsapp user . add_whatsapp ( "+15555555555" ) // add fcm push token user . add_androidpush ( "__android_push_fcm_token__" ) // add apns push token user . add_iospush ( "__iospush_token__" ) // add Slack using email user . add_slack ({ email: " [email protected] " , access_token: "xoxb-XXXXXXXX" }); // add Slack if slack member_id is known user . add_slack ({ user_id: "U03XXXXXXXX" , access_token: "xoxb-XXXXXXXX" }); // add Slack channel user . add_slack ({ channel_id: "CXXXXXXXX" , access_token: "xoxb-XXXXXXXX" }); // add Slack incoming webhook user . add_slack ({ incoming_webhook: { url: "https://hooks.slack.com/services/TXXXX/BXXXX/XXXXXXX" } }); // add MS teams user or channel using conversation_id user . add_ms_teams ({ tenant_id: "c19xxxx2-9aaf-xxxx-xxxx" , service_url: "https://smba.trafficmanager.net/amer" , conversation_id: "19:c1524d7c-a06f-456f-8abe-xxxx" }); // add MS teams user using user_id user . add_ms_teams ({ tenant_id: "c19xxxx2-9aaf-xxxx-xxxx" , service_url: "https://smba.trafficmanager.net/amer" , user_id: "29:1nsLcmJ2RKtYH6Cxxxx-xxxx" }); // add MS teams using incoming webhook user . add_ms_teams ({ incoming_webhook: { url: "https://wnk1z.webhook.office.com/webhookb2/XXXXXXXXX" } }); Remove User Channels Use user.remove_* method(s) to remove user channels. These methods will detach provided value from the user profile in specified channel. Request Copy Ask AI // remove Email user . remove_email ( " [email protected] " ) // remove SMS user . remove_sms ( "+15555555555" ) // remove Whatsapp user . remove_whatsapp ( "+15555555555" ) // remove fcm push token user . remove_androidpush ( "__android_push_fcm_token__" ) // remove apns push token user . remove_iospush ( "__iospush_token__" ) // remove Slack email user . remove_slack ({ email: " [email protected] " , access_token: "xoxb-XXXXXXXX" }); // remove Slack if slack member_id is known user . remove_slack ({ user_id: "U03XXXXXXXX" , access_token: "xoxb-XXXXXXXX" }); // remove Slack channel user . remove_slack ({ channel_id: "CXXXXXXXX" , access_token: "xoxb-XXXXXXXX" }); // remove Slack incoming webhook user . remove_slack ({ incoming_webhook: { url: "https://hooks.slack.com/services/TXXXX/BXXXX/XXXXXXX" } }); // remove MS teams user or channel using conversation_id user . remove_ms_teams ({ tenant_id: "c19xxxx2-9aaf-xxxx-xxxx" , service_url: "https://smba.trafficmanager.net/amer" , conversation_id: "19:c1524d7c-a06f-456f-8abe-xxxx" }); // remove MS teams user using user_id user . remove_ms_teams ({ tenant_id: "c19xxxx2-9aaf-xxxx-xxxx" , service_url: "https://smba.trafficmanager.net/amer" , user_id: "29:1nsLcmJ2RKtYH6Cxxxx-xxxx" }); // remove MS teams using incoming webhook user . remove_ms_teams ({ incoming_webhook: { url: "https://wnk1z.webhook.office.com/webhookb2/XXXXXXXXX" } }); Remove User Channels in bulk This method will delete/unset all values in specified channel for user (ex: remove all emails attached to user). Request Copy Ask AI user . unset ( "$email" ) user . unset ([ "$email" , "$sms" , "$whatsapp" ]) // what value to pass to unset channels // for email: $email // for whatsapp: $whatsapp // for SMS: $sms // for androidpush tokens: $androidpush // for iospush tokens: $iospush // for webpush tokens: $webpush // for slack: $slack // for ms_teams: $ms_teams Set Preferred Language If you want to send notification in user’s preferred language, you can set it by passing language code in this method. This is useful especially for the applications which offer vernacular or multi-lingual support. Request Copy Ask AI user . set_preferred_language ( "en" ) Set Preferred Timezone You can set timezone of user using this method. Value for timezone must be from amongst the IANA timezones . Request Copy Ask AI user . set_timezone ( "America/Los_Angeles" ) Set Set is used to set the custom user property or properties. The given key and value will be assigned to the user, overwriting an existing property with the same key if present. Request Copy Ask AI user . set ( key , value ) user . set ( "name" , "John Doe" ) user . set ({ key1: value1 , key2: value2 }) user . set ({ "name" : "John Doe" , "city" : "San Francisco" }) Parameters type key string value any Set Once Works just like user.set , except it will not override already existing property values. This is useful for properties like first_login_date. Request Copy Ask AI user . set_once ( key , value ) user . set_once ( "first_login" , "2021-11-02" ) user . set_once ({ key1: value1 , key2: value2 }) user . set_once ({ "first_login" : "2021-11-02" , "signup_date" : "2021-11-02" }) Append This method will append a value to the list for a given property. Request Copy Ask AI user . append ( key , value ) user . append ( "played_games" , "game_1" ) user . append ({ key1: value1 , key2: value2 }) user . append ({ "played_games" : "game_1" , "liked_games" : "game_2" }) Remove This method will remove a value from the list for a given property. Request Copy Ask AI user . remove ( key , value ) user . remove ( "played_games" , "game_1" ) user . remove ({ key1: value1 , key2: value2 }) user . remove ({ "played_games" : "game_1" , "liked_games" : "game_2" }) Increment Add the given number to an existing property on the user. If the user does not already have the associated property, the amount will be added to zero. To reduce a property, provide a negative number for the value. Request Copy Ask AI user . increment ( key , value ) user . increment ( "login_count" , 1 ) user . increment ({ key1: value1 , key2: value2 }) user . increment ({ "login_count" : 1 , "order_count" : 1 }) Parameters type key string value number (+ or -) Unset This will remove a property permanently from user properties. Request Copy Ask AI user . unset ( key ) user . unset ( "wishlist" ) user . unset ([ key1 , key2 ]) user . unset ([ "wishlist" , "cart" ]) Parameters type keys string After calling add*/remove*/unset methods, don’t forget to call the user.save() request. the changes will be sent to SuprSend only after calling this method. Bulk Update Users Bulk operations use UPSERT to create or update users. There isn’t any limit on number-of-records that can be added to bulk_users instance. Use .append() on bulk_users instance to add however-many-records to call in bulk. Rate limit: 1000 requests per second. The SDK automatically chunks requests based on the size of the payload. So, you don’t need to worry about these rate limits while using bulk operations. Request Bulk Response Copy Ask AI const { Suprsend } = require ( "@suprsend/node-sdk" ); const supr_client = new Suprsend ( "workspace_key" , "workspace_secret" ); const bulk_ins = supr_client . bulk_users . new_instance () // user1 instance const user1 = supr_client . user . get_instance ( "_distinct_id_1" ) user1 . add_email ( " [email protected] " ) user1 . set_preferred_language ( "en" ) // user2 instance const user2 = supr_client . user . get_instance ( "_distinct_id_2" ) user2 . remove_email ( " [email protected] " ) //append users instance to bulk instance bulk_ins . append ( user1 ) bulk_ins . append ( user2 ) // OR bulk_ins . append ( user1 , user2 ) // trigger request const response = bulk_ins . save () response . then (( res ) => console . log ( "response" , res )); Get user details Request Copy Ask AI const response = await supr_client . users . get ( _distinct_id_ ); Delete user Request Copy Ask AI const response = await supr_client . users . delete ( _distinct_id_ ); Get list of objects subscribed by user Request Copy Ask AI const response = await supr_client . users . get_objects_subscribed_to ( _distinct_id_ , { limit: 20 }); You can pass optional query parameters - limit , before , after . Get lists subscribed by user Request Copy Ask AI const response = await supr_client . users . get_lists_subscribed_to ( _distinct_id_ , { limit: 20 }); You can pass optional query parameters - limit , before , after . Was this page helpful? Yes No Suggest edits Raise issue Previous Objects Create, update, & manage objects and their subscriptions using NodeJS SDK. 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https://docs.python.org/3/library/socket.html#module-socket | socket — Low-level networking interface — Python 3.14.2 documentation Theme Auto Light Dark Table of Contents socket — Low-level networking interface Socket families Module contents Exceptions Constants Functions Creating sockets Other functions Socket Objects Notes on socket timeouts Timeouts and the connect method Timeouts and the accept method Example Previous topic Developing with asyncio Next topic ssl — TLS/SSL wrapper for socket objects This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Standard Library » Networking and Interprocess Communication » socket — Low-level networking interface | Theme Auto Light Dark | socket — Low-level networking interface ¶ Source code: Lib/socket.py This module provides access to the BSD socket interface. It is available on all modern Unix systems, Windows, MacOS, and probably additional platforms. Note Some behavior may be platform dependent, since calls are made to the operating system socket APIs. Availability : not WASI. This module does not work or is not available on WebAssembly. See WebAssembly platforms for more information. The Python interface is a straightforward transliteration of the Unix system call and library interface for sockets to Python’s object-oriented style: the socket() function returns a socket object whose methods implement the various socket system calls. Parameter types are somewhat higher-level than in the C interface: as with read() and write() operations on Python files, buffer allocation on receive operations is automatic, and buffer length is implicit on send operations. See also Module socketserver Classes that simplify writing network servers. Module ssl A TLS/SSL wrapper for socket objects. Socket families ¶ Depending on the system and the build options, various socket families are supported by this module. The address format required by a particular socket object is automatically selected based on the address family specified when the socket object was created. Socket addresses are represented as follows: The address of an AF_UNIX socket bound to a file system node is represented as a string, using the file system encoding and the 'surrogateescape' error handler (see PEP 383 ). An address in Linux’s abstract namespace is returned as a bytes-like object with an initial null byte; note that sockets in this namespace can communicate with normal file system sockets, so programs intended to run on Linux may need to deal with both types of address. A string or bytes-like object can be used for either type of address when passing it as an argument. Changed in version 3.3: Previously, AF_UNIX socket paths were assumed to use UTF-8 encoding. Changed in version 3.5: Writable bytes-like object is now accepted. A pair (host, port) is used for the AF_INET address family, where host is a string representing either a hostname in internet domain notation like 'daring.cwi.nl' or an IPv4 address like '100.50.200.5' , and port is an integer. For IPv4 addresses, two special forms are accepted instead of a host address: '' represents INADDR_ANY , which is used to bind to all interfaces, and the string '<broadcast>' represents INADDR_BROADCAST . This behavior is not compatible with IPv6, therefore, you may want to avoid these if you intend to support IPv6 with your Python programs. For AF_INET6 address family, a four-tuple (host, port, flowinfo, scope_id) is used, where flowinfo and scope_id represent the sin6_flowinfo and sin6_scope_id members in struct sockaddr_in6 in C. For socket module methods, flowinfo and scope_id can be omitted just for backward compatibility. Note, however, omission of scope_id can cause problems in manipulating scoped IPv6 addresses. Changed in version 3.7: For multicast addresses (with scope_id meaningful) address may not contain %scope_id (or zone id ) part. This information is superfluous and may be safely omitted (recommended). AF_NETLINK sockets are represented as pairs (pid, groups) . Linux-only support for TIPC is available using the AF_TIPC address family. TIPC is an open, non-IP based networked protocol designed for use in clustered computer environments. Addresses are represented by a tuple, and the fields depend on the address type. The general tuple form is (addr_type, v1, v2, v3 [, scope]) , where: addr_type is one of TIPC_ADDR_NAMESEQ , TIPC_ADDR_NAME , or TIPC_ADDR_ID . scope is one of TIPC_ZONE_SCOPE , TIPC_CLUSTER_SCOPE , and TIPC_NODE_SCOPE . If addr_type is TIPC_ADDR_NAME , then v1 is the server type, v2 is the port identifier, and v3 should be 0. If addr_type is TIPC_ADDR_NAMESEQ , then v1 is the server type, v2 is the lower port number, and v3 is the upper port number. If addr_type is TIPC_ADDR_ID , then v1 is the node, v2 is the reference, and v3 should be set to 0. A tuple (interface, ) is used for the AF_CAN address family, where interface is a string representing a network interface name like 'can0' . The network interface name '' can be used to receive packets from all network interfaces of this family. CAN_ISOTP protocol require a tuple (interface, rx_addr, tx_addr) where both additional parameters are unsigned long integer that represent a CAN identifier (standard or extended). CAN_J1939 protocol require a tuple (interface, name, pgn, addr) where additional parameters are 64-bit unsigned integer representing the ECU name, a 32-bit unsigned integer representing the Parameter Group Number (PGN), and an 8-bit integer representing the address. A string or a tuple (id, unit) is used for the SYSPROTO_CONTROL protocol of the PF_SYSTEM family. The string is the name of a kernel control using a dynamically assigned ID. The tuple can be used if ID and unit number of the kernel control are known or if a registered ID is used. Added in version 3.3. AF_BLUETOOTH supports the following protocols and address formats: BTPROTO_L2CAP accepts a tuple (bdaddr, psm[, cid[, bdaddr_type]]) where: bdaddr is a string specifying the Bluetooth address. psm is an integer specifying the Protocol/Service Multiplexer. cid is an optional integer specifying the Channel Identifier. If not given, defaults to zero. bdaddr_type is an optional integer specifying the address type; one of BDADDR_BREDR (default), BDADDR_LE_PUBLIC , BDADDR_LE_RANDOM . Changed in version 3.14: Added cid and bdaddr_type fields. BTPROTO_RFCOMM accepts (bdaddr, channel) where bdaddr is the Bluetooth address as a string and channel is an integer. BTPROTO_HCI accepts a format that depends on your OS. On Linux it accepts an integer device_id or a tuple (device_id, [channel]) where device_id specifies the number of the Bluetooth device, and channel is an optional integer specifying the HCI channel ( HCI_CHANNEL_RAW by default). On FreeBSD, NetBSD and DragonFly BSD it accepts bdaddr where bdaddr is the Bluetooth address as a string. Changed in version 3.2: NetBSD and DragonFlyBSD support added. Changed in version 3.13.3: FreeBSD support added. Changed in version 3.14: Added channel field. device_id not packed in a tuple is now accepted. BTPROTO_SCO accepts bdaddr where bdaddr is the Bluetooth address as a string or a bytes object. (ex. '12:23:34:45:56:67' or b'12:23:34:45:56:67' ) Changed in version 3.14: FreeBSD support added. AF_ALG is a Linux-only socket based interface to Kernel cryptography. An algorithm socket is configured with a tuple of two to four elements (type, name [, feat [, mask]]) , where: type is the algorithm type as string, e.g. aead , hash , skcipher or rng . name is the algorithm name and operation mode as string, e.g. sha256 , hmac(sha256) , cbc(aes) or drbg_nopr_ctr_aes256 . feat and mask are unsigned 32bit integers. Availability : Linux >= 2.6.38. Some algorithm types require more recent Kernels. Added in version 3.6. AF_VSOCK allows communication between virtual machines and their hosts. The sockets are represented as a (CID, port) tuple where the context ID or CID and port are integers. Availability : Linux >= 3.9 See vsock(7) Added in version 3.7. AF_PACKET is a low-level interface directly to network devices. The addresses are represented by the tuple (ifname, proto[, pkttype[, hatype[, addr]]]) where: ifname - String specifying the device name. proto - The Ethernet protocol number. May be ETH_P_ALL to capture all protocols, one of the ETHERTYPE_* constants or any other Ethernet protocol number. pkttype - Optional integer specifying the packet type: PACKET_HOST (the default) - Packet addressed to the local host. PACKET_BROADCAST - Physical-layer broadcast packet. PACKET_MULTICAST - Packet sent to a physical-layer multicast address. PACKET_OTHERHOST - Packet to some other host that has been caught by a device driver in promiscuous mode. PACKET_OUTGOING - Packet originating from the local host that is looped back to a packet socket. hatype - Optional integer specifying the ARP hardware address type. addr - Optional bytes-like object specifying the hardware physical address, whose interpretation depends on the device. Availability : Linux >= 2.2. AF_QIPCRTR is a Linux-only socket based interface for communicating with services running on co-processors in Qualcomm platforms. The address family is represented as a (node, port) tuple where the node and port are non-negative integers. Availability : Linux >= 4.7. Added in version 3.8. IPPROTO_UDPLITE is a variant of UDP which allows you to specify what portion of a packet is covered with the checksum. It adds two socket options that you can change. self.setsockopt(IPPROTO_UDPLITE, UDPLITE_SEND_CSCOV, length) will change what portion of outgoing packets are covered by the checksum and self.setsockopt(IPPROTO_UDPLITE, UDPLITE_RECV_CSCOV, length) will filter out packets which cover too little of their data. In both cases length should be in range(8, 2**16, 8) . Such a socket should be constructed with socket(AF_INET, SOCK_DGRAM, IPPROTO_UDPLITE) for IPv4 or socket(AF_INET6, SOCK_DGRAM, IPPROTO_UDPLITE) for IPv6. Availability : Linux >= 2.6.20, FreeBSD >= 10.1 Added in version 3.9. AF_HYPERV is a Windows-only socket based interface for communicating with Hyper-V hosts and guests. The address family is represented as a (vm_id, service_id) tuple where the vm_id and service_id are UUID strings. The vm_id is the virtual machine identifier or a set of known VMID values if the target is not a specific virtual machine. Known VMID constants defined on socket are: HV_GUID_ZERO HV_GUID_BROADCAST HV_GUID_WILDCARD - Used to bind on itself and accept connections from all partitions. HV_GUID_CHILDREN - Used to bind on itself and accept connection from child partitions. HV_GUID_LOOPBACK - Used as a target to itself. HV_GUID_PARENT - When used as a bind accepts connection from the parent partition. When used as an address target it will connect to the parent partition. The service_id is the service identifier of the registered service. Added in version 3.12. If you use a hostname in the host portion of IPv4/v6 socket address, the program may show a nondeterministic behavior, as Python uses the first address returned from the DNS resolution. The socket address will be resolved differently into an actual IPv4/v6 address, depending on the results from DNS resolution and/or the host configuration. For deterministic behavior use a numeric address in host portion. All errors raise exceptions. The normal exceptions for invalid argument types and out-of-memory conditions can be raised. Errors related to socket or address semantics raise OSError or one of its subclasses. Non-blocking mode is supported through setblocking() . A generalization of this based on timeouts is supported through settimeout() . Module contents ¶ The module socket exports the following elements. Exceptions ¶ exception socket. error ¶ A deprecated alias of OSError . Changed in version 3.3: Following PEP 3151 , this class was made an alias of OSError . exception socket. herror ¶ A subclass of OSError , this exception is raised for address-related errors, i.e. for functions that use h_errno in the POSIX C API, including gethostbyname_ex() and gethostbyaddr() . The accompanying value is a pair (h_errno, string) representing an error returned by a library call. h_errno is a numeric value, while string represents the description of h_errno , as returned by the hstrerror() C function. Changed in version 3.3: This class was made a subclass of OSError . exception socket. gaierror ¶ A subclass of OSError , this exception is raised for address-related errors by getaddrinfo() and getnameinfo() . The accompanying value is a pair (error, string) representing an error returned by a library call. string represents the description of error , as returned by the gai_strerror() C function. The numeric error value will match one of the EAI_* constants defined in this module. Changed in version 3.3: This class was made a subclass of OSError . exception socket. timeout ¶ A deprecated alias of TimeoutError . A subclass of OSError , this exception is raised when a timeout occurs on a socket which has had timeouts enabled via a prior call to settimeout() (or implicitly through setdefaulttimeout() ). The accompanying value is a string whose value is currently always “timed out”. Changed in version 3.3: This class was made a subclass of OSError . Changed in version 3.10: This class was made an alias of TimeoutError . Constants ¶ The AF_* and SOCK_* constants are now AddressFamily and SocketKind IntEnum collections. Added in version 3.4. socket. AF_UNIX ¶ socket. AF_INET ¶ socket. AF_INET6 ¶ These constants represent the address (and protocol) families, used for the first argument to socket() . If the AF_UNIX constant is not defined then this protocol is unsupported. More constants may be available depending on the system. socket. AF_UNSPEC ¶ AF_UNSPEC means that getaddrinfo() should return socket addresses for any address family (either IPv4, IPv6, or any other) that can be used. socket. SOCK_STREAM ¶ socket. SOCK_DGRAM ¶ socket. SOCK_RAW ¶ socket. SOCK_RDM ¶ socket. SOCK_SEQPACKET ¶ These constants represent the socket types, used for the second argument to socket() . More constants may be available depending on the system. (Only SOCK_STREAM and SOCK_DGRAM appear to be generally useful.) socket. SOCK_CLOEXEC ¶ socket. SOCK_NONBLOCK ¶ These two constants, if defined, can be combined with the socket types and allow you to set some flags atomically (thus avoiding possible race conditions and the need for separate calls). See also Secure File Descriptor Handling for a more thorough explanation. Availability : Linux >= 2.6.27. Added in version 3.2. SO_* socket. SOMAXCONN ¶ MSG_* SOL_* SCM_* IPPROTO_* IPPORT_* INADDR_* IP_* IPV6_* EAI_* AI_* NI_* TCP_* Many constants of these forms, documented in the Unix documentation on sockets and/or the IP protocol, are also defined in the socket module. They are generally used in arguments to the setsockopt() and getsockopt() methods of socket objects. In most cases, only those symbols that are defined in the Unix header files are defined; for a few symbols, default values are provided. Changed in version 3.6: SO_DOMAIN , SO_PROTOCOL , SO_PEERSEC , SO_PASSSEC , TCP_USER_TIMEOUT , TCP_CONGESTION were added. Changed in version 3.6.5: Added support for TCP_FASTOPEN , TCP_KEEPCNT on Windows platforms when available. Changed in version 3.7: TCP_NOTSENT_LOWAT was added. Added support for TCP_KEEPIDLE , TCP_KEEPINTVL on Windows platforms when available. Changed in version 3.10: IP_RECVTOS was added. Added TCP_KEEPALIVE . On MacOS this constant can be used in the same way that TCP_KEEPIDLE is used on Linux. Changed in version 3.11: Added TCP_CONNECTION_INFO . On MacOS this constant can be used in the same way that TCP_INFO is used on Linux and BSD. Changed in version 3.12: Added SO_RTABLE and SO_USER_COOKIE . On OpenBSD and FreeBSD respectively those constants can be used in the same way that SO_MARK is used on Linux. Also added missing TCP socket options from Linux: TCP_MD5SIG , TCP_THIN_LINEAR_TIMEOUTS , TCP_THIN_DUPACK , TCP_REPAIR , TCP_REPAIR_QUEUE , TCP_QUEUE_SEQ , TCP_REPAIR_OPTIONS , TCP_TIMESTAMP , TCP_CC_INFO , TCP_SAVE_SYN , TCP_SAVED_SYN , TCP_REPAIR_WINDOW , TCP_FASTOPEN_CONNECT , TCP_ULP , TCP_MD5SIG_EXT , TCP_FASTOPEN_KEY , TCP_FASTOPEN_NO_COOKIE , TCP_ZEROCOPY_RECEIVE , TCP_INQ , TCP_TX_DELAY . Added IP_PKTINFO , IP_UNBLOCK_SOURCE , IP_BLOCK_SOURCE , IP_ADD_SOURCE_MEMBERSHIP , IP_DROP_SOURCE_MEMBERSHIP . Changed in version 3.13: Added SO_BINDTOIFINDEX . On Linux this constant can be used in the same way that SO_BINDTODEVICE is used, but with the index of a network interface instead of its name. Changed in version 3.14: Added missing IP_FREEBIND , IP_RECVERR , IPV6_RECVERR , IP_RECVTTL , and IP_RECVORIGDSTADDR on Linux. Changed in version 3.14: Added support for TCP_QUICKACK on Windows platforms when available. socket. AF_CAN ¶ socket. PF_CAN ¶ SOL_CAN_* CAN_* Many constants of these forms, documented in the Linux documentation, are also defined in the socket module. Availability : Linux >= 2.6.25, NetBSD >= 8. Added in version 3.3. Changed in version 3.11: NetBSD support was added. Changed in version 3.14: Restored missing CAN_RAW_ERR_FILTER on Linux. socket. CAN_BCM ¶ CAN_BCM_* CAN_BCM, in the CAN protocol family, is the broadcast manager (BCM) protocol. Broadcast manager constants, documented in the Linux documentation, are also defined in the socket module. Availability : Linux >= 2.6.25. Note The CAN_BCM_CAN_FD_FRAME flag is only available on Linux >= 4.8. Added in version 3.4. socket. CAN_RAW_FD_FRAMES ¶ Enables CAN FD support in a CAN_RAW socket. This is disabled by default. This allows your application to send both CAN and CAN FD frames; however, you must accept both CAN and CAN FD frames when reading from the socket. This constant is documented in the Linux documentation. Availability : Linux >= 3.6. Added in version 3.5. socket. CAN_RAW_JOIN_FILTERS ¶ Joins the applied CAN filters such that only CAN frames that match all given CAN filters are passed to user space. This constant is documented in the Linux documentation. Availability : Linux >= 4.1. Added in version 3.9. socket. CAN_ISOTP ¶ CAN_ISOTP, in the CAN protocol family, is the ISO-TP (ISO 15765-2) protocol. ISO-TP constants, documented in the Linux documentation. Availability : Linux >= 2.6.25. Added in version 3.7. socket. CAN_J1939 ¶ CAN_J1939, in the CAN protocol family, is the SAE J1939 protocol. J1939 constants, documented in the Linux documentation. Availability : Linux >= 5.4. Added in version 3.9. socket. AF_DIVERT ¶ socket. PF_DIVERT ¶ These two constants, documented in the FreeBSD divert(4) manual page, are also defined in the socket module. Availability : FreeBSD >= 14.0. Added in version 3.12. socket. AF_PACKET ¶ socket. PF_PACKET ¶ PACKET_* Many constants of these forms, documented in the Linux documentation, are also defined in the socket module. Availability : Linux >= 2.2. socket. ETH_P_ALL ¶ ETH_P_ALL can be used in the socket constructor as proto for the AF_PACKET family in order to capture every packet, regardless of protocol. For more information, see the packet(7) manpage. Availability : Linux. Added in version 3.12. socket. AF_RDS ¶ socket. PF_RDS ¶ socket. SOL_RDS ¶ RDS_* Many constants of these forms, documented in the Linux documentation, are also defined in the socket module. Availability : Linux >= 2.6.30. Added in version 3.3. socket. SIO_RCVALL ¶ socket. SIO_KEEPALIVE_VALS ¶ socket. SIO_LOOPBACK_FAST_PATH ¶ RCVALL_* Constants for Windows’ WSAIoctl(). The constants are used as arguments to the ioctl() method of socket objects. Changed in version 3.6: SIO_LOOPBACK_FAST_PATH was added. TIPC_* TIPC related constants, matching the ones exported by the C socket API. See the TIPC documentation for more information. socket. AF_ALG ¶ socket. SOL_ALG ¶ ALG_* Constants for Linux Kernel cryptography. Availability : Linux >= 2.6.38. Added in version 3.6. socket. AF_VSOCK ¶ socket. IOCTL_VM_SOCKETS_GET_LOCAL_CID ¶ VMADDR* SO_VM* Constants for Linux host/guest communication. Availability : Linux >= 4.8. Added in version 3.7. socket. AF_LINK ¶ Availability : BSD, macOS. Added in version 3.4. socket. has_ipv6 ¶ This constant contains a boolean value which indicates if IPv6 is supported on this platform. socket. AF_BLUETOOTH ¶ socket. BTPROTO_L2CAP ¶ socket. BTPROTO_RFCOMM ¶ socket. BTPROTO_HCI ¶ socket. BTPROTO_SCO ¶ Integer constants for use with Bluetooth addresses. socket. BDADDR_ANY ¶ socket. BDADDR_LOCAL ¶ These are string constants containing Bluetooth addresses with special meanings. For example, BDADDR_ANY can be used to indicate any address when specifying the binding socket with BTPROTO_RFCOMM . socket. BDADDR_BREDR ¶ socket. BDADDR_LE_PUBLIC ¶ socket. BDADDR_LE_RANDOM ¶ These constants describe the Bluetooth address type when binding or connecting a BTPROTO_L2CAP socket. Availability : Linux, FreeBSD Added in version 3.14. socket. SOL_RFCOMM ¶ socket. SOL_L2CAP ¶ socket. SOL_HCI ¶ socket. SOL_SCO ¶ socket. SOL_BLUETOOTH ¶ Used in the level argument to the setsockopt() and getsockopt() methods of Bluetooth socket objects. SOL_BLUETOOTH is only available on Linux. Other constants are available if the corresponding protocol is supported. SO_L2CAP_* socket. L2CAP_LM ¶ L2CAP_LM_* SO_RFCOMM_* RFCOMM_LM_* SO_SCO_* SO_BTH_* BT_* Used in the option name and value argument to the setsockopt() and getsockopt() methods of Bluetooth socket objects. BT_* and L2CAP_LM are only available on Linux. SO_BTH_* are only available on Windows. Other constants may be available on Linux and various BSD platforms. Added in version 3.14. socket. HCI_FILTER ¶ socket. HCI_TIME_STAMP ¶ socket. HCI_DATA_DIR ¶ socket. SO_HCI_EVT_FILTER ¶ socket. SO_HCI_PKT_FILTER ¶ Option names for use with BTPROTO_HCI . Availability and format of the option values depend on platform. Changed in version 3.14: Added SO_HCI_EVT_FILTER and SO_HCI_PKT_FILTER on NetBSD and DragonFly BSD. Added HCI_DATA_DIR on FreeBSD, NetBSD and DragonFly BSD. socket. HCI_DEV_NONE ¶ The device_id value used to create an HCI socket that isn’t specific to a single Bluetooth adapter. Availability : Linux Added in version 3.14. socket. HCI_CHANNEL_RAW ¶ socket. HCI_CHANNEL_USER ¶ socket. HCI_CHANNEL_MONITOR ¶ socket. HCI_CHANNEL_CONTROL ¶ socket. HCI_CHANNEL_LOGGING ¶ Possible values for channel field in the BTPROTO_HCI address. Availability : Linux Added in version 3.14. socket. AF_QIPCRTR ¶ Constant for Qualcomm’s IPC router protocol, used to communicate with service providing remote processors. Availability : Linux >= 4.7. socket. SCM_CREDS2 ¶ socket. LOCAL_CREDS ¶ socket. LOCAL_CREDS_PERSISTENT ¶ LOCAL_CREDS and LOCAL_CREDS_PERSISTENT can be used with SOCK_DGRAM, SOCK_STREAM sockets, equivalent to Linux/DragonFlyBSD SO_PASSCRED, while LOCAL_CREDS sends the credentials at first read, LOCAL_CREDS_PERSISTENT sends for each read, SCM_CREDS2 must be then used for the latter for the message type. Added in version 3.11. Availability : FreeBSD. socket. SO_INCOMING_CPU ¶ Constant to optimize CPU locality, to be used in conjunction with SO_REUSEPORT . Added in version 3.11. Availability : Linux >= 3.9 socket. SO_REUSEPORT_LB ¶ Constant to enable duplicate address and port bindings with load balancing. Added in version 3.14. Availability : FreeBSD >= 12.0 socket. AF_HYPERV ¶ socket. HV_PROTOCOL_RAW ¶ socket. HVSOCKET_CONNECT_TIMEOUT ¶ socket. HVSOCKET_CONNECT_TIMEOUT_MAX ¶ socket. HVSOCKET_CONNECTED_SUSPEND ¶ socket. HVSOCKET_ADDRESS_FLAG_PASSTHRU ¶ socket. HV_GUID_ZERO ¶ socket. HV_GUID_WILDCARD ¶ socket. HV_GUID_BROADCAST ¶ socket. HV_GUID_CHILDREN ¶ socket. HV_GUID_LOOPBACK ¶ socket. HV_GUID_PARENT ¶ Constants for Windows Hyper-V sockets for host/guest communications. Availability : Windows. Added in version 3.12. socket. ETHERTYPE_ARP ¶ socket. ETHERTYPE_IP ¶ socket. ETHERTYPE_IPV6 ¶ socket. ETHERTYPE_VLAN ¶ IEEE 802.3 protocol number . constants. Availability : Linux, FreeBSD, macOS. Added in version 3.12. socket. SHUT_RD ¶ socket. SHUT_WR ¶ socket. SHUT_RDWR ¶ These constants are used by the shutdown() method of socket objects. Availability : not WASI. Functions ¶ Creating sockets ¶ The following functions all create socket objects . class socket. socket ( family = AF_INET , type = SOCK_STREAM , proto = 0 , fileno = None ) ¶ Create a new socket using the given address family, socket type and protocol number. The address family should be AF_INET (the default), AF_INET6 , AF_UNIX , AF_CAN , AF_PACKET , or AF_RDS . The socket type should be SOCK_STREAM (the default), SOCK_DGRAM , SOCK_RAW or perhaps one of the other SOCK_ constants. The protocol number is usually zero and may be omitted or in the case where the address family is AF_CAN the protocol should be one of CAN_RAW , CAN_BCM , CAN_ISOTP or CAN_J1939 . If fileno is specified, the values for family , type , and proto are auto-detected from the specified file descriptor. Auto-detection can be overruled by calling the function with explicit family , type , or proto arguments. This only affects how Python represents e.g. the return value of socket.getpeername() but not the actual OS resource. Unlike socket.fromfd() , fileno will return the same socket and not a duplicate. This may help close a detached socket using socket.close() . The newly created socket is non-inheritable . Raises an auditing event socket.__new__ with arguments self , family , type , protocol . Changed in version 3.3: The AF_CAN family was added. The AF_RDS family was added. Changed in version 3.4: The CAN_BCM protocol was added. Changed in version 3.4: The returned socket is now non-inheritable. Changed in version 3.7: The CAN_ISOTP protocol was added. Changed in version 3.7: When SOCK_NONBLOCK or SOCK_CLOEXEC bit flags are applied to type they are cleared, and socket.type will not reflect them. They are still passed to the underlying system socket() call. Therefore, sock = socket . socket ( socket . AF_INET , socket . SOCK_STREAM | socket . SOCK_NONBLOCK ) will still create a non-blocking socket on OSes that support SOCK_NONBLOCK , but sock.type will be set to socket.SOCK_STREAM . Changed in version 3.9: The CAN_J1939 protocol was added. Changed in version 3.10: The IPPROTO_MPTCP protocol was added. socket. socketpair ( [ family [ , type [ , proto ] ] ] ) ¶ Build a pair of connected socket objects using the given address family, socket type, and protocol number. Address family, socket type, and protocol number are as for the socket() function above. The default family is AF_UNIX if defined on the platform; otherwise, the default is AF_INET . The newly created sockets are non-inheritable . Changed in version 3.2: The returned socket objects now support the whole socket API, rather than a subset. Changed in version 3.4: The returned sockets are now non-inheritable. Changed in version 3.5: Windows support added. socket. create_connection ( address , timeout = GLOBAL_DEFAULT , source_address = None , * , all_errors = False ) ¶ Connect to a TCP service listening on the internet address (a 2-tuple (host, port) ), and return the socket object. This is a higher-level function than socket.connect() : if host is a non-numeric hostname, it will try to resolve it for both AF_INET and AF_INET6 , and then try to connect to all possible addresses in turn until a connection succeeds. This makes it easy to write clients that are compatible to both IPv4 and IPv6. Passing the optional timeout parameter will set the timeout on the socket instance before attempting to connect. If no timeout is supplied, the global default timeout setting returned by getdefaulttimeout() is used. If supplied, source_address must be a 2-tuple (host, port) for the socket to bind to as its source address before connecting. If host or port are ‘’ or 0 respectively the OS default behavior will be used. When a connection cannot be created, an exception is raised. By default, it is the exception from the last address in the list. If all_errors is True , it is an ExceptionGroup containing the errors of all attempts. Changed in version 3.2: source_address was added. Changed in version 3.11: all_errors was added. socket. create_server ( address , * , family = AF_INET , backlog = None , reuse_port = False , dualstack_ipv6 = False ) ¶ Convenience function which creates a TCP socket bound to address (a 2-tuple (host, port) ) and returns the socket object. family should be either AF_INET or AF_INET6 . backlog is the queue size passed to socket.listen() ; if not specified , a default reasonable value is chosen. reuse_port dictates whether to set the SO_REUSEPORT socket option. If dualstack_ipv6 is true, family is AF_INET6 and the platform supports it the socket will be able to accept both IPv4 and IPv6 connections, else it will raise ValueError . Most POSIX platforms and Windows are supposed to support this functionality. When this functionality is enabled the address returned by socket.getpeername() when an IPv4 connection occurs will be an IPv6 address represented as an IPv4-mapped IPv6 address. If dualstack_ipv6 is false it will explicitly disable this functionality on platforms that enable it by default (e.g. Linux). This parameter can be used in conjunction with has_dualstack_ipv6() : import socket addr = ( "" , 8080 ) # all interfaces, port 8080 if socket . has_dualstack_ipv6 (): s = socket . create_server ( addr , family = socket . AF_INET6 , dualstack_ipv6 = True ) else : s = socket . create_server ( addr ) Note On POSIX platforms the SO_REUSEADDR socket option is set in order to immediately reuse previous sockets which were bound on the same address and remained in TIME_WAIT state. Added in version 3.8. socket. has_dualstack_ipv6 ( ) ¶ Return True if the platform supports creating a TCP socket which can handle both IPv4 and IPv6 connections. Added in version 3.8. socket. fromfd ( fd , family , type , proto = 0 ) ¶ Duplicate the file descriptor fd (an integer as returned by a file object’s fileno() method) and build a socket object from the result. Address family, socket type and protocol number are as for the socket() function above. The file descriptor should refer to a socket, but this is not checked — subsequent operations on the object may fail if the file descriptor is invalid. This function is rarely needed, but can be used to get or set socket options on a socket passed to a program as standard input or output (such as a server started by the Unix inet daemon). The socket is assumed to be in blocking mode. The newly created socket is non-inheritable . Changed in version 3.4: The returned socket is now non-inheritable. socket. fromshare ( data ) ¶ Instantiate a socket from data obtained from the socket.share() method. The socket is assumed to be in blocking mode. Availability : Windows. Added in version 3.3. socket. SocketType ¶ This is a Python type object that represents the socket object type. It is the same as type(socket(...)) . Other functions ¶ The socket module also offers various network-related services: socket. close ( fd ) ¶ Close a socket file descriptor. This is like os.close() , but for sockets. On some platforms (most noticeable Windows) os.close() does not work for socket file descriptors. Added in version 3.7. socket. getaddrinfo ( host , port , family = AF_UNSPEC , type = 0 , proto = 0 , flags = 0 ) ¶ This function wraps the C function getaddrinfo of the underlying system. Translate the host / port argument into a sequence of 5-tuples that contain all the necessary arguments for creating a socket connected to that service. host is a domain name, a string representation of an IPv4/v6 address or None . port is a string service name such as 'http' , a numeric port number or None . By passing None as the value of host and port , you can pass NULL to the underlying C API. The family , type and proto arguments can be optionally specified in order to provide options and limit the list of addresses returned. Pass their default values ( AF_UNSPEC , 0, and 0, respectively) to not limit the results. See the note below for details. The flags argument can be one or several of the AI_* constants, and will influence how results are computed and returned. For example, AI_NUMERICHOST will disable domain name resolution and will raise an error if host is a domain name. The function returns a list of 5-tuples with the following structure: (family, type, proto, canonname, sockaddr) In these tuples, family , type , proto are all integers and are meant to be passed to the socket() function. canonname will be a string representing the canonical name of the host if AI_CANONNAME is part of the flags argument; else canonname will be empty. sockaddr is a tuple describing a socket address, whose format depends on the returned family (a (address, port) 2-tuple for AF_INET , a (address, port, flowinfo, scope_id) 4-tuple for AF_INET6 ), and is meant to be passed to the socket.connect() method. Note If you intend to use results from getaddrinfo() to create a socket (rather than, for example, retrieve canonname ), consider limiting the results by type (e.g. SOCK_STREAM or SOCK_DGRAM ) and/or proto (e.g. IPPROTO_TCP or IPPROTO_UDP ) that your application can handle. The behavior with default values of family , type , proto and flags is system-specific. Many systems (for example, most Linux configurations) will return a sorted list of all matching addresses. These addresses should generally be tried in order until a connection succeeds (possibly tried in parallel, for example, using a Happy Eyeballs algorithm). In these cases, limiting the type and/or proto can help eliminate unsuccessful or unusable connection attempts. Some systems will, however, only return a single address. (For example, this was reported on Solaris and AIX configurations.) On these systems, limiting the type and/or proto helps ensure that this address is usable. Raises an auditing event socket.getaddrinfo with arguments host , port , family , type , protocol . The following example fetches address information for a hypothetical TCP connection to example.org on port 80 (results may differ on your system if IPv6 isn’t enabled): >>> socket . getaddrinfo ( "example.org" , 80 , proto = socket . IPPROTO_TCP ) [(socket.AF_INET6, socket.SOCK_STREAM, 6, '', ('2606:2800:220:1:248:1893:25c8:1946', 80, 0, 0)), (socket.AF_INET, socket.SOCK_STREAM, 6, '', ('93.184.216.34', 80))] Changed in version 3.2: parameters can now be passed using keyword arguments. Changed in version 3.7: for IPv6 multicast addresses, string representing an address will not contain %scope_id part. socket. getfqdn ( [ name ] ) ¶ Return a fully qualified domain name for name . If name is omitted or empty, it is interpreted as the local host. To find the fully qualified name, the hostname returned by gethostbyaddr() is checked, followed by aliases for the host, if available. The first name which includes a period is selected. In case no fully qualified domain name is available and name was provided, it is returned unchanged. If name was empty or equal to '0.0.0.0' , the hostname from gethostname() is returned. socket. gethostbyname ( hostname ) ¶ Translate a host name to IPv4 address format. The IPv4 address is returned as a string, such as '100.50.200.5' . If the host name is an IPv4 address itself it is returned unchanged. See gethostbyname_ex() for a more complete interface. gethostbyname() does not support IPv6 name resolution, and getaddrinfo() should be used instead for IPv4/v6 dual stack support. Raises an auditing event socket.gethostbyname with argument hostname . Availability : not WASI. socket. gethostbyname_ex ( hostname ) ¶ Translate a host name to IPv4 address format, extended interface. Return a 3-tuple (hostname, aliaslist, ipaddrlist) where hostname is the host’s primary host name, aliaslist is a (possibly empty) list of alternative host names for the same address, and ipaddrlist is a list of IPv4 addresses for the same interface on the same host (often but not always a single address). gethostbyname_ex() does not support IPv6 name resolution, and getaddrinfo() should be used instead for IPv4/v6 dual stack support. Raises an auditing event socket.gethostbyname with argument hostname . Availability : not WASI. socket. gethostname ( ) ¶ Return a string containing the hostname of the machine where the Python interpreter is currently executing. Raises an auditing event socket.gethostname with no arguments. Note: gethostname() doesn’t always return the fully qualified domain name; use getfqdn() for that. Availability : not WASI. socket. gethostbyaddr ( ip_address ) ¶ Return a 3-tuple (hostname, aliaslist, ipaddrlist) where hostname is the primary host name responding to the given ip_address , aliaslist is a (possibly empty) list of alternative host names for the same address, and ipaddrlist is a list of IPv4/v6 addresses for the same interface on the same host (most likely containing only a single address). To find the fully qualified domain name, use the function getfqdn() . gethostbyaddr() supports both IPv4 and IPv6. Raises an auditing event socket.gethostbyaddr with argument ip_address . Availability : not WASI. socket. getnameinfo ( sockaddr , flags ) ¶ Translate a socket address sockaddr into a 2-tuple (host, port) . Depending on the settings of flags , the result can contain a fully qualified domain name or numeric address representation in host . Similarly, port can contain a string port name or a numeric port number. For IPv6 addresses, %scope_id is appended to the host part if sockaddr contains meaningful scope_id . Usually this happens for multicast addresses. For more information about flags you can consult getnameinfo(3) . Raises an auditing event socket.getnameinfo with argument sockaddr . Availability : not WASI. socket. getprotobyname ( protocolname ) ¶ Translate an internet protocol name (for example, 'icmp' ) to a constant suitable for passing as the (optional) third argument to the socket() function. This is usually only needed for sockets opened in “raw” mode ( SOCK_RAW ); for the normal socket modes, the correct protocol is chosen automatically if the protocol is omitted or zero. Availability : not WASI. socket. getservbyname ( servicename [ , protocolname ] ) ¶ Translate an internet service name and protocol name to a port number for that service. The optional protocol name, if given, should be 'tcp' or 'udp' , otherwise any protocol will match. Raises an auditing event socket.getservbyname with arguments servicename , protocolname . Availability : not WASI. socket. getservbyport ( port [ , protocolname ] ) ¶ Translate an internet port number and protocol name to a service name for that service. The optional protocol name, if given, should be 'tcp' or 'udp' , otherwise any protocol will match. Raises an auditing event socket.getservbyport with arguments port , protocolname . Availability : not WASI. socket. ntohl ( x ) ¶ Convert 32-bit positive integers from network to host byte order. On machines where the host byte order is the same as network byte order, this is a no-op; otherwise, it performs a 4-byte swap operation. socket. ntohs ( x ) ¶ Convert 16-bit positive integers from network to host byte order. On machines where the host byte order is the same as network byte order, this is a no-op; otherwise, it performs a 2-byte swap operation. Changed in version 3.10: Raises OverflowError if x does not fit in a 16-bit unsigned integer. socket. htonl ( x ) ¶ Convert 32-bit positive integers from host to network byte order. On machines where the host byte order is the same as network byte order, this is a no-op; otherwise, it performs a 4-byte swap operation. socket. htons ( x ) ¶ Convert 16-bit positive integers from host to network byte order. On machines where the host byte order is the same as network byte order, this is a no-op; otherwise, it performs a 2-byte swap operation. Changed in version 3.10: Raises OverflowError if x does not fit in a 16-bit unsigned integer. socket. inet_aton ( ip_string ) ¶ Convert an IPv4 address from dotted-quad string format (for example, ‘123.45.67.89’) to 32-bit packed binary format, as a bytes object four characters in length. This is useful when conversing with a program that uses the standard C library and needs objects of type in_addr , which is the C type for the 32-bit packed binary this function returns. inet_aton() also accepts strings with less than three dots; see the Unix manual page inet(3) for details. If the IPv4 address string passed to this function is invalid, OSError will be raised. Note that exactly what is valid depends on the underlying C implementation of inet_aton() . inet_aton() does not support IPv6, and inet_pton() should be used instead for IPv4/v6 dual stack support. socket. inet_ntoa ( packed_ip ) ¶ Convert a 32-bit packed IPv4 address (a bytes-like object four bytes in length) to its standard dotted-quad string representation (for example, ‘123.45.67.89’). This is useful when conversing with a program that uses the standard C library and needs objects of type in_addr , which is the C type for the 32-bit packed binary data this function takes as an argument. If the byte sequence passed to this function is not exactly 4 bytes in length, OSError will be raised. inet_ntoa() does not support IPv6, and inet_ntop() should be used instead for IPv4/v6 dual stack support. Changed in version 3.5: Writable bytes-like object is now accepted. socket. inet_pton ( address_family , ip_string ) ¶ Convert an IP address from its family-specific string format to a packed, binary format. inet_pton() is useful when a library or network protocol calls for an object of type in_addr (similar to inet_aton() ) or in6_addr . Supported values for address_family are currently AF_INET and AF_INET6 . If the IP address string ip_string is invalid, OSError will be raised. Note that exactly what is valid depends on both the value of address_family and the underlying implementation of inet_pton() . Availability : Unix, Windows. Changed in version 3.4: Windows support added socket. inet_ntop ( address_family , packed_ip ) ¶ Convert a packed IP address (a bytes-like object of some number of bytes) to its standard, family-specific string representation (for example, '7.10.0.5' or '5aef:2b::8' ). inet_ntop() is useful when a library or network protocol returns an object of type in_addr (similar to inet_ntoa() ) or in6_addr . Supported values for address_family are currently AF_INET and AF_INET6 . If the bytes object packed_ip is not the correct length for the specified address family, ValueError will be raised. OSError is raised for errors from the call to inet_ntop() . Availability : Unix, Windows. Changed in version 3.4: Windows support added Changed in version 3.5: Writable bytes-like object is now accepted. socket. CMSG_LEN ( length ) ¶ Return the total length, without trailing padding, of an ancillary data item with associated data of the given length . This value can often be used as the buffer size for recvmsg() to receive a single item of ancillary data, but RFC 3542 requires portable applications to use CMSG_SPACE() and thus include space for padding, even when the item will be the last in the buffer. Raises OverflowError if length is outside the permissible range of values. Availability : Unix, not WASI. Most Unix platforms. Added in version 3.3. socket. CMSG_SPACE ( length ) ¶ Return the buffer size needed for recvmsg() to receive an ancillary data item with associated data of the given length , along with any trailing padding. The buffer space needed to receive multiple items is the sum of the CMSG_SPACE() values for their associated data lengths. Raises OverflowError if length is outside the permissible range of values. Note that some systems might support ancillary data without providing this function. Also note that setting the buffer size using the results of this function may not precisely limit the amount of ancillary data that can be received, since additional data may be able to fit into the padding area. Availability : Unix, not WASI. most Unix platforms. Added in version 3.3. socket. getdefaulttimeout ( ) ¶ Return the default timeout in seconds (float) for new socket objects. A value of None indicates that new socket objects have no timeout. When the socket module is first imported, the default is None . socket. setdefaulttimeout ( timeout ) ¶ Set the default timeout in seconds (float) for new socket objects. When the socket module is first imported, the default is None . See settimeout() for possible values and their respective meanings. socket. sethostname ( name ) ¶ Set the machine’s hostname to name . This will raise an OSError if you don’t have enough rights. Raises an auditing event socket.sethostname with argument name . Availability : Unix, not Android. Added in version 3.3. socket. if_nameindex ( ) ¶ Return a list of network interface information (index int, name string) tuples. OSError if the system call fails. Availability : Unix, Windows, not WASI. Added in version 3.3. Changed in version 3.8: Windows support was added. Note On Windows network interfaces have different names in different contexts (all names are examples): UUID: {FB605B73-AAC2-49A6-9A2F-25416AEA0573} name: ethernet_32770 friendly name: vEthernet (nat) description: Hyper-V Virtual Ethernet Adapter This function returns names of the second form from the list, ethernet_32770 in this example case. socket. if_nametoindex ( if_name ) ¶ Return a network interface index number corresponding to an interface name. OSError if no interface with the given name exists. Availability : Unix, Windows, not WASI. Added in version 3.3. Changed in version 3.8: Windows support was added. See also “Interface name” is a name as documented in if_nameindex() . socket. if_indextoname ( if_index ) ¶ Return a network interface name corresponding to an interface index number. OSError if no interface with the given index exists. Availability : Unix, Windows, not WASI. Added in version 3.3. Changed in version 3.8: Windows support was added. See also “Interface name” is a name as documented in if_nameindex() . socket. send_fds ( sock , buffers , fds [ , flags [ , address ] ] ) ¶ Send the list of file descriptors fds over an AF_UNIX socket sock . The fds parameter is a sequence of file descriptors. Consult sendmsg() for the documentation of these parameters. Availability : Unix, not WASI. Unix platforms supporting sendmsg() and SCM_RIGHTS mechanism. Added in version 3.9. socket. recv_fds ( sock , bufsize , maxfds [ , flags ] ) ¶ Receive up to maxfds file descriptors from an AF_UNIX socket sock . Return (msg, list(fds), flags, addr) . Consult recvmsg() for the documentation of these parameters. Availability : Unix, not WASI. Unix platforms supporting recvmsg() and SCM_RIGHTS mechanism. Added in version 3.9. Note Any truncated integers at the end of the list of file descriptors. Socket Objects ¶ Socket objects have the following methods. Except for makefile() , these correspond to Unix system calls applicable to sockets. Changed in version 3.2: Support for the context manager protocol was added. Exiting the context manager is equivalent to calling close() . socket. accept ( ) ¶ Accept a connection. The socket must be bound to an address and listening for connections. The return value is a pair (conn, address) where conn is a new socket object usable to send and receive data on the connection, and address is the address bound to the socket on the other end of the connection. The newly created socket is non-inheritable . Changed in version 3.4: The socket is now non-inheritable. Changed in version 3.5: If the system call is interrupted and the signal handler does not raise an exception, the method now retries the system call instead of raising an InterruptedError exception (see PEP 475 for the rationale). socket. bind ( address ) ¶ Bind the socket to address . The socket must not already be bound. (The format of address depends on the address family — see above.) Raises an auditing event socket.bind with arguments self , address . Availability : not WASI. socket. close ( ) ¶ Mark the socket closed. The underlying system resource (e.g. a file descriptor) is also closed when all file objects from makefile() are closed. Once that happens, all future operations on the socket object will fail. The remote end will receive no more data (after queued data is flushed). Sockets are automatically closed when they are garbage-collected, but it is recommended to close() them explicitly, or to use a with statement around them. Changed in version 3.6: OSError is now raised if an error occurs when the underlying close() call is made. Note close() releases the resource associated with a connection but does not necessarily close the connection immediately. If you want to close the connection in a timely fashion, call shutdown() before close() . socket. connect ( address ) ¶ Connect to a remote socket at address . (The format of address depends on the address family — see above.) If the connection is interrupted by a signal, the method waits until the connection completes, or raise a TimeoutError on timeout, if the signal handler doesn’t raise an exception and the socket is blocking or has a timeout. For non-blocking sockets, the method raises an InterruptedError exception if the connection is interrupted by a signal (or the exception raised by the signal handler). Raises an auditing event socket.connect with arguments self , address . Changed in version 3.5: The method now waits until the connection completes | 2026-01-13T08:48:45 |
https://commission.europa.eu/law/law-topic/data-protection/international-dimension-data-protection/standard-contractual-clauses-scc_es | Standard Contractual Clauses (SCC) - Comisión Europea Ir al contenido principal es Select your language Cerrar bg български es español cs čeština da dansk de Deutsch et eesti el ελληνικά en English fr français ga Gaeilge hr hrvatski it italiano lv latviešu lt lietuvių hu magyar mt Malti nl Nederlands pl polski pt português ro română sk slovenčina sl slovenščina fi suomi sv svenska Búsqueda Búsqueda Comisión Europea Menu Back Inicio Quiénes somos Quiénes somos Más información sobre el papel de la Comisión Europea, su liderazgo y sus políticas empresariales Organización Presidenta Comisarios Servicios y agencias ejecutivas Personal Ver todo Función En materia de estrategia y políticas En materia de legislación En materia de presupuesto y financiación Relaciones internacionales Ver todo Normas y principios de servicio Transparencia Códigos de conducta La Comisión Europea se moderniza Uso de las lenguas por la Comisión Ver todo Contacto Más información DESTACADO Comisión 2024-2029: prioridades y liderazgo Nuestras prioridades Nuestras prioridades Descubra cómo la UE está construyendo un futuro sostenible, competitivo e integrador a través de sus siete prioridades clave. 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Publicaciones Estadísticas Buscar estadísticas de Eurostat Tendencias y previsiones económicas Seguir los resultados de las políticas de la UE Encuesta de opinión pública Portal de datos abiertos de la UE Guía de las estadísticas europeas Ver todo Eurobarómetro Derecho de la UE Zona de aprendizaje Europa Web Guide European Commission visual identity Más información Europa y tú Participa Comparte tus opiniones sobre las políticas y la legislación de la UE, participa en debates sobre el futuro de Europa y encuentra financiación para tus proyectos de la UE. Participe en la elaboración de las políticas de la UE Díganos lo que piensa Paneles europeos de ciudadanos Iniciativa Ciudadana Europea Peticiones a la UE Ver todo Empleos Financiación y licitaciones Actos Visítenos Centro de Visitantes Centro de exposiciones «Experience Europe» Ver todo La Comisión Europea en los medios sociales Más información 10 formas en que la UE te hace la vida más fácil Inicio … Derecho de la UE Legislación por temas Data protection International dimension of data protection Standard Contractual Clauses (SCC) Standard Contractual Clauses (SCC) Standard contractual clauses for data transfers between EU and non-EU countries. Page contents Page contents EU Standard Contractual Clauses According to the General Data Protection Regulation (GDPR), contractual clauses ensuring appropriate data protection safeguards can be used as a ground for data transfers from the EU to third countries. This includes model contract clauses – so-called standard contractual clauses (SCCs) – that have been “pre-approved” by the European Commission. On 4 June 2021 , the Commission issued modernised standard contractual clauses under the GDPR for data transfers from controllers or processors in the EU/EEA (or otherwise subject to the GDPR) to controllers or processors established outside the EU/EEA (and not subject to the GDPR). These modernised SCCs replace the three sets of SCCs that were adopted under the previous Data Protection Directive 95/46. The Commission developed Questions and Answers (Q&As) to provide practical guidance on the use of the SCCs and assist stakeholders in their compliance efforts under the GDPR. These Q&As are based on feedback received from various stakeholders on their experience with using the new SCCs in the first months after their adoption. The Q&As are intended to be a ‘dynamic’ source of information and will be updated as new questions arise. The Commission is in the process of developing additional sets of SCCs for data transfers to third countries by EU institutions and bodies, and for data transfers to controllers or processors outside the EU whose processing operations are directly subject to the GDPR. Model clauses around the world Several organisations and third countries are developing or have issued their own model contractual clauses on the basis of converging principles that are also shared by the EU SCCs. Some jurisdictions have endorsed the EU SCCs as a transfer mechanism under their own national data protection legislation, with limited formal adaptations to their domestic legal order (e.g. the United Kingdom and Switzerland . Others have developed model clauses that share a number of commonalities with the EU SCCs. This for instance includes: - the Model Contractual Clauses for transborder data flows of personal data developed on the basis of Convention 108+ by the Council of Europe Consultative Committee of Convention 108, - the Model Contractual Clauses developed by the Ibero-American Data Protection Network, as well as the accompanying implementation Guide , - the ASEAN Model Contractual Clauses for Cross Border Data Flows developed by the Association of Southeast Asian Nations, - as well as clauses developed at national level, e.g. in New Zealand , Argentina , and the United Kingdom . EU and ASEAN develop joint guidance on the use of model clauses for data transfers The Commission is intensifying its cooperation with international partners to further facilitate data transfers between different regions of the world on the basis of model clauses. ASEAN (the Association of Southeast Asian Nations) is a key partner in this respect. Together with ASEAN, the Commission has developed a Guide on the EU standard contractual clauses and ASEAN model contractual clauses, to assist companies present in both jurisdictions with their compliance efforts under both sets of clauses. The Guide identifies the commonalities between the two sets of clauses and provides non-exhaustive examples of best practices companies can consider to operationalise safeguards required under the clauses. Documents General publications 4 de junio de 2021 Dirección General de Justicia y Consumidores Publications on the Standard Contractual Clauses (SCCs) Access documents related to the two sets of Standard Contractual Clauses (SCCs), including questions and answers on their use. 24 DE MAYO DE 2023 Joint Guide to ASEAN Model Contractual Clauses and EU Standard Contractual Clauses English (535.22 KB - PDF) Descargar 25 DE MAYO DE 2022 Questions and Answers for the two sets of Standard Contractual Clauses English (435.42 KB - PDF) Descargar Compartir esta página Este sitio está gestionado por: Dirección General de Comunicación Quiénes somos Contacto Prioridades Temas Financiación y licitaciones Empleos Zona de prensa Eventos Síganos Facebook Instagram X LinkedIn Other networks Notificar una vulnerabilidad informática Idiomas en nuestros sitios web Cookies Política de privacidad Aviso jurídico Accesibilidad | 2026-01-13T08:48:45 |
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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close # development Follow Hide Tracking and discussing physical and cognitive milestones. Create Post Older #development posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . 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https://nextjs.org/ | Next.js by Vercel - The React Framework Skip to content Search documentation... Search... ⌘K Showcase Docs Blog Templates Enterprise Search documentation... Search... ⌘K Deploy Learn The React Framework for the Web Used by some of the world's largest companies, Next.js enables you to create high-quality web applications with the power of React components. Get Started Learn Next.js ▲ ~ npx create-next-app@latest What's in Next.js? Everything you need to build great products on the web. Data Fetching Make your React component async and await your data. Next.js supports both server and client data fetching. Server Actions Run server code by calling a function. Skip the API. Then, easily revalidate cached data and update your UI in one network roundtrip. Advanced Routing & Nested Layouts Create routes using the file system, including support for more advanced routing patterns and UI layouts. CSS Support Style your application with your favorite tools, including support for CSS Modules, Tailwind CSS, and popular community libraries. Route Handlers Build API endpoints to securely connect with third-party services for handling auth or listening for webhooks. Middleware Take control of the incoming request. Use code to define routing and access rules for authentication, experimentation, and internationalization. React Server Components Add components without sending additional client-side JavaScript. Built on the latest React features. Client and Server Rendering Flexible rendering and caching options, including Incremental Static Regeneration (ISR), on a per-page level. React Server Components Add components without sending additional client-side JavaScript. Built on the latest React features. Data Fetching Make your React component async and await your data. Next.js supports both server and client data fetching. Server Actions Run server code by calling a function. Skip the API. Then, easily revalidate cached data and update your UI in one network roundtrip. Advanced Routing & Nested Layouts Create routes using the file system, including support for more advanced routing patterns and UI layouts. CSS Support Style your application with your favorite tools, including support for CSS Modules, Tailwind CSS, and popular community libraries. Route Handlers Build API endpoints to securely connect with third-party services for handling auth or listening for webhooks. Middleware Take control of the incoming request. Use code to define routing and access rules for authentication, experimentation, and internationalization. Client and Server Rendering Flexible rendering and caching options, including Incremental Static Regeneration (ISR), on a per-page level. React Server Components Add components without sending additional client-side JavaScript. Built on the latest React features. Data Fetching Make your React component async and await your data. Next.js supports both server and client data fetching. Server Actions Run server code by calling a function. Skip the API. Then, easily revalidate cached data and update your UI in one network roundtrip. Advanced Routing & Nested Layouts Create routes using the file system, including support for more advanced routing patterns and UI layouts. CSS Support Style your application with your favorite tools, including support for CSS Modules, Tailwind CSS, and popular community libraries. Route Handlers Build API endpoints to securely connect with third-party services for handling auth or listening for webhooks. Middleware Take control of the incoming request. Use code to define routing and access rules for authentication, experimentation, and internationalization. Client and Server Rendering Flexible rendering and caching options, including Incremental Static Regeneration (ISR), on a per-page level. Next.js 16 The power of full-stack to the frontend. Read the release notes. Built on a foundation of fast, production-grade tooling Powered By React The library for web and native user interfaces. Next.js is built on the latest React features, including Server Components and Actions. Turbopack An incremental bundler optimized for JavaScript and TypeScript, written in Rust , and built into Next.js. Speedy Web Compiler An extensible Rust based platform for the next generation of fast developer tools, and can be used for both compilation and minification. Get started in seconds Deploy Next.js to Vercel Starter Ecommerce Blog AI Portfolio SaaS Multi-tenant Apps Realtime Apps Documentation Virtual Event Web3 Vercel is a frontend cloud from the creators of Next.js, making it easy to get started with Next.js quickly. Jumpstart your Next.js development with pre-built solutions from Vercel and our community. Deploy a Template on Vercel Next.js Boilerplate A Next.js starter from create-next-app. Image Gallery Starter An image gallery built on Next.js and Cloudinary. Next.js Commerce An all-in-one starter kit for high-performance ecommerce sites. The framework of choice when it matters Audible Sonos Dice Notion Today ProductHunt Nike Washington Post Sonos Audible Nike Notion ProductHunt Washington Post For performance , efficiency and developer experience . Next.js is trusted by some of the biggest names on the web. View the Next.js Showcase Customer Testimonials “ With Next.js, we now consistently average 0.09 or lower for Cumulative Layout Shift, placing our site in the top tier for user experience and Core Web Vitals. ” Senior Software Engineer , Frontend “ Our UI for Frame.io responds to user input within 100ms and all animations run at a consistent 60fps with Next.js. ” Charlton Roberts , Product Engineering “ Next.js has been a game-changer for our agency work and team collaboration. Its powerful features have allowed us to build high-performance websites quickly and efficiently like never before. ” Daniel Lopes , Frontend Developer Resources Docs Support Policy Learn Showcase Blog Team Analytics Next.js Conf Previews Evals More Next.js Commerce Contact Sales Community GitHub Releases Telemetry Governance About Vercel Next.js + Vercel Open Source Software GitHub Bluesky X Legal Privacy Policy Cookie Preferences Subscribe to our newsletter Stay updated on new releases and features, guides, and case studies. Subscribe © 2026 Vercel, Inc. Original 1440px 375px Built-in Optimizations Automatic Image, Font, and Script Optimizations for improved UX and Core Web Vitals. Dynamic HTML Streaming Instantly stream UI from the server, integrated with the App Router and React Suspense. Next.js 16 The power of full-stack to the frontend. Read the release notes. Built-in Optimizations Automatic Image, Font, and Script Optimizations for improved UX and Core Web Vitals. Dynamic HTML Streaming Instantly stream UI from the server, integrated with the App Router and React Suspense. Next.js 16 The power of full-stack to the frontend. Read the release notes. Built-in Optimizations Automatic Image, Font, and Script Optimizations for improved UX and Core Web Vitals. Dynamic HTML Streaming Instantly stream UI from the server, integrated with the App Router and React Suspense. | 2026-01-13T08:48:45 |
https://dev.to/dinesh_04/how-speed-finally-made-my-character-feel-alive-3aai | How Speed Finally Made My Character Feel Alive - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Dinesh Posted on Jan 12 How Speed Finally Made My Character Feel Alive # gamedev # unrealengine # beginners # animation Game Designing and Development (9 Part Series) 1 🎮 Learning Game Development – Day 4 2 Understanding Starter Content and Selection Mode in Unreal Engine (Day 10) ... 5 more parts... 3 Actor Panel and Landscape Tool Basics in Unreal Engine (Day 11) 4 Learning Landscape Heightmaps and Sculpting Tools in Unreal Engine (Day 12) 5 Learning the Foliage Tool in Unreal Engine (Day 13) 6 Creating Materials in Unreal Engine 5 and Understanding ORM Textures (Day 14) 7 How I Turned a Static Character into a Moving One in Unreal Engine 8 Why My First Animation Blueprint Didn’t Work in Unreal Engine 9 How Speed Finally Made My Character Feel Alive My character was moving… but it felt wrong. Walking and running looked the same. Speed was the missing piece. This post is part of my daily learning journey in game development. I’m sharing what I learn each day — the basics, the confusion, and the real progress — from the perspective of a beginner. On Day 17 of my game development journey, I learned about Blend Spaces and basic movement logic in Unreal Engine. What I tried / learned today I created a Blend Space 1D for my character using a Speed parameter. I set a reasonable speed range so it matches natural movement: Idle at 0 Walk at a mid value Run at the max value Then I connected the Blend Space inside the Idle/Walk/Run state in the Animation Blueprint. To drive the Blend Space, I calculated speed using: Character movement velocity Vector length That value controlled how the animations blended smoothly. What confused me At first, the animation changes didn’t feel natural. I didn’t understand why walking and running looked almost the same. What worked or finally clicked Once I matched the movement speed values with the animation speeds, everything felt right. Matching animation speed with movement speed was the key . In the Character Blueprint, I added simple logic: Normal speed for walking Increased speed while holding Shift This made walking and running feel intentional and different. One lesson for beginners Blend Spaces depend on correct speed values Movement logic and animation must match Small tweaks create big improvements Slow progress — but I’m building a strong foundation. If you’re also learning game development, what was the first thing that confused you when you started? See you in the next post 🎮🚀 Game Designing and Development (9 Part Series) 1 🎮 Learning Game Development – Day 4 2 Understanding Starter Content and Selection Mode in Unreal Engine (Day 10) ... 5 more parts... 3 Actor Panel and Landscape Tool Basics in Unreal Engine (Day 11) 4 Learning Landscape Heightmaps and Sculpting Tools in Unreal Engine (Day 12) 5 Learning the Foliage Tool in Unreal Engine (Day 13) 6 Creating Materials in Unreal Engine 5 and Understanding ORM Textures (Day 14) 7 How I Turned a Static Character into a Moving One in Unreal Engine 8 Why My First Animation Blueprint Didn’t Work in Unreal Engine 9 How Speed Finally Made My Character Feel Alive Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Dinesh Follow I am currently learning Game Designing and Development. I also share my learning journey on Medium site (profile link in website url). Location Chennai, India Education Monolith Research and Training labs Joined Dec 27, 2025 More from Dinesh Why My First Animation Blueprint Didn’t Work in Unreal Engine # gamedev # unrealengine # beginners # animation How I Turned a Static Character into a Moving One in Unreal Engine # gamedev # unrealengine # beginners # animation Creating Materials in Unreal Engine 5 and Understanding ORM Textures (Day 14) # gamedev # unrealengine # beginners # learning 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://github.com/visakhvjn | visakhvjn (Visakh Vijayan) · GitHub Skip to content Navigation Menu Toggle navigation Sign in Appearance settings Platform AI CODE CREATION GitHub Copilot Write better code with AI GitHub Spark Build and deploy intelligent apps GitHub Models Manage and compare prompts MCP Registry New Integrate external tools DEVELOPER WORKFLOWS Actions Automate any workflow Codespaces Instant dev environments Issues Plan and track work Code Review Manage code changes APPLICATION SECURITY GitHub Advanced Security Find and fix vulnerabilities Code security Secure your code as you build Secret protection Stop leaks before they start EXPLORE Why GitHub Documentation Blog Changelog Marketplace View all features Solutions BY COMPANY SIZE Enterprises Small and medium teams Startups Nonprofits BY USE CASE App Modernization DevSecOps DevOps CI/CD View all use cases BY INDUSTRY Healthcare Financial services Manufacturing Government View all industries View all solutions Resources EXPLORE BY TOPIC AI Software Development DevOps Security View all topics EXPLORE BY TYPE Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills SUPPORT & SERVICES Documentation Customer support Community forum Trust center Partners Open Source COMMUNITY GitHub Sponsors Fund open source developers PROGRAMS Security Lab Maintainer Community Accelerator Archive Program REPOSITORIES Topics Trending Collections Enterprise ENTERPRISE SOLUTIONS Enterprise platform AI-powered developer platform AVAILABLE ADD-ONS GitHub Advanced Security Enterprise-grade security features Copilot for Business Enterprise-grade AI features Premium Support Enterprise-grade 24/7 support Pricing Search or jump to... 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Dismiss alert {{ message }} visakhvjn Follow Overview Repositories 22 Projects 0 Packages 0 Stars 1 More Overview Repositories Projects Packages Stars visakhvjn Follow 🏠 Working from home Visakh Vijayan visakhvjn 🏠 Working from home Follow As a MERN Dev, I've had the privilege of helping companies unlock value and achieve their goals through innovative solutions. By leveraging my expertise, I've d 10 followers · 5 following Jalan Technologies Bangalore X @vjnvisakh LinkedIn in/vjnvisakh Achievements x2 Achievements x2 Block or Report Block or report visakhvjn --> Block user Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users . You must be logged in to block users. Add an optional note Maximum 250 characters. Please don't include any personal information such as legal names or email addresses. Markdown supported. This note will be visible to only you. Block user Report abuse Contact GitHub support about this user’s behavior. Learn more about reporting abuse . Report abuse Overview Repositories 22 Projects 0 Packages 0 Stars 1 More Overview Repositories Projects Packages Stars visakhvjn / README .md Visakh Vijayan Download Resume Having worked closely with all the stakeholders(client, customer, and technical), I am easily flexible in handling pressure conditions. I am also motivated to work individually or as a team as the situation arises. As an accomplished software engineer with seven+ years of dedicated experience, I bring a proven track record of delivering innovative software solutions and contributing to the success of dynamic projects. My passion for programming and commitment to excellence have enabled me to consistently exceed expectations and drive results in the ever-evolving tech industry. PROFILES Contact @ LinkedIn | Medium | Fiverr | Stack Overflow Compete @ Hacker Rank | Code Chef | Leet Code | Hacker Earth | Coder Byte Reading @ Goodreads Streak @ FreeCodeCamp | Codecademy TECH STACK Languages & Frameworks - Node, Express, React, TypeScript, NextJs Databases - Mongodb, Mongoose Testing - Mocha Cloud & DevOps - AWS, Terraform, Docker (compose) Gen AI - Openai APIs, RAGs, Embeddings, etc Other - Microservices WORK EXPERIENCE (7+ years) Unify Technologoes, Hyderabad, India (June' 25 - Present) MyKula - A closed community for parents, educators and local businesses. Better Software, Bangalore, India (Oct’ 21 - March' 25) Nesh - BE developer for an AI-powered knowledge engine Bionic - FE developer for an AI-powered Fiverr-like platform with Artica The Pinch Life - Team Lead for a popular Facility Management Saas in India. SunLead - Senior Engineer for a solar lead generation tool for US markets. Recco Joy - Senior Engineer for a product that allowed giving recommendations to products and businesses. Allowed businesses a bird’s eye view of the ad performance and offer disbursals. SeenIt Online Pvt Ltd, Kolkata, India (Feb’ 20 - Sep’ 21) StyleAde - Migrating the company’s legacy stack built on PHP to the MERN stack. Worked on an eCommerce vendor onboarding app that allowed luxury brand CRMs to have a B2C app with the least latency. Worked with elastic search to improve the user search experience along with faceted search. Vawsum Schools Pvt Ltd (Oct’ 16 - Jan’ 20) Vawsum - Designed a payments module for school fee collection and an aggregator panel for the company and the school admins. Paved way for all types of transactions at schools using payment gateways. Vawme - A teaching assistant that allowed to prescribe courses to students based on the classes and curriculum. Integration of a 3rd party time-table generation software for classes. Allowed to assign teachers to free periods and adjusted for absent teachers. Enquiry - Admission inquiry using a Google Forms type model. Customized drag-and-drop forms that allowed to creation of forms for any occasion. Schools used them for admissions, certificates, mark sheets, etc. Integrated RFID readers at schools to set up student attendances which were funneled to parents as well. Trakkerz - Worked on .net to create services for a school bus tracking application. Integrated Google Maps to show a live view of buses on the admin panel. A simple SMS module for the company to keep track of the SMSes being sent via multiple vendors in a single panel. The panel allowed easy switching between vendors and auto-prioritizing based on load. CERTIFICATIONS Digital Ocean Cloud Platform Fundamentals PROJECTS dumpd.in - A blogging platform managed by AI personalities. It has everything you need - topics, stories, custom blogs etc. Running successfully with over 100 DAU. Typing Master - If you have ever felt the need to up your typing game, then wait no more. Typing Master allows you to practice daily and build a streak. Pinned Loading typing-master typing-master Public Whether you're a beginner looking to improve your typing speed or an advanced typist aiming for perfection, our app offers personalized lessons and exercises tailored to your skill level TypeScript linkedin-commentor linkedin-commentor Public A chrome extension that allows you to add an AI generated comment on a post JavaScript microservices-express microservices-express Public A microservices architecture using express with users and todo domains connected via api gateway for monitoring JavaScript ai-powered-trivia ai-powered-trivia Public Get ready to challenge your knowledge with questions curated by cutting-edge artificial intelligence algorithms. With an intuitive interface and a vast database of questions, our app offers an eng… TypeScript random-quotes random-quotes Public beautifully designed and user-friendly app that delivers daily doses of inspiration and wisdom through a collection of random quotes from various sources. With just a tap, you can access a vast re… TypeScript minutes minutes Public Minutes is what powers the popular android news app - Minutes. You can download it here - https://play.google.com/store/apps/details?id=com.souparnika.minutes TypeScript Something went wrong, please refresh the page to try again. If the problem persists, check the GitHub status page or contact support . Uh oh! There was an error while loading. Please reload this page . Footer © 2026 GitHub, Inc. Footer navigation Terms Privacy Security Status Community Docs Contact Manage cookies Do not share my personal information You can’t perform that action at this time. | 2026-01-13T08:48:45 |
https://about.x.com/en/who-we-are/brand-toolkit | About X | Our logo, brand guidelines, and tools Skip to main content About <path opacity="0" d="M0 0h24v24H0z" /> <path d="M17.207 11.293l-7.5-7.5c-.39-.39-1.023-.39-1.414 0s-.39 1.023 0 1.414L15.086 12l-6.793 6.793c-.39.39-.39 1.023 0 1.414.195.195.45.293.707.293s.512-.098.707-.293l7.5-7.5c.39-.39.39-1.023 0-1.414z" /> </svg>" data-icon-arrow-left="<svg width="28px" height="28px" viewbox="0 0 28 28" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="none" class="twtr-icon u01b__icon-arrow-left"> <g stroke="none" stroke-width="1" fill="none" fill-rule="evenodd" stroke-linecap="round"> <g transform="translate(-1216.000000, -298.000000)" stroke-width="2.25"> <g transform="translate(1200.000000, 282.000000)"> <g transform="translate(17.000000, 17.000000)"> <path d="M0.756410256,12.8589744 L25.7179487,12.8589744"></path> <path d="M13.2371795,25.3397436 L25.7179487,12.8589744"></path> <path d="M13.2371795,12.4807692 L25.3397436,0.378205128" transform="translate(19.288462, 6.429487) rotate(-90.000000) translate(-19.288462, -6.429487) "></path> </g> </g> </g> </g> </svg>" data-icon-chevron-down="<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewbox="0 0 24 24" aria-hidden="true" focusable="false" role="none" class="twtr-icon"> <path opacity="0" d="M0 0h24v24H0z" /> <path d="M20.207 7.043c-.39-.39-1.023-.39-1.414 0L12 13.836 5.207 7.043c-.39-.39-1.023-.39-1.414 0s-.39 1.023 0 1.414l7.5 7.5c.195.195.45.293.707.293s.512-.098.707-.293l7.5-7.5c.39-.39.39-1.023 0-1.414z" /> </svg>" data-icon-close="<svg version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px" viewbox="0 0 24 24" style="enable-background:new 0 0 24 24;" xml:space="preserve" aria-hidden="true" focusable="false" role="none" class="twtr-icon--md"> <g> <g> <defs> <rect id="SVGID_1_" x="-468" y="-1360" width="1440" height="3027" /> </defs> <clippath id="SVGID_2_"> <use xlink:href="#SVGID_1_" style="overflow:visible;" /> </clippath> </g> </g> <rect x="-468" y="-1360" class="st0" width="1440" height="3027" style="fill:rgb(0,0,0,0);stroke-width:3;stroke:rgb(0,0,0)" /> <path d="M13.4,12l5.8-5.8c0.4-0.4,0.4-1,0-1.4c-0.4-0.4-1-0.4-1.4,0L12,10.6L6.2,4.8c-0.4-0.4-1-0.4-1.4,0c-0.4,0.4-0.4,1,0,1.4 l5.8,5.8l-5.8,5.8c-0.4,0.4-0.4,1,0,1.4c0.2,0.2,0.4,0.3,0.7,0.3s0.5-0.1,0.7-0.3l5.8-5.8l5.8,5.8c0.2,0.2,0.5,0.3,0.7,0.3 s0.5-0.1,0.7-0.3c0.4-0.4,0.4-1,0-1.4L13.4,12z" /> </svg>" data-icon-search="<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewbox="0 0 24 24" aria-hidden="true" focusable="false" role="none" class="twtr-icon"> <path opacity="0" d="M0 0h24v24H0z" /> <path d="M22.06 19.94l-3.73-3.73C19.38 14.737 20 12.942 20 11c0-4.97-4.03-9-9-9s-9 4.03-9 9 4.03 9 9 9c1.943 0 3.738-.622 5.21-1.67l3.73 3.73c.292.294.676.44 1.06.44s.768-.146 1.06-.44c.586-.585.586-1.535 0-2.12zM11 17c-3.308 0-6-2.692-6-6s2.692-6 6-6 6 2.692 6 6-2.692 6-6 6z" /> </svg>" data-icon-search-submit="<svg width="21" height="21" viewbox="0 0 21 21" fill="none" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" role="none" class="twtr-icon"> <path fill-rule="evenodd" clip-rule="evenodd" d="M16.33 14.21L20.06 17.94C20.646 18.525 20.646 19.475 20.06 20.06C19.768 20.354 19.384 20.5 19 20.5C18.616 20.5 18.232 20.354 17.94 20.06L14.21 16.33C12.738 17.378 10.943 18 9 18C4.03 18 0 13.97 0 9C0 4.03 4.03 0 9 0C13.97 0 18 4.03 18 9C18 10.942 17.38 12.737 16.33 14.21ZM3 9C3 12.308 5.692 15 9 15C12.308 15 15 12.308 15 9C15 5.692 12.308 3 9 3C5.692 3 3 5.692 3 9Z" fill="white" /> </svg>" data-bg-color="white-neutral" data-root-page-title="About" data-search-placeholder="Search" data-search-page="https://about.x.com/en-delete/search.html" data-search-query-key="q" data-search-query-type="?" data-scribe-element="2XR5" data-scribe-section="u01b-navigation" data-cta-enabled="true" data-cta-text="Go to X.com" data-cta-link="https://x.com/" data-cta-link-new-tab="true"> Brand toolkit Your one-stop shop for X assets. 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https://creators.spotify.com/pod/profile/apisyouwonthate/episodes/Episode-2-New-OSS-Open-API-Tooling-Abound-e4ud5i | Episode 2: New OSS Open API Tooling Abound! by APIs You Won't Hate APIs You Won't Hate By Phil Sturgeon A no-nonsense podcast about API design, development, HTTP in general, service-orientated architecture, microservices, and probably bikes. Listen on Spotify Available on Report content on Spotify Episode 2: New OSS Open API Tooling Abound! APIs You Won't Hate Aug 12, 2019 Share 00:00 36:28 GraphQL Monitoring and how to travel via Train This episode is brought to you by Stoplight.io ( https://stoplight.io )! Check out Studio today if you are creating an API with the OpenAPI Specification. In this episode, Phil talks about how his trip across the United States via train went. We also talk about how to monitor APIs and what is the best APM solution for monitoring GraphQL endpoints. We also talk about the progress being made by the Stoplight team with both their tooling around Async APIs and also work being done on Studio. Links: Article: GraphQL Performance Monitoring Is Hard Why GraphQL Performance Monitoring is hard Phil's repo of companies working to help save the earth Awesome Earth Sep 25, 2019 45:56 Episode 2: New OSS Open API Tooling Abound! Last time on APIs You Won't Hate, we laid the ground work for this podcast. This time (after a failed attempt when Phil didn't press record) Mike, Phil, and Matt talk about whats new with Stoplight.io, how front end developers like Mike can use the Stoplight suite of OSS products to make Front End Development better, and where they are with the books! Notes: https://stoplight.io https://github.com/stoplight https://twitter.com/philsturgeon https://twitter.com/irreverentmike https://twitter.com/matthewtrask Sponsors: Huge thank you to Stoplight.io ( https://stoplight.io ) for sponsoring this episode! If you are looking to make your API workflow better, check them out for tools ranging from linting (Spectral) to mocking (Prism) to their new release Studio! Aug 12, 2019 36:28 Episode 1: APIs and Bikes Go Together Great Welcome to our new podcast! Phil Sturgeon (@philsturgeon), Mike Bifulco (@irreverentmike) and Matt Trask (@matthewtrask) get started with the first episode where we talk about bikes, APIs and our goal for the podcast. We break down Phil's adventures in Europe, how his new books are going with the help of Mike, and some other nonsense. Find us in the APIs You Wont Hate slack for questions, help, mentoring or other things! Jun 23, 2019 33:27 © 2026 Spotify AB Careers Legal Help App Store Google Play | 2026-01-13T08:48:45 |
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Engagér dig i EU's politiske beslutningsproces Deltag i debatten Europæiske borgerpaneler Det europæiske borgerinitiativ Indgiv et andragende til EU Se alle Job Finansiering og udbud Arrangementer Besøg os Besøgscentret Udstillingen Experience Europe Se alle Europa-Kommissionen på de sociale medier Læs mere 10 måder, som EU gør dit liv lettere på Forside … EU-lovgivning Lovgivning efter emne Data protection International dimension of data protection Standard Contractual Clauses (SCC) Standard Contractual Clauses (SCC) Standard contractual clauses for data transfers between EU and non-EU countries. Page contents Page contents EU Standard Contractual Clauses According to the General Data Protection Regulation (GDPR), contractual clauses ensuring appropriate data protection safeguards can be used as a ground for data transfers from the EU to third countries. This includes model contract clauses – so-called standard contractual clauses (SCCs) – that have been “pre-approved” by the European Commission. On 4 June 2021 , the Commission issued modernised standard contractual clauses under the GDPR for data transfers from controllers or processors in the EU/EEA (or otherwise subject to the GDPR) to controllers or processors established outside the EU/EEA (and not subject to the GDPR). These modernised SCCs replace the three sets of SCCs that were adopted under the previous Data Protection Directive 95/46. The Commission developed Questions and Answers (Q&As) to provide practical guidance on the use of the SCCs and assist stakeholders in their compliance efforts under the GDPR. These Q&As are based on feedback received from various stakeholders on their experience with using the new SCCs in the first months after their adoption. The Q&As are intended to be a ‘dynamic’ source of information and will be updated as new questions arise. The Commission is in the process of developing additional sets of SCCs for data transfers to third countries by EU institutions and bodies, and for data transfers to controllers or processors outside the EU whose processing operations are directly subject to the GDPR. Model clauses around the world Several organisations and third countries are developing or have issued their own model contractual clauses on the basis of converging principles that are also shared by the EU SCCs. Some jurisdictions have endorsed the EU SCCs as a transfer mechanism under their own national data protection legislation, with limited formal adaptations to their domestic legal order (e.g. the United Kingdom and Switzerland . Others have developed model clauses that share a number of commonalities with the EU SCCs. This for instance includes: - the Model Contractual Clauses for transborder data flows of personal data developed on the basis of Convention 108+ by the Council of Europe Consultative Committee of Convention 108, - the Model Contractual Clauses developed by the Ibero-American Data Protection Network, as well as the accompanying implementation Guide , - the ASEAN Model Contractual Clauses for Cross Border Data Flows developed by the Association of Southeast Asian Nations, - as well as clauses developed at national level, e.g. in New Zealand , Argentina , and the United Kingdom . EU and ASEAN develop joint guidance on the use of model clauses for data transfers The Commission is intensifying its cooperation with international partners to further facilitate data transfers between different regions of the world on the basis of model clauses. ASEAN (the Association of Southeast Asian Nations) is a key partner in this respect. Together with ASEAN, the Commission has developed a Guide on the EU standard contractual clauses and ASEAN model contractual clauses, to assist companies present in both jurisdictions with their compliance efforts under both sets of clauses. The Guide identifies the commonalities between the two sets of clauses and provides non-exhaustive examples of best practices companies can consider to operationalise safeguards required under the clauses. Documents General publications 4. juni 2021 Generaldirektoratet for Retlige Anliggender og Forbrugere Publications on the Standard Contractual Clauses (SCCs) Access documents related to the two sets of Standard Contractual Clauses (SCCs), including questions and answers on their use. 24. MAJ 2023 Joint Guide to ASEAN Model Contractual Clauses and EU Standard Contractual Clauses English (535.22 KB - PDF) Download 25. MAJ 2022 Questions and Answers for the two sets of Standard Contractual Clauses English (435.42 KB - PDF) Download Del denne side Dette website administreres af: Generaldirektoratet for Kommunikation Om os Kontakt os Prioriteter Emner Finansiering og udbud Job Pressehjørnet Arrangementer Følg os Facebook Instagram X LinkedIn Other networks Indberet en IT-sårbarhed Sprog på vores websites Cookies Databeskyttelsespolitik Juridisk meddelelse Tilgængelighed | 2026-01-13T08:48:45 |
https://docs.python.org/3/tutorial/controlflow.html#tut-match | 4. More Control Flow Tools — Python 3.14.2 documentation Theme Auto Light Dark Table of Contents 4. More Control Flow Tools 4.1. if Statements 4.2. for Statements 4.3. The range() Function 4.4. break and continue Statements 4.5. else Clauses on Loops 4.6. pass Statements 4.7. match Statements 4.8. Defining Functions 4.9. More on Defining Functions 4.9.1. Default Argument Values 4.9.2. Keyword Arguments 4.9.3. Special parameters 4.9.3.1. Positional-or-Keyword Arguments 4.9.3.2. Positional-Only Parameters 4.9.3.3. Keyword-Only Arguments 4.9.3.4. Function Examples 4.9.3.5. Recap 4.9.4. Arbitrary Argument Lists 4.9.5. Unpacking Argument Lists 4.9.6. Lambda Expressions 4.9.7. Documentation Strings 4.9.8. Function Annotations 4.10. Intermezzo: Coding Style Previous topic 3. An Informal Introduction to Python Next topic 5. Data Structures This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Tutorial » 4. More Control Flow Tools | Theme Auto Light Dark | 4. More Control Flow Tools ¶ As well as the while statement just introduced, Python uses a few more that we will encounter in this chapter. 4.1. if Statements ¶ Perhaps the most well-known statement type is the if statement. For example: >>> x = int ( input ( "Please enter an integer: " )) Please enter an integer: 42 >>> if x < 0 : ... x = 0 ... print ( 'Negative changed to zero' ) ... elif x == 0 : ... print ( 'Zero' ) ... elif x == 1 : ... print ( 'Single' ) ... else : ... print ( 'More' ) ... More There can be zero or more elif parts, and the else part is optional. The keyword ‘ elif ’ is short for ‘else if’, and is useful to avoid excessive indentation. An if … elif … elif … sequence is a substitute for the switch or case statements found in other languages. If you’re comparing the same value to several constants, or checking for specific types or attributes, you may also find the match statement useful. For more details see match Statements . 4.2. for Statements ¶ The for statement in Python differs a bit from what you may be used to in C or Pascal. Rather than always iterating over an arithmetic progression of numbers (like in Pascal), or giving the user the ability to define both the iteration step and halting condition (as C), Python’s for statement iterates over the items of any sequence (a list or a string), in the order that they appear in the sequence. For example (no pun intended): >>> # Measure some strings: >>> words = [ 'cat' , 'window' , 'defenestrate' ] >>> for w in words : ... print ( w , len ( w )) ... cat 3 window 6 defenestrate 12 Code that modifies a collection while iterating over that same collection can be tricky to get right. Instead, it is usually more straight-forward to loop over a copy of the collection or to create a new collection: # Create a sample collection users = { 'Hans' : 'active' , 'Éléonore' : 'inactive' , '景太郎' : 'active' } # Strategy: Iterate over a copy for user , status in users . copy () . items (): if status == 'inactive' : del users [ user ] # Strategy: Create a new collection active_users = {} for user , status in users . items (): if status == 'active' : active_users [ user ] = status 4.3. The range() Function ¶ If you do need to iterate over a sequence of numbers, the built-in function range() comes in handy. It generates arithmetic progressions: >>> for i in range ( 5 ): ... print ( i ) ... 0 1 2 3 4 The given end point is never part of the generated sequence; range(10) generates 10 values, the legal indices for items of a sequence of length 10. It is possible to let the range start at another number, or to specify a different increment (even negative; sometimes this is called the ‘step’): >>> list ( range ( 5 , 10 )) [5, 6, 7, 8, 9] >>> list ( range ( 0 , 10 , 3 )) [0, 3, 6, 9] >>> list ( range ( - 10 , - 100 , - 30 )) [-10, -40, -70] To iterate over the indices of a sequence, you can combine range() and len() as follows: >>> a = [ 'Mary' , 'had' , 'a' , 'little' , 'lamb' ] >>> for i in range ( len ( a )): ... print ( i , a [ i ]) ... 0 Mary 1 had 2 a 3 little 4 lamb In most such cases, however, it is convenient to use the enumerate() function, see Looping Techniques . A strange thing happens if you just print a range: >>> range ( 10 ) range(0, 10) In many ways the object returned by range() behaves as if it is a list, but in fact it isn’t. It is an object which returns the successive items of the desired sequence when you iterate over it, but it doesn’t really make the list, thus saving space. We say such an object is iterable , that is, suitable as a target for functions and constructs that expect something from which they can obtain successive items until the supply is exhausted. We have seen that the for statement is such a construct, while an example of a function that takes an iterable is sum() : >>> sum ( range ( 4 )) # 0 + 1 + 2 + 3 6 Later we will see more functions that return iterables and take iterables as arguments. In chapter Data Structures , we will discuss in more detail about list() . 4.4. break and continue Statements ¶ The break statement breaks out of the innermost enclosing for or while loop: >>> for n in range ( 2 , 10 ): ... for x in range ( 2 , n ): ... if n % x == 0 : ... print ( f " { n } equals { x } * { n // x } " ) ... break ... 4 equals 2 * 2 6 equals 2 * 3 8 equals 2 * 4 9 equals 3 * 3 The continue statement continues with the next iteration of the loop: >>> for num in range ( 2 , 10 ): ... if num % 2 == 0 : ... print ( f "Found an even number { num } " ) ... continue ... print ( f "Found an odd number { num } " ) ... Found an even number 2 Found an odd number 3 Found an even number 4 Found an odd number 5 Found an even number 6 Found an odd number 7 Found an even number 8 Found an odd number 9 4.5. else Clauses on Loops ¶ In a for or while loop the break statement may be paired with an else clause. If the loop finishes without executing the break , the else clause executes. In a for loop, the else clause is executed after the loop finishes its final iteration, that is, if no break occurred. In a while loop, it’s executed after the loop’s condition becomes false. In either kind of loop, the else clause is not executed if the loop was terminated by a break . Of course, other ways of ending the loop early, such as a return or a raised exception, will also skip execution of the else clause. This is exemplified in the following for loop, which searches for prime numbers: >>> for n in range ( 2 , 10 ): ... for x in range ( 2 , n ): ... if n % x == 0 : ... print ( n , 'equals' , x , '*' , n // x ) ... break ... else : ... # loop fell through without finding a factor ... print ( n , 'is a prime number' ) ... 2 is a prime number 3 is a prime number 4 equals 2 * 2 5 is a prime number 6 equals 2 * 3 7 is a prime number 8 equals 2 * 4 9 equals 3 * 3 (Yes, this is the correct code. Look closely: the else clause belongs to the for loop, not the if statement.) One way to think of the else clause is to imagine it paired with the if inside the loop. As the loop executes, it will run a sequence like if/if/if/else. The if is inside the loop, encountered a number of times. If the condition is ever true, a break will happen. If the condition is never true, the else clause outside the loop will execute. When used with a loop, the else clause has more in common with the else clause of a try statement than it does with that of if statements: a try statement’s else clause runs when no exception occurs, and a loop’s else clause runs when no break occurs. For more on the try statement and exceptions, see Handling Exceptions . 4.6. pass Statements ¶ The pass statement does nothing. It can be used when a statement is required syntactically but the program requires no action. For example: >>> while True : ... pass # Busy-wait for keyboard interrupt (Ctrl+C) ... This is commonly used for creating minimal classes: >>> class MyEmptyClass : ... pass ... Another place pass can be used is as a place-holder for a function or conditional body when you are working on new code, allowing you to keep thinking at a more abstract level. The pass is silently ignored: >>> def initlog ( * args ): ... pass # Remember to implement this! ... For this last case, many people use the ellipsis literal ... instead of pass . This use has no special meaning to Python, and is not part of the language definition (you could use any constant expression here), but ... is used conventionally as a placeholder body as well. See The Ellipsis Object . 4.7. match Statements ¶ A match statement takes an expression and compares its value to successive patterns given as one or more case blocks. This is superficially similar to a switch statement in C, Java or JavaScript (and many other languages), but it’s more similar to pattern matching in languages like Rust or Haskell. Only the first pattern that matches gets executed and it can also extract components (sequence elements or object attributes) from the value into variables. If no case matches, none of the branches is executed. The simplest form compares a subject value against one or more literals: def http_error ( status ): match status : case 400 : return "Bad request" case 404 : return "Not found" case 418 : return "I'm a teapot" case _ : return "Something's wrong with the internet" Note the last block: the “variable name” _ acts as a wildcard and never fails to match. You can combine several literals in a single pattern using | (“or”): case 401 | 403 | 404 : return "Not allowed" Patterns can look like unpacking assignments, and can be used to bind variables: # point is an (x, y) tuple match point : case ( 0 , 0 ): print ( "Origin" ) case ( 0 , y ): print ( f "Y= { y } " ) case ( x , 0 ): print ( f "X= { x } " ) case ( x , y ): print ( f "X= { x } , Y= { y } " ) case _ : raise ValueError ( "Not a point" ) Study that one carefully! The first pattern has two literals, and can be thought of as an extension of the literal pattern shown above. But the next two patterns combine a literal and a variable, and the variable binds a value from the subject ( point ). The fourth pattern captures two values, which makes it conceptually similar to the unpacking assignment (x, y) = point . If you are using classes to structure your data you can use the class name followed by an argument list resembling a constructor, but with the ability to capture attributes into variables: class Point : def __init__ ( self , x , y ): self . x = x self . y = y def where_is ( point ): match point : case Point ( x = 0 , y = 0 ): print ( "Origin" ) case Point ( x = 0 , y = y ): print ( f "Y= { y } " ) case Point ( x = x , y = 0 ): print ( f "X= { x } " ) case Point (): print ( "Somewhere else" ) case _ : print ( "Not a point" ) You can use positional parameters with some builtin classes that provide an ordering for their attributes (e.g. dataclasses). You can also define a specific position for attributes in patterns by setting the __match_args__ special attribute in your classes. If it’s set to (“x”, “y”), the following patterns are all equivalent (and all bind the y attribute to the var variable): Point ( 1 , var ) Point ( 1 , y = var ) Point ( x = 1 , y = var ) Point ( y = var , x = 1 ) A recommended way to read patterns is to look at them as an extended form of what you would put on the left of an assignment, to understand which variables would be set to what. Only the standalone names (like var above) are assigned to by a match statement. Dotted names (like foo.bar ), attribute names (the x= and y= above) or class names (recognized by the “(…)” next to them like Point above) are never assigned to. Patterns can be arbitrarily nested. For example, if we have a short list of Points, with __match_args__ added, we could match it like this: class Point : __match_args__ = ( 'x' , 'y' ) def __init__ ( self , x , y ): self . x = x self . y = y match points : case []: print ( "No points" ) case [ Point ( 0 , 0 )]: print ( "The origin" ) case [ Point ( x , y )]: print ( f "Single point { x } , { y } " ) case [ Point ( 0 , y1 ), Point ( 0 , y2 )]: print ( f "Two on the Y axis at { y1 } , { y2 } " ) case _ : print ( "Something else" ) We can add an if clause to a pattern, known as a “guard”. If the guard is false, match goes on to try the next case block. Note that value capture happens before the guard is evaluated: match point : case Point ( x , y ) if x == y : print ( f "Y=X at { x } " ) case Point ( x , y ): print ( f "Not on the diagonal" ) Several other key features of this statement: Like unpacking assignments, tuple and list patterns have exactly the same meaning and actually match arbitrary sequences. An important exception is that they don’t match iterators or strings. Sequence patterns support extended unpacking: [x, y, *rest] and (x, y, *rest) work similar to unpacking assignments. The name after * may also be _ , so (x, y, *_) matches a sequence of at least two items without binding the remaining items. Mapping patterns: {"bandwidth": b, "latency": l} captures the "bandwidth" and "latency" values from a dictionary. Unlike sequence patterns, extra keys are ignored. An unpacking like **rest is also supported. (But **_ would be redundant, so it is not allowed.) Subpatterns may be captured using the as keyword: case ( Point ( x1 , y1 ), Point ( x2 , y2 ) as p2 ): ... will capture the second element of the input as p2 (as long as the input is a sequence of two points) Most literals are compared by equality, however the singletons True , False and None are compared by identity. Patterns may use named constants. These must be dotted names to prevent them from being interpreted as capture variable: from enum import Enum class Color ( Enum ): RED = 'red' GREEN = 'green' BLUE = 'blue' color = Color ( input ( "Enter your choice of 'red', 'blue' or 'green': " )) match color : case Color . RED : print ( "I see red!" ) case Color . GREEN : print ( "Grass is green" ) case Color . BLUE : print ( "I'm feeling the blues :(" ) For a more detailed explanation and additional examples, you can look into PEP 636 which is written in a tutorial format. 4.8. Defining Functions ¶ We can create a function that writes the Fibonacci series to an arbitrary boundary: >>> def fib ( n ): # write Fibonacci series less than n ... """Print a Fibonacci series less than n.""" ... a , b = 0 , 1 ... while a < n : ... print ( a , end = ' ' ) ... a , b = b , a + b ... print () ... >>> # Now call the function we just defined: >>> fib ( 2000 ) 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597 The keyword def introduces a function definition . It must be followed by the function name and the parenthesized list of formal parameters. The statements that form the body of the function start at the next line, and must be indented. The first statement of the function body can optionally be a string literal; this string literal is the function’s documentation string, or docstring . (More about docstrings can be found in the section Documentation Strings .) There are tools which use docstrings to automatically produce online or printed documentation, or to let the user interactively browse through code; it’s good practice to include docstrings in code that you write, so make a habit of it. The execution of a function introduces a new symbol table used for the local variables of the function. More precisely, all variable assignments in a function store the value in the local symbol table; whereas variable references first look in the local symbol table, then in the local symbol tables of enclosing functions, then in the global symbol table, and finally in the table of built-in names. Thus, global variables and variables of enclosing functions cannot be directly assigned a value within a function (unless, for global variables, named in a global statement, or, for variables of enclosing functions, named in a nonlocal statement), although they may be referenced. The actual parameters (arguments) to a function call are introduced in the local symbol table of the called function when it is called; thus, arguments are passed using call by value (where the value is always an object reference , not the value of the object). [ 1 ] When a function calls another function, or calls itself recursively, a new local symbol table is created for that call. A function definition associates the function name with the function object in the current symbol table. The interpreter recognizes the object pointed to by that name as a user-defined function. Other names can also point to that same function object and can also be used to access the function: >>> fib <function fib at 10042ed0> >>> f = fib >>> f ( 100 ) 0 1 1 2 3 5 8 13 21 34 55 89 Coming from other languages, you might object that fib is not a function but a procedure since it doesn’t return a value. In fact, even functions without a return statement do return a value, albeit a rather boring one. This value is called None (it’s a built-in name). Writing the value None is normally suppressed by the interpreter if it would be the only value written. You can see it if you really want to using print() : >>> fib ( 0 ) >>> print ( fib ( 0 )) None It is simple to write a function that returns a list of the numbers of the Fibonacci series, instead of printing it: >>> def fib2 ( n ): # return Fibonacci series up to n ... """Return a list containing the Fibonacci series up to n.""" ... result = [] ... a , b = 0 , 1 ... while a < n : ... result . append ( a ) # see below ... a , b = b , a + b ... return result ... >>> f100 = fib2 ( 100 ) # call it >>> f100 # write the result [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89] This example, as usual, demonstrates some new Python features: The return statement returns with a value from a function. return without an expression argument returns None . Falling off the end of a function also returns None . The statement result.append(a) calls a method of the list object result . A method is a function that ‘belongs’ to an object and is named obj.methodname , where obj is some object (this may be an expression), and methodname is the name of a method that is defined by the object’s type. Different types define different methods. Methods of different types may have the same name without causing ambiguity. (It is possible to define your own object types and methods, using classes , see Classes ) The method append() shown in the example is defined for list objects; it adds a new element at the end of the list. In this example it is equivalent to result = result + [a] , but more efficient. 4.9. More on Defining Functions ¶ It is also possible to define functions with a variable number of arguments. There are three forms, which can be combined. 4.9.1. Default Argument Values ¶ The most useful form is to specify a default value for one or more arguments. This creates a function that can be called with fewer arguments than it is defined to allow. For example: def ask_ok ( prompt , retries = 4 , reminder = 'Please try again!' ): while True : reply = input ( prompt ) if reply in { 'y' , 'ye' , 'yes' }: return True if reply in { 'n' , 'no' , 'nop' , 'nope' }: return False retries = retries - 1 if retries < 0 : raise ValueError ( 'invalid user response' ) print ( reminder ) This function can be called in several ways: giving only the mandatory argument: ask_ok('Do you really want to quit?') giving one of the optional arguments: ask_ok('OK to overwrite the file?', 2) or even giving all arguments: ask_ok('OK to overwrite the file?', 2, 'Come on, only yes or no!') This example also introduces the in keyword. This tests whether or not a sequence contains a certain value. The default values are evaluated at the point of function definition in the defining scope, so that i = 5 def f ( arg = i ): print ( arg ) i = 6 f () will print 5 . Important warning: The default value is evaluated only once. This makes a difference when the default is a mutable object such as a list, dictionary, or instances of most classes. For example, the following function accumulates the arguments passed to it on subsequent calls: def f ( a , L = []): L . append ( a ) return L print ( f ( 1 )) print ( f ( 2 )) print ( f ( 3 )) This will print [ 1 ] [ 1 , 2 ] [ 1 , 2 , 3 ] If you don’t want the default to be shared between subsequent calls, you can write the function like this instead: def f ( a , L = None ): if L is None : L = [] L . append ( a ) return L 4.9.2. Keyword Arguments ¶ Functions can also be called using keyword arguments of the form kwarg=value . For instance, the following function: def parrot ( voltage , state = 'a stiff' , action = 'voom' , type = 'Norwegian Blue' ): print ( "-- This parrot wouldn't" , action , end = ' ' ) print ( "if you put" , voltage , "volts through it." ) print ( "-- Lovely plumage, the" , type ) print ( "-- It's" , state , "!" ) accepts one required argument ( voltage ) and three optional arguments ( state , action , and type ). This function can be called in any of the following ways: parrot ( 1000 ) # 1 positional argument parrot ( voltage = 1000 ) # 1 keyword argument parrot ( voltage = 1000000 , action = 'VOOOOOM' ) # 2 keyword arguments parrot ( action = 'VOOOOOM' , voltage = 1000000 ) # 2 keyword arguments parrot ( 'a million' , 'bereft of life' , 'jump' ) # 3 positional arguments parrot ( 'a thousand' , state = 'pushing up the daisies' ) # 1 positional, 1 keyword but all the following calls would be invalid: parrot () # required argument missing parrot ( voltage = 5.0 , 'dead' ) # non-keyword argument after a keyword argument parrot ( 110 , voltage = 220 ) # duplicate value for the same argument parrot ( actor = 'John Cleese' ) # unknown keyword argument In a function call, keyword arguments must follow positional arguments. All the keyword arguments passed must match one of the arguments accepted by the function (e.g. actor is not a valid argument for the parrot function), and their order is not important. This also includes non-optional arguments (e.g. parrot(voltage=1000) is valid too). No argument may receive a value more than once. Here’s an example that fails due to this restriction: >>> def function ( a ): ... pass ... >>> function ( 0 , a = 0 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : function() got multiple values for argument 'a' When a final formal parameter of the form **name is present, it receives a dictionary (see Mapping Types — dict ) containing all keyword arguments except for those corresponding to a formal parameter. This may be combined with a formal parameter of the form *name (described in the next subsection) which receives a tuple containing the positional arguments beyond the formal parameter list. ( *name must occur before **name .) For example, if we define a function like this: def cheeseshop ( kind , * arguments , ** keywords ): print ( "-- Do you have any" , kind , "?" ) print ( "-- I'm sorry, we're all out of" , kind ) for arg in arguments : print ( arg ) print ( "-" * 40 ) for kw in keywords : print ( kw , ":" , keywords [ kw ]) It could be called like this: cheeseshop ( "Limburger" , "It's very runny, sir." , "It's really very, VERY runny, sir." , shopkeeper = "Michael Palin" , client = "John Cleese" , sketch = "Cheese Shop Sketch" ) and of course it would print: -- Do you have any Limburger ? -- I'm sorry, we're all out of Limburger It's very runny, sir. It's really very, VERY runny, sir. ---------------------------------------- shopkeeper : Michael Palin client : John Cleese sketch : Cheese Shop Sketch Note that the order in which the keyword arguments are printed is guaranteed to match the order in which they were provided in the function call. 4.9.3. Special parameters ¶ By default, arguments may be passed to a Python function either by position or explicitly by keyword. For readability and performance, it makes sense to restrict the way arguments can be passed so that a developer need only look at the function definition to determine if items are passed by position, by position or keyword, or by keyword. A function definition may look like: def f(pos1, pos2, /, pos_or_kwd, *, kwd1, kwd2): ----------- ---------- ---------- | | | | Positional or keyword | | - Keyword only -- Positional only where / and * are optional. If used, these symbols indicate the kind of parameter by how the arguments may be passed to the function: positional-only, positional-or-keyword, and keyword-only. Keyword parameters are also referred to as named parameters. 4.9.3.1. Positional-or-Keyword Arguments ¶ If / and * are not present in the function definition, arguments may be passed to a function by position or by keyword. 4.9.3.2. Positional-Only Parameters ¶ Looking at this in a bit more detail, it is possible to mark certain parameters as positional-only . If positional-only , the parameters’ order matters, and the parameters cannot be passed by keyword. Positional-only parameters are placed before a / (forward-slash). The / is used to logically separate the positional-only parameters from the rest of the parameters. If there is no / in the function definition, there are no positional-only parameters. Parameters following the / may be positional-or-keyword or keyword-only . 4.9.3.3. Keyword-Only Arguments ¶ To mark parameters as keyword-only , indicating the parameters must be passed by keyword argument, place an * in the arguments list just before the first keyword-only parameter. 4.9.3.4. Function Examples ¶ Consider the following example function definitions paying close attention to the markers / and * : >>> def standard_arg ( arg ): ... print ( arg ) ... >>> def pos_only_arg ( arg , / ): ... print ( arg ) ... >>> def kwd_only_arg ( * , arg ): ... print ( arg ) ... >>> def combined_example ( pos_only , / , standard , * , kwd_only ): ... print ( pos_only , standard , kwd_only ) The first function definition, standard_arg , the most familiar form, places no restrictions on the calling convention and arguments may be passed by position or keyword: >>> standard_arg ( 2 ) 2 >>> standard_arg ( arg = 2 ) 2 The second function pos_only_arg is restricted to only use positional parameters as there is a / in the function definition: >>> pos_only_arg ( 1 ) 1 >>> pos_only_arg ( arg = 1 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : pos_only_arg() got some positional-only arguments passed as keyword arguments: 'arg' The third function kwd_only_arg only allows keyword arguments as indicated by a * in the function definition: >>> kwd_only_arg ( 3 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : kwd_only_arg() takes 0 positional arguments but 1 was given >>> kwd_only_arg ( arg = 3 ) 3 And the last uses all three calling conventions in the same function definition: >>> combined_example ( 1 , 2 , 3 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : combined_example() takes 2 positional arguments but 3 were given >>> combined_example ( 1 , 2 , kwd_only = 3 ) 1 2 3 >>> combined_example ( 1 , standard = 2 , kwd_only = 3 ) 1 2 3 >>> combined_example ( pos_only = 1 , standard = 2 , kwd_only = 3 ) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : combined_example() got some positional-only arguments passed as keyword arguments: 'pos_only' Finally, consider this function definition which has a potential collision between the positional argument name and **kwds which has name as a key: def foo ( name , ** kwds ): return 'name' in kwds There is no possible call that will make it return True as the keyword 'name' will always bind to the first parameter. For example: >>> foo ( 1 , ** { 'name' : 2 }) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> TypeError : foo() got multiple values for argument 'name' >>> But using / (positional only arguments), it is possible since it allows name as a positional argument and 'name' as a key in the keyword arguments: >>> def foo ( name , / , ** kwds ): ... return 'name' in kwds ... >>> foo ( 1 , ** { 'name' : 2 }) True In other words, the names of positional-only parameters can be used in **kwds without ambiguity. 4.9.3.5. Recap ¶ The use case will determine which parameters to use in the function definition: def f ( pos1 , pos2 , / , pos_or_kwd , * , kwd1 , kwd2 ): As guidance: Use positional-only if you want the name of the parameters to not be available to the user. This is useful when parameter names have no real meaning, if you want to enforce the order of the arguments when the function is called or if you need to take some positional parameters and arbitrary keywords. Use keyword-only when names have meaning and the function definition is more understandable by being explicit with names or you want to prevent users relying on the position of the argument being passed. For an API, use positional-only to prevent breaking API changes if the parameter’s name is modified in the future. 4.9.4. Arbitrary Argument Lists ¶ Finally, the least frequently used option is to specify that a function can be called with an arbitrary number of arguments. These arguments will be wrapped up in a tuple (see Tuples and Sequences ). Before the variable number of arguments, zero or more normal arguments may occur. def write_multiple_items ( file , separator , * args ): file . write ( separator . join ( args )) Normally, these variadic arguments will be last in the list of formal parameters, because they scoop up all remaining input arguments that are passed to the function. Any formal parameters which occur after the *args parameter are ‘keyword-only’ arguments, meaning that they can only be used as keywords rather than positional arguments. >>> def concat ( * args , sep = "/" ): ... return sep . join ( args ) ... >>> concat ( "earth" , "mars" , "venus" ) 'earth/mars/venus' >>> concat ( "earth" , "mars" , "venus" , sep = "." ) 'earth.mars.venus' 4.9.5. Unpacking Argument Lists ¶ The reverse situation occurs when the arguments are already in a list or tuple but need to be unpacked for a function call requiring separate positional arguments. For instance, the built-in range() function expects separate start and stop arguments. If they are not available separately, write the function call with the * -operator to unpack the arguments out of a list or tuple: >>> list ( range ( 3 , 6 )) # normal call with separate arguments [3, 4, 5] >>> args = [ 3 , 6 ] >>> list ( range ( * args )) # call with arguments unpacked from a list [3, 4, 5] In the same fashion, dictionaries can deliver keyword arguments with the ** -operator: >>> def parrot ( voltage , state = 'a stiff' , action = 'voom' ): ... print ( "-- This parrot wouldn't" , action , end = ' ' ) ... print ( "if you put" , voltage , "volts through it." , end = ' ' ) ... print ( "E's" , state , "!" ) ... >>> d = { "voltage" : "four million" , "state" : "bleedin' demised" , "action" : "VOOM" } >>> parrot ( ** d ) -- This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised ! 4.9.6. Lambda Expressions ¶ Small anonymous functions can be created with the lambda keyword. This function returns the sum of its two arguments: lambda a, b: a+b . Lambda functions can be used wherever function objects are required. They are syntactically restricted to a single expression. Semantically, they are just syntactic sugar for a normal function definition. Like nested function definitions, lambda functions can reference variables from the containing scope: >>> def make_incrementor ( n ): ... return lambda x : x + n ... >>> f = make_incrementor ( 42 ) >>> f ( 0 ) 42 >>> f ( 1 ) 43 The above example uses a lambda expression to return a function. Another use is to pass a small function as an argument. For instance, list.sort() takes a sorting key function key which can be a lambda function: >>> pairs = [( 1 , 'one' ), ( 2 , 'two' ), ( 3 , 'three' ), ( 4 , 'four' )] >>> pairs . sort ( key = lambda pair : pair [ 1 ]) >>> pairs [(4, 'four'), (1, 'one'), (3, 'three'), (2, 'two')] 4.9.7. Documentation Strings ¶ Here are some conventions about the content and formatting of documentation strings. The first line should always be a short, concise summary of the object’s purpose. For brevity, it should not explicitly state the object’s name or type, since these are available by other means (except if the name happens to be a verb describing a function’s operation). This line should begin with a capital letter and end with a period. If there are more lines in the documentation string, the second line should be blank, visually separating the summary from the rest of the description. The following lines should be one or more paragraphs describing the object’s calling conventions, its side effects, etc. The Python parser strips indentation from multi-line string literals when they serve as module, class, or function docstrings. Here is an example of a multi-line docstring: >>> def my_function (): ... """Do nothing, but document it. ... ... No, really, it doesn't do anything: ... ... >>> my_function() ... >>> ... """ ... pass ... >>> print ( my_function . __doc__ ) Do nothing, but document it. No, really, it doesn't do anything: >>> my_function() >>> 4.9.8. Function Annotations ¶ Function annotations are completely optional metadata information about the types used by user-defined functions (see PEP 3107 and PEP 484 for more information). Annotations are stored in the __annotations__ attribute of the function as a dictionary and have no effect on any other part of the function. Parameter annotations are defined by a colon after the parameter name, followed by an expression evaluating to the value of the annotation. Return annotations are defined by a literal -> , followed by an expression, between the parameter list and the colon denoting the end of the def statement. The following example has a required argument, an optional argument, and the return value annotated: >>> def f ( ham : str , eggs : str = 'eggs' ) -> str : ... print ( "Annotations:" , f . __annotations__ ) ... print ( "Arguments:" , ham , eggs ) ... return ham + ' and ' + eggs ... >>> f ( 'spam' ) Annotations: {'ham': <class 'str'>, 'return': <class 'str'>, 'eggs': <class 'str'>} Arguments: spam eggs 'spam and eggs' 4.10. Intermezzo: Coding Style ¶ Now that you are about to write longer, more complex pieces of Python, it is a good time to talk about coding style . Most languages can be written (or more concise, formatted ) in different styles; some are more readable than others. Making it easy for others to read your code is always a good idea, and adopting a nice coding style helps tremendously for that. For Python, PEP 8 has emerged as the style guide that most projects adhere to; it promotes a very readable and eye-pleasing coding style. Every Python developer should read it at some point; here are the most important points extracted for you: Use 4-space indentation, and no tabs. 4 spaces are a good compromise between small indentation (allows greater nesting depth) and large indentation (easier to read). Tabs introduce confusion, and are best left out. Wrap lines so that they don’t exceed 79 characters. This helps users with small displays and makes it possible to have several code files side-by-side on larger displays. Use blank lines to separate functions and classes, and larger blocks of code inside functions. When possible, put comments on a line of their own. Use docstrings. Use spaces around operators and after commas, but not directly inside bracketing constructs: a = f(1, 2) + g(3, 4) . Name your classes and functions consistently; the convention is to use UpperCamelCase for classes and lowercase_with_underscores for functions and methods. Always use self as the name for the first method argument (see A First Look at Classes for more on classes and methods). Don’t use fancy encodings if your code is meant to be used in international environments. Python’s default, UTF-8, or even plain ASCII work best in any case. Likewise, don’t use non-ASCII characters in identifiers if there is only the slightest chance people speaking a different language will read or maintain the code. Footnotes [ 1 ] Actually, call by object reference would be a better description, since if a mutable object is passed, the caller will see any changes the callee makes to it (items inserted into a list). Table of Contents 4. More Control Flow Tools 4.1. if Statements 4.2. for Statements 4.3. The range() Function 4.4. break and continue Statements 4.5. else Clauses on Loops 4.6. pass Statements 4.7. match Statements 4.8. Defining Functions 4.9. More on Defining Functions 4.9.1. Default Argument Values 4.9.2. Keyword Arguments 4.9.3. Special parameters 4.9.3.1. Positional-or-Keyword Arguments 4.9.3.2. Positional-Only Parameters 4.9.3.3. Keyword-Only Arguments 4.9.3.4. Function Examples 4.9.3.5. Recap 4.9.4. Arbitrary Argument Lists 4.9.5. Unpacking Argument Lists 4.9.6. Lambda Expressions 4.9.7. Documentation Strings 4.9.8. Function Annotations 4.10. Intermezzo: Coding Style Previous topic 3. An Informal Introduction to Python Next topic 5. Data Structures This page Report a bug Show source « Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Tutorial » 4. More Control Flow Tools | Theme Auto Light Dark | © Copyright 2001 Python Software Foundation. This page is licensed under the Python Software Foundation License Version 2. Examples, recipes, and other code in the documentation are additionally licensed under the Zero Clause BSD License. See History and License for more information. The Python Software Foundation is a non-profit corporation. Please donate. 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https://docs.python.org/3/library/functions.html#print | Built-in Functions — Python 3.14.2 documentation Theme Auto Light Dark Previous topic Introduction Next topic Built-in Constants This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Standard Library » Built-in Functions | Theme Auto Light Dark | Built-in Functions ¶ The Python interpreter has a number of functions and types built into it that are always available. They are listed here in alphabetical order. Built-in Functions A abs() aiter() all() anext() any() ascii() B bin() bool() breakpoint() bytearray() bytes() C callable() chr() classmethod() compile() complex() D delattr() dict() dir() divmod() E enumerate() eval() exec() F filter() float() format() frozenset() G getattr() globals() H hasattr() hash() help() hex() I id() input() int() isinstance() issubclass() iter() L len() list() locals() M map() max() memoryview() min() N next() O object() oct() open() ord() P pow() print() property() R range() repr() reversed() round() S set() setattr() slice() sorted() staticmethod() str() sum() super() T tuple() type() V vars() Z zip() _ __import__() abs ( number , / ) ¶ Return the absolute value of a number. The argument may be an integer, a floating-point number, or an object implementing __abs__() . If the argument is a complex number, its magnitude is returned. aiter ( async_iterable , / ) ¶ Return an asynchronous iterator for an asynchronous iterable . Equivalent to calling x.__aiter__() . Note: Unlike iter() , aiter() has no 2-argument variant. Added in version 3.10. all ( iterable , / ) ¶ Return True if all elements of the iterable are true (or if the iterable is empty). Equivalent to: def all ( iterable ): for element in iterable : if not element : return False return True awaitable anext ( async_iterator , / ) ¶ awaitable anext ( async_iterator , default , / ) When awaited, return the next item from the given asynchronous iterator , or default if given and the iterator is exhausted. This is the async variant of the next() builtin, and behaves similarly. This calls the __anext__() method of async_iterator , returning an awaitable . Awaiting this returns the next value of the iterator. If default is given, it is returned if the iterator is exhausted, otherwise StopAsyncIteration is raised. Added in version 3.10. any ( iterable , / ) ¶ Return True if any element of the iterable is true. If the iterable is empty, return False . Equivalent to: def any ( iterable ): for element in iterable : if element : return True return False ascii ( object , / ) ¶ As repr() , return a string containing a printable representation of an object, but escape the non-ASCII characters in the string returned by repr() using \x , \u , or \U escapes. This generates a string similar to that returned by repr() in Python 2. bin ( integer , / ) ¶ Convert an integer number to a binary string prefixed with “0b”. The result is a valid Python expression. If integer is not a Python int object, it has to define an __index__() method that returns an integer. Some examples: >>> bin ( 3 ) '0b11' >>> bin ( - 10 ) '-0b1010' If the prefix “0b” is desired or not, you can use either of the following ways. >>> format ( 14 , '#b' ), format ( 14 , 'b' ) ('0b1110', '1110') >>> f ' { 14 : #b } ' , f ' { 14 : b } ' ('0b1110', '1110') See also enum.bin() to represent negative values as twos-complement. See also format() for more information. class bool ( object = False , / ) ¶ Return a Boolean value, i.e. one of True or False . The argument is converted using the standard truth testing procedure . If the argument is false or omitted, this returns False ; otherwise, it returns True . The bool class is a subclass of int (see Numeric Types — int, float, complex ). It cannot be subclassed further. Its only instances are False and True (see Boolean Type - bool ). Changed in version 3.7: The parameter is now positional-only. breakpoint ( * args , ** kws ) ¶ This function drops you into the debugger at the call site. Specifically, it calls sys.breakpointhook() , passing args and kws straight through. By default, sys.breakpointhook() calls pdb.set_trace() expecting no arguments. In this case, it is purely a convenience function so you don’t have to explicitly import pdb or type as much code to enter the debugger. However, sys.breakpointhook() can be set to some other function and breakpoint() will automatically call that, allowing you to drop into the debugger of choice. If sys.breakpointhook() is not accessible, this function will raise RuntimeError . By default, the behavior of breakpoint() can be changed with the PYTHONBREAKPOINT environment variable. See sys.breakpointhook() for usage details. Note that this is not guaranteed if sys.breakpointhook() has been replaced. Raises an auditing event builtins.breakpoint with argument breakpointhook . Added in version 3.7. class bytearray ( source = b'' ) class bytearray ( source , encoding , errors = 'strict' ) Return a new array of bytes. The bytearray class is a mutable sequence of integers in the range 0 <= x < 256. It has most of the usual methods of mutable sequences, described in Mutable Sequence Types , as well as most methods that the bytes type has, see Bytes and Bytearray Operations . The optional source parameter can be used to initialize the array in a few different ways: If it is a string , you must also give the encoding (and optionally, errors ) parameters; bytearray() then converts the string to bytes using str.encode() . If it is an integer , the array will have that size and will be initialized with null bytes. If it is an object conforming to the buffer interface , a read-only buffer of the object will be used to initialize the bytes array. If it is an iterable , it must be an iterable of integers in the range 0 <= x < 256 , which are used as the initial contents of the array. Without an argument, an array of size 0 is created. See also Binary Sequence Types — bytes, bytearray, memoryview and Bytearray Objects . class bytes ( source = b'' ) class bytes ( source , encoding , errors = 'strict' ) Return a new “bytes” object which is an immutable sequence of integers in the range 0 <= x < 256 . bytes is an immutable version of bytearray – it has the same non-mutating methods and the same indexing and slicing behavior. Accordingly, constructor arguments are interpreted as for bytearray() . Bytes objects can also be created with literals, see String and Bytes literals . See also Binary Sequence Types — bytes, bytearray, memoryview , Bytes Objects , and Bytes and Bytearray Operations . callable ( object , / ) ¶ Return True if the object argument appears callable, False if not. If this returns True , it is still possible that a call fails, but if it is False , calling object will never succeed. Note that classes are callable (calling a class returns a new instance); instances are callable if their class has a __call__() method. Added in version 3.2: This function was first removed in Python 3.0 and then brought back in Python 3.2. chr ( codepoint , / ) ¶ Return the string representing a character with the specified Unicode code point. For example, chr(97) returns the string 'a' , while chr(8364) returns the string '€' . This is the inverse of ord() . The valid range for the argument is from 0 through 1,114,111 (0x10FFFF in base 16). ValueError will be raised if it is outside that range. @ classmethod ¶ Transform a method into a class method. A class method receives the class as an implicit first argument, just like an instance method receives the instance. To declare a class method, use this idiom: class C : @classmethod def f ( cls , arg1 , arg2 ): ... The @classmethod form is a function decorator – see Function definitions for details. A class method can be called either on the class (such as C.f() ) or on an instance (such as C().f() ). The instance is ignored except for its class. If a class method is called for a derived class, the derived class object is passed as the implied first argument. Class methods are different than C++ or Java static methods. If you want those, see staticmethod() in this section. For more information on class methods, see The standard type hierarchy . Changed in version 3.9: Class methods can now wrap other descriptors such as property() . Changed in version 3.10: Class methods now inherit the method attributes ( __module__ , __name__ , __qualname__ , __doc__ and __annotations__ ) and have a new __wrapped__ attribute. Deprecated since version 3.11, removed in version 3.13: Class methods can no longer wrap other descriptors such as property() . compile ( source , filename , mode , flags = 0 , dont_inherit = False , optimize = -1 ) ¶ Compile the source into a code or AST object. Code objects can be executed by exec() or eval() . source can either be a normal string, a byte string, or an AST object. Refer to the ast module documentation for information on how to work with AST objects. The filename argument should give the file from which the code was read; pass some recognizable value if it wasn’t read from a file ( '<string>' is commonly used). The mode argument specifies what kind of code must be compiled; it can be 'exec' if source consists of a sequence of statements, 'eval' if it consists of a single expression, or 'single' if it consists of a single interactive statement (in the latter case, expression statements that evaluate to something other than None will be printed). The optional arguments flags and dont_inherit control which compiler options should be activated and which future features should be allowed. If neither is present (or both are zero) the code is compiled with the same flags that affect the code that is calling compile() . If the flags argument is given and dont_inherit is not (or is zero) then the compiler options and the future statements specified by the flags argument are used in addition to those that would be used anyway. If dont_inherit is a non-zero integer then the flags argument is it – the flags (future features and compiler options) in the surrounding code are ignored. Compiler options and future statements are specified by bits which can be bitwise ORed together to specify multiple options. The bitfield required to specify a given future feature can be found as the compiler_flag attribute on the _Feature instance in the __future__ module. Compiler flags can be found in ast module, with PyCF_ prefix. The argument optimize specifies the optimization level of the compiler; the default value of -1 selects the optimization level of the interpreter as given by -O options. Explicit levels are 0 (no optimization; __debug__ is true), 1 (asserts are removed, __debug__ is false) or 2 (docstrings are removed too). This function raises SyntaxError or ValueError if the compiled source is invalid. If you want to parse Python code into its AST representation, see ast.parse() . Raises an auditing event compile with arguments source and filename . This event may also be raised by implicit compilation. Note When compiling a string with multi-line code in 'single' or 'eval' mode, input must be terminated by at least one newline character. This is to facilitate detection of incomplete and complete statements in the code module. Warning It is possible to crash the Python interpreter with a sufficiently large/complex string when compiling to an AST object due to stack depth limitations in Python’s AST compiler. Changed in version 3.2: Allowed use of Windows and Mac newlines. Also, input in 'exec' mode does not have to end in a newline anymore. Added the optimize parameter. Changed in version 3.5: Previously, TypeError was raised when null bytes were encountered in source . Added in version 3.8: ast.PyCF_ALLOW_TOP_LEVEL_AWAIT can now be passed in flags to enable support for top-level await , async for , and async with . class complex ( number = 0 , / ) ¶ class complex ( string , / ) class complex ( real = 0 , imag = 0 ) Convert a single string or number to a complex number, or create a complex number from real and imaginary parts. Examples: >>> complex ( '+1.23' ) (1.23+0j) >>> complex ( '-4.5j' ) -4.5j >>> complex ( '-1.23+4.5j' ) (-1.23+4.5j) >>> complex ( ' \t ( -1.23+4.5J ) \n ' ) (-1.23+4.5j) >>> complex ( '-Infinity+NaNj' ) (-inf+nanj) >>> complex ( 1.23 ) (1.23+0j) >>> complex ( imag =- 4.5 ) -4.5j >>> complex ( - 1.23 , 4.5 ) (-1.23+4.5j) If the argument is a string, it must contain either a real part (in the same format as for float() ) or an imaginary part (in the same format but with a 'j' or 'J' suffix), or both real and imaginary parts (the sign of the imaginary part is mandatory in this case). The string can optionally be surrounded by whitespaces and the round parentheses '(' and ')' , which are ignored. The string must not contain whitespace between '+' , '-' , the 'j' or 'J' suffix, and the decimal number. For example, complex('1+2j') is fine, but complex('1 + 2j') raises ValueError . More precisely, the input must conform to the complexvalue production rule in the following grammar, after parentheses and leading and trailing whitespace characters are removed: complexvalue : floatvalue | floatvalue ( "j" | "J" ) | floatvalue sign absfloatvalue ( "j" | "J" ) If the argument is a number, the constructor serves as a numeric conversion like int and float . For a general Python object x , complex(x) delegates to x.__complex__() . If __complex__() is not defined then it falls back to __float__() . If __float__() is not defined then it falls back to __index__() . If two arguments are provided or keyword arguments are used, each argument may be any numeric type (including complex). If both arguments are real numbers, return a complex number with the real component real and the imaginary component imag . If both arguments are complex numbers, return a complex number with the real component real.real-imag.imag and the imaginary component real.imag+imag.real . If one of arguments is a real number, only its real component is used in the above expressions. See also complex.from_number() which only accepts a single numeric argument. If all arguments are omitted, returns 0j . The complex type is described in Numeric Types — int, float, complex . Changed in version 3.6: Grouping digits with underscores as in code literals is allowed. Changed in version 3.8: Falls back to __index__() if __complex__() and __float__() are not defined. Deprecated since version 3.14: Passing a complex number as the real or imag argument is now deprecated; it should only be passed as a single positional argument. delattr ( object , name , / ) ¶ This is a relative of setattr() . The arguments are an object and a string. The string must be the name of one of the object’s attributes. The function deletes the named attribute, provided the object allows it. For example, delattr(x, 'foobar') is equivalent to del x.foobar . name need not be a Python identifier (see setattr() ). class dict ( ** kwargs ) class dict ( mapping , / , ** kwargs ) class dict ( iterable , / , ** kwargs ) Create a new dictionary. The dict object is the dictionary class. See dict and Mapping Types — dict for documentation about this class. For other containers see the built-in list , set , and tuple classes, as well as the collections module. dir ( ) ¶ dir ( object , / ) Without arguments, return the list of names in the current local scope. With an argument, attempt to return a list of valid attributes for that object. If the object has a method named __dir__() , this method will be called and must return the list of attributes. This allows objects that implement a custom __getattr__() or __getattribute__() function to customize the way dir() reports their attributes. If the object does not provide __dir__() , the function tries its best to gather information from the object’s __dict__ attribute, if defined, and from its type object. The resulting list is not necessarily complete and may be inaccurate when the object has a custom __getattr__() . The default dir() mechanism behaves differently with different types of objects, as it attempts to produce the most relevant, rather than complete, information: If the object is a module object, the list contains the names of the module’s attributes. If the object is a type or class object, the list contains the names of its attributes, and recursively of the attributes of its bases. Otherwise, the list contains the object’s attributes’ names, the names of its class’s attributes, and recursively of the attributes of its class’s base classes. The resulting list is sorted alphabetically. For example: >>> import struct >>> dir () # show the names in the module namespace ['__builtins__', '__name__', 'struct'] >>> dir ( struct ) # show the names in the struct module ['Struct', '__all__', '__builtins__', '__cached__', '__doc__', '__file__', '__initializing__', '__loader__', '__name__', '__package__', '_clearcache', 'calcsize', 'error', 'pack', 'pack_into', 'unpack', 'unpack_from'] >>> class Shape : ... def __dir__ ( self ): ... return [ 'area' , 'perimeter' , 'location' ] ... >>> s = Shape () >>> dir ( s ) ['area', 'location', 'perimeter'] Note Because dir() is supplied primarily as a convenience for use at an interactive prompt, it tries to supply an interesting set of names more than it tries to supply a rigorously or consistently defined set of names, and its detailed behavior may change across releases. For example, metaclass attributes are not in the result list when the argument is a class. divmod ( a , b , / ) ¶ Take two (non-complex) numbers as arguments and return a pair of numbers consisting of their quotient and remainder when using integer division. With mixed operand types, the rules for binary arithmetic operators apply. For integers, the result is the same as (a // b, a % b) . For floating-point numbers the result is (q, a % b) , where q is usually math.floor(a / b) but may be 1 less than that. In any case q * b + a % b is very close to a , if a % b is non-zero it has the same sign as b , and 0 <= abs(a % b) < abs(b) . enumerate ( iterable , start = 0 ) ¶ Return an enumerate object. iterable must be a sequence, an iterator , or some other object which supports iteration. The __next__() method of the iterator returned by enumerate() returns a tuple containing a count (from start which defaults to 0) and the values obtained from iterating over iterable . >>> seasons = [ 'Spring' , 'Summer' , 'Fall' , 'Winter' ] >>> list ( enumerate ( seasons )) [(0, 'Spring'), (1, 'Summer'), (2, 'Fall'), (3, 'Winter')] >>> list ( enumerate ( seasons , start = 1 )) [(1, 'Spring'), (2, 'Summer'), (3, 'Fall'), (4, 'Winter')] Equivalent to: def enumerate ( iterable , start = 0 ): n = start for elem in iterable : yield n , elem n += 1 eval ( source , / , globals = None , locals = None ) ¶ Parameters : source ( str | code object ) – A Python expression. globals ( dict | None ) – The global namespace (default: None ). locals ( mapping | None ) – The local namespace (default: None ). Returns : The result of the evaluated expression. Raises : Syntax errors are reported as exceptions. Warning This function executes arbitrary code. Calling it with user-supplied input may lead to security vulnerabilities. The source argument is parsed and evaluated as a Python expression (technically speaking, a condition list) using the globals and locals mappings as global and local namespace. If the globals dictionary is present and does not contain a value for the key __builtins__ , a reference to the dictionary of the built-in module builtins is inserted under that key before source is parsed. That way you can control what builtins are available to the executed code by inserting your own __builtins__ dictionary into globals before passing it to eval() . If the locals mapping is omitted it defaults to the globals dictionary. If both mappings are omitted, the source is executed with the globals and locals in the environment where eval() is called. Note, eval() will only have access to the nested scopes (non-locals) in the enclosing environment if they are already referenced in the scope that is calling eval() (e.g. via a nonlocal statement). Example: >>> x = 1 >>> eval ( 'x+1' ) 2 This function can also be used to execute arbitrary code objects (such as those created by compile() ). In this case, pass a code object instead of a string. If the code object has been compiled with 'exec' as the mode argument, eval() 's return value will be None . Hints: dynamic execution of statements is supported by the exec() function. The globals() and locals() functions return the current global and local dictionary, respectively, which may be useful to pass around for use by eval() or exec() . If the given source is a string, then leading and trailing spaces and tabs are stripped. See ast.literal_eval() for a function that can safely evaluate strings with expressions containing only literals. Raises an auditing event exec with the code object as the argument. Code compilation events may also be raised. Changed in version 3.13: The globals and locals arguments can now be passed as keywords. Changed in version 3.13: The semantics of the default locals namespace have been adjusted as described for the locals() builtin. exec ( source , / , globals = None , locals = None , * , closure = None ) ¶ Warning This function executes arbitrary code. Calling it with user-supplied input may lead to security vulnerabilities. This function supports dynamic execution of Python code. source must be either a string or a code object. If it is a string, the string is parsed as a suite of Python statements which is then executed (unless a syntax error occurs). [ 1 ] If it is a code object, it is simply executed. In all cases, the code that’s executed is expected to be valid as file input (see the section File input in the Reference Manual). Be aware that the nonlocal , yield , and return statements may not be used outside of function definitions even within the context of code passed to the exec() function. The return value is None . In all cases, if the optional parts are omitted, the code is executed in the current scope. If only globals is provided, it must be a dictionary (and not a subclass of dictionary), which will be used for both the global and the local variables. If globals and locals are given, they are used for the global and local variables, respectively. If provided, locals can be any mapping object. Remember that at the module level, globals and locals are the same dictionary. Note When exec gets two separate objects as globals and locals , the code will be executed as if it were embedded in a class definition. This means functions and classes defined in the executed code will not be able to access variables assigned at the top level (as the “top level” variables are treated as class variables in a class definition). If the globals dictionary does not contain a value for the key __builtins__ , a reference to the dictionary of the built-in module builtins is inserted under that key. That way you can control what builtins are available to the executed code by inserting your own __builtins__ dictionary into globals before passing it to exec() . The closure argument specifies a closure–a tuple of cellvars. It’s only valid when the object is a code object containing free (closure) variables . The length of the tuple must exactly match the length of the code object’s co_freevars attribute. Raises an auditing event exec with the code object as the argument. Code compilation events may also be raised. Note The built-in functions globals() and locals() return the current global and local namespace, respectively, which may be useful to pass around for use as the second and third argument to exec() . Note The default locals act as described for function locals() below. Pass an explicit locals dictionary if you need to see effects of the code on locals after function exec() returns. Changed in version 3.11: Added the closure parameter. Changed in version 3.13: The globals and locals arguments can now be passed as keywords. Changed in version 3.13: The semantics of the default locals namespace have been adjusted as described for the locals() builtin. filter ( function , iterable , / ) ¶ Construct an iterator from those elements of iterable for which function is true. iterable may be either a sequence, a container which supports iteration, or an iterator. If function is None , the identity function is assumed, that is, all elements of iterable that are false are removed. Note that filter(function, iterable) is equivalent to the generator expression (item for item in iterable if function(item)) if function is not None and (item for item in iterable if item) if function is None . See itertools.filterfalse() for the complementary function that returns elements of iterable for which function is false. class float ( number = 0.0 , / ) ¶ class float ( string , / ) Return a floating-point number constructed from a number or a string. Examples: >>> float ( '+1.23' ) 1.23 >>> float ( ' -12345 \n ' ) -12345.0 >>> float ( '1e-003' ) 0.001 >>> float ( '+1E6' ) 1000000.0 >>> float ( '-Infinity' ) -inf If the argument is a string, it should contain a decimal number, optionally preceded by a sign, and optionally embedded in whitespace. The optional sign may be '+' or '-' ; a '+' sign has no effect on the value produced. The argument may also be a string representing a NaN (not-a-number), or positive or negative infinity. More precisely, the input must conform to the floatvalue production rule in the following grammar, after leading and trailing whitespace characters are removed: sign : "+" | "-" infinity : "Infinity" | "inf" nan : "nan" digit : <a Unicode decimal digit, i.e. characters in Unicode general category Nd> digitpart : digit ([ "_" ] digit )* number : [ digitpart ] "." digitpart | digitpart [ "." ] exponent : ( "e" | "E" ) [ sign ] digitpart floatnumber : number [ exponent ] absfloatvalue : floatnumber | infinity | nan floatvalue : [ sign ] absfloatvalue Case is not significant, so, for example, “inf”, “Inf”, “INFINITY”, and “iNfINity” are all acceptable spellings for positive infinity. Otherwise, if the argument is an integer or a floating-point number, a floating-point number with the same value (within Python’s floating-point precision) is returned. If the argument is outside the range of a Python float, an OverflowError will be raised. For a general Python object x , float(x) delegates to x.__float__() . If __float__() is not defined then it falls back to __index__() . See also float.from_number() which only accepts a numeric argument. If no argument is given, 0.0 is returned. The float type is described in Numeric Types — int, float, complex . Changed in version 3.6: Grouping digits with underscores as in code literals is allowed. Changed in version 3.7: The parameter is now positional-only. Changed in version 3.8: Falls back to __index__() if __float__() is not defined. format ( value , format_spec = '' , / ) ¶ Convert a value to a “formatted” representation, as controlled by format_spec . The interpretation of format_spec will depend on the type of the value argument; however, there is a standard formatting syntax that is used by most built-in types: Format Specification Mini-Language . The default format_spec is an empty string which usually gives the same effect as calling str(value) . A call to format(value, format_spec) is translated to type(value).__format__(value, format_spec) which bypasses the instance dictionary when searching for the value’s __format__() method. A TypeError exception is raised if the method search reaches object and the format_spec is non-empty, or if either the format_spec or the return value are not strings. Changed in version 3.4: object().__format__(format_spec) raises TypeError if format_spec is not an empty string. class frozenset ( iterable = () , / ) Return a new frozenset object, optionally with elements taken from iterable . frozenset is a built-in class. See frozenset and Set Types — set, frozenset for documentation about this class. For other containers see the built-in set , list , tuple , and dict classes, as well as the collections module. getattr ( object , name , / ) ¶ getattr ( object , name , default , / ) Return the value of the named attribute of object . name must be a string. If the string is the name of one of the object’s attributes, the result is the value of that attribute. For example, getattr(x, 'foobar') is equivalent to x.foobar . If the named attribute does not exist, default is returned if provided, otherwise AttributeError is raised. name need not be a Python identifier (see setattr() ). Note Since private name mangling happens at compilation time, one must manually mangle a private attribute’s (attributes with two leading underscores) name in order to retrieve it with getattr() . globals ( ) ¶ Return the dictionary implementing the current module namespace. For code within functions, this is set when the function is defined and remains the same regardless of where the function is called. hasattr ( object , name , / ) ¶ The arguments are an object and a string. The result is True if the string is the name of one of the object’s attributes, False if not. (This is implemented by calling getattr(object, name) and seeing whether it raises an AttributeError or not.) hash ( object , / ) ¶ Return the hash value of the object (if it has one). Hash values are integers. They are used to quickly compare dictionary keys during a dictionary lookup. Numeric values that compare equal have the same hash value (even if they are of different types, as is the case for 1 and 1.0). Note For objects with custom __hash__() methods, note that hash() truncates the return value based on the bit width of the host machine. help ( ) ¶ help ( request ) Invoke the built-in help system. (This function is intended for interactive use.) If no argument is given, the interactive help system starts on the interpreter console. If the argument is a string, then the string is looked up as the name of a module, function, class, method, keyword, or documentation topic, and a help page is printed on the console. If the argument is any other kind of object, a help page on the object is generated. Note that if a slash(/) appears in the parameter list of a function when invoking help() , it means that the parameters prior to the slash are positional-only. For more info, see the FAQ entry on positional-only parameters . This function is added to the built-in namespace by the site module. Changed in version 3.4: Changes to pydoc and inspect mean that the reported signatures for callables are now more comprehensive and consistent. hex ( integer , / ) ¶ Convert an integer number to a lowercase hexadecimal string prefixed with “0x”. If integer is not a Python int object, it has to define an __index__() method that returns an integer. Some examples: >>> hex ( 255 ) '0xff' >>> hex ( - 42 ) '-0x2a' If you want to convert an integer number to an uppercase or lower hexadecimal string with prefix or not, you can use either of the following ways: >>> ' %#x ' % 255 , ' %x ' % 255 , ' %X ' % 255 ('0xff', 'ff', 'FF') >>> format ( 255 , '#x' ), format ( 255 , 'x' ), format ( 255 , 'X' ) ('0xff', 'ff', 'FF') >>> f ' { 255 : #x } ' , f ' { 255 : x } ' , f ' { 255 : X } ' ('0xff', 'ff', 'FF') See also format() for more information. See also int() for converting a hexadecimal string to an integer using a base of 16. Note To obtain a hexadecimal string representation for a float, use the float.hex() method. id ( object , / ) ¶ Return the “identity” of an object. This is an integer which is guaranteed to be unique and constant for this object during its lifetime. Two objects with non-overlapping lifetimes may have the same id() value. CPython implementation detail: This is the address of the object in memory. Raises an auditing event builtins.id with argument id . input ( ) ¶ input ( prompt , / ) If the prompt argument is present, it is written to standard output without a trailing newline. The function then reads a line from input, converts it to a string (stripping a trailing newline), and returns that. When EOF is read, EOFError is raised. Example: >>> s = input ( '--> ' ) --> Monty Python's Flying Circus >>> s "Monty Python's Flying Circus" If the readline module was loaded, then input() will use it to provide elaborate line editing and history features. Raises an auditing event builtins.input with argument prompt before reading input Raises an auditing event builtins.input/result with the result after successfully reading input. class int ( number = 0 , / ) ¶ class int ( string , / , base = 10 ) Return an integer object constructed from a number or a string, or return 0 if no arguments are given. Examples: >>> int ( 123.45 ) 123 >>> int ( '123' ) 123 >>> int ( ' -12_345 \n ' ) -12345 >>> int ( 'FACE' , 16 ) 64206 >>> int ( '0xface' , 0 ) 64206 >>> int ( '01110011' , base = 2 ) 115 If the argument defines __int__() , int(x) returns x.__int__() . If the argument defines __index__() , it returns x.__index__() . For floating-point numbers, this truncates towards zero. If the argument is not a number or if base is given, then it must be a string, bytes , or bytearray instance representing an integer in radix base . Optionally, the string can be preceded by + or - (with no space in between), have leading zeros, be surrounded by whitespace, and have single underscores interspersed between digits. A base-n integer string contains digits, each representing a value from 0 to n-1. The values 0–9 can be represented by any Unicode decimal digit. The values 10–35 can be represented by a to z (or A to Z ). The default base is 10. The allowed bases are 0 and 2–36. Base-2, -8, and -16 strings can be optionally prefixed with 0b / 0B , 0o / 0O , or 0x / 0X , as with integer literals in code. For base 0, the string is interpreted in a similar way to an integer literal in code , in that the actual base is 2, 8, 10, or 16 as determined by the prefix. Base 0 also disallows leading zeros: int('010', 0) is not legal, while int('010') and int('010', 8) are. The integer type is described in Numeric Types — int, float, complex . Changed in version 3.4: If base is not an instance of int and the base object has a base.__index__ method, that method is called to obtain an integer for the base. Previous versions used base.__int__ instead of base.__index__ . Changed in version 3.6: Grouping digits with underscores as in code literals is allowed. Changed in version 3.7: The first parameter is now positional-only. Changed in version 3.8: Falls back to __index__() if __int__() is not defined. Changed in version 3.11: int string inputs and string representations can be limited to help avoid denial of service attacks. A ValueError is raised when the limit is exceeded while converting a string to an int or when converting an int into a string would exceed the limit. See the integer string conversion length limitation documentation. Changed in version 3.14: int() no longer delegates to the __trunc__() method. isinstance ( object , classinfo , / ) ¶ Return True if the object argument is an instance of the classinfo argument, or of a (direct, indirect, or virtual ) subclass thereof. If object is not an object of the given type, the function always returns False . If classinfo is a tuple of type objects (or recursively, other such tuples) or a Union Type of multiple types, return True if object is an instance of any of the types. If classinfo is not a type or tuple of types and such tuples, a TypeError exception is raised. TypeError may not be raised for an invalid type if an earlier check succeeds. Changed in version 3.10: classinfo can be a Union Type . issubclass ( class , classinfo , / ) ¶ Return True if class is a subclass (direct, indirect, or virtual ) of classinfo . A class is considered a subclass of itself. classinfo may be a tuple of class objects (or recursively, other such tuples) or a Union Type , in which case return True if class is a subclass of any entry in classinfo . In any other case, a TypeError exception is raised. Changed in version 3.10: classinfo can be a Union Type . iter ( iterable , / ) ¶ iter ( callable , sentinel , / ) Return an iterator object. The first argument is interpreted very differently depending on the presence of the second argument. Without a second argument, the single argument must be a collection object which supports the iterable protocol (the __iter__() method), or it must support the sequence protocol (the __getitem__() method with integer arguments starting at 0 ). If it does not support either of those protocols, TypeError is raised. If the second argument, sentinel , is given, then the first argument must be a callable object. The iterator created in this case will call callable with no arguments for each call to its __next__() method; if the value returned is equal to sentinel , StopIteration will be raised, otherwise the value will be returned. See also Iterator Types . One useful application of the second form of iter() is to build a block-reader. For example, reading fixed-width blocks from a binary database file until the end of file is reached: from functools import partial with open ( 'mydata.db' , 'rb' ) as f : for block in iter ( partial ( f . read , 64 ), b '' ): process_block ( block ) len ( object , / ) ¶ Return the length (the number of items) of an object. The argument may be a sequence (such as a string, bytes, tuple, list, or range) or a collection (such as a dictionary, set, or frozen set). CPython implementation detail: len raises OverflowError on lengths larger than sys.maxsize , such as range(2 ** 100) . class list ( iterable = () , / ) Rather than being a function, list is actually a mutable sequence type, as documented in Lists and Sequence Types — list, tuple, range . locals ( ) ¶ Return a mapping object representing the current local symbol table, with variable names as the keys, and their currently bound references as the values. At module scope, as well as when using exec() or eval() with a single namespace, this function returns the same namespace as globals() . At class scope, it returns the namespace that will be passed to the metaclass constructor. When using exec() or eval() with separate local and global arguments, it returns the local namespace passed in to the function call. In all of the above cases, each call to locals() in a given frame of execution will return the same mapping object. Changes made through the mapping object returned from locals() will be visible as assigned, reassigned, or deleted local variables, and assigning, reassigning, or deleting local variables will immediately affect the contents of the returned mapping object. In an optimized scope (including functions, generators, and coroutines), each call to locals() instead returns a fresh dictionary containing the current bindings of the function’s local variables and any nonlocal cell references. In this case, name binding changes made via the returned dict are not written back to the corresponding local variables or nonlocal cell references, and assigning, reassigning, or deleting local variables and nonlocal cell references does not affect the contents of previously returned dictionaries. Calling locals() as part of a comprehension in a function, generator, or coroutine is equivalent to calling it in the containing scope, except that the comprehension’s initialised iteration variables will be included. In other scopes, it behaves as if the comprehension were running as a nested function. Calling locals() as part of a generator expression is equivalent to calling it in a nested generator function. Changed in version 3.12: The behaviour of locals() in a comprehension has been updated as described in PEP 709 . Changed in version 3.13: As part of PEP 667 , the semantics of mutating the mapping objects returned from this function are now defined. The behavior in optimized scopes is now as described above. Aside from being defined, the behaviour in other scopes remains unchanged from previous versions. map ( function , iterable , / , * iterables , strict = False ) ¶ Return an iterator that applies function to every item of iterable , yielding the results. If additional iterables arguments are passed, function must take that many arguments and is applied to the items from all iterables in parallel. With multiple iterables, the iterator stops when the shortest iterable is exhausted. If strict is True and one of the iterables is exhausted before the others, a ValueError is raised. For cases where the function inputs are already arranged into argument tuples, see itertools.starmap() . Changed in version 3.14: Added the strict parameter. max ( iterable , / , * , key = None ) ¶ max ( iterable , / , * , default , key = None ) max ( arg1 , arg2 , / , * args , key = None ) Return the largest item in an iterable or the largest of two or more arguments. If one positional argument is provided, it should be an iterable . The largest item in the iterable is returned. If two or more positional arguments are provided, the largest of the positional arguments is returned. There are two optional keyword-only arguments. The key argument specifies a one-argument ordering function like that used for list.sort() . The default argument specifies an object to return if the provided iterable is empty. If the iterable is empty and default is not provided, a ValueError is raised. If multiple items are maximal, the function returns the first one encountered. This is consistent with other sort-stability preserving tools such as sorted(iterable, key=keyfunc, reverse=True)[0] and heapq.nlargest(1, iterable, key=keyfunc) . Changed in version 3.4: Added the default keyword-only parameter. Changed in version 3.8: The key can be None . class memoryview ( object ) Return a “memory view” object created from the given argument. See Memory Views for more information. min ( iterable , / , * , key = None ) ¶ min ( iterable , / , * , default , key = None ) min ( arg1 , arg2 , / , * args , key = None ) Return the smallest item in an iterable or the smallest of two or more arguments. If one positional argument is provided, it should be an iterable . The smallest item in the iterable is returned. If two or more positional arguments are provided, the smallest of the positional arguments is returned. There are two optional keyword-only arguments. The key argument specifies a one-argument ordering function like that used for list.sort() . The default argument specifies an object to return if the provided iterable is empty. If the iterable is empty and default is not provided, a ValueError is raised. If multiple items are minimal, the function returns the first one encountered. This is consistent with other sort-stability preserving tools such as sorted(iterable, key=keyfunc)[0] and heapq.nsmallest(1, iterable, key=keyfunc) . Changed in version 3.4: Added the default keyword-only parameter. Changed in version 3.8: The key can be None . next ( iterator , / ) ¶ next ( iterator , default , / ) Retrieve the next item from the iterator by calling its __next__() method. If default is given, it is returned if the iterator is exhausted, otherwise StopIteration is raised. class object ¶ This is the ultimate base class of all other classes. It has methods that are common to all instances of Python classes. When the constructor is called, it returns a new featureless object. The constructor does not accept any arguments. Note object instances do not have __dict__ attributes, so you can’t assign arbitrary attributes to an instance of object . oct ( integer , / ) ¶ Convert an integer number to an octal string prefixed with “0o”. The result is a valid Python expression. If integer is not a Python int object, it has to define an __index__() method that returns an integer. For example: >>> oct ( 8 ) '0o10' >>> oct ( - 56 ) '-0o70' If you want to convert an integer number to an octal string either with the prefix “0o” or not, you can use either of the following ways. >>> ' %#o ' % 10 , ' %o ' % 10 ('0o12', '12') >>> format ( 10 , '#o' ), format ( 10 , 'o' ) ('0o12', '12') >>> f ' { 10 : #o } ' , f ' { 10 : o } ' ('0o12', '12') See also format() for more information. open ( file , mode = 'r' , buffering = -1 , encoding = None , errors = None , newline = None , closefd = True , opener = None ) ¶ Open file and return a corresponding file object . If the file cannot be opened, an OSError is raised. See Reading and Writing Files for more examples of how to use this function. file is a path-like object giving the pathname (absolute or relative to the current working directory) of the file to be opened or an integer file descriptor of the file to be wrapped. (If a file descriptor is given, it is closed when the returned I/O object is closed unless closefd is set to False .) mode is an optional string that specifies the mode in which the file is opened. It defaults to 'r' which means open for reading in text mode. Other common values are 'w' for writing (truncating the file if it already exists), 'x' for exclusive creation, and 'a' for appending (which on some Unix systems, means that all writes append to the end of the file regardless of the current seek position). In text mode, if encoding is not specified the encoding used is platform-dependent: locale.getencoding() is called to get the current locale encoding. (For reading and writing raw bytes use binary mode and leave encoding unspecified.) The available modes are: Character Meaning 'r' open for reading (default) 'w' open for writing, truncating the file first 'x' open for exclusive creation, failing if the file already exists 'a' open for writing, appending to the end of file if it exists 'b' binary mode 't' text mode (default) '+' open for updating (reading and writing) The default mode is 'r' (open for reading text, a synonym of 'rt' ). Modes 'w+' and 'w+b' open and truncate the file. Modes 'r+' and 'r+b' open the file with no truncation. As mentioned in the Overview , Python distinguishes between binary and text I/O. Files opened in binary mode (including 'b' in the mode argument) return contents as bytes objects without any decoding. In text mode (the default, or when 't' is included in the mode argument), the contents of the file are returned as str , the bytes having been first decoded using a platform-dependent encoding or using the specified encoding if given. Note Python doesn’t depend on the underlying operating system’s notion of text files; all the processing is done by Python itself, and is therefore platform-independent. buffering is an optional integer used to set the buffering policy. Pass 0 to switch buffering off (only allowed in binary mode), 1 to select line buffering (only usable when writing in text mode), and an integer > 1 to indicate the size in bytes of a fixed-size chunk buffer. Note that specifying a buffer size this way applies for binary buffered I/O, but TextIOWrapper (i.e., files opened with mode='r+' ) would have another buffering. To disable buffering in TextIOWrapper , consider using the write_through flag for io.TextIOWrapper.reconfigure() . When no buffering argument is given, the default buffering policy works as follows: Binary files are buffered in fixed-size chunks; the size of the buffer is max(min(blocksize, 8 MiB), DEFAULT_BUFFER_SIZE) when the device block size is available. On most systems, the buffer will typically be 128 kilobytes long. “Interactive” text files (files for which isatty() returns True ) use line buffering. Other text files use the policy described above for binary files. encoding is the name of the encoding used to decode or encode the file. This should only be used in text mode. The default encoding is platform dependent (whatever locale.getencoding() returns), but any text encoding supported by Python can be used. See the codecs module for the list of supported encodings. errors is an optional string that specifies how encoding and decoding errors are to be handled—this cannot be used in binary mode. A variety of standard error handlers are available (listed under Error Handlers ), though any error handling name that has | 2026-01-13T08:48:45 |
https://www.iana.org/dnssec/ceremonies | Root KSK Ceremonies Domains Protocols Numbers About Key Signing Ceremonies Ceremonies are usually conducted four times a year to perform operations using the Root Key Signing Key, and involving Trusted Community Representatives . In a typical ceremony, the KSK is used to sign a set of operational ZSKs that will be used for a three month period to sign the DNS root zone. Other operations that may occur during ceremonies include installing new cryptographic officers, replacing hardware, or generating or replacing a KSK. Ceremonies Date Ceremony Agenda 2026-04-30 KSK Ceremony 61 Sign 2026Q3 ZSKs 2026-02-11 KSK Ceremony 60 Sign 2026Q2 ZSKs 2025-11-13 KSK Ceremony 59 Sign 2026Q1 ZSKs; Replace CO4 (East); Introduce BHSM3E 2025-07-16 KSK Ceremony 58 Sign 2025Q4 ZSKs 2025-04-24 KSK Ceremony 57 Sign 2025Q3 ZSKs 2025-02-12 KSK Ceremony 56 Sign 2025Q2 ZSKs; Replace CO3 & CO4 (West) 2024-10-17 KSK Ceremony 55 Sign 2025Q1 ZSKs; Replace CO1 (East) 2024-07-17 KSK Ceremony 54 Sign 2024Q4 ZSKs; Introduce Successor HSMs; Import KSK-2024 2024-04-26 KSK Ceremony 53-2 Introduce Successor HSMs; Generate KSK-2024 2024-04-25 KSK Ceremony 53-1 Sign 2024Q3 ZSKs; Replace RKSHs 1 & 6; Reissue RKSH Cards 2024-02-14 KSK Ceremony 52 Sign 2024Q2 ZSKs; Introduce HSM8W 2023-11-30 KSK Ceremony 51 Sign 2024Q1 ZSKs; Replace CO5 (East); Introduce HSM7E & HSM8E 2023-07-19 KSK Ceremony 50 Sign 2023Q4 ZSKs; Import KSK-2023 2023-04-27 KSK Ceremony 49 Sign 2023Q3 ZSKs; Generate KSK-2023; Replace CO6 (East) 2023-02-01 KSK Ceremony 48 Sign 2023Q2 ZSKs; Reissue CO Cards; Replace CO2 (West); Introduce HSM7W 2022-11-03 KSK Ceremony 47 Sign 2023Q1 ZSKs; Replace CO2 & CO7 (East) 2022-08-17 KSK Ceremony 46 Sign 2022Q4 ZSKs; Replace CO6 (West); Destroy HSMs 3&4 (West) 2022-05-12 KSK Ceremony 45 Sign 2022Q3 ZSKs; Reissue CO Cards; Replace 2 TCRs; Destroy HSM4 (East) 2022-02-16 KSK Ceremony 44 Sign 2022Q2 ZSKs; Introduce HSM6W 2021-10-14 KSK Ceremony 43 Sign 2022Q1 ZSKs; Introduce HSM6E 2021-02-11 KSK Ceremony 42 Sign 2021Q2-2021Q4 ZSKs 2020-04-23 KSK Ceremony 41 Sign 2020Q3-2021Q1 ZSKs 2020-02-16 KSK Ceremony 40 Sign 2020Q2 ZSKs 2019-11-14 KSK Ceremony 39 Sign 2020Q1 ZSKs; Destroy HSM3 (East) 2019-08-14 KSK Ceremony 38 Sign 2019Q4 ZSKs; KSK Delete; Destroy HSMs 1&2; Introduce HSM5W 2019-05-16 KSK Ceremony 37 Sign 2019Q3 ZSKs; KSK Delete; Destroy HSMs 1&2; Introduce HSM5E 2019-02-27 KSK Ceremony 36 Sign 2019Q2 ZSKs 2018-11-15 KSK Ceremony 35 Sign 2019Q1 ZSKs 2018-08-15 KSK Ceremony 34 Sign 2018Q4 ZSKs 2018-04-11 KSK Ceremony 33 Sign 2018Q3 ZSKs 2018-02-07 KSK Ceremony 32 Sign 2018Q2 ZSKs; Destruction Test HSM1 (West) 2017-10-18 KSK Ceremony 31 Sign 2018Q1 ZSKs; Replace RKSH 3 2017-08-17 KSK Ceremony 30 Sign 2017Q4 ZSKs 2017-04-27 KSK Ceremony 29 Sign 2017Q3 ZSKs 2017-02-02 KSK Ceremony 28 Sign 2017Q2 ZSKs; Import KSK-2017 2016-10-27 KSK Ceremony 27 Sign 2017Q1 ZSKs; Generate KSK-2017; Zeroize HSMs 1&2 (East) 2016-08-11 KSK Ceremony 26 Sign 2016Q4 ZSKs; Zeroize HSMs 1&2 (West) 2016-05-12 KSK Ceremony 25 Sign 2016Q3 ZSKs 2016-02-11 KSK Ceremony 24 Sign 2016Q2 ZSKs; Replace CO6 (West) 2015-11-12 KSK Ceremony 23 Sign 2016Q1 ZSKs 2015-08-13 KSK Ceremony 22 Sign 2015Q4 ZSKs; Introduce HSMs 3&4 (West); Replace CO1 (West) 2015-04-09 KSK Ceremony 21 Sign 2015Q3 ZSKs; Introduce HSMs 3&4 (East) 2015-01-22 KSK Ceremony 20 Sign 2015Q2 ZSKs 2014-11-20 KSK Ceremony 19 Sign 2015Q1 ZSKs 2014-08-14 KSK Ceremony 18 Sign 2014Q4 ZSKs; Replace CO5 (West) 2014-04-17 KSK Ceremony 17 Sign 2014Q3 ZSKs 2014-02-13 KSK Ceremony 16 Sign 2014Q2 ZSKs 2013-10-24 KSK Ceremony 15 Sign 2014Q1 ZSKs 2013-08-07 KSK Ceremony 14 Sign 2013Q4 ZSKs 2013-05-02 KSK Ceremony 13 Sign 2013Q3 ZSKs; Replace CO5 (East) 2013-02-12 KSK Ceremony 12 Sign 2013Q2 ZSKs 2012-11-12 KSK Ceremony 11 Sign 2013Q1 ZSKs 2012-07-26 KSK Ceremony 10 Sign 2012Q4 ZSKs 2012-05-22 KSK Ceremony 9 Sign 2012Q3 ZSKs 2012-02-02 KSK Ceremony 8 Sign 2012Q2 ZSKs 2011-09-30 KSK Ceremony 7 Sign 2012Q1 ZSKs 2011-07-20 KSK Ceremony 6 Sign 2011Q4 ZSKs 2011-05-11 KSK Ceremony 5 Sign 2011Q3 ZSKs 2011-02-07 KSK Ceremony 4 Sign 2011Q2 ZSKs 2010-11-01 KSK Ceremony 3 Sign 2011Q1 ZSKs 2010-07-12 KSK Ceremony 2 Instantiate El Segundo KMF; Import KSK-2010; Sign 2010Q4 ZSKs 2010-06-16 KSK Ceremony 1 Instantiate Culpeper KMF; Generate KSK-2010; Sign 2010Q3 ZSKs Domain Names Overview Root Zone Management Overview Root Database Hint and Zone Files Change Requests Instructions & Guides Root Servers .INT Registry Overview Register/modify an .INT domain Eligibility .ARPA Registry IDN Practices Repository Overview Tables --> Submit a table Root Key Signing Key (DNSSEC) Overview Trust Anchors and Rollovers Key Signing Ceremonies Policies & Procedures Community Representatives Reserved Domains Domain Names Root Zone Registry .INT Registry .ARPA Registry IDN Repository Number Resources Abuse Information Protocols Protocol Registries Time Zone Database About Us News Performance Excellence Archive Contact Us The IANA functions coordinate the Internet’s globally unique identifiers, and are provided by Public Technical Identifiers , an affiliate of ICANN . 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https://docs.python.org/3/reference/compound_stmts.html#else | 8. Compound statements — Python 3.14.2 documentation Theme Auto Light Dark Table of Contents 8. Compound statements 8.1. The if statement 8.2. The while statement 8.3. The for statement 8.4. The try statement 8.4.1. except clause 8.4.2. except* clause 8.4.3. else clause 8.4.4. finally clause 8.5. The with statement 8.6. The match statement 8.6.1. Overview 8.6.2. Guards 8.6.3. Irrefutable Case Blocks 8.6.4. Patterns 8.6.4.1. OR Patterns 8.6.4.2. AS Patterns 8.6.4.3. Literal Patterns 8.6.4.4. Capture Patterns 8.6.4.5. Wildcard Patterns 8.6.4.6. Value Patterns 8.6.4.7. Group Patterns 8.6.4.8. Sequence Patterns 8.6.4.9. Mapping Patterns 8.6.4.10. Class Patterns 8.7. Function definitions 8.8. Class definitions 8.9. Coroutines 8.9.1. Coroutine function definition 8.9.2. The async for statement 8.9.3. The async with statement 8.10. Type parameter lists 8.10.1. Generic functions 8.10.2. Generic classes 8.10.3. Generic type aliases 8.11. Annotations Previous topic 7. Simple statements Next topic 9. Top-level components This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Language Reference » 8. Compound statements | Theme Auto Light Dark | 8. Compound statements ¶ Compound statements contain (groups of) other statements; they affect or control the execution of those other statements in some way. In general, compound statements span multiple lines, although in simple incarnations a whole compound statement may be contained in one line. The if , while and for statements implement traditional control flow constructs. try specifies exception handlers and/or cleanup code for a group of statements, while the with statement allows the execution of initialization and finalization code around a block of code. Function and class definitions are also syntactically compound statements. A compound statement consists of one or more ‘clauses.’ A clause consists of a header and a ‘suite.’ The clause headers of a particular compound statement are all at the same indentation level. Each clause header begins with a uniquely identifying keyword and ends with a colon. A suite is a group of statements controlled by a clause. A suite can be one or more semicolon-separated simple statements on the same line as the header, following the header’s colon, or it can be one or more indented statements on subsequent lines. Only the latter form of a suite can contain nested compound statements; the following is illegal, mostly because it wouldn’t be clear to which if clause a following else clause would belong: if test1 : if test2 : print ( x ) Also note that the semicolon binds tighter than the colon in this context, so that in the following example, either all or none of the print() calls are executed: if x < y < z : print ( x ); print ( y ); print ( z ) Summarizing: compound_stmt : if_stmt | while_stmt | for_stmt | try_stmt | with_stmt | match_stmt | funcdef | classdef | async_with_stmt | async_for_stmt | async_funcdef suite : stmt_list NEWLINE | NEWLINE INDENT statement + DEDENT statement : stmt_list NEWLINE | compound_stmt stmt_list : simple_stmt ( ";" simple_stmt )* [ ";" ] Note that statements always end in a NEWLINE possibly followed by a DEDENT . Also note that optional continuation clauses always begin with a keyword that cannot start a statement, thus there are no ambiguities (the ‘dangling else ’ problem is solved in Python by requiring nested if statements to be indented). The formatting of the grammar rules in the following sections places each clause on a separate line for clarity. 8.1. The if statement ¶ The if statement is used for conditional execution: if_stmt : "if" assignment_expression ":" suite ( "elif" assignment_expression ":" suite )* [ "else" ":" suite ] It selects exactly one of the suites by evaluating the expressions one by one until one is found to be true (see section Boolean operations for the definition of true and false); then that suite is executed (and no other part of the if statement is executed or evaluated). If all expressions are false, the suite of the else clause, if present, is executed. 8.2. The while statement ¶ The while statement is used for repeated execution as long as an expression is true: while_stmt : "while" assignment_expression ":" suite [ "else" ":" suite ] This repeatedly tests the expression and, if it is true, executes the first suite; if the expression is false (which may be the first time it is tested) the suite of the else clause, if present, is executed and the loop terminates. A break statement executed in the first suite terminates the loop without executing the else clause’s suite. A continue statement executed in the first suite skips the rest of the suite and goes back to testing the expression. 8.3. The for statement ¶ The for statement is used to iterate over the elements of a sequence (such as a string, tuple or list) or other iterable object: for_stmt : "for" target_list "in" starred_expression_list ":" suite [ "else" ":" suite ] The starred_expression_list expression is evaluated once; it should yield an iterable object. An iterator is created for that iterable. The first item provided by the iterator is then assigned to the target list using the standard rules for assignments (see Assignment statements ), and the suite is executed. This repeats for each item provided by the iterator. When the iterator is exhausted, the suite in the else clause, if present, is executed, and the loop terminates. A break statement executed in the first suite terminates the loop without executing the else clause’s suite. A continue statement executed in the first suite skips the rest of the suite and continues with the next item, or with the else clause if there is no next item. The for-loop makes assignments to the variables in the target list. This overwrites all previous assignments to those variables including those made in the suite of the for-loop: for i in range ( 10 ): print ( i ) i = 5 # this will not affect the for-loop # because i will be overwritten with the next # index in the range Names in the target list are not deleted when the loop is finished, but if the sequence is empty, they will not have been assigned to at all by the loop. Hint: the built-in type range() represents immutable arithmetic sequences of integers. For instance, iterating range(3) successively yields 0, 1, and then 2. Changed in version 3.11: Starred elements are now allowed in the expression list. 8.4. The try statement ¶ The try statement specifies exception handlers and/or cleanup code for a group of statements: try_stmt : try1_stmt | try2_stmt | try3_stmt try1_stmt : "try" ":" suite ( "except" [ expression [ "as" identifier ]] ":" suite )+ [ "else" ":" suite ] [ "finally" ":" suite ] try2_stmt : "try" ":" suite ( "except" "*" expression [ "as" identifier ] ":" suite )+ [ "else" ":" suite ] [ "finally" ":" suite ] try3_stmt : "try" ":" suite "finally" ":" suite Additional information on exceptions can be found in section Exceptions , and information on using the raise statement to generate exceptions may be found in section The raise statement . Changed in version 3.14: Support for optionally dropping grouping parentheses when using multiple exception types. See PEP 758 . 8.4.1. except clause ¶ The except clause(s) specify one or more exception handlers. When no exception occurs in the try clause, no exception handler is executed. When an exception occurs in the try suite, a search for an exception handler is started. This search inspects the except clauses in turn until one is found that matches the exception. An expression-less except clause, if present, must be last; it matches any exception. For an except clause with an expression, the expression must evaluate to an exception type or a tuple of exception types. Parentheses can be dropped if multiple exception types are provided and the as clause is not used. The raised exception matches an except clause whose expression evaluates to the class or a non-virtual base class of the exception object, or to a tuple that contains such a class. If no except clause matches the exception, the search for an exception handler continues in the surrounding code and on the invocation stack. [ 1 ] If the evaluation of an expression in the header of an except clause raises an exception, the original search for a handler is canceled and a search starts for the new exception in the surrounding code and on the call stack (it is treated as if the entire try statement raised the exception). When a matching except clause is found, the exception is assigned to the target specified after the as keyword in that except clause, if present, and the except clause’s suite is executed. All except clauses must have an executable block. When the end of this block is reached, execution continues normally after the entire try statement. (This means that if two nested handlers exist for the same exception, and the exception occurs in the try clause of the inner handler, the outer handler will not handle the exception.) When an exception has been assigned using as target , it is cleared at the end of the except clause. This is as if except E as N : foo was translated to except E as N : try : foo finally : del N This means the exception must be assigned to a different name to be able to refer to it after the except clause. Exceptions are cleared because with the traceback attached to them, they form a reference cycle with the stack frame, keeping all locals in that frame alive until the next garbage collection occurs. Before an except clause’s suite is executed, the exception is stored in the sys module, where it can be accessed from within the body of the except clause by calling sys.exception() . When leaving an exception handler, the exception stored in the sys module is reset to its previous value: >>> print ( sys . exception ()) None >>> try : ... raise TypeError ... except : ... print ( repr ( sys . exception ())) ... try : ... raise ValueError ... except : ... print ( repr ( sys . exception ())) ... print ( repr ( sys . exception ())) ... TypeError() ValueError() TypeError() >>> print ( sys . exception ()) None 8.4.2. except* clause ¶ The except* clause(s) specify one or more handlers for groups of exceptions ( BaseExceptionGroup instances). A try statement can have either except or except* clauses, but not both. The exception type for matching is mandatory in the case of except* , so except*: is a syntax error. The type is interpreted as in the case of except , but matching is performed on the exceptions contained in the group that is being handled. An TypeError is raised if a matching type is a subclass of BaseExceptionGroup , because that would have ambiguous semantics. When an exception group is raised in the try block, each except* clause splits (see split() ) it into the subgroups of matching and non-matching exceptions. If the matching subgroup is not empty, it becomes the handled exception (the value returned from sys.exception() ) and assigned to the target of the except* clause (if there is one). Then, the body of the except* clause executes. If the non-matching subgroup is not empty, it is processed by the next except* in the same manner. This continues until all exceptions in the group have been matched, or the last except* clause has run. After all except* clauses execute, the group of unhandled exceptions is merged with any exceptions that were raised or re-raised from within except* clauses. This merged exception group propagates on.: >>> try : ... raise ExceptionGroup ( "eg" , ... [ ValueError ( 1 ), TypeError ( 2 ), OSError ( 3 ), OSError ( 4 )]) ... except * TypeError as e : ... print ( f 'caught { type ( e ) } with nested { e . exceptions } ' ) ... except * OSError as e : ... print ( f 'caught { type ( e ) } with nested { e . exceptions } ' ) ... caught <class 'ExceptionGroup'> with nested (TypeError(2),) caught <class 'ExceptionGroup'> with nested (OSError(3), OSError(4)) + Exception Group Traceback (most recent call last): | File "<doctest default[0]>", line 2, in <module> | raise ExceptionGroup("eg", | [ValueError(1), TypeError(2), OSError(3), OSError(4)]) | ExceptionGroup: eg (1 sub-exception) +-+---------------- 1 ---------------- | ValueError: 1 +------------------------------------ If the exception raised from the try block is not an exception group and its type matches one of the except* clauses, it is caught and wrapped by an exception group with an empty message string. This ensures that the type of the target e is consistently BaseExceptionGroup : >>> try : ... raise BlockingIOError ... except * BlockingIOError as e : ... print ( repr ( e )) ... ExceptionGroup('', (BlockingIOError(),)) break , continue and return cannot appear in an except* clause. 8.4.3. else clause ¶ The optional else clause is executed if the control flow leaves the try suite, no exception was raised, and no return , continue , or break statement was executed. Exceptions in the else clause are not handled by the preceding except clauses. 8.4.4. finally clause ¶ If finally is present, it specifies a ‘cleanup’ handler. The try clause is executed, including any except and else clauses. If an exception occurs in any of the clauses and is not handled, the exception is temporarily saved. The finally clause is executed. If there is a saved exception it is re-raised at the end of the finally clause. If the finally clause raises another exception, the saved exception is set as the context of the new exception. If the finally clause executes a return , break or continue statement, the saved exception is discarded. For example, this function returns 42. def f (): try : 1 / 0 finally : return 42 The exception information is not available to the program during execution of the finally clause. When a return , break or continue statement is executed in the try suite of a try … finally statement, the finally clause is also executed ‘on the way out.’ The return value of a function is determined by the last return statement executed. Since the finally clause always executes, a return statement executed in the finally clause will always be the last one executed. The following function returns ‘finally’. def foo (): try : return 'try' finally : return 'finally' Changed in version 3.8: Prior to Python 3.8, a continue statement was illegal in the finally clause due to a problem with the implementation. Changed in version 3.14: The compiler emits a SyntaxWarning when a return , break or continue appears in a finally block (see PEP 765 ). 8.5. The with statement ¶ The with statement is used to wrap the execution of a block with methods defined by a context manager (see section With Statement Context Managers ). This allows common try … except … finally usage patterns to be encapsulated for convenient reuse. with_stmt : "with" ( "(" with_stmt_contents "," ? ")" | with_stmt_contents ) ":" suite with_stmt_contents : with_item ( "," with_item )* with_item : expression [ "as" target ] The execution of the with statement with one “item” proceeds as follows: The context expression (the expression given in the with_item ) is evaluated to obtain a context manager. The context manager’s __enter__() is loaded for later use. The context manager’s __exit__() is loaded for later use. The context manager’s __enter__() method is invoked. If a target was included in the with statement, the return value from __enter__() is assigned to it. Note The with statement guarantees that if the __enter__() method returns without an error, then __exit__() will always be called. Thus, if an error occurs during the assignment to the target list, it will be treated the same as an error occurring within the suite would be. See step 7 below. The suite is executed. The context manager’s __exit__() method is invoked. If an exception caused the suite to be exited, its type, value, and traceback are passed as arguments to __exit__() . Otherwise, three None arguments are supplied. If the suite was exited due to an exception, and the return value from the __exit__() method was false, the exception is reraised. If the return value was true, the exception is suppressed, and execution continues with the statement following the with statement. If the suite was exited for any reason other than an exception, the return value from __exit__() is ignored, and execution proceeds at the normal location for the kind of exit that was taken. The following code: with EXPRESSION as TARGET : SUITE is semantically equivalent to: manager = ( EXPRESSION ) enter = type ( manager ) . __enter__ exit = type ( manager ) . __exit__ value = enter ( manager ) hit_except = False try : TARGET = value SUITE except : hit_except = True if not exit ( manager , * sys . exc_info ()): raise finally : if not hit_except : exit ( manager , None , None , None ) With more than one item, the context managers are processed as if multiple with statements were nested: with A () as a , B () as b : SUITE is semantically equivalent to: with A () as a : with B () as b : SUITE You can also write multi-item context managers in multiple lines if the items are surrounded by parentheses. For example: with ( A () as a , B () as b , ): SUITE Changed in version 3.1: Support for multiple context expressions. Changed in version 3.10: Support for using grouping parentheses to break the statement in multiple lines. See also PEP 343 - The “with” statement The specification, background, and examples for the Python with statement. 8.6. The match statement ¶ Added in version 3.10. The match statement is used for pattern matching. Syntax: match_stmt : 'match' subject_expr ":" NEWLINE INDENT case_block + DEDENT subject_expr : `!star_named_expression` "," `!star_named_expressions`? | `!named_expression` case_block : 'case' patterns [ guard ] ":" `!block` Note This section uses single quotes to denote soft keywords . Pattern matching takes a pattern as input (following case ) and a subject value (following match ). The pattern (which may contain subpatterns) is matched against the subject value. The outcomes are: A match success or failure (also termed a pattern success or failure). Possible binding of matched values to a name. The prerequisites for this are further discussed below. The match and case keywords are soft keywords . See also PEP 634 – Structural Pattern Matching: Specification PEP 636 – Structural Pattern Matching: Tutorial 8.6.1. Overview ¶ Here’s an overview of the logical flow of a match statement: The subject expression subject_expr is evaluated and a resulting subject value obtained. If the subject expression contains a comma, a tuple is constructed using the standard rules . Each pattern in a case_block is attempted to match with the subject value. The specific rules for success or failure are described below. The match attempt can also bind some or all of the standalone names within the pattern. The precise pattern binding rules vary per pattern type and are specified below. Name bindings made during a successful pattern match outlive the executed block and can be used after the match statement . Note During failed pattern matches, some subpatterns may succeed. Do not rely on bindings being made for a failed match. Conversely, do not rely on variables remaining unchanged after a failed match. The exact behavior is dependent on implementation and may vary. This is an intentional decision made to allow different implementations to add optimizations. If the pattern succeeds, the corresponding guard (if present) is evaluated. In this case all name bindings are guaranteed to have happened. If the guard evaluates as true or is missing, the block inside case_block is executed. Otherwise, the next case_block is attempted as described above. If there are no further case blocks, the match statement is completed. Note Users should generally never rely on a pattern being evaluated. Depending on implementation, the interpreter may cache values or use other optimizations which skip repeated evaluations. A sample match statement: >>> flag = False >>> match ( 100 , 200 ): ... case ( 100 , 300 ): # Mismatch: 200 != 300 ... print ( 'Case 1' ) ... case ( 100 , 200 ) if flag : # Successful match, but guard fails ... print ( 'Case 2' ) ... case ( 100 , y ): # Matches and binds y to 200 ... print ( f 'Case 3, y: { y } ' ) ... case _ : # Pattern not attempted ... print ( 'Case 4, I match anything!' ) ... Case 3, y: 200 In this case, if flag is a guard. Read more about that in the next section. 8.6.2. Guards ¶ guard : "if" `!named_expression` A guard (which is part of the case ) must succeed for code inside the case block to execute. It takes the form: if followed by an expression. The logical flow of a case block with a guard follows: Check that the pattern in the case block succeeded. If the pattern failed, the guard is not evaluated and the next case block is checked. If the pattern succeeded, evaluate the guard . If the guard condition evaluates as true, the case block is selected. If the guard condition evaluates as false, the case block is not selected. If the guard raises an exception during evaluation, the exception bubbles up. Guards are allowed to have side effects as they are expressions. Guard evaluation must proceed from the first to the last case block, one at a time, skipping case blocks whose pattern(s) don’t all succeed. (I.e., guard evaluation must happen in order.) Guard evaluation must stop once a case block is selected. 8.6.3. Irrefutable Case Blocks ¶ An irrefutable case block is a match-all case block. A match statement may have at most one irrefutable case block, and it must be last. A case block is considered irrefutable if it has no guard and its pattern is irrefutable. A pattern is considered irrefutable if we can prove from its syntax alone that it will always succeed. Only the following patterns are irrefutable: AS Patterns whose left-hand side is irrefutable OR Patterns containing at least one irrefutable pattern Capture Patterns Wildcard Patterns parenthesized irrefutable patterns 8.6.4. Patterns ¶ Note This section uses grammar notations beyond standard EBNF: the notation SEP.RULE+ is shorthand for RULE (SEP RULE)* the notation !RULE is shorthand for a negative lookahead assertion The top-level syntax for patterns is: patterns : open_sequence_pattern | pattern pattern : as_pattern | or_pattern closed_pattern : | literal_pattern | capture_pattern | wildcard_pattern | value_pattern | group_pattern | sequence_pattern | mapping_pattern | class_pattern The descriptions below will include a description “in simple terms” of what a pattern does for illustration purposes (credits to Raymond Hettinger for a document that inspired most of the descriptions). Note that these descriptions are purely for illustration purposes and may not reflect the underlying implementation. Furthermore, they do not cover all valid forms. 8.6.4.1. OR Patterns ¶ An OR pattern is two or more patterns separated by vertical bars | . Syntax: or_pattern : "|" . closed_pattern + Only the final subpattern may be irrefutable , and each subpattern must bind the same set of names to avoid ambiguity. An OR pattern matches each of its subpatterns in turn to the subject value, until one succeeds. The OR pattern is then considered successful. Otherwise, if none of the subpatterns succeed, the OR pattern fails. In simple terms, P1 | P2 | ... will try to match P1 , if it fails it will try to match P2 , succeeding immediately if any succeeds, failing otherwise. 8.6.4.2. AS Patterns ¶ An AS pattern matches an OR pattern on the left of the as keyword against a subject. Syntax: as_pattern : or_pattern "as" capture_pattern If the OR pattern fails, the AS pattern fails. Otherwise, the AS pattern binds the subject to the name on the right of the as keyword and succeeds. capture_pattern cannot be a _ . In simple terms P as NAME will match with P , and on success it will set NAME = <subject> . 8.6.4.3. Literal Patterns ¶ A literal pattern corresponds to most literals in Python. Syntax: literal_pattern : signed_number | signed_number "+" NUMBER | signed_number "-" NUMBER | strings | "None" | "True" | "False" signed_number : [ "-" ] NUMBER The rule strings and the token NUMBER are defined in the standard Python grammar . Triple-quoted strings are supported. Raw strings and byte strings are supported. f-strings and t-strings are not supported. The forms signed_number '+' NUMBER and signed_number '-' NUMBER are for expressing complex numbers ; they require a real number on the left and an imaginary number on the right. E.g. 3 + 4j . In simple terms, LITERAL will succeed only if <subject> == LITERAL . For the singletons None , True and False , the is operator is used. 8.6.4.4. Capture Patterns ¶ A capture pattern binds the subject value to a name. Syntax: capture_pattern : ! '_' NAME A single underscore _ is not a capture pattern (this is what !'_' expresses). It is instead treated as a wildcard_pattern . In a given pattern, a given name can only be bound once. E.g. case x, x: ... is invalid while case [x] | x: ... is allowed. Capture patterns always succeed. The binding follows scoping rules established by the assignment expression operator in PEP 572 ; the name becomes a local variable in the closest containing function scope unless there’s an applicable global or nonlocal statement. In simple terms NAME will always succeed and it will set NAME = <subject> . 8.6.4.5. Wildcard Patterns ¶ A wildcard pattern always succeeds (matches anything) and binds no name. Syntax: wildcard_pattern : '_' _ is a soft keyword within any pattern, but only within patterns. It is an identifier, as usual, even within match subject expressions, guard s, and case blocks. In simple terms, _ will always succeed. 8.6.4.6. Value Patterns ¶ A value pattern represents a named value in Python. Syntax: value_pattern : attr attr : name_or_attr "." NAME name_or_attr : attr | NAME The dotted name in the pattern is looked up using standard Python name resolution rules . The pattern succeeds if the value found compares equal to the subject value (using the == equality operator). In simple terms NAME1.NAME2 will succeed only if <subject> == NAME1.NAME2 Note If the same value occurs multiple times in the same match statement, the interpreter may cache the first value found and reuse it rather than repeat the same lookup. This cache is strictly tied to a given execution of a given match statement. 8.6.4.7. Group Patterns ¶ A group pattern allows users to add parentheses around patterns to emphasize the intended grouping. Otherwise, it has no additional syntax. Syntax: group_pattern : "(" pattern ")" In simple terms (P) has the same effect as P . 8.6.4.8. Sequence Patterns ¶ A sequence pattern contains several subpatterns to be matched against sequence elements. The syntax is similar to the unpacking of a list or tuple. sequence_pattern : "[" [ maybe_sequence_pattern ] "]" | "(" [ open_sequence_pattern ] ")" open_sequence_pattern : maybe_star_pattern "," [ maybe_sequence_pattern ] maybe_sequence_pattern : "," . maybe_star_pattern + "," ? maybe_star_pattern : star_pattern | pattern star_pattern : "*" ( capture_pattern | wildcard_pattern ) There is no difference if parentheses or square brackets are used for sequence patterns (i.e. (...) vs [...] ). Note A single pattern enclosed in parentheses without a trailing comma (e.g. (3 | 4) ) is a group pattern . While a single pattern enclosed in square brackets (e.g. [3 | 4] ) is still a sequence pattern. At most one star subpattern may be in a sequence pattern. The star subpattern may occur in any position. If no star subpattern is present, the sequence pattern is a fixed-length sequence pattern; otherwise it is a variable-length sequence pattern. The following is the logical flow for matching a sequence pattern against a subject value: If the subject value is not a sequence [ 2 ] , the sequence pattern fails. If the subject value is an instance of str , bytes or bytearray the sequence pattern fails. The subsequent steps depend on whether the sequence pattern is fixed or variable-length. If the sequence pattern is fixed-length: If the length of the subject sequence is not equal to the number of subpatterns, the sequence pattern fails Subpatterns in the sequence pattern are matched to their corresponding items in the subject sequence from left to right. Matching stops as soon as a subpattern fails. If all subpatterns succeed in matching their corresponding item, the sequence pattern succeeds. Otherwise, if the sequence pattern is variable-length: If the length of the subject sequence is less than the number of non-star subpatterns, the sequence pattern fails. The leading non-star subpatterns are matched to their corresponding items as for fixed-length sequences. If the previous step succeeds, the star subpattern matches a list formed of the remaining subject items, excluding the remaining items corresponding to non-star subpatterns following the star subpattern. Remaining non-star subpatterns are matched to their corresponding subject items, as for a fixed-length sequence. Note The length of the subject sequence is obtained via len() (i.e. via the __len__() protocol). This length may be cached by the interpreter in a similar manner as value patterns . In simple terms [P1, P2, P3, … , P<N>] matches only if all the following happens: check <subject> is a sequence len(subject) == <N> P1 matches <subject>[0] (note that this match can also bind names) P2 matches <subject>[1] (note that this match can also bind names) … and so on for the corresponding pattern/element. 8.6.4.9. Mapping Patterns ¶ A mapping pattern contains one or more key-value patterns. The syntax is similar to the construction of a dictionary. Syntax: mapping_pattern : "{" [ items_pattern ] "}" items_pattern : "," . key_value_pattern + "," ? key_value_pattern : ( literal_pattern | value_pattern ) ":" pattern | double_star_pattern double_star_pattern : "**" capture_pattern At most one double star pattern may be in a mapping pattern. The double star pattern must be the last subpattern in the mapping pattern. Duplicate keys in mapping patterns are disallowed. Duplicate literal keys will raise a SyntaxError . Two keys that otherwise have the same value will raise a ValueError at runtime. The following is the logical flow for matching a mapping pattern against a subject value: If the subject value is not a mapping [ 3 ] ,the mapping pattern fails. If every key given in the mapping pattern is present in the subject mapping, and the pattern for each key matches the corresponding item of the subject mapping, the mapping pattern succeeds. If duplicate keys are detected in the mapping pattern, the pattern is considered invalid. A SyntaxError is raised for duplicate literal values; or a ValueError for named keys of the same value. Note Key-value pairs are matched using the two-argument form of the mapping subject’s get() method. Matched key-value pairs must already be present in the mapping, and not created on-the-fly via __missing__() or __getitem__() . In simple terms {KEY1: P1, KEY2: P2, ... } matches only if all the following happens: check <subject> is a mapping KEY1 in <subject> P1 matches <subject>[KEY1] … and so on for the corresponding KEY/pattern pair. 8.6.4.10. Class Patterns ¶ A class pattern represents a class and its positional and keyword arguments (if any). Syntax: class_pattern : name_or_attr "(" [ pattern_arguments "," ?] ")" pattern_arguments : positional_patterns [ "," keyword_patterns ] | keyword_patterns positional_patterns : "," . pattern + keyword_patterns : "," . keyword_pattern + keyword_pattern : NAME "=" pattern The same keyword should not be repeated in class patterns. The following is the logical flow for matching a class pattern against a subject value: If name_or_attr is not an instance of the builtin type , raise TypeError . If the subject value is not an instance of name_or_attr (tested via isinstance() ), the class pattern fails. If no pattern arguments are present, the pattern succeeds. Otherwise, the subsequent steps depend on whether keyword or positional argument patterns are present. For a number of built-in types (specified below), a single positional subpattern is accepted which will match the entire subject; for these types keyword patterns also work as for other types. If only keyword patterns are present, they are processed as follows, one by one: The keyword is looked up as an attribute on the subject. If this raises an exception other than AttributeError , the exception bubbles up. If this raises AttributeError , the class pattern has failed. Else, the subpattern associated with the keyword pattern is matched against the subject’s attribute value. If this fails, the class pattern fails; if this succeeds, the match proceeds to the next keyword. If all keyword patterns succeed, the class pattern succeeds. If any positional patterns are present, they are converted to keyword patterns using the __match_args__ attribute on the class name_or_attr before matching: The equivalent of getattr(cls, "__match_args__", ()) is called. If this raises an exception, the exception bubbles up. If the returned value is not a tuple, the conversion fails and TypeError is raised. If there are more positional patterns than len(cls.__match_args__) , TypeError is raised. Otherwise, positional pattern i is converted to a keyword pattern using __match_args__[i] as the keyword. __match_args__[i] must be a string; if not TypeError is raised. If there are duplicate keywords, TypeError is raised. See also Customizing positional arguments in class pattern matching Once all positional patterns have been converted to keyword patterns, the match proceeds as if there were only keyword patterns. For the following built-in types the handling of positional subpatterns is different: bool bytearray bytes dict float frozenset int list set str tuple These classes accept a single positional argument, and the pattern there is matched against the whole object rather than an attribute. For example int(0|1) matches the value 0 , but not the value 0.0 . In simple terms CLS(P1, attr=P2) matches only if the following happens: isinstance(<subject>, CLS) convert P1 to a keyword pattern using CLS.__match_args__ For each keyword argument attr=P2 : hasattr(<subject>, "attr") P2 matches <subject>.attr … and so on for the corresponding keyword argument/pattern pair. See also PEP 634 – Structural Pattern Matching: Specification PEP 636 – Structural Pattern Matching: Tutorial 8.7. Function definitions ¶ A function definition defines a user-defined function object (see section The standard type hierarchy ): funcdef : [ decorators ] "def" funcname [ type_params ] "(" [ parameter_list ] ")" [ "->" expression ] ":" suite decorators : decorator + decorator : "@" assignment_expression NEWLINE parameter_list : defparameter ( "," defparameter )* "," "/" [ "," [ parameter_list_no_posonly ]] | parameter_list_no_posonly parameter_list_no_posonly : defparameter ( "," defparameter )* [ "," [ parameter_list_starargs ]] | parameter_list_starargs parameter_list_starargs : "*" [ star_parameter ] ( "," defparameter )* [ "," [ parameter_star_kwargs ]] | "*" ( "," defparameter )+ [ "," [ parameter_star_kwargs ]] | parameter_star_kwargs parameter_star_kwargs : "**" parameter [ "," ] parameter : identifier [ ":" expression ] star_parameter : identifier [ ":" [ "*" ] expression ] defparameter : parameter [ "=" expression ] funcname : identifier A function definition is an executable statement. Its execution binds the function name in the current local namespace to a function object (a wrapper around the executable code for the function). This function object contains a reference to the current global namespace as the global namespace to be used when the function is called. The function definition does not execute the function body; this gets executed only when the function is called. [ 4 ] A function definition may be wrapped by one or more decorator expressions. Decorator expressions are evaluated when the function is defined, in the scope that contains the function definition. The result must be a callable, which is invoked with the function object as the only argument. The returned value is bound to the function name instead of the function object. Multiple decorators are applied in nested fashion. For example, the following code @f1 ( arg ) @f2 def func (): pass is roughly equivalent to def func (): pass func = f1 ( arg )( f2 ( func )) except that the original function is not temporarily bound to the name func . Changed in version 3.9: Functions may be decorated with any valid assignment_expression . Previously, the grammar was much more restrictive; see PEP 614 for details. A list of type parameters may be given in square brackets between the function’s name and the opening parenthesis for its parameter list. This indicates to static type checkers that the function is generic. At runtime, the type parameters can be retrieved from the function’s __type_params__ attribute. See Generic functions for more. Changed in version 3.12: Type parameter lists are new in Python 3.12. When one or more parameters have the form parameter = expression , the function is said to have “default parameter values.” For a parameter with a default value, the corresponding argument may be omitted from a call, in which case the parameter’s default value is substituted. If a parameter has a default value, all following parameters up until the “ * ” must also have a default value — this is a syntactic restriction that is not expressed by the grammar. Default parameter values are evaluated from left to right when the function definition is executed. This means that the expression is evaluated once, when the function is defined, and that the same “pre-computed” value is used for each call. This is especially important to understand when a default parameter value is a mutable object, such as a list or a dictionary: if the function modifies the object (e.g. by appending an item to a list), the default parameter value is in effect modified. This is generally not what was intended. A way around this is to use None as the default, and explicitly test for it in the body of the function, e.g.: def whats_on_the_telly ( penguin = None ): if penguin is None : penguin = [] penguin . append ( "property of the zoo" ) return penguin Function call semantics are described in more detail in section Calls . A function call always assigns values to all parameters mentioned in the parameter list, either from positional arguments, from keyword arguments, or from default values. If the form “ *identifier ” is present, it is initialized to a tuple receiving any excess positional parameters, defaulting to the empty tuple. If the form “ **identifier ” is present, it is initialized to a new ordered mapping receiving any excess keyword arguments, defaulting to a new empty mapping of the same type. Parameters after “ * ” or “ *identifier ” are keyword-only parameters and may only be passed by keyword arguments. Parameters before “ / ” are positional-only parameters and may only be passed by positional arguments. Changed in version 3.8: The / function parameter syntax may be used to indicate positional-only parameters. See PEP 570 for details. Parameters may have an annotation of the form “ : expression ” following the parameter name. Any parameter may have an annotation, even those of the form *identifier or **identifier . (As a special case, parameters of the form *identifier may have an annotation “ : *expression ”.) Functions may have “return” annotation of the form “ -> expression ” after the parameter list. These annotations can be any valid Python expression. The presence of annotations does not change the semantics of a function. See Annotations for more information on annotations. Changed in version 3.11: Parameters of the form “ *identifier ” may have an annotation “ : *expression ”. See PEP 646 . It is also possible to create anonymous functions (functions not bound to a name), for immediate use in expressions. This uses lambda expressions, described in section Lambdas . Note that the lambda expression is merely a shorthand for a simplified function definition; a function defined in a “ def ” statement can be passed around or assigned to another name just like a function defined by a lambda expression. The “ def ” form is actually more powerful since it allows the execution of multiple statements and annotations. Programmer’s note: Functions are first-class objects. A “ def ” statement executed inside a function definition defines a local function that can be returned or passed around. Free variables used in the nested function can access the local variables of the function containing the def. See section Naming and binding for details. See also PEP 3107 - Function Annotations The original specification for function annotations. PEP 484 - Type Hints Definition of a standard meaning for annotations: type hints. PEP 526 - Syntax for Variable Annotations Ability to type hint variable declarations, including class variables and instance variables. PEP 563 - Postponed Evaluation of Annotations Support for forward references within annotations by preserving annotations in a string form at runtime instead of eager evaluation. PEP 318 - Decorators for Functions and Methods Function and method decorators were introduced. Class decorators were introduced in PEP 3129 . 8.8. Class definitions ¶ A class definition defines a class object (see section The standard type hierarchy ): classdef : [ decorators ] "class" classname [ type_params ] [ inheritance ] ":" suite inheritance : "(" [ argument_list ] ")" classname : identifier A class definition is an executable statement. The inheritance list usually gives a list of base classes (see Metaclasses for more advanced uses), so each item in the list should evaluate to a class object which allows subclassing. Classes without an inheritance list inherit, by default, from the base class object ; hence, class Foo : pass is equivalent to class Foo ( object ): pass The class’s suite is then executed in a new execution frame (see Naming and binding ), using a newly created local namespace and the original global namespace. (Usually, the suite contains mostly function definitions.) When the class’s suite finishes execution, its execution frame is discarded but its local namespace is saved. [ 5 ] A class object is then created using the inheritance list for the base classes and the saved local namespace for the attribute dictionary. The class name is bound to this class object in the original local namespace. The order in which attributes are defined in the class body is preserved in the new class’s __dict__ . Note that this is reliable only right after the class is created and only for classes that were defined using the definition syntax. Class creation can be customized heavily using metaclasses . Classes can also be decorated: just like when decorating functions, @f1 ( arg ) @f2 class Foo : pass is roughly equivalent to class Foo : pass Foo = f1 ( arg )( f2 ( Foo )) The evaluation rules for the decorator expressions are the same as for function decorators. The result is then bound to the class name. Changed in version 3.9: Classes may be decorated with any valid assignment_expression . Previously, the grammar was much more restrictive; see PEP 614 for details. A list of type parameters may be given in square brackets immediately after the class’s name. This indicates to static type checkers that the class is generic. At runtime, the type parameters can be retrieved from the class’s __type_params__ attribute. See Generic classes for more. Changed in version 3.12: Type parameter lists are new in Python 3.12. Programmer’s note: Variables defined in the class definition are class attributes; they are shared by instances. Instance attributes can be set in a method with self.name = value . Both class and instance attributes are accessible through the notation “ self.name ”, and an instance attribute hides a class attribute with the same name when accessed in this way. Class attributes can be used as defaults for instance attributes, but using mutable values there can lead to unexpected results. Descriptors can be used to create instance variables with different implementation details. See also PEP 3115 - Metaclasses in Python 3000 The proposal that changed the declaration of metaclasses to the current syntax, and the semantics for how classes with metaclasses are constructed. PEP 3129 - Class Decorators The proposal that added class decorators. Function and method decorators were introduced in PEP 318 . 8.9. Coroutines ¶ Added in version 3.5. 8.9.1. Coroutine function definition ¶ async_funcdef : [ decorators ] "async" "def" funcname "(" [ parameter_list ] ")" [ "->" expression ] ":" suite Execution of Python coroutines can be suspended and resumed at many points (see coroutine ). await expressions, async for and async with can only be used in the body of a coroutine function. Functions defined with async def syntax are always coroutine functions, even if they do not contain await or async keywords. It is a SyntaxError to use a yield from expression inside the body of a coroutine function. An example of a coroutine function: async def func ( param1 , param2 ): do_stuff () await some_coroutine () Changed in version 3.7: await and async are now keywords; previously they were only treated as such inside the body of a coroutine function. 8.9.2. The async for statement ¶ async_for_stmt : "async" for_stmt An asynchronous iterable provides an __aiter__ method that directly returns an asynchronous iterator , which can call asynchronous code in its __anext__ method. The async for statement allows convenient iteration over asynchronous iterables. The following code: async for TARGET in ITER : SUITE else : SUITE2 Is semantically equivalent to: iter = ( ITER ) iter = type ( iter ) . __aiter__ ( iter ) running = True while running : try : TARGET = await type ( iter ) . __anext__ ( iter ) except StopAsyncIteration : running = False else : SUITE else : SUITE2 See also __aiter__() and __anext__() for details. It is a SyntaxError to use an async for statement outside the body of a coroutine function. 8.9.3. The async with statement ¶ async_with_stmt : "async" with_stmt An asynchronous context manager is a context manager that is able to suspend execution in its enter and exit methods. The following code: async with EXPRESSION as TARGET : SUITE is semantically equivalent to: manager = ( EXPRESSION ) aenter = type ( manager ) . __aenter__ aexit = type ( manager ) . __aexit__ value = await aenter ( manager ) hit_except = False try : TARGET = value SUITE except : hit_except = True if not await aexit ( manager , * sys . exc_info ()): raise finally : if not hit_except : await aexit ( manager , None , None , None ) See also __aenter__() and __aexit__() for details. It is a SyntaxError to use an async with statement outside the body of a coroutine function. See also PEP 492 - Coroutines with async and await syntax The proposal that made coroutines a proper standalone concept in Python, and added supporting syntax. 8.10. Type parameter lists ¶ Added in version 3.12. Changed in version 3.13: Support for default values was added (see PEP 696 ). type_params : "[" type_param ( "," type_param )* "]" type_param : typevar | typevartuple | paramspec typevar : identifier ( ":" expression )? ( "=" expression )? typevartuple : "*" identifier ( "=" expression )? paramspec : "**" identifier ( "=" expression )? Functions (including coroutines ), classes and type aliases may contain a type parameter list: def max [ T ]( args : list [ T ]) -> T : ... async def amax [ T ]( args : list [ T ]) -> T : ... class Bag [ T ]: def __iter__ ( self ) -> Iterator [ T ]: ... def add ( self , arg : T ) -> None : ... type ListOrSet [ T ] = list [ T ] | set [ T ] Semantically, this indicates that the function, class, or type | 2026-01-13T08:48:45 |
https://docs.python.org/3/reference/compound_stmts.html#try | 8. Compound statements — Python 3.14.2 documentation Theme Auto Light Dark Table of Contents 8. Compound statements 8.1. The if statement 8.2. The while statement 8.3. The for statement 8.4. The try statement 8.4.1. except clause 8.4.2. except* clause 8.4.3. else clause 8.4.4. finally clause 8.5. The with statement 8.6. The match statement 8.6.1. Overview 8.6.2. Guards 8.6.3. Irrefutable Case Blocks 8.6.4. Patterns 8.6.4.1. OR Patterns 8.6.4.2. AS Patterns 8.6.4.3. Literal Patterns 8.6.4.4. Capture Patterns 8.6.4.5. Wildcard Patterns 8.6.4.6. Value Patterns 8.6.4.7. Group Patterns 8.6.4.8. Sequence Patterns 8.6.4.9. Mapping Patterns 8.6.4.10. Class Patterns 8.7. Function definitions 8.8. Class definitions 8.9. Coroutines 8.9.1. Coroutine function definition 8.9.2. The async for statement 8.9.3. The async with statement 8.10. Type parameter lists 8.10.1. Generic functions 8.10.2. Generic classes 8.10.3. Generic type aliases 8.11. Annotations Previous topic 7. Simple statements Next topic 9. Top-level components This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Language Reference » 8. Compound statements | Theme Auto Light Dark | 8. Compound statements ¶ Compound statements contain (groups of) other statements; they affect or control the execution of those other statements in some way. In general, compound statements span multiple lines, although in simple incarnations a whole compound statement may be contained in one line. The if , while and for statements implement traditional control flow constructs. try specifies exception handlers and/or cleanup code for a group of statements, while the with statement allows the execution of initialization and finalization code around a block of code. Function and class definitions are also syntactically compound statements. A compound statement consists of one or more ‘clauses.’ A clause consists of a header and a ‘suite.’ The clause headers of a particular compound statement are all at the same indentation level. Each clause header begins with a uniquely identifying keyword and ends with a colon. A suite is a group of statements controlled by a clause. A suite can be one or more semicolon-separated simple statements on the same line as the header, following the header’s colon, or it can be one or more indented statements on subsequent lines. Only the latter form of a suite can contain nested compound statements; the following is illegal, mostly because it wouldn’t be clear to which if clause a following else clause would belong: if test1 : if test2 : print ( x ) Also note that the semicolon binds tighter than the colon in this context, so that in the following example, either all or none of the print() calls are executed: if x < y < z : print ( x ); print ( y ); print ( z ) Summarizing: compound_stmt : if_stmt | while_stmt | for_stmt | try_stmt | with_stmt | match_stmt | funcdef | classdef | async_with_stmt | async_for_stmt | async_funcdef suite : stmt_list NEWLINE | NEWLINE INDENT statement + DEDENT statement : stmt_list NEWLINE | compound_stmt stmt_list : simple_stmt ( ";" simple_stmt )* [ ";" ] Note that statements always end in a NEWLINE possibly followed by a DEDENT . Also note that optional continuation clauses always begin with a keyword that cannot start a statement, thus there are no ambiguities (the ‘dangling else ’ problem is solved in Python by requiring nested if statements to be indented). The formatting of the grammar rules in the following sections places each clause on a separate line for clarity. 8.1. The if statement ¶ The if statement is used for conditional execution: if_stmt : "if" assignment_expression ":" suite ( "elif" assignment_expression ":" suite )* [ "else" ":" suite ] It selects exactly one of the suites by evaluating the expressions one by one until one is found to be true (see section Boolean operations for the definition of true and false); then that suite is executed (and no other part of the if statement is executed or evaluated). If all expressions are false, the suite of the else clause, if present, is executed. 8.2. The while statement ¶ The while statement is used for repeated execution as long as an expression is true: while_stmt : "while" assignment_expression ":" suite [ "else" ":" suite ] This repeatedly tests the expression and, if it is true, executes the first suite; if the expression is false (which may be the first time it is tested) the suite of the else clause, if present, is executed and the loop terminates. A break statement executed in the first suite terminates the loop without executing the else clause’s suite. A continue statement executed in the first suite skips the rest of the suite and goes back to testing the expression. 8.3. The for statement ¶ The for statement is used to iterate over the elements of a sequence (such as a string, tuple or list) or other iterable object: for_stmt : "for" target_list "in" starred_expression_list ":" suite [ "else" ":" suite ] The starred_expression_list expression is evaluated once; it should yield an iterable object. An iterator is created for that iterable. The first item provided by the iterator is then assigned to the target list using the standard rules for assignments (see Assignment statements ), and the suite is executed. This repeats for each item provided by the iterator. When the iterator is exhausted, the suite in the else clause, if present, is executed, and the loop terminates. A break statement executed in the first suite terminates the loop without executing the else clause’s suite. A continue statement executed in the first suite skips the rest of the suite and continues with the next item, or with the else clause if there is no next item. The for-loop makes assignments to the variables in the target list. This overwrites all previous assignments to those variables including those made in the suite of the for-loop: for i in range ( 10 ): print ( i ) i = 5 # this will not affect the for-loop # because i will be overwritten with the next # index in the range Names in the target list are not deleted when the loop is finished, but if the sequence is empty, they will not have been assigned to at all by the loop. Hint: the built-in type range() represents immutable arithmetic sequences of integers. For instance, iterating range(3) successively yields 0, 1, and then 2. Changed in version 3.11: Starred elements are now allowed in the expression list. 8.4. The try statement ¶ The try statement specifies exception handlers and/or cleanup code for a group of statements: try_stmt : try1_stmt | try2_stmt | try3_stmt try1_stmt : "try" ":" suite ( "except" [ expression [ "as" identifier ]] ":" suite )+ [ "else" ":" suite ] [ "finally" ":" suite ] try2_stmt : "try" ":" suite ( "except" "*" expression [ "as" identifier ] ":" suite )+ [ "else" ":" suite ] [ "finally" ":" suite ] try3_stmt : "try" ":" suite "finally" ":" suite Additional information on exceptions can be found in section Exceptions , and information on using the raise statement to generate exceptions may be found in section The raise statement . Changed in version 3.14: Support for optionally dropping grouping parentheses when using multiple exception types. See PEP 758 . 8.4.1. except clause ¶ The except clause(s) specify one or more exception handlers. When no exception occurs in the try clause, no exception handler is executed. When an exception occurs in the try suite, a search for an exception handler is started. This search inspects the except clauses in turn until one is found that matches the exception. An expression-less except clause, if present, must be last; it matches any exception. For an except clause with an expression, the expression must evaluate to an exception type or a tuple of exception types. Parentheses can be dropped if multiple exception types are provided and the as clause is not used. The raised exception matches an except clause whose expression evaluates to the class or a non-virtual base class of the exception object, or to a tuple that contains such a class. If no except clause matches the exception, the search for an exception handler continues in the surrounding code and on the invocation stack. [ 1 ] If the evaluation of an expression in the header of an except clause raises an exception, the original search for a handler is canceled and a search starts for the new exception in the surrounding code and on the call stack (it is treated as if the entire try statement raised the exception). When a matching except clause is found, the exception is assigned to the target specified after the as keyword in that except clause, if present, and the except clause’s suite is executed. All except clauses must have an executable block. When the end of this block is reached, execution continues normally after the entire try statement. (This means that if two nested handlers exist for the same exception, and the exception occurs in the try clause of the inner handler, the outer handler will not handle the exception.) When an exception has been assigned using as target , it is cleared at the end of the except clause. This is as if except E as N : foo was translated to except E as N : try : foo finally : del N This means the exception must be assigned to a different name to be able to refer to it after the except clause. Exceptions are cleared because with the traceback attached to them, they form a reference cycle with the stack frame, keeping all locals in that frame alive until the next garbage collection occurs. Before an except clause’s suite is executed, the exception is stored in the sys module, where it can be accessed from within the body of the except clause by calling sys.exception() . When leaving an exception handler, the exception stored in the sys module is reset to its previous value: >>> print ( sys . exception ()) None >>> try : ... raise TypeError ... except : ... print ( repr ( sys . exception ())) ... try : ... raise ValueError ... except : ... print ( repr ( sys . exception ())) ... print ( repr ( sys . exception ())) ... TypeError() ValueError() TypeError() >>> print ( sys . exception ()) None 8.4.2. except* clause ¶ The except* clause(s) specify one or more handlers for groups of exceptions ( BaseExceptionGroup instances). A try statement can have either except or except* clauses, but not both. The exception type for matching is mandatory in the case of except* , so except*: is a syntax error. The type is interpreted as in the case of except , but matching is performed on the exceptions contained in the group that is being handled. An TypeError is raised if a matching type is a subclass of BaseExceptionGroup , because that would have ambiguous semantics. When an exception group is raised in the try block, each except* clause splits (see split() ) it into the subgroups of matching and non-matching exceptions. If the matching subgroup is not empty, it becomes the handled exception (the value returned from sys.exception() ) and assigned to the target of the except* clause (if there is one). Then, the body of the except* clause executes. If the non-matching subgroup is not empty, it is processed by the next except* in the same manner. This continues until all exceptions in the group have been matched, or the last except* clause has run. After all except* clauses execute, the group of unhandled exceptions is merged with any exceptions that were raised or re-raised from within except* clauses. This merged exception group propagates on.: >>> try : ... raise ExceptionGroup ( "eg" , ... [ ValueError ( 1 ), TypeError ( 2 ), OSError ( 3 ), OSError ( 4 )]) ... except * TypeError as e : ... print ( f 'caught { type ( e ) } with nested { e . exceptions } ' ) ... except * OSError as e : ... print ( f 'caught { type ( e ) } with nested { e . exceptions } ' ) ... caught <class 'ExceptionGroup'> with nested (TypeError(2),) caught <class 'ExceptionGroup'> with nested (OSError(3), OSError(4)) + Exception Group Traceback (most recent call last): | File "<doctest default[0]>", line 2, in <module> | raise ExceptionGroup("eg", | [ValueError(1), TypeError(2), OSError(3), OSError(4)]) | ExceptionGroup: eg (1 sub-exception) +-+---------------- 1 ---------------- | ValueError: 1 +------------------------------------ If the exception raised from the try block is not an exception group and its type matches one of the except* clauses, it is caught and wrapped by an exception group with an empty message string. This ensures that the type of the target e is consistently BaseExceptionGroup : >>> try : ... raise BlockingIOError ... except * BlockingIOError as e : ... print ( repr ( e )) ... ExceptionGroup('', (BlockingIOError(),)) break , continue and return cannot appear in an except* clause. 8.4.3. else clause ¶ The optional else clause is executed if the control flow leaves the try suite, no exception was raised, and no return , continue , or break statement was executed. Exceptions in the else clause are not handled by the preceding except clauses. 8.4.4. finally clause ¶ If finally is present, it specifies a ‘cleanup’ handler. The try clause is executed, including any except and else clauses. If an exception occurs in any of the clauses and is not handled, the exception is temporarily saved. The finally clause is executed. If there is a saved exception it is re-raised at the end of the finally clause. If the finally clause raises another exception, the saved exception is set as the context of the new exception. If the finally clause executes a return , break or continue statement, the saved exception is discarded. For example, this function returns 42. def f (): try : 1 / 0 finally : return 42 The exception information is not available to the program during execution of the finally clause. When a return , break or continue statement is executed in the try suite of a try … finally statement, the finally clause is also executed ‘on the way out.’ The return value of a function is determined by the last return statement executed. Since the finally clause always executes, a return statement executed in the finally clause will always be the last one executed. The following function returns ‘finally’. def foo (): try : return 'try' finally : return 'finally' Changed in version 3.8: Prior to Python 3.8, a continue statement was illegal in the finally clause due to a problem with the implementation. Changed in version 3.14: The compiler emits a SyntaxWarning when a return , break or continue appears in a finally block (see PEP 765 ). 8.5. The with statement ¶ The with statement is used to wrap the execution of a block with methods defined by a context manager (see section With Statement Context Managers ). This allows common try … except … finally usage patterns to be encapsulated for convenient reuse. with_stmt : "with" ( "(" with_stmt_contents "," ? ")" | with_stmt_contents ) ":" suite with_stmt_contents : with_item ( "," with_item )* with_item : expression [ "as" target ] The execution of the with statement with one “item” proceeds as follows: The context expression (the expression given in the with_item ) is evaluated to obtain a context manager. The context manager’s __enter__() is loaded for later use. The context manager’s __exit__() is loaded for later use. The context manager’s __enter__() method is invoked. If a target was included in the with statement, the return value from __enter__() is assigned to it. Note The with statement guarantees that if the __enter__() method returns without an error, then __exit__() will always be called. Thus, if an error occurs during the assignment to the target list, it will be treated the same as an error occurring within the suite would be. See step 7 below. The suite is executed. The context manager’s __exit__() method is invoked. If an exception caused the suite to be exited, its type, value, and traceback are passed as arguments to __exit__() . Otherwise, three None arguments are supplied. If the suite was exited due to an exception, and the return value from the __exit__() method was false, the exception is reraised. If the return value was true, the exception is suppressed, and execution continues with the statement following the with statement. If the suite was exited for any reason other than an exception, the return value from __exit__() is ignored, and execution proceeds at the normal location for the kind of exit that was taken. The following code: with EXPRESSION as TARGET : SUITE is semantically equivalent to: manager = ( EXPRESSION ) enter = type ( manager ) . __enter__ exit = type ( manager ) . __exit__ value = enter ( manager ) hit_except = False try : TARGET = value SUITE except : hit_except = True if not exit ( manager , * sys . exc_info ()): raise finally : if not hit_except : exit ( manager , None , None , None ) With more than one item, the context managers are processed as if multiple with statements were nested: with A () as a , B () as b : SUITE is semantically equivalent to: with A () as a : with B () as b : SUITE You can also write multi-item context managers in multiple lines if the items are surrounded by parentheses. For example: with ( A () as a , B () as b , ): SUITE Changed in version 3.1: Support for multiple context expressions. Changed in version 3.10: Support for using grouping parentheses to break the statement in multiple lines. See also PEP 343 - The “with” statement The specification, background, and examples for the Python with statement. 8.6. The match statement ¶ Added in version 3.10. The match statement is used for pattern matching. Syntax: match_stmt : 'match' subject_expr ":" NEWLINE INDENT case_block + DEDENT subject_expr : `!star_named_expression` "," `!star_named_expressions`? | `!named_expression` case_block : 'case' patterns [ guard ] ":" `!block` Note This section uses single quotes to denote soft keywords . Pattern matching takes a pattern as input (following case ) and a subject value (following match ). The pattern (which may contain subpatterns) is matched against the subject value. The outcomes are: A match success or failure (also termed a pattern success or failure). Possible binding of matched values to a name. The prerequisites for this are further discussed below. The match and case keywords are soft keywords . See also PEP 634 – Structural Pattern Matching: Specification PEP 636 – Structural Pattern Matching: Tutorial 8.6.1. Overview ¶ Here’s an overview of the logical flow of a match statement: The subject expression subject_expr is evaluated and a resulting subject value obtained. If the subject expression contains a comma, a tuple is constructed using the standard rules . Each pattern in a case_block is attempted to match with the subject value. The specific rules for success or failure are described below. The match attempt can also bind some or all of the standalone names within the pattern. The precise pattern binding rules vary per pattern type and are specified below. Name bindings made during a successful pattern match outlive the executed block and can be used after the match statement . Note During failed pattern matches, some subpatterns may succeed. Do not rely on bindings being made for a failed match. Conversely, do not rely on variables remaining unchanged after a failed match. The exact behavior is dependent on implementation and may vary. This is an intentional decision made to allow different implementations to add optimizations. If the pattern succeeds, the corresponding guard (if present) is evaluated. In this case all name bindings are guaranteed to have happened. If the guard evaluates as true or is missing, the block inside case_block is executed. Otherwise, the next case_block is attempted as described above. If there are no further case blocks, the match statement is completed. Note Users should generally never rely on a pattern being evaluated. Depending on implementation, the interpreter may cache values or use other optimizations which skip repeated evaluations. A sample match statement: >>> flag = False >>> match ( 100 , 200 ): ... case ( 100 , 300 ): # Mismatch: 200 != 300 ... print ( 'Case 1' ) ... case ( 100 , 200 ) if flag : # Successful match, but guard fails ... print ( 'Case 2' ) ... case ( 100 , y ): # Matches and binds y to 200 ... print ( f 'Case 3, y: { y } ' ) ... case _ : # Pattern not attempted ... print ( 'Case 4, I match anything!' ) ... Case 3, y: 200 In this case, if flag is a guard. Read more about that in the next section. 8.6.2. Guards ¶ guard : "if" `!named_expression` A guard (which is part of the case ) must succeed for code inside the case block to execute. It takes the form: if followed by an expression. The logical flow of a case block with a guard follows: Check that the pattern in the case block succeeded. If the pattern failed, the guard is not evaluated and the next case block is checked. If the pattern succeeded, evaluate the guard . If the guard condition evaluates as true, the case block is selected. If the guard condition evaluates as false, the case block is not selected. If the guard raises an exception during evaluation, the exception bubbles up. Guards are allowed to have side effects as they are expressions. Guard evaluation must proceed from the first to the last case block, one at a time, skipping case blocks whose pattern(s) don’t all succeed. (I.e., guard evaluation must happen in order.) Guard evaluation must stop once a case block is selected. 8.6.3. Irrefutable Case Blocks ¶ An irrefutable case block is a match-all case block. A match statement may have at most one irrefutable case block, and it must be last. A case block is considered irrefutable if it has no guard and its pattern is irrefutable. A pattern is considered irrefutable if we can prove from its syntax alone that it will always succeed. Only the following patterns are irrefutable: AS Patterns whose left-hand side is irrefutable OR Patterns containing at least one irrefutable pattern Capture Patterns Wildcard Patterns parenthesized irrefutable patterns 8.6.4. Patterns ¶ Note This section uses grammar notations beyond standard EBNF: the notation SEP.RULE+ is shorthand for RULE (SEP RULE)* the notation !RULE is shorthand for a negative lookahead assertion The top-level syntax for patterns is: patterns : open_sequence_pattern | pattern pattern : as_pattern | or_pattern closed_pattern : | literal_pattern | capture_pattern | wildcard_pattern | value_pattern | group_pattern | sequence_pattern | mapping_pattern | class_pattern The descriptions below will include a description “in simple terms” of what a pattern does for illustration purposes (credits to Raymond Hettinger for a document that inspired most of the descriptions). Note that these descriptions are purely for illustration purposes and may not reflect the underlying implementation. Furthermore, they do not cover all valid forms. 8.6.4.1. OR Patterns ¶ An OR pattern is two or more patterns separated by vertical bars | . Syntax: or_pattern : "|" . closed_pattern + Only the final subpattern may be irrefutable , and each subpattern must bind the same set of names to avoid ambiguity. An OR pattern matches each of its subpatterns in turn to the subject value, until one succeeds. The OR pattern is then considered successful. Otherwise, if none of the subpatterns succeed, the OR pattern fails. In simple terms, P1 | P2 | ... will try to match P1 , if it fails it will try to match P2 , succeeding immediately if any succeeds, failing otherwise. 8.6.4.2. AS Patterns ¶ An AS pattern matches an OR pattern on the left of the as keyword against a subject. Syntax: as_pattern : or_pattern "as" capture_pattern If the OR pattern fails, the AS pattern fails. Otherwise, the AS pattern binds the subject to the name on the right of the as keyword and succeeds. capture_pattern cannot be a _ . In simple terms P as NAME will match with P , and on success it will set NAME = <subject> . 8.6.4.3. Literal Patterns ¶ A literal pattern corresponds to most literals in Python. Syntax: literal_pattern : signed_number | signed_number "+" NUMBER | signed_number "-" NUMBER | strings | "None" | "True" | "False" signed_number : [ "-" ] NUMBER The rule strings and the token NUMBER are defined in the standard Python grammar . Triple-quoted strings are supported. Raw strings and byte strings are supported. f-strings and t-strings are not supported. The forms signed_number '+' NUMBER and signed_number '-' NUMBER are for expressing complex numbers ; they require a real number on the left and an imaginary number on the right. E.g. 3 + 4j . In simple terms, LITERAL will succeed only if <subject> == LITERAL . For the singletons None , True and False , the is operator is used. 8.6.4.4. Capture Patterns ¶ A capture pattern binds the subject value to a name. Syntax: capture_pattern : ! '_' NAME A single underscore _ is not a capture pattern (this is what !'_' expresses). It is instead treated as a wildcard_pattern . In a given pattern, a given name can only be bound once. E.g. case x, x: ... is invalid while case [x] | x: ... is allowed. Capture patterns always succeed. The binding follows scoping rules established by the assignment expression operator in PEP 572 ; the name becomes a local variable in the closest containing function scope unless there’s an applicable global or nonlocal statement. In simple terms NAME will always succeed and it will set NAME = <subject> . 8.6.4.5. Wildcard Patterns ¶ A wildcard pattern always succeeds (matches anything) and binds no name. Syntax: wildcard_pattern : '_' _ is a soft keyword within any pattern, but only within patterns. It is an identifier, as usual, even within match subject expressions, guard s, and case blocks. In simple terms, _ will always succeed. 8.6.4.6. Value Patterns ¶ A value pattern represents a named value in Python. Syntax: value_pattern : attr attr : name_or_attr "." NAME name_or_attr : attr | NAME The dotted name in the pattern is looked up using standard Python name resolution rules . The pattern succeeds if the value found compares equal to the subject value (using the == equality operator). In simple terms NAME1.NAME2 will succeed only if <subject> == NAME1.NAME2 Note If the same value occurs multiple times in the same match statement, the interpreter may cache the first value found and reuse it rather than repeat the same lookup. This cache is strictly tied to a given execution of a given match statement. 8.6.4.7. Group Patterns ¶ A group pattern allows users to add parentheses around patterns to emphasize the intended grouping. Otherwise, it has no additional syntax. Syntax: group_pattern : "(" pattern ")" In simple terms (P) has the same effect as P . 8.6.4.8. Sequence Patterns ¶ A sequence pattern contains several subpatterns to be matched against sequence elements. The syntax is similar to the unpacking of a list or tuple. sequence_pattern : "[" [ maybe_sequence_pattern ] "]" | "(" [ open_sequence_pattern ] ")" open_sequence_pattern : maybe_star_pattern "," [ maybe_sequence_pattern ] maybe_sequence_pattern : "," . maybe_star_pattern + "," ? maybe_star_pattern : star_pattern | pattern star_pattern : "*" ( capture_pattern | wildcard_pattern ) There is no difference if parentheses or square brackets are used for sequence patterns (i.e. (...) vs [...] ). Note A single pattern enclosed in parentheses without a trailing comma (e.g. (3 | 4) ) is a group pattern . While a single pattern enclosed in square brackets (e.g. [3 | 4] ) is still a sequence pattern. At most one star subpattern may be in a sequence pattern. The star subpattern may occur in any position. If no star subpattern is present, the sequence pattern is a fixed-length sequence pattern; otherwise it is a variable-length sequence pattern. The following is the logical flow for matching a sequence pattern against a subject value: If the subject value is not a sequence [ 2 ] , the sequence pattern fails. If the subject value is an instance of str , bytes or bytearray the sequence pattern fails. The subsequent steps depend on whether the sequence pattern is fixed or variable-length. If the sequence pattern is fixed-length: If the length of the subject sequence is not equal to the number of subpatterns, the sequence pattern fails Subpatterns in the sequence pattern are matched to their corresponding items in the subject sequence from left to right. Matching stops as soon as a subpattern fails. If all subpatterns succeed in matching their corresponding item, the sequence pattern succeeds. Otherwise, if the sequence pattern is variable-length: If the length of the subject sequence is less than the number of non-star subpatterns, the sequence pattern fails. The leading non-star subpatterns are matched to their corresponding items as for fixed-length sequences. If the previous step succeeds, the star subpattern matches a list formed of the remaining subject items, excluding the remaining items corresponding to non-star subpatterns following the star subpattern. Remaining non-star subpatterns are matched to their corresponding subject items, as for a fixed-length sequence. Note The length of the subject sequence is obtained via len() (i.e. via the __len__() protocol). This length may be cached by the interpreter in a similar manner as value patterns . In simple terms [P1, P2, P3, … , P<N>] matches only if all the following happens: check <subject> is a sequence len(subject) == <N> P1 matches <subject>[0] (note that this match can also bind names) P2 matches <subject>[1] (note that this match can also bind names) … and so on for the corresponding pattern/element. 8.6.4.9. Mapping Patterns ¶ A mapping pattern contains one or more key-value patterns. The syntax is similar to the construction of a dictionary. Syntax: mapping_pattern : "{" [ items_pattern ] "}" items_pattern : "," . key_value_pattern + "," ? key_value_pattern : ( literal_pattern | value_pattern ) ":" pattern | double_star_pattern double_star_pattern : "**" capture_pattern At most one double star pattern may be in a mapping pattern. The double star pattern must be the last subpattern in the mapping pattern. Duplicate keys in mapping patterns are disallowed. Duplicate literal keys will raise a SyntaxError . Two keys that otherwise have the same value will raise a ValueError at runtime. The following is the logical flow for matching a mapping pattern against a subject value: If the subject value is not a mapping [ 3 ] ,the mapping pattern fails. If every key given in the mapping pattern is present in the subject mapping, and the pattern for each key matches the corresponding item of the subject mapping, the mapping pattern succeeds. If duplicate keys are detected in the mapping pattern, the pattern is considered invalid. A SyntaxError is raised for duplicate literal values; or a ValueError for named keys of the same value. Note Key-value pairs are matched using the two-argument form of the mapping subject’s get() method. Matched key-value pairs must already be present in the mapping, and not created on-the-fly via __missing__() or __getitem__() . In simple terms {KEY1: P1, KEY2: P2, ... } matches only if all the following happens: check <subject> is a mapping KEY1 in <subject> P1 matches <subject>[KEY1] … and so on for the corresponding KEY/pattern pair. 8.6.4.10. Class Patterns ¶ A class pattern represents a class and its positional and keyword arguments (if any). Syntax: class_pattern : name_or_attr "(" [ pattern_arguments "," ?] ")" pattern_arguments : positional_patterns [ "," keyword_patterns ] | keyword_patterns positional_patterns : "," . pattern + keyword_patterns : "," . keyword_pattern + keyword_pattern : NAME "=" pattern The same keyword should not be repeated in class patterns. The following is the logical flow for matching a class pattern against a subject value: If name_or_attr is not an instance of the builtin type , raise TypeError . If the subject value is not an instance of name_or_attr (tested via isinstance() ), the class pattern fails. If no pattern arguments are present, the pattern succeeds. Otherwise, the subsequent steps depend on whether keyword or positional argument patterns are present. For a number of built-in types (specified below), a single positional subpattern is accepted which will match the entire subject; for these types keyword patterns also work as for other types. If only keyword patterns are present, they are processed as follows, one by one: The keyword is looked up as an attribute on the subject. If this raises an exception other than AttributeError , the exception bubbles up. If this raises AttributeError , the class pattern has failed. Else, the subpattern associated with the keyword pattern is matched against the subject’s attribute value. If this fails, the class pattern fails; if this succeeds, the match proceeds to the next keyword. If all keyword patterns succeed, the class pattern succeeds. If any positional patterns are present, they are converted to keyword patterns using the __match_args__ attribute on the class name_or_attr before matching: The equivalent of getattr(cls, "__match_args__", ()) is called. If this raises an exception, the exception bubbles up. If the returned value is not a tuple, the conversion fails and TypeError is raised. If there are more positional patterns than len(cls.__match_args__) , TypeError is raised. Otherwise, positional pattern i is converted to a keyword pattern using __match_args__[i] as the keyword. __match_args__[i] must be a string; if not TypeError is raised. If there are duplicate keywords, TypeError is raised. See also Customizing positional arguments in class pattern matching Once all positional patterns have been converted to keyword patterns, the match proceeds as if there were only keyword patterns. For the following built-in types the handling of positional subpatterns is different: bool bytearray bytes dict float frozenset int list set str tuple These classes accept a single positional argument, and the pattern there is matched against the whole object rather than an attribute. For example int(0|1) matches the value 0 , but not the value 0.0 . In simple terms CLS(P1, attr=P2) matches only if the following happens: isinstance(<subject>, CLS) convert P1 to a keyword pattern using CLS.__match_args__ For each keyword argument attr=P2 : hasattr(<subject>, "attr") P2 matches <subject>.attr … and so on for the corresponding keyword argument/pattern pair. See also PEP 634 – Structural Pattern Matching: Specification PEP 636 – Structural Pattern Matching: Tutorial 8.7. Function definitions ¶ A function definition defines a user-defined function object (see section The standard type hierarchy ): funcdef : [ decorators ] "def" funcname [ type_params ] "(" [ parameter_list ] ")" [ "->" expression ] ":" suite decorators : decorator + decorator : "@" assignment_expression NEWLINE parameter_list : defparameter ( "," defparameter )* "," "/" [ "," [ parameter_list_no_posonly ]] | parameter_list_no_posonly parameter_list_no_posonly : defparameter ( "," defparameter )* [ "," [ parameter_list_starargs ]] | parameter_list_starargs parameter_list_starargs : "*" [ star_parameter ] ( "," defparameter )* [ "," [ parameter_star_kwargs ]] | "*" ( "," defparameter )+ [ "," [ parameter_star_kwargs ]] | parameter_star_kwargs parameter_star_kwargs : "**" parameter [ "," ] parameter : identifier [ ":" expression ] star_parameter : identifier [ ":" [ "*" ] expression ] defparameter : parameter [ "=" expression ] funcname : identifier A function definition is an executable statement. Its execution binds the function name in the current local namespace to a function object (a wrapper around the executable code for the function). This function object contains a reference to the current global namespace as the global namespace to be used when the function is called. The function definition does not execute the function body; this gets executed only when the function is called. [ 4 ] A function definition may be wrapped by one or more decorator expressions. Decorator expressions are evaluated when the function is defined, in the scope that contains the function definition. The result must be a callable, which is invoked with the function object as the only argument. The returned value is bound to the function name instead of the function object. Multiple decorators are applied in nested fashion. For example, the following code @f1 ( arg ) @f2 def func (): pass is roughly equivalent to def func (): pass func = f1 ( arg )( f2 ( func )) except that the original function is not temporarily bound to the name func . Changed in version 3.9: Functions may be decorated with any valid assignment_expression . Previously, the grammar was much more restrictive; see PEP 614 for details. A list of type parameters may be given in square brackets between the function’s name and the opening parenthesis for its parameter list. This indicates to static type checkers that the function is generic. At runtime, the type parameters can be retrieved from the function’s __type_params__ attribute. See Generic functions for more. Changed in version 3.12: Type parameter lists are new in Python 3.12. When one or more parameters have the form parameter = expression , the function is said to have “default parameter values.” For a parameter with a default value, the corresponding argument may be omitted from a call, in which case the parameter’s default value is substituted. If a parameter has a default value, all following parameters up until the “ * ” must also have a default value — this is a syntactic restriction that is not expressed by the grammar. Default parameter values are evaluated from left to right when the function definition is executed. This means that the expression is evaluated once, when the function is defined, and that the same “pre-computed” value is used for each call. This is especially important to understand when a default parameter value is a mutable object, such as a list or a dictionary: if the function modifies the object (e.g. by appending an item to a list), the default parameter value is in effect modified. This is generally not what was intended. A way around this is to use None as the default, and explicitly test for it in the body of the function, e.g.: def whats_on_the_telly ( penguin = None ): if penguin is None : penguin = [] penguin . append ( "property of the zoo" ) return penguin Function call semantics are described in more detail in section Calls . A function call always assigns values to all parameters mentioned in the parameter list, either from positional arguments, from keyword arguments, or from default values. If the form “ *identifier ” is present, it is initialized to a tuple receiving any excess positional parameters, defaulting to the empty tuple. If the form “ **identifier ” is present, it is initialized to a new ordered mapping receiving any excess keyword arguments, defaulting to a new empty mapping of the same type. Parameters after “ * ” or “ *identifier ” are keyword-only parameters and may only be passed by keyword arguments. Parameters before “ / ” are positional-only parameters and may only be passed by positional arguments. Changed in version 3.8: The / function parameter syntax may be used to indicate positional-only parameters. See PEP 570 for details. Parameters may have an annotation of the form “ : expression ” following the parameter name. Any parameter may have an annotation, even those of the form *identifier or **identifier . (As a special case, parameters of the form *identifier may have an annotation “ : *expression ”.) Functions may have “return” annotation of the form “ -> expression ” after the parameter list. These annotations can be any valid Python expression. The presence of annotations does not change the semantics of a function. See Annotations for more information on annotations. Changed in version 3.11: Parameters of the form “ *identifier ” may have an annotation “ : *expression ”. See PEP 646 . It is also possible to create anonymous functions (functions not bound to a name), for immediate use in expressions. This uses lambda expressions, described in section Lambdas . Note that the lambda expression is merely a shorthand for a simplified function definition; a function defined in a “ def ” statement can be passed around or assigned to another name just like a function defined by a lambda expression. The “ def ” form is actually more powerful since it allows the execution of multiple statements and annotations. Programmer’s note: Functions are first-class objects. A “ def ” statement executed inside a function definition defines a local function that can be returned or passed around. Free variables used in the nested function can access the local variables of the function containing the def. See section Naming and binding for details. See also PEP 3107 - Function Annotations The original specification for function annotations. PEP 484 - Type Hints Definition of a standard meaning for annotations: type hints. PEP 526 - Syntax for Variable Annotations Ability to type hint variable declarations, including class variables and instance variables. PEP 563 - Postponed Evaluation of Annotations Support for forward references within annotations by preserving annotations in a string form at runtime instead of eager evaluation. PEP 318 - Decorators for Functions and Methods Function and method decorators were introduced. Class decorators were introduced in PEP 3129 . 8.8. Class definitions ¶ A class definition defines a class object (see section The standard type hierarchy ): classdef : [ decorators ] "class" classname [ type_params ] [ inheritance ] ":" suite inheritance : "(" [ argument_list ] ")" classname : identifier A class definition is an executable statement. The inheritance list usually gives a list of base classes (see Metaclasses for more advanced uses), so each item in the list should evaluate to a class object which allows subclassing. Classes without an inheritance list inherit, by default, from the base class object ; hence, class Foo : pass is equivalent to class Foo ( object ): pass The class’s suite is then executed in a new execution frame (see Naming and binding ), using a newly created local namespace and the original global namespace. (Usually, the suite contains mostly function definitions.) When the class’s suite finishes execution, its execution frame is discarded but its local namespace is saved. [ 5 ] A class object is then created using the inheritance list for the base classes and the saved local namespace for the attribute dictionary. The class name is bound to this class object in the original local namespace. The order in which attributes are defined in the class body is preserved in the new class’s __dict__ . Note that this is reliable only right after the class is created and only for classes that were defined using the definition syntax. Class creation can be customized heavily using metaclasses . Classes can also be decorated: just like when decorating functions, @f1 ( arg ) @f2 class Foo : pass is roughly equivalent to class Foo : pass Foo = f1 ( arg )( f2 ( Foo )) The evaluation rules for the decorator expressions are the same as for function decorators. The result is then bound to the class name. Changed in version 3.9: Classes may be decorated with any valid assignment_expression . Previously, the grammar was much more restrictive; see PEP 614 for details. A list of type parameters may be given in square brackets immediately after the class’s name. This indicates to static type checkers that the class is generic. At runtime, the type parameters can be retrieved from the class’s __type_params__ attribute. See Generic classes for more. Changed in version 3.12: Type parameter lists are new in Python 3.12. Programmer’s note: Variables defined in the class definition are class attributes; they are shared by instances. Instance attributes can be set in a method with self.name = value . Both class and instance attributes are accessible through the notation “ self.name ”, and an instance attribute hides a class attribute with the same name when accessed in this way. Class attributes can be used as defaults for instance attributes, but using mutable values there can lead to unexpected results. Descriptors can be used to create instance variables with different implementation details. See also PEP 3115 - Metaclasses in Python 3000 The proposal that changed the declaration of metaclasses to the current syntax, and the semantics for how classes with metaclasses are constructed. PEP 3129 - Class Decorators The proposal that added class decorators. Function and method decorators were introduced in PEP 318 . 8.9. Coroutines ¶ Added in version 3.5. 8.9.1. Coroutine function definition ¶ async_funcdef : [ decorators ] "async" "def" funcname "(" [ parameter_list ] ")" [ "->" expression ] ":" suite Execution of Python coroutines can be suspended and resumed at many points (see coroutine ). await expressions, async for and async with can only be used in the body of a coroutine function. Functions defined with async def syntax are always coroutine functions, even if they do not contain await or async keywords. It is a SyntaxError to use a yield from expression inside the body of a coroutine function. An example of a coroutine function: async def func ( param1 , param2 ): do_stuff () await some_coroutine () Changed in version 3.7: await and async are now keywords; previously they were only treated as such inside the body of a coroutine function. 8.9.2. The async for statement ¶ async_for_stmt : "async" for_stmt An asynchronous iterable provides an __aiter__ method that directly returns an asynchronous iterator , which can call asynchronous code in its __anext__ method. The async for statement allows convenient iteration over asynchronous iterables. The following code: async for TARGET in ITER : SUITE else : SUITE2 Is semantically equivalent to: iter = ( ITER ) iter = type ( iter ) . __aiter__ ( iter ) running = True while running : try : TARGET = await type ( iter ) . __anext__ ( iter ) except StopAsyncIteration : running = False else : SUITE else : SUITE2 See also __aiter__() and __anext__() for details. It is a SyntaxError to use an async for statement outside the body of a coroutine function. 8.9.3. The async with statement ¶ async_with_stmt : "async" with_stmt An asynchronous context manager is a context manager that is able to suspend execution in its enter and exit methods. The following code: async with EXPRESSION as TARGET : SUITE is semantically equivalent to: manager = ( EXPRESSION ) aenter = type ( manager ) . __aenter__ aexit = type ( manager ) . __aexit__ value = await aenter ( manager ) hit_except = False try : TARGET = value SUITE except : hit_except = True if not await aexit ( manager , * sys . exc_info ()): raise finally : if not hit_except : await aexit ( manager , None , None , None ) See also __aenter__() and __aexit__() for details. It is a SyntaxError to use an async with statement outside the body of a coroutine function. See also PEP 492 - Coroutines with async and await syntax The proposal that made coroutines a proper standalone concept in Python, and added supporting syntax. 8.10. Type parameter lists ¶ Added in version 3.12. Changed in version 3.13: Support for default values was added (see PEP 696 ). type_params : "[" type_param ( "," type_param )* "]" type_param : typevar | typevartuple | paramspec typevar : identifier ( ":" expression )? ( "=" expression )? typevartuple : "*" identifier ( "=" expression )? paramspec : "**" identifier ( "=" expression )? Functions (including coroutines ), classes and type aliases may contain a type parameter list: def max [ T ]( args : list [ T ]) -> T : ... async def amax [ T ]( args : list [ T ]) -> T : ... class Bag [ T ]: def __iter__ ( self ) -> Iterator [ T ]: ... def add ( self , arg : T ) -> None : ... type ListOrSet [ T ] = list [ T ] | set [ T ] Semantically, this indicates that the function, class, or type | 2026-01-13T08:48:45 |
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c=c===void 0?"0":c;var e;var f=(e=ada(a,1))!=null?e:c;b=b(f);a=a.getNanos();return new Date(b*1E3+a/1E6)} function rj(){var a=new Date(Date.now()),b=new pj;a=a.getTime();Number.isFinite(a)||(a=0);return b.setSeconds(Math.floor(a/1E3)).setNanos((a%1E3+1E3)%1E3*1E6)} ;function sj(a){this.Aa=se(a)} u(sj,ih);var tj=[0,Zh,fi];pj.prototype.Ca=Di(tj);var uj=[0,ni,oj,x,Gh,Ai,ni,Qea,ni,Rea,x,[0,[0,vi,tj],tj],Gh,[!0,Wh,Pea]];sj.prototype.Ca=Di(uj);var vj=[0,ni,function(){return vj}, x,-3,Xh,hi,ni,function(){return vj}, hi,vi,x,vi,x,-1,vi];function wj(a){this.Aa=se(a)} u(wj,ih);n=wj.prototype;n.getName=function(){return Ef(this,1)}; n.Sf=function(){return Of(this,1)}; n.setName=function(a){return dg(this,1,a)}; n.tf=la(9);n.Uo=function(){return Af(this,3)}; n.Qh=function(a){return Xf(this,3,a)};var xj=[0,x,-1,hi,Wh];wj.prototype.Ca=Di(xj);function yj(a){this.Aa=se(a)} u(yj,ih);yj.prototype.getFrdIdentifier=function(){return Ff(this,1)}; function zj(a,b){return fg(a,1,b)} yj.prototype.Yq=function(){return Ff(this,2)}; yj.prototype.Wc=function(a){return fg(this,2,a)};function Aj(a){this.Aa=se(a)} u(Aj,ih);Aj.prototype.Lg=function(a){return Xe(this,1,a,cca)}; Aj.prototype.getValue=function(a){var b=Kf(this,3,void 0,!0);Tc(b,a);return b[a]}; Aj.prototype.setValue=function(a,b){return af(this,1,cca,a,b,Ve)};function Bj(a){this.Aa=se(a)} u(Bj,ih);function Cj(a){return Qe(a,1,Qd,1,void 0,1024)} function Sea(a,b){return Xe(a,1,b,Gd)} ;function Dj(a){this.Aa=se(a)} u(Dj,ih);function Ej(a){return Qe(a,1,Qd,1,void 0,1024)} Dj.prototype.Lg=function(a){return Xe(this,1,a,Gd)}; Dj.prototype.getValue=function(a){return Hf(this,1,a)}; Dj.prototype.setValue=function(a,b){return af(this,1,Gd,a,b,Od)};function Fj(a){this.Aa=se(a)} u(Fj,ih);function Gj(a){return nf(a,Dj,1,Pe())} function Hj(a,b){return qf(a,1,b)} ;function Ij(a){this.Aa=se(a)} u(Ij,ih);function Jj(a,b){return If(a,1,Pe(b))} Ij.prototype.Lg=function(a){return Xe(this,1,a,Vd)}; 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Ff(this,5)}; function Tj(a,b){return fg(a,5,b)} function Uj(a){return lf(a,Kj,2)} function Vj(a,b){return of(a,Kj,2,b)} Rj.prototype.setFieldName=function(a){return dg(this,4,a)};var Wj=[0,Wh,x];var Yj=[0,vi,-1];yj.prototype.Ca=Di(Yj);var Tea=[0,ri];Aj.prototype.Ca=Di(Tea);var Uea=[0,Xh];Bj.prototype.Ca=Di(Uea);var Zj=[0,Xh];Dj.prototype.Ca=Di(Zj);var Vea=[0,ni,Zj];Fj.prototype.Ca=Di(Vea);var ak=[0,ki];Ij.prototype.Ca=Di(ak);var bk=[0,Rf,1,oi,Zj,oi,ak,oi,Uea,oi,Tea,oi,Vea,ji,oi,ak];Kj.prototype.Ca=Di(bk);var ck=[0,Yj,bk,vi,x,vi,bk];Rj.prototype.Ca=Di(ck);var Wea=[0,1,x,3,x,vi,2,x];var Xea=[0,x,hi,-1,Xh,hi,x,-2];var Yea=[0,x,-4,ni,[0,x,Xh]];var dk=[0,x,-1,vi,x,Xh,x,-1,hi,91,x];var Zea=[0,x,-1,[0,ki],x];var $ea=[0,ni,nj];var afa=[0,x,-2,hi,ki,hi];var bfa=[0,x,Wh];var ek=[0,Wj,ck,-1,ni,ck];var cfa=[0,x,-2,vi];var dfa=[0,x,ni,[0,x,vi]];var efa=[0,x];var ffa=[0,x,vi];var gfa=[0,x,-2];var hfa=[0,vi,1,vi,ni,[0,vi,x,-1]];var ifa=[0,[4],vi,ci,x,gi,x];var jfa=[0,ni,[0,[2,3],x,oi,[0,ki],oi,[0,x],hi,-1],vi];var kfa=[0,x,-2];var lfa=[0,hi,ci];var mfa=[0,lfa];var nfa=[0,ci];var gk=[0,Gh,[!0,x,function(){return fk}]],fk=[0, [1,2,3,4,5,6],zi,Qh,mi,ji,oi,function(){return gk}, oi,function(){return ofa}],ofa=[0, ni,function(){return fk}];var pfa=[0,x,vi,[0,hi,ni,[0,vi,ni,[0,x,-2,fk]]],[0,hi,ni,[0,x,-1,ni,[0,x,-1]]]];var qfa=[0,ni,[0,x,ci,hi,vi,hi,vi,[0,vi,x],pfa],ci,vi,pfa,hi];var rfa=[0,vi,ni,nj];var sfa=[0,vi,2,wi];var tfa=[0,x,-1,ci];var ufa=[0,x,-1,hi,-1,x,-1,1,hi,Xh,ck,sfa,Yh,ki];function hk(a){this.Aa=se(a)} u(hk,ih);function ik(a,b){return qf(a,1,b)} function jk(a){var b=new hk;return rf(b,1,Rj,a)} var vfa=Fi(hk);function kk(a){this.Aa=se(a)} u(kk,ih);n=kk.prototype;n.getId=function(){return Ef(this,1)}; n.setId=function(a){return dg(this,1,a)}; n.getType=function(){return Ff(this,3)}; n.setType=function(a){return fg(this,3,a)}; n.getTitle=function(){return Ef(this,4)}; n.setTitle=function(a){return dg(this,4,a)}; n.getDescription=function(){return Ef(this,5)}; n.setDescription=function(a){return dg(this,5,a)}; n.getValue=function(){return Ef(this,6)}; n.setValue=function(a){return dg(this,6,a)}; n.Tb=function(){return ig(this,6)};function lk(a){this.Aa=se(a)} u(lk,ih);function mk(a){this.Aa=se(a)} u(mk,ih);function nk(a){this.Aa=se(a)} u(nk,ih);n=nk.prototype;n.getType=function(){return Ff(this,1)}; n.setType=function(a){return fg(this,1,a)}; n.getDescription=function(){return Ef(this,3)}; n.setDescription=function(a){return dg(this,3,a)}; n.getValue=function(){return Ef(this,4)}; n.setValue=function(a){return dg(this,4,a)}; n.Tb=function(){return ig(this,4)}; var ok=[10,17];function pk(a){this.Aa=se(a,3)} u(pk,ih);function qk(a){return lf(a,nk,1)} var wfa=Fi(pk);var rk=[0,ni,ck,Wh,x,Wj];hk.prototype.Ca=Di(rk);var xfa=[0,x,Xh,vi,x,-6,ki,-1,x,vi,-1,ni,ck,ni,rk,rk,x,-1];kk.prototype.Ca=Di(xfa);var yfa=[0,ci,x];lk.prototype.Ca=Di(yfa);var sk=[0,hi,x,-3];mk.prototype.Ca=Di(sk);var zfa=[0,ok,vi,x,-2,ci,x,ci,-2,mi,1,vi,-1,di,ni,rk,1,oi,yfa,1,sk,Xh,ni,[0,rk,vi]];nk.prototype.Ca=Di(zfa);var tk=[-3,{},zfa,xfa];pk.prototype.Ca=Di(tk);var Afa=[0,[27,28,29,30,31,35,38,40,41,43,45,46,47],x,-1,hi,vi,ni,ufa,x,rfa,tfa,x,-5,Xh,x,hi,ki,ni,ufa,vi,x,ci,hi,ci,uj,ki,oi,nfa,oi,jfa,oi,qfa,oi,hfa,oi,gfa,ck,sfa,x,oi,dfa,hi,1,oi,tk,vi,oi,mfa,oi,kfa,hi,oi,cfa,1,oi,ifa,oi,efa,oi,ffa,hi];function uk(a){this.Aa=se(a)} u(uk,ih);function vk(a){return lf(a,Rj,1)} function yk(a,b){return of(a,Rj,1,b)} ;var zk=[0,ck,ci,vi,wi,hi];uk.prototype.Ca=Di(zk);var Ak=[0,[0,x,-2],qi,3,x];var Bfa=[0,x,ki,ni,Afa,x,-2,2,x,-3,hi,-2,ki,ci,vi,1,ki,-1,afa,x,hi,-1,x,-1,1,hi,lfa,vi,x,ci,Xh,Ak,-1,uj,x,-1,bfa,2,ek,1,hi,-1,1,vi,ni,zk,x,-1,ci,Wh,46,x];var Bk=[0,ni,zk,Wj,vi,Xh];var Ck=[0,Zh,fi];function Dk(a){this.Aa=se(a)} u(Dk,ih);Dk.prototype.jr=function(){return Vf(this,1)}; Dk.prototype.getTimestamp=function(){return xf(this,5,ze)}; Dk.prototype.setTimestamp=function(a){return cg(this,5,a)};function Ek(a){this.Aa=se(a)} u(Ek,ih);Ek.prototype.getUrl=function(){return Of(this,1)}; Ek.prototype.setUrl=function(a){return dg(this,1,a)};function Fk(a){this.Aa=se(a)} u(Fk,ih);function Gk(a){this.Aa=se(a)} u(Gk,ih);n=Gk.prototype;n.getViews=function(){return wf(this,1,ze)}; n.getThumbnail=function(){return Of(this,2)}; n.hasThumbnail=function(){return ig(this,2)}; n.getTimestamp=function(){return xf(this,4,ze)}; n.setTimestamp=function(a){return cg(this,4,a)};function Hk(a){this.Aa=se(a)} u(Hk,ih);n=Hk.prototype;n.getUrl=function(){return Of(this,1)}; n.setUrl=function(a){return dg(this,1,a)}; n.getTitle=function(){return Of(this,2)}; n.setTitle=function(a){return dg(this,2,a)}; n.Td=function(){return Of(this,3)}; function Ik(a,b){return dg(a,3,b)} n.getLanguage=function(){return Of(this,10)}; n.setLanguage=function(a){return dg(this,10,a)}; n.getPageType=function(){return Wf(this,15)}; function Jk(a,b){return dg(a,21,b)} n.Rb=function(){return Of(this,22)}; function Kk(a,b){return 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n.setLanguage=function(a){return dg(this,2,a)}; n.getName=function(){return Of(this,3)}; n.Sf=function(){return Of(this,3)}; n.setName=function(a){return dg(this,3,a)}; n.tf=la(8);n.getTitle=function(){return Of(this,4)}; n.setTitle=function(a){return dg(this,4,a)}; function Cfa(a,b){return dg(a,5,b)} n.getContent=function(){return Of(this,6)}; n.setContent=function(a){return dg(this,6,a)}; n.clearContent=function(){return Ce(this,6)}; n.getMetadata=function(){return lf(this,sj,13)}; n.Lf=function(a){return of(this,sj,13,a)}; n.setProperty=function(a,b){return Ne(this,20,wj,a,b)}; n.getAuthorEmail=function(){return Of(this,22)};function Xk(a){this.Aa=se(a)} u(Xk,ih);Xk.prototype.Uo=function(){return Af(this,2)}; Xk.prototype.Qh=function(a){return Xf(this,2,a)}; function Yk(a){return Cf(a,3)} ;function Zk(a){this.Aa=se(a)} u(Zk,ih);function $k(a){return nf(a,Xk,3,Pe())} Zk.prototype.Lg=function(a){return qf(this,3,a)}; Zk.prototype.setValue=function(a,b){return Ne(this,3,Xk,a,b)};function al(a){this.Aa=se(a)} u(al,ih);function bl(a,b){return nf(a,Zk,5,Pe(b))} var cl=Fi(al);var dl=[0,x,-3];var el=[0,x,vi,1,x];var fl=[0,vi,x,-5];var Dfa=[0,x,-9,2,x,-12];var Efa=[0,x,-1,Wh,-1];var Ffa=[0,x];var Gfa=[0,ci,-2,x,bi,x,-1,hi,vi];Dk.prototype.Ca=Di(Gfa);var Hfa=[0,x];Ek.prototype.Ca=Di(Hfa);var Ifa=[0,Hfa,-4];Fk.prototype.Ca=Di(Ifa);var Jfa=[0,Wh,x,ci,bi,x,hi,x,Ifa];Gk.prototype.Ca=Di(Jfa);var gl=[0,x,-2,vi,x,ni,vj,x,-1,Ak,x,-2,1,hi,vi,hi,x,-1,hi,x,-2,vi,ni,function(){return gl}, 1,Gfa,ni,function(){return gl}, Jfa,1,Ffa,Efa];Hk.prototype.Ca=Di(gl);var hl=[0,ni,gl];Nk.prototype.Ca=Di(hl);Pk.prototype.Ca=Di([0,ni,gl,Wh,x,Dfa,ni,gl,-1,x,ni,gl,fl,ni,dl,ni,el,ci,-1,x,hl]);var Kfa=[0,x,-1,hi];Qk.prototype.Ca=Di(Kfa);Rk.prototype.Ca=Di([0,ni,Kfa]);Sk.prototype.Ca=Di([0,Tk,mi,ci,-1,x,mi,vi,x,ci,hi,-1,ci]);var il=[0,1,x];Uk.prototype.Ca=Di(il);var Lfa=[0,x,vi,x,-1];var jl=[0,x,-1,vi];Vk.prototype.Ca=Di(jl);var Mfa=[0,ni,oj,-1,x,ni,oj,Gh,Ai];var kl=[0,x,-1,hi,ci,Rh,hi,-2,ni,func | 2026-01-13T08:48:45 |
https://www.iana.org/ | Internet Assigned Numbers Authority Internet Assigned Numbers Authority The global coordination of the DNS Root, IP addressing, and other Internet protocol resources is performed as the Internet Assigned Numbers Authority (IANA) functions. Learn more. Domain Names Management of the DNS Root Zone (assignments of ccTLDs and gTLDs) along with other functions such as the .int and .arpa zones. Root Zone Management Database of Top Level Domains .int Registry .arpa Registry IDN Practices Repository Number Resources Coordination of the global IP and AS number spaces, such as allocations made to Regional Internet Registries. IP Addresses & AS Numbers Network abuse information Protocol Assignments The central repository for protocol name and number registries used in many Internet protocols. Protocol Registries Apply for an assignment Time Zone Database Domain Names Root Zone Registry .INT Registry .ARPA Registry IDN Repository Number Resources Abuse Information Protocols Protocol Registries Time Zone Database About Us News Performance Excellence Archive Contact Us The IANA functions coordinate the Internet’s globally unique identifiers, and are provided by Public Technical Identifiers , an affiliate of ICANN . Privacy Policy Terms of Service | 2026-01-13T08:48:45 |
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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close # development Follow Hide Tracking and discussing physical and cognitive milestones. Create Post Older #development posts 4 5 6 7 8 9 10 11 12 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Introducing brew-coffee - One Command Dev Environment Setup Naveen Thurimerla Naveen Thurimerla Naveen Thurimerla Follow Nov 24 '25 Introducing brew-coffee - One Command Dev Environment Setup # homebrew # devops # development # developer Comments Add Comment 2 min read Training a model to predict a persuasion score for documents, but hitting a wall Howard Shaw Howard Shaw Howard Shaw Follow Nov 24 '25 Training a model to predict a persuasion score for documents, but hitting a wall # machinelearning # development # buildinpublic 1 reaction Comments 1 comment 1 min read Web Design Through the Lens of UI/UX, HCI, and CX iQuipe Digital iQuipe Digital iQuipe Digital Follow Nov 28 '25 Web Design Through the Lens of UI/UX, HCI, and CX # webdev # programming # devops # development 1 reaction Comments Add Comment 2 min read I made a Cyberpunk themed calculator app SPID ROID SPID ROID SPID ROID Follow Dec 7 '25 I made a Cyberpunk themed calculator app # discuss # android # development # java Comments 1 comment 1 min read The Giant That Builds Smaller Giants: Custom AI Agents for Privacy and Efficiency Dexmac Dexmac Dexmac Follow Dec 27 '25 The Giant That Builds Smaller Giants: Custom AI Agents for Privacy and Efficiency # ai # agents # programming # development Comments Add Comment 11 min read How I’d Become a Backend Developer in 2026 (If I Were Starting Today) Ankit Kumar Ankit Kumar Ankit Kumar Follow Dec 27 '25 How I’d Become a Backend Developer in 2026 (If I Were Starting Today) # backenddevelopment # backend # developer # development 5 reactions Comments Add Comment 3 min read Impostor Syndrome in Tech: Why You Might Feel Like a Fraud — and How to Move Forward Anderson Contreira Anderson Contreira Anderson Contreira Follow Nov 27 '25 Impostor Syndrome in Tech: Why You Might Feel Like a Fraud — and How to Move Forward # career # development Comments Add Comment 2 min read WARNING TO DEVELOPERS: A new wave of “technical test scams” is targeting devs Anderson Contreira Anderson Contreira Anderson Contreira Follow Dec 6 '25 WARNING TO DEVELOPERS: A new wave of “technical test scams” is targeting devs # development # scam # recruiting 1 reaction Comments Add Comment 3 min read Building Own Block Cipher: Part 3 - AES Dmytro Huz Dmytro Huz Dmytro Huz Follow Dec 25 '25 Building Own Block Cipher: Part 3 - AES # security # programming # learning # development Comments Add Comment 6 min read Publishing Your First NPM Package: A Real-World Guide That Actually Helps Mir Mursalin Ankur Mir Mursalin Ankur Mir Mursalin Ankur Follow Nov 22 '25 Publishing Your First NPM Package: A Real-World Guide That Actually Helps # node # npm # development # opensource Comments Add Comment 9 min read 2025: AI-Assisted Developers Are Shipping Faster Than Ever Farhan Nasir Farhan Nasir Farhan Nasir Follow Nov 23 '25 2025: AI-Assisted Developers Are Shipping Faster Than Ever # webdev # ai # programming # development Comments Add Comment 1 min read Axelang - A Systems Programming Language with Concurrency as a First-Class feature Navid Navid Navid Follow Nov 21 '25 Axelang - A Systems Programming Language with Concurrency as a First-Class feature # programming # performance # development Comments Add Comment 2 min read 24 Claude Code Tips: #claude_code_advent_calendar Oikon Oikon Oikon Follow Dec 25 '25 24 Claude Code Tips: #claude_code_advent_calendar # claudecode # ai # productivity # development 1 reaction Comments Add Comment 13 min read Développer pour le déploiement distribué Patrick Turcotte Patrick Turcotte Patrick Turcotte Follow for Onepoint Dec 14 '25 Développer pour le déploiement distribué # cloud # adventoftech2025 # development 3 reactions Comments Add Comment 24 min read Why You Should Use a Database In Your Projects! afonso faro afonso faro afonso faro Follow Nov 21 '25 Why You Should Use a Database In Your Projects! # database # development # java # javascript Comments Add Comment 3 min read What is None network driver Megha Sharma Megha Sharma Megha Sharma Follow Dec 25 '25 What is None network driver # docker # devops # learning # development Comments Add Comment 3 min read gookit/goutil v0.7.2 Released: Enhanced Features & Fixes for an Improved Development Experience Inhere Inhere Inhere Follow Nov 20 '25 gookit/goutil v0.7.2 Released: Enhanced Features & Fixes for an Improved Development Experience # programming # github # development # backend Comments Add Comment 4 min read When Documentation Fails: Brute-Force Specification Discovery with AI synthaicode synthaicode synthaicode Follow Dec 23 '25 When Documentation Fails: Brute-Force Specification Discovery with AI # ai # testing # development # architecture Comments Add Comment 3 min read Introducing Codebox: an open-source tool for remote development workspaces (beta) Davide Bianchi Davide Bianchi Davide Bianchi Follow Nov 18 '25 Introducing Codebox: an open-source tool for remote development workspaces (beta) # devops # development # remotedev Comments Add Comment 3 min read JSON: The Simple Data Format That Transformed the Modern Web Devendra Singh Devendra Singh Devendra Singh Follow Nov 18 '25 JSON: The Simple Data Format That Transformed the Modern Web # development # developer # programming # webdev Comments Add Comment 3 min read Python Load Json From File Pineapple Pineapple Pineapple Follow Nov 20 '25 Python Load Json From File # webdev # ai # python # development Comments Add Comment 2 min read It's time to try OMARCHY! Pepe Pepe Pepe Follow Nov 18 '25 It's time to try OMARCHY! # linux # development # archlinux Comments Add Comment 4 min read Don't Let 'Copy-Paste' Syndrome Halt Your Coding Journey: Mastering Real Learning Erin Kerr Erin Kerr Erin Kerr Follow Nov 19 '25 Don't Let 'Copy-Paste' Syndrome Halt Your Coding Journey: Mastering Real Learning # beginners # learning # devjournal # development Comments Add Comment 4 min read Use Fork Git Client to Remove Passwords from Git History Jayson Rawlins Jayson Rawlins Jayson Rawlins Follow Nov 24 '25 Use Fork Git Client to Remove Passwords from Git History # git # fork # development Comments Add Comment 2 min read JSON Example with All Data Types Pineapple Pineapple Pineapple Follow Nov 18 '25 JSON Example with All Data Types # development # webdev # api # pinecode Comments Add Comment 3 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://react.dev/blog | React Blog – React React v 19.2 Search ⌘ Ctrl K Learn Reference Community Blog Blog React Blog This blog is the official source for the updates from the React team. Anything important, including release notes or deprecation notices, will be posted here first. You can also follow the @react.dev account on Bluesky, or @reactjs account on Twitter, but you won’t miss anything essential if you only read this blog. Denial of Service and Source Code Exposure in React Server Components December 11, 2025 Security researchers have found and disclosed two additional vulnerabilities in React Server Components while attempting to exploit the patches in last week’s critical vulnerability… Read more Critical Security Vulnerability in React Server Components December 3, 2025 There is an unauthenticated remote code execution vulnerability in React Server Components. A fix has been published in versions 19.0.1, 19.1.2, and 19.2.1. We recommend upgrading immediately. Read more React Conf 2025 Recap October 16, 2025 Last week we hosted React Conf 2025. In this post, we summarize the talks and announcements from the event… Read more React Compiler v1.0 October 7, 2025 We’re releasing the compiler’s first stable release today, plus linting and tooling improvements to make adoption easier. Read more Introducing the React Foundation October 7, 2025 Today, we’re announcing our plans to create the React Foundation and a new technical governance structure … Read more React 19.2 October 1, 2025 React 19.2 adds new features like Activity, React Performance Tracks, useEffectEvent, and more. In this post … Read more React Labs: View Transitions, Activity, and more April 23, 2025 In React Labs posts, we write about projects in active research and development. In this post, we’re sharing two new experimental features that are ready to try today, and sharing other areas we’re working on now … Read more Sunsetting Create React App February 14, 2025 Today, we’re deprecating Create React App for new apps, and encouraging existing apps to migrate to a framework, or to migrate to a build tool like Vite, Parcel, or RSBuild. We’re also providing docs for when a framework isn’t a good fit for your project, you want to build your own framework, or you just want to learn how React works by building a React app from scratch … Read more React v19 December 5, 2024 In the React 19 Upgrade Guide, we shared step-by-step instructions for upgrading your app to React 19. In this post, we’ll give an overview of the new features in React 19, and how you can adopt them … Read more React Compiler Beta Release October 21, 2024 We announced an experimental release of React Compiler at React Conf 2024. We’ve made a lot of progress since then, and in this post we want to share what’s next for React Compiler … Read more React Conf 2024 Recap May 22, 2024 Last week we hosted React Conf 2024, a two-day conference in Henderson, Nevada where 700+ attendees gathered in-person to discuss the latest in UI engineering. This was our first in-person conference since 2019, and we were thrilled to be able to bring the community together again … Read more React 19 Upgrade Guide April 25, 2024 The improvements added to React 19 require some breaking changes, but we’ve worked to make the upgrade as smooth as possible, and we don’t expect the changes to impact most apps. In this post, we will guide you through the steps for upgrading libraries to React 19 … Read more React Labs: What We've Been Working On – February 2024 February 15, 2024 In React Labs posts, we write about projects in active research and development. Since our last update, we’ve made significant progress on React Compiler, new features, and React 19, and we’d like to share what we learned. Read more React Canaries: Incremental Feature Rollout Outside Meta May 3, 2023 Traditionally, new React features used to only be available at Meta first, and land in the open source releases later. We’d like to offer the React community an option to adopt individual new features as soon as their design is close to final—similar to how Meta uses React internally. We are introducing a new officially supported Canary release channel. It lets curated setups like frameworks decouple adoption of individual React features from the React release schedule. Read more React Labs: What We've Been Working On – March 2023 March 22, 2023 In React Labs posts, we write about projects in active research and development. Since our last update, we’ve made significant progress on React Server Components, Asset Loading, Optimizing Compiler, Offscreen Rendering, and Transition Tracing, and we’d like to share what we learned. Read more Introducing react.dev March 16, 2023 Today we are thrilled to launch react.dev, the new home for React and its documentation. In this post, we would like to give you a tour of the new site. Read more React Labs: What We've Been Working On – June 2022 June 15, 2022 React 18 was years in the making, and with it brought valuable lessons for the React team. Its release was the result of many years of research and exploring many paths. Some of those paths were successful; many more were dead-ends that led to new insights. One lesson we’ve learned is that it’s frustrating for the community to wait for new features without having insight into these paths that we’re exploring… Read more React v18.0 March 29, 2022 React 18 is now available on npm! In our last post, we shared step-by-step instructions for upgrading your app to React 18. In this post, we’ll give an overview of what’s new in React 18, and what it means for the future… Read more How to Upgrade to React 18 March 8, 2022 As we shared in the release post, React 18 introduces features powered by our new concurrent renderer, with a gradual adoption strategy for existing applications. In this post, we will guide you through the steps for upgrading to React 18… Read more React Conf 2021 Recap December 17, 2021 Last week we hosted our 6th React Conf. In previous years, we’ve used the React Conf stage to deliver industry changing announcements such as React Native and React Hooks. This year, we shared our multi-platform vision for React, starting with the release of React 18 and gradual adoption of concurrent features… Read more The Plan for React 18 June 8, 2021 The React team is excited to share a few updates: We’ve started work on the React 18 release, which will be our next major version. We’ve created a Working Group to prepare the community for gradual adoption of new features in React 18. We’ve published a React 18 Alpha so that library authors can try it and provide feedback… Read more Introducing Zero-Bundle-Size React Server Components December 21, 2020 2020 has been a long year. As it comes to an end we wanted to share a special Holiday Update on our research into zero-bundle-size React Server Components. To introduce React Server Components, we have prepared a talk and a demo. If you want, you can check them out during the holidays, or later when work picks back up in the new year… Read more All release notes Not every React release deserves its own blog post, but you can find a detailed changelog for every release in the CHANGELOG.md file in the React repository, as well as on the Releases page. Older posts See the older posts. Copyright © Meta Platforms, Inc no uwu plz uwu? Logo by @sawaratsuki1004 Learn React Quick Start Installation Describing the UI Adding Interactivity Managing State Escape Hatches API Reference React APIs React DOM APIs Community Code of Conduct Meet the Team Docs Contributors Acknowledgements More Blog React Native Privacy Terms | 2026-01-13T08:48:45 |
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c=c===void 0?"0":c;var e;var f=(e=ada(a,1))!=null?e:c;b=b(f);a=a.getNanos();return new Date(b*1E3+a/1E6)} function rj(){var a=new Date(Date.now()),b=new pj;a=a.getTime();Number.isFinite(a)||(a=0);return b.setSeconds(Math.floor(a/1E3)).setNanos((a%1E3+1E3)%1E3*1E6)} ;function sj(a){this.Aa=se(a)} u(sj,ih);var tj=[0,Zh,fi];pj.prototype.Ca=Di(tj);var uj=[0,ni,oj,x,Gh,Ai,ni,Qea,ni,Rea,x,[0,[0,vi,tj],tj],Gh,[!0,Wh,Pea]];sj.prototype.Ca=Di(uj);var vj=[0,ni,function(){return vj}, x,-3,Xh,hi,ni,function(){return vj}, hi,vi,x,vi,x,-1,vi];function wj(a){this.Aa=se(a)} u(wj,ih);n=wj.prototype;n.getName=function(){return Ef(this,1)}; n.Sf=function(){return Of(this,1)}; n.setName=function(a){return dg(this,1,a)}; n.tf=la(9);n.Uo=function(){return Af(this,3)}; n.Qh=function(a){return Xf(this,3,a)};var xj=[0,x,-1,hi,Wh];wj.prototype.Ca=Di(xj);function yj(a){this.Aa=se(a)} u(yj,ih);yj.prototype.getFrdIdentifier=function(){return Ff(this,1)}; function zj(a,b){return fg(a,1,b)} yj.prototype.Yq=function(){return Ff(this,2)}; yj.prototype.Wc=function(a){return fg(this,2,a)};function Aj(a){this.Aa=se(a)} u(Aj,ih);Aj.prototype.Lg=function(a){return Xe(this,1,a,cca)}; Aj.prototype.getValue=function(a){var b=Kf(this,3,void 0,!0);Tc(b,a);return b[a]}; Aj.prototype.setValue=function(a,b){return af(this,1,cca,a,b,Ve)};function Bj(a){this.Aa=se(a)} u(Bj,ih);function Cj(a){return Qe(a,1,Qd,1,void 0,1024)} function Sea(a,b){return Xe(a,1,b,Gd)} ;function Dj(a){this.Aa=se(a)} u(Dj,ih);function Ej(a){return Qe(a,1,Qd,1,void 0,1024)} Dj.prototype.Lg=function(a){return Xe(this,1,a,Gd)}; Dj.prototype.getValue=function(a){return Hf(this,1,a)}; Dj.prototype.setValue=function(a,b){return af(this,1,Gd,a,b,Od)};function Fj(a){this.Aa=se(a)} u(Fj,ih);function Gj(a){return nf(a,Dj,1,Pe())} function Hj(a,b){return qf(a,1,b)} ;function Ij(a){this.Aa=se(a)} u(Ij,ih);function Jj(a,b){return If(a,1,Pe(b))} Ij.prototype.Lg=function(a){return Xe(this,1,a,Vd)}; Ij.prototype.getValue=function(a){return Jf(this,1,a)}; Ij.prototype.setValue=function(a,b){return af(this,1,Vd,a,b,Xd)};function Kj(a){this.Aa=se(a)} u(Kj,ih);function Lj(a){return Pf(a,Ij,8,Rf)} function Mj(a,b){return pf(a,8,Rf,b)} n=Kj.prototype;n.zg=function(){return Pf(this,Dj,2,Rf)}; n.Ji=function(a){return pf(this,2,Rf,a)}; n.ej=function(){return Pf(this,Ij,3,Rf)}; n.Kg=function(a){return pf(this,3,Rf,a)}; function Nj(a){return Pf(a,Bj,4,Rf)} function Oj(a,b){return pf(a,4,Rf,b)} function Pj(a){return Pf(a,Aj,5,Rf)} function Qj(a,b){return pf(a,5,Rf,b)} n.hm=function(){return Pf(this,Fj,6,Rf)}; n.hw=function(a){return pf(this,6,Rf,a)}; n.Uo=function(){return Lf(this,7,Rf)}; n.Qh=function(a){return bf(this,7,Rf,vd(a))}; var Rf=[2,3,4,5,6,7,8];function Rj(a){this.Aa=se(a)} u(Rj,ih);Rj.prototype.getFrdContext=function(){return lf(this,yj,1)}; function Sj(a,b){return of(a,yj,1,b)} Rj.prototype.Oy=function(){return Ee(this,yj,1)}; Rj.prototype.getFrdIdentifier=function(){return Ff(this,5)}; function Tj(a,b){return fg(a,5,b)} function Uj(a){return lf(a,Kj,2)} function Vj(a,b){return of(a,Kj,2,b)} Rj.prototype.setFieldName=function(a){return dg(this,4,a)};var Wj=[0,Wh,x];var Yj=[0,vi,-1];yj.prototype.Ca=Di(Yj);var Tea=[0,ri];Aj.prototype.Ca=Di(Tea);var Uea=[0,Xh];Bj.prototype.Ca=Di(Uea);var Zj=[0,Xh];Dj.prototype.Ca=Di(Zj);var Vea=[0,ni,Zj];Fj.prototype.Ca=Di(Vea);var ak=[0,ki];Ij.prototype.Ca=Di(ak);var bk=[0,Rf,1,oi,Zj,oi,ak,oi,Uea,oi,Tea,oi,Vea,ji,oi,ak];Kj.prototype.Ca=Di(bk);var ck=[0,Yj,bk,vi,x,vi,bk];Rj.prototype.Ca=Di(ck);var Wea=[0,1,x,3,x,vi,2,x];var Xea=[0,x,hi,-1,Xh,hi,x,-2];var Yea=[0,x,-4,ni,[0,x,Xh]];var dk=[0,x,-1,vi,x,Xh,x,-1,hi,91,x];var Zea=[0,x,-1,[0,ki],x];var $ea=[0,ni,nj];var afa=[0,x,-2,hi,ki,hi];var bfa=[0,x,Wh];var ek=[0,Wj,ck,-1,ni,ck];var cfa=[0,x,-2,vi];var dfa=[0,x,ni,[0,x,vi]];var efa=[0,x];var ffa=[0,x,vi];var gfa=[0,x,-2];var hfa=[0,vi,1,vi,ni,[0,vi,x,-1]];var ifa=[0,[4],vi,ci,x,gi,x];var jfa=[0,ni,[0,[2,3],x,oi,[0,ki],oi,[0,x],hi,-1],vi];var kfa=[0,x,-2];var lfa=[0,hi,ci];var mfa=[0,lfa];var nfa=[0,ci];var gk=[0,Gh,[!0,x,function(){return fk}]],fk=[0, [1,2,3,4,5,6],zi,Qh,mi,ji,oi,function(){return gk}, oi,function(){return ofa}],ofa=[0, ni,function(){return fk}];var pfa=[0,x,vi,[0,hi,ni,[0,vi,ni,[0,x,-2,fk]]],[0,hi,ni,[0,x,-1,ni,[0,x,-1]]]];var qfa=[0,ni,[0,x,ci,hi,vi,hi,vi,[0,vi,x],pfa],ci,vi,pfa,hi];var rfa=[0,vi,ni,nj];var sfa=[0,vi,2,wi];var tfa=[0,x,-1,ci];var ufa=[0,x,-1,hi,-1,x,-1,1,hi,Xh,ck,sfa,Yh,ki];function hk(a){this.Aa=se(a)} u(hk,ih);function ik(a,b){return qf(a,1,b)} function jk(a){var b=new hk;return rf(b,1,Rj,a)} var vfa=Fi(hk);function kk(a){this.Aa=se(a)} u(kk,ih);n=kk.prototype;n.getId=function(){return Ef(this,1)}; n.setId=function(a){return dg(this,1,a)}; n.getType=function(){return Ff(this,3)}; n.setType=function(a){return fg(this,3,a)}; n.getTitle=function(){return Ef(this,4)}; n.setTitle=function(a){return dg(this,4,a)}; n.getDescription=function(){return Ef(this,5)}; n.setDescription=function(a){return dg(this,5,a)}; n.getValue=function(){return Ef(this,6)}; n.setValue=function(a){return dg(this,6,a)}; n.Tb=function(){return ig(this,6)};function lk(a){this.Aa=se(a)} u(lk,ih);function mk(a){this.Aa=se(a)} u(mk,ih);function nk(a){this.Aa=se(a)} u(nk,ih);n=nk.prototype;n.getType=function(){return Ff(this,1)}; n.setType=function(a){return fg(this,1,a)}; n.getDescription=function(){return Ef(this,3)}; n.setDescription=function(a){return dg(this,3,a)}; n.getValue=function(){return Ef(this,4)}; n.setValue=function(a){return dg(this,4,a)}; n.Tb=function(){return ig(this,4)}; var ok=[10,17];function pk(a){this.Aa=se(a,3)} u(pk,ih);function qk(a){return lf(a,nk,1)} var wfa=Fi(pk);var rk=[0,ni,ck,Wh,x,Wj];hk.prototype.Ca=Di(rk);var xfa=[0,x,Xh,vi,x,-6,ki,-1,x,vi,-1,ni,ck,ni,rk,rk,x,-1];kk.prototype.Ca=Di(xfa);var yfa=[0,ci,x];lk.prototype.Ca=Di(yfa);var sk=[0,hi,x,-3];mk.prototype.Ca=Di(sk);var zfa=[0,ok,vi,x,-2,ci,x,ci,-2,mi,1,vi,-1,di,ni,rk,1,oi,yfa,1,sk,Xh,ni,[0,rk,vi]];nk.prototype.Ca=Di(zfa);var tk=[-3,{},zfa,xfa];pk.prototype.Ca=Di(tk);var Afa=[0,[27,28,29,30,31,35,38,40,41,43,45,46,47],x,-1,hi,vi,ni,ufa,x,rfa,tfa,x,-5,Xh,x,hi,ki,ni,ufa,vi,x,ci,hi,ci,uj,ki,oi,nfa,oi,jfa,oi,qfa,oi,hfa,oi,gfa,ck,sfa,x,oi,dfa,hi,1,oi,tk,vi,oi,mfa,oi,kfa,hi,oi,cfa,1,oi,ifa,oi,efa,oi,ffa,hi];function uk(a){this.Aa=se(a)} u(uk,ih);function vk(a){return lf(a,Rj,1)} function yk(a,b){return of(a,Rj,1,b)} ;var zk=[0,ck,ci,vi,wi,hi];uk.prototype.Ca=Di(zk);var Ak=[0,[0,x,-2],qi,3,x];var Bfa=[0,x,ki,ni,Afa,x,-2,2,x,-3,hi,-2,ki,ci,vi,1,ki,-1,afa,x,hi,-1,x,-1,1,hi,lfa,vi,x,ci,Xh,Ak,-1,uj,x,-1,bfa,2,ek,1,hi,-1,1,vi,ni,zk,x,-1,ci,Wh,46,x];var Bk=[0,ni,zk,Wj,vi,Xh];var Ck=[0,Zh,fi];function Dk(a){this.Aa=se(a)} u(Dk,ih);Dk.prototype.jr=function(){return Vf(this,1)}; Dk.prototype.getTimestamp=function(){return xf(this,5,ze)}; Dk.prototype.setTimestamp=function(a){return cg(this,5,a)};function Ek(a){this.Aa=se(a)} u(Ek,ih);Ek.prototype.getUrl=function(){return Of(this,1)}; Ek.prototype.setUrl=function(a){return dg(this,1,a)};function Fk(a){this.Aa=se(a)} u(Fk,ih);function Gk(a){this.Aa=se(a)} u(Gk,ih);n=Gk.prototype;n.getViews=function(){return wf(this,1,ze)}; n.getThumbnail=function(){return Of(this,2)}; n.hasThumbnail=function(){return ig(this,2)}; n.getTimestamp=function(){return xf(this,4,ze)}; n.setTimestamp=function(a){return cg(this,4,a)};function Hk(a){this.Aa=se(a)} u(Hk,ih);n=Hk.prototype;n.getUrl=function(){return Of(this,1)}; n.setUrl=function(a){return dg(this,1,a)}; n.getTitle=function(){return Of(this,2)}; n.setTitle=function(a){return dg(this,2,a)}; n.Td=function(){return Of(this,3)}; function Ik(a,b){return dg(a,3,b)} n.getLanguage=function(){return Of(this,10)}; n.setLanguage=function(a){return dg(this,10,a)}; n.getPageType=function(){return Wf(this,15)}; function Jk(a,b){return dg(a,21,b)} n.Rb=function(){return Of(this,22)}; function Kk(a,b){return 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kl=[0,x,-1,hi,ci,Rh,hi,-2,ni,func | 2026-01-13T08:48:45 |
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https://docs.python.org/3/library/functions.html#print | Built-in Functions — Python 3.14.2 documentation Theme Auto Light Dark Previous topic Introduction Next topic Built-in Constants This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Standard Library » Built-in Functions | Theme Auto Light Dark | Built-in Functions ¶ The Python interpreter has a number of functions and types built into it that are always available. They are listed here in alphabetical order. Built-in Functions A abs() aiter() all() anext() any() ascii() B bin() bool() breakpoint() bytearray() bytes() C callable() chr() classmethod() compile() complex() D delattr() dict() dir() divmod() E enumerate() eval() exec() F filter() float() format() frozenset() G getattr() globals() H hasattr() hash() help() hex() I id() input() int() isinstance() issubclass() iter() L len() list() locals() M map() max() memoryview() min() N next() O object() oct() open() ord() P pow() print() property() R range() repr() reversed() round() S set() setattr() slice() sorted() staticmethod() str() sum() super() T tuple() type() V vars() Z zip() _ __import__() abs ( number , / ) ¶ Return the absolute value of a number. The argument may be an integer, a floating-point number, or an object implementing __abs__() . If the argument is a complex number, its magnitude is returned. aiter ( async_iterable , / ) ¶ Return an asynchronous iterator for an asynchronous iterable . Equivalent to calling x.__aiter__() . Note: Unlike iter() , aiter() has no 2-argument variant. Added in version 3.10. all ( iterable , / ) ¶ Return True if all elements of the iterable are true (or if the iterable is empty). Equivalent to: def all ( iterable ): for element in iterable : if not element : return False return True awaitable anext ( async_iterator , / ) ¶ awaitable anext ( async_iterator , default , / ) When awaited, return the next item from the given asynchronous iterator , or default if given and the iterator is exhausted. This is the async variant of the next() builtin, and behaves similarly. This calls the __anext__() method of async_iterator , returning an awaitable . Awaiting this returns the next value of the iterator. If default is given, it is returned if the iterator is exhausted, otherwise StopAsyncIteration is raised. Added in version 3.10. any ( iterable , / ) ¶ Return True if any element of the iterable is true. If the iterable is empty, return False . Equivalent to: def any ( iterable ): for element in iterable : if element : return True return False ascii ( object , / ) ¶ As repr() , return a string containing a printable representation of an object, but escape the non-ASCII characters in the string returned by repr() using \x , \u , or \U escapes. This generates a string similar to that returned by repr() in Python 2. bin ( integer , / ) ¶ Convert an integer number to a binary string prefixed with “0b”. The result is a valid Python expression. If integer is not a Python int object, it has to define an __index__() method that returns an integer. Some examples: >>> bin ( 3 ) '0b11' >>> bin ( - 10 ) '-0b1010' If the prefix “0b” is desired or not, you can use either of the following ways. >>> format ( 14 , '#b' ), format ( 14 , 'b' ) ('0b1110', '1110') >>> f ' { 14 : #b } ' , f ' { 14 : b } ' ('0b1110', '1110') See also enum.bin() to represent negative values as twos-complement. See also format() for more information. class bool ( object = False , / ) ¶ Return a Boolean value, i.e. one of True or False . The argument is converted using the standard truth testing procedure . If the argument is false or omitted, this returns False ; otherwise, it returns True . The bool class is a subclass of int (see Numeric Types — int, float, complex ). It cannot be subclassed further. Its only instances are False and True (see Boolean Type - bool ). Changed in version 3.7: The parameter is now positional-only. breakpoint ( * args , ** kws ) ¶ This function drops you into the debugger at the call site. Specifically, it calls sys.breakpointhook() , passing args and kws straight through. By default, sys.breakpointhook() calls pdb.set_trace() expecting no arguments. In this case, it is purely a convenience function so you don’t have to explicitly import pdb or type as much code to enter the debugger. However, sys.breakpointhook() can be set to some other function and breakpoint() will automatically call that, allowing you to drop into the debugger of choice. If sys.breakpointhook() is not accessible, this function will raise RuntimeError . By default, the behavior of breakpoint() can be changed with the PYTHONBREAKPOINT environment variable. See sys.breakpointhook() for usage details. Note that this is not guaranteed if sys.breakpointhook() has been replaced. Raises an auditing event builtins.breakpoint with argument breakpointhook . Added in version 3.7. class bytearray ( source = b'' ) class bytearray ( source , encoding , errors = 'strict' ) Return a new array of bytes. The bytearray class is a mutable sequence of integers in the range 0 <= x < 256. It has most of the usual methods of mutable sequences, described in Mutable Sequence Types , as well as most methods that the bytes type has, see Bytes and Bytearray Operations . The optional source parameter can be used to initialize the array in a few different ways: If it is a string , you must also give the encoding (and optionally, errors ) parameters; bytearray() then converts the string to bytes using str.encode() . If it is an integer , the array will have that size and will be initialized with null bytes. If it is an object conforming to the buffer interface , a read-only buffer of the object will be used to initialize the bytes array. If it is an iterable , it must be an iterable of integers in the range 0 <= x < 256 , which are used as the initial contents of the array. Without an argument, an array of size 0 is created. See also Binary Sequence Types — bytes, bytearray, memoryview and Bytearray Objects . class bytes ( source = b'' ) class bytes ( source , encoding , errors = 'strict' ) Return a new “bytes” object which is an immutable sequence of integers in the range 0 <= x < 256 . bytes is an immutable version of bytearray – it has the same non-mutating methods and the same indexing and slicing behavior. Accordingly, constructor arguments are interpreted as for bytearray() . Bytes objects can also be created with literals, see String and Bytes literals . See also Binary Sequence Types — bytes, bytearray, memoryview , Bytes Objects , and Bytes and Bytearray Operations . callable ( object , / ) ¶ Return True if the object argument appears callable, False if not. If this returns True , it is still possible that a call fails, but if it is False , calling object will never succeed. Note that classes are callable (calling a class returns a new instance); instances are callable if their class has a __call__() method. Added in version 3.2: This function was first removed in Python 3.0 and then brought back in Python 3.2. chr ( codepoint , / ) ¶ Return the string representing a character with the specified Unicode code point. For example, chr(97) returns the string 'a' , while chr(8364) returns the string '€' . This is the inverse of ord() . The valid range for the argument is from 0 through 1,114,111 (0x10FFFF in base 16). ValueError will be raised if it is outside that range. @ classmethod ¶ Transform a method into a class method. A class method receives the class as an implicit first argument, just like an instance method receives the instance. To declare a class method, use this idiom: class C : @classmethod def f ( cls , arg1 , arg2 ): ... The @classmethod form is a function decorator – see Function definitions for details. A class method can be called either on the class (such as C.f() ) or on an instance (such as C().f() ). The instance is ignored except for its class. If a class method is called for a derived class, the derived class object is passed as the implied first argument. Class methods are different than C++ or Java static methods. If you want those, see staticmethod() in this section. For more information on class methods, see The standard type hierarchy . Changed in version 3.9: Class methods can now wrap other descriptors such as property() . Changed in version 3.10: Class methods now inherit the method attributes ( __module__ , __name__ , __qualname__ , __doc__ and __annotations__ ) and have a new __wrapped__ attribute. Deprecated since version 3.11, removed in version 3.13: Class methods can no longer wrap other descriptors such as property() . compile ( source , filename , mode , flags = 0 , dont_inherit = False , optimize = -1 ) ¶ Compile the source into a code or AST object. Code objects can be executed by exec() or eval() . source can either be a normal string, a byte string, or an AST object. Refer to the ast module documentation for information on how to work with AST objects. The filename argument should give the file from which the code was read; pass some recognizable value if it wasn’t read from a file ( '<string>' is commonly used). The mode argument specifies what kind of code must be compiled; it can be 'exec' if source consists of a sequence of statements, 'eval' if it consists of a single expression, or 'single' if it consists of a single interactive statement (in the latter case, expression statements that evaluate to something other than None will be printed). The optional arguments flags and dont_inherit control which compiler options should be activated and which future features should be allowed. If neither is present (or both are zero) the code is compiled with the same flags that affect the code that is calling compile() . If the flags argument is given and dont_inherit is not (or is zero) then the compiler options and the future statements specified by the flags argument are used in addition to those that would be used anyway. If dont_inherit is a non-zero integer then the flags argument is it – the flags (future features and compiler options) in the surrounding code are ignored. Compiler options and future statements are specified by bits which can be bitwise ORed together to specify multiple options. The bitfield required to specify a given future feature can be found as the compiler_flag attribute on the _Feature instance in the __future__ module. Compiler flags can be found in ast module, with PyCF_ prefix. The argument optimize specifies the optimization level of the compiler; the default value of -1 selects the optimization level of the interpreter as given by -O options. Explicit levels are 0 (no optimization; __debug__ is true), 1 (asserts are removed, __debug__ is false) or 2 (docstrings are removed too). This function raises SyntaxError or ValueError if the compiled source is invalid. If you want to parse Python code into its AST representation, see ast.parse() . Raises an auditing event compile with arguments source and filename . This event may also be raised by implicit compilation. Note When compiling a string with multi-line code in 'single' or 'eval' mode, input must be terminated by at least one newline character. This is to facilitate detection of incomplete and complete statements in the code module. Warning It is possible to crash the Python interpreter with a sufficiently large/complex string when compiling to an AST object due to stack depth limitations in Python’s AST compiler. Changed in version 3.2: Allowed use of Windows and Mac newlines. Also, input in 'exec' mode does not have to end in a newline anymore. Added the optimize parameter. Changed in version 3.5: Previously, TypeError was raised when null bytes were encountered in source . Added in version 3.8: ast.PyCF_ALLOW_TOP_LEVEL_AWAIT can now be passed in flags to enable support for top-level await , async for , and async with . class complex ( number = 0 , / ) ¶ class complex ( string , / ) class complex ( real = 0 , imag = 0 ) Convert a single string or number to a complex number, or create a complex number from real and imaginary parts. Examples: >>> complex ( '+1.23' ) (1.23+0j) >>> complex ( '-4.5j' ) -4.5j >>> complex ( '-1.23+4.5j' ) (-1.23+4.5j) >>> complex ( ' \t ( -1.23+4.5J ) \n ' ) (-1.23+4.5j) >>> complex ( '-Infinity+NaNj' ) (-inf+nanj) >>> complex ( 1.23 ) (1.23+0j) >>> complex ( imag =- 4.5 ) -4.5j >>> complex ( - 1.23 , 4.5 ) (-1.23+4.5j) If the argument is a string, it must contain either a real part (in the same format as for float() ) or an imaginary part (in the same format but with a 'j' or 'J' suffix), or both real and imaginary parts (the sign of the imaginary part is mandatory in this case). The string can optionally be surrounded by whitespaces and the round parentheses '(' and ')' , which are ignored. The string must not contain whitespace between '+' , '-' , the 'j' or 'J' suffix, and the decimal number. For example, complex('1+2j') is fine, but complex('1 + 2j') raises ValueError . More precisely, the input must conform to the complexvalue production rule in the following grammar, after parentheses and leading and trailing whitespace characters are removed: complexvalue : floatvalue | floatvalue ( "j" | "J" ) | floatvalue sign absfloatvalue ( "j" | "J" ) If the argument is a number, the constructor serves as a numeric conversion like int and float . For a general Python object x , complex(x) delegates to x.__complex__() . If __complex__() is not defined then it falls back to __float__() . If __float__() is not defined then it falls back to __index__() . If two arguments are provided or keyword arguments are used, each argument may be any numeric type (including complex). If both arguments are real numbers, return a complex number with the real component real and the imaginary component imag . If both arguments are complex numbers, return a complex number with the real component real.real-imag.imag and the imaginary component real.imag+imag.real . If one of arguments is a real number, only its real component is used in the above expressions. See also complex.from_number() which only accepts a single numeric argument. If all arguments are omitted, returns 0j . The complex type is described in Numeric Types — int, float, complex . Changed in version 3.6: Grouping digits with underscores as in code literals is allowed. Changed in version 3.8: Falls back to __index__() if __complex__() and __float__() are not defined. Deprecated since version 3.14: Passing a complex number as the real or imag argument is now deprecated; it should only be passed as a single positional argument. delattr ( object , name , / ) ¶ This is a relative of setattr() . The arguments are an object and a string. The string must be the name of one of the object’s attributes. The function deletes the named attribute, provided the object allows it. For example, delattr(x, 'foobar') is equivalent to del x.foobar . name need not be a Python identifier (see setattr() ). class dict ( ** kwargs ) class dict ( mapping , / , ** kwargs ) class dict ( iterable , / , ** kwargs ) Create a new dictionary. The dict object is the dictionary class. See dict and Mapping Types — dict for documentation about this class. For other containers see the built-in list , set , and tuple classes, as well as the collections module. dir ( ) ¶ dir ( object , / ) Without arguments, return the list of names in the current local scope. With an argument, attempt to return a list of valid attributes for that object. If the object has a method named __dir__() , this method will be called and must return the list of attributes. This allows objects that implement a custom __getattr__() or __getattribute__() function to customize the way dir() reports their attributes. If the object does not provide __dir__() , the function tries its best to gather information from the object’s __dict__ attribute, if defined, and from its type object. The resulting list is not necessarily complete and may be inaccurate when the object has a custom __getattr__() . The default dir() mechanism behaves differently with different types of objects, as it attempts to produce the most relevant, rather than complete, information: If the object is a module object, the list contains the names of the module’s attributes. If the object is a type or class object, the list contains the names of its attributes, and recursively of the attributes of its bases. Otherwise, the list contains the object’s attributes’ names, the names of its class’s attributes, and recursively of the attributes of its class’s base classes. The resulting list is sorted alphabetically. For example: >>> import struct >>> dir () # show the names in the module namespace ['__builtins__', '__name__', 'struct'] >>> dir ( struct ) # show the names in the struct module ['Struct', '__all__', '__builtins__', '__cached__', '__doc__', '__file__', '__initializing__', '__loader__', '__name__', '__package__', '_clearcache', 'calcsize', 'error', 'pack', 'pack_into', 'unpack', 'unpack_from'] >>> class Shape : ... def __dir__ ( self ): ... return [ 'area' , 'perimeter' , 'location' ] ... >>> s = Shape () >>> dir ( s ) ['area', 'location', 'perimeter'] Note Because dir() is supplied primarily as a convenience for use at an interactive prompt, it tries to supply an interesting set of names more than it tries to supply a rigorously or consistently defined set of names, and its detailed behavior may change across releases. For example, metaclass attributes are not in the result list when the argument is a class. divmod ( a , b , / ) ¶ Take two (non-complex) numbers as arguments and return a pair of numbers consisting of their quotient and remainder when using integer division. With mixed operand types, the rules for binary arithmetic operators apply. For integers, the result is the same as (a // b, a % b) . For floating-point numbers the result is (q, a % b) , where q is usually math.floor(a / b) but may be 1 less than that. In any case q * b + a % b is very close to a , if a % b is non-zero it has the same sign as b , and 0 <= abs(a % b) < abs(b) . enumerate ( iterable , start = 0 ) ¶ Return an enumerate object. iterable must be a sequence, an iterator , or some other object which supports iteration. The __next__() method of the iterator returned by enumerate() returns a tuple containing a count (from start which defaults to 0) and the values obtained from iterating over iterable . >>> seasons = [ 'Spring' , 'Summer' , 'Fall' , 'Winter' ] >>> list ( enumerate ( seasons )) [(0, 'Spring'), (1, 'Summer'), (2, 'Fall'), (3, 'Winter')] >>> list ( enumerate ( seasons , start = 1 )) [(1, 'Spring'), (2, 'Summer'), (3, 'Fall'), (4, 'Winter')] Equivalent to: def enumerate ( iterable , start = 0 ): n = start for elem in iterable : yield n , elem n += 1 eval ( source , / , globals = None , locals = None ) ¶ Parameters : source ( str | code object ) – A Python expression. globals ( dict | None ) – The global namespace (default: None ). locals ( mapping | None ) – The local namespace (default: None ). Returns : The result of the evaluated expression. Raises : Syntax errors are reported as exceptions. Warning This function executes arbitrary code. Calling it with user-supplied input may lead to security vulnerabilities. The source argument is parsed and evaluated as a Python expression (technically speaking, a condition list) using the globals and locals mappings as global and local namespace. If the globals dictionary is present and does not contain a value for the key __builtins__ , a reference to the dictionary of the built-in module builtins is inserted under that key before source is parsed. That way you can control what builtins are available to the executed code by inserting your own __builtins__ dictionary into globals before passing it to eval() . If the locals mapping is omitted it defaults to the globals dictionary. If both mappings are omitted, the source is executed with the globals and locals in the environment where eval() is called. Note, eval() will only have access to the nested scopes (non-locals) in the enclosing environment if they are already referenced in the scope that is calling eval() (e.g. via a nonlocal statement). Example: >>> x = 1 >>> eval ( 'x+1' ) 2 This function can also be used to execute arbitrary code objects (such as those created by compile() ). In this case, pass a code object instead of a string. If the code object has been compiled with 'exec' as the mode argument, eval() 's return value will be None . Hints: dynamic execution of statements is supported by the exec() function. The globals() and locals() functions return the current global and local dictionary, respectively, which may be useful to pass around for use by eval() or exec() . If the given source is a string, then leading and trailing spaces and tabs are stripped. See ast.literal_eval() for a function that can safely evaluate strings with expressions containing only literals. Raises an auditing event exec with the code object as the argument. Code compilation events may also be raised. Changed in version 3.13: The globals and locals arguments can now be passed as keywords. Changed in version 3.13: The semantics of the default locals namespace have been adjusted as described for the locals() builtin. exec ( source , / , globals = None , locals = None , * , closure = None ) ¶ Warning This function executes arbitrary code. Calling it with user-supplied input may lead to security vulnerabilities. This function supports dynamic execution of Python code. source must be either a string or a code object. If it is a string, the string is parsed as a suite of Python statements which is then executed (unless a syntax error occurs). [ 1 ] If it is a code object, it is simply executed. In all cases, the code that’s executed is expected to be valid as file input (see the section File input in the Reference Manual). Be aware that the nonlocal , yield , and return statements may not be used outside of function definitions even within the context of code passed to the exec() function. The return value is None . In all cases, if the optional parts are omitted, the code is executed in the current scope. If only globals is provided, it must be a dictionary (and not a subclass of dictionary), which will be used for both the global and the local variables. If globals and locals are given, they are used for the global and local variables, respectively. If provided, locals can be any mapping object. Remember that at the module level, globals and locals are the same dictionary. Note When exec gets two separate objects as globals and locals , the code will be executed as if it were embedded in a class definition. This means functions and classes defined in the executed code will not be able to access variables assigned at the top level (as the “top level” variables are treated as class variables in a class definition). If the globals dictionary does not contain a value for the key __builtins__ , a reference to the dictionary of the built-in module builtins is inserted under that key. That way you can control what builtins are available to the executed code by inserting your own __builtins__ dictionary into globals before passing it to exec() . The closure argument specifies a closure–a tuple of cellvars. It’s only valid when the object is a code object containing free (closure) variables . The length of the tuple must exactly match the length of the code object’s co_freevars attribute. Raises an auditing event exec with the code object as the argument. Code compilation events may also be raised. Note The built-in functions globals() and locals() return the current global and local namespace, respectively, which may be useful to pass around for use as the second and third argument to exec() . Note The default locals act as described for function locals() below. Pass an explicit locals dictionary if you need to see effects of the code on locals after function exec() returns. Changed in version 3.11: Added the closure parameter. Changed in version 3.13: The globals and locals arguments can now be passed as keywords. Changed in version 3.13: The semantics of the default locals namespace have been adjusted as described for the locals() builtin. filter ( function , iterable , / ) ¶ Construct an iterator from those elements of iterable for which function is true. iterable may be either a sequence, a container which supports iteration, or an iterator. If function is None , the identity function is assumed, that is, all elements of iterable that are false are removed. Note that filter(function, iterable) is equivalent to the generator expression (item for item in iterable if function(item)) if function is not None and (item for item in iterable if item) if function is None . See itertools.filterfalse() for the complementary function that returns elements of iterable for which function is false. class float ( number = 0.0 , / ) ¶ class float ( string , / ) Return a floating-point number constructed from a number or a string. Examples: >>> float ( '+1.23' ) 1.23 >>> float ( ' -12345 \n ' ) -12345.0 >>> float ( '1e-003' ) 0.001 >>> float ( '+1E6' ) 1000000.0 >>> float ( '-Infinity' ) -inf If the argument is a string, it should contain a decimal number, optionally preceded by a sign, and optionally embedded in whitespace. The optional sign may be '+' or '-' ; a '+' sign has no effect on the value produced. The argument may also be a string representing a NaN (not-a-number), or positive or negative infinity. More precisely, the input must conform to the floatvalue production rule in the following grammar, after leading and trailing whitespace characters are removed: sign : "+" | "-" infinity : "Infinity" | "inf" nan : "nan" digit : <a Unicode decimal digit, i.e. characters in Unicode general category Nd> digitpart : digit ([ "_" ] digit )* number : [ digitpart ] "." digitpart | digitpart [ "." ] exponent : ( "e" | "E" ) [ sign ] digitpart floatnumber : number [ exponent ] absfloatvalue : floatnumber | infinity | nan floatvalue : [ sign ] absfloatvalue Case is not significant, so, for example, “inf”, “Inf”, “INFINITY”, and “iNfINity” are all acceptable spellings for positive infinity. Otherwise, if the argument is an integer or a floating-point number, a floating-point number with the same value (within Python’s floating-point precision) is returned. If the argument is outside the range of a Python float, an OverflowError will be raised. For a general Python object x , float(x) delegates to x.__float__() . If __float__() is not defined then it falls back to __index__() . See also float.from_number() which only accepts a numeric argument. If no argument is given, 0.0 is returned. The float type is described in Numeric Types — int, float, complex . Changed in version 3.6: Grouping digits with underscores as in code literals is allowed. Changed in version 3.7: The parameter is now positional-only. Changed in version 3.8: Falls back to __index__() if __float__() is not defined. format ( value , format_spec = '' , / ) ¶ Convert a value to a “formatted” representation, as controlled by format_spec . The interpretation of format_spec will depend on the type of the value argument; however, there is a standard formatting syntax that is used by most built-in types: Format Specification Mini-Language . The default format_spec is an empty string which usually gives the same effect as calling str(value) . A call to format(value, format_spec) is translated to type(value).__format__(value, format_spec) which bypasses the instance dictionary when searching for the value’s __format__() method. A TypeError exception is raised if the method search reaches object and the format_spec is non-empty, or if either the format_spec or the return value are not strings. Changed in version 3.4: object().__format__(format_spec) raises TypeError if format_spec is not an empty string. class frozenset ( iterable = () , / ) Return a new frozenset object, optionally with elements taken from iterable . frozenset is a built-in class. See frozenset and Set Types — set, frozenset for documentation about this class. For other containers see the built-in set , list , tuple , and dict classes, as well as the collections module. getattr ( object , name , / ) ¶ getattr ( object , name , default , / ) Return the value of the named attribute of object . name must be a string. If the string is the name of one of the object’s attributes, the result is the value of that attribute. For example, getattr(x, 'foobar') is equivalent to x.foobar . If the named attribute does not exist, default is returned if provided, otherwise AttributeError is raised. name need not be a Python identifier (see setattr() ). Note Since private name mangling happens at compilation time, one must manually mangle a private attribute’s (attributes with two leading underscores) name in order to retrieve it with getattr() . globals ( ) ¶ Return the dictionary implementing the current module namespace. For code within functions, this is set when the function is defined and remains the same regardless of where the function is called. hasattr ( object , name , / ) ¶ The arguments are an object and a string. The result is True if the string is the name of one of the object’s attributes, False if not. (This is implemented by calling getattr(object, name) and seeing whether it raises an AttributeError or not.) hash ( object , / ) ¶ Return the hash value of the object (if it has one). Hash values are integers. They are used to quickly compare dictionary keys during a dictionary lookup. Numeric values that compare equal have the same hash value (even if they are of different types, as is the case for 1 and 1.0). Note For objects with custom __hash__() methods, note that hash() truncates the return value based on the bit width of the host machine. help ( ) ¶ help ( request ) Invoke the built-in help system. (This function is intended for interactive use.) If no argument is given, the interactive help system starts on the interpreter console. If the argument is a string, then the string is looked up as the name of a module, function, class, method, keyword, or documentation topic, and a help page is printed on the console. If the argument is any other kind of object, a help page on the object is generated. Note that if a slash(/) appears in the parameter list of a function when invoking help() , it means that the parameters prior to the slash are positional-only. For more info, see the FAQ entry on positional-only parameters . This function is added to the built-in namespace by the site module. Changed in version 3.4: Changes to pydoc and inspect mean that the reported signatures for callables are now more comprehensive and consistent. hex ( integer , / ) ¶ Convert an integer number to a lowercase hexadecimal string prefixed with “0x”. If integer is not a Python int object, it has to define an __index__() method that returns an integer. Some examples: >>> hex ( 255 ) '0xff' >>> hex ( - 42 ) '-0x2a' If you want to convert an integer number to an uppercase or lower hexadecimal string with prefix or not, you can use either of the following ways: >>> ' %#x ' % 255 , ' %x ' % 255 , ' %X ' % 255 ('0xff', 'ff', 'FF') >>> format ( 255 , '#x' ), format ( 255 , 'x' ), format ( 255 , 'X' ) ('0xff', 'ff', 'FF') >>> f ' { 255 : #x } ' , f ' { 255 : x } ' , f ' { 255 : X } ' ('0xff', 'ff', 'FF') See also format() for more information. See also int() for converting a hexadecimal string to an integer using a base of 16. Note To obtain a hexadecimal string representation for a float, use the float.hex() method. id ( object , / ) ¶ Return the “identity” of an object. This is an integer which is guaranteed to be unique and constant for this object during its lifetime. Two objects with non-overlapping lifetimes may have the same id() value. CPython implementation detail: This is the address of the object in memory. Raises an auditing event builtins.id with argument id . input ( ) ¶ input ( prompt , / ) If the prompt argument is present, it is written to standard output without a trailing newline. The function then reads a line from input, converts it to a string (stripping a trailing newline), and returns that. When EOF is read, EOFError is raised. Example: >>> s = input ( '--> ' ) --> Monty Python's Flying Circus >>> s "Monty Python's Flying Circus" If the readline module was loaded, then input() will use it to provide elaborate line editing and history features. Raises an auditing event builtins.input with argument prompt before reading input Raises an auditing event builtins.input/result with the result after successfully reading input. class int ( number = 0 , / ) ¶ class int ( string , / , base = 10 ) Return an integer object constructed from a number or a string, or return 0 if no arguments are given. Examples: >>> int ( 123.45 ) 123 >>> int ( '123' ) 123 >>> int ( ' -12_345 \n ' ) -12345 >>> int ( 'FACE' , 16 ) 64206 >>> int ( '0xface' , 0 ) 64206 >>> int ( '01110011' , base = 2 ) 115 If the argument defines __int__() , int(x) returns x.__int__() . If the argument defines __index__() , it returns x.__index__() . For floating-point numbers, this truncates towards zero. If the argument is not a number or if base is given, then it must be a string, bytes , or bytearray instance representing an integer in radix base . Optionally, the string can be preceded by + or - (with no space in between), have leading zeros, be surrounded by whitespace, and have single underscores interspersed between digits. A base-n integer string contains digits, each representing a value from 0 to n-1. The values 0–9 can be represented by any Unicode decimal digit. The values 10–35 can be represented by a to z (or A to Z ). The default base is 10. The allowed bases are 0 and 2–36. Base-2, -8, and -16 strings can be optionally prefixed with 0b / 0B , 0o / 0O , or 0x / 0X , as with integer literals in code. For base 0, the string is interpreted in a similar way to an integer literal in code , in that the actual base is 2, 8, 10, or 16 as determined by the prefix. Base 0 also disallows leading zeros: int('010', 0) is not legal, while int('010') and int('010', 8) are. The integer type is described in Numeric Types — int, float, complex . Changed in version 3.4: If base is not an instance of int and the base object has a base.__index__ method, that method is called to obtain an integer for the base. Previous versions used base.__int__ instead of base.__index__ . Changed in version 3.6: Grouping digits with underscores as in code literals is allowed. Changed in version 3.7: The first parameter is now positional-only. Changed in version 3.8: Falls back to __index__() if __int__() is not defined. Changed in version 3.11: int string inputs and string representations can be limited to help avoid denial of service attacks. A ValueError is raised when the limit is exceeded while converting a string to an int or when converting an int into a string would exceed the limit. See the integer string conversion length limitation documentation. Changed in version 3.14: int() no longer delegates to the __trunc__() method. isinstance ( object , classinfo , / ) ¶ Return True if the object argument is an instance of the classinfo argument, or of a (direct, indirect, or virtual ) subclass thereof. If object is not an object of the given type, the function always returns False . If classinfo is a tuple of type objects (or recursively, other such tuples) or a Union Type of multiple types, return True if object is an instance of any of the types. If classinfo is not a type or tuple of types and such tuples, a TypeError exception is raised. TypeError may not be raised for an invalid type if an earlier check succeeds. Changed in version 3.10: classinfo can be a Union Type . issubclass ( class , classinfo , / ) ¶ Return True if class is a subclass (direct, indirect, or virtual ) of classinfo . A class is considered a subclass of itself. classinfo may be a tuple of class objects (or recursively, other such tuples) or a Union Type , in which case return True if class is a subclass of any entry in classinfo . In any other case, a TypeError exception is raised. Changed in version 3.10: classinfo can be a Union Type . iter ( iterable , / ) ¶ iter ( callable , sentinel , / ) Return an iterator object. The first argument is interpreted very differently depending on the presence of the second argument. Without a second argument, the single argument must be a collection object which supports the iterable protocol (the __iter__() method), or it must support the sequence protocol (the __getitem__() method with integer arguments starting at 0 ). If it does not support either of those protocols, TypeError is raised. If the second argument, sentinel , is given, then the first argument must be a callable object. The iterator created in this case will call callable with no arguments for each call to its __next__() method; if the value returned is equal to sentinel , StopIteration will be raised, otherwise the value will be returned. See also Iterator Types . One useful application of the second form of iter() is to build a block-reader. For example, reading fixed-width blocks from a binary database file until the end of file is reached: from functools import partial with open ( 'mydata.db' , 'rb' ) as f : for block in iter ( partial ( f . read , 64 ), b '' ): process_block ( block ) len ( object , / ) ¶ Return the length (the number of items) of an object. The argument may be a sequence (such as a string, bytes, tuple, list, or range) or a collection (such as a dictionary, set, or frozen set). CPython implementation detail: len raises OverflowError on lengths larger than sys.maxsize , such as range(2 ** 100) . class list ( iterable = () , / ) Rather than being a function, list is actually a mutable sequence type, as documented in Lists and Sequence Types — list, tuple, range . locals ( ) ¶ Return a mapping object representing the current local symbol table, with variable names as the keys, and their currently bound references as the values. At module scope, as well as when using exec() or eval() with a single namespace, this function returns the same namespace as globals() . At class scope, it returns the namespace that will be passed to the metaclass constructor. When using exec() or eval() with separate local and global arguments, it returns the local namespace passed in to the function call. In all of the above cases, each call to locals() in a given frame of execution will return the same mapping object. Changes made through the mapping object returned from locals() will be visible as assigned, reassigned, or deleted local variables, and assigning, reassigning, or deleting local variables will immediately affect the contents of the returned mapping object. In an optimized scope (including functions, generators, and coroutines), each call to locals() instead returns a fresh dictionary containing the current bindings of the function’s local variables and any nonlocal cell references. In this case, name binding changes made via the returned dict are not written back to the corresponding local variables or nonlocal cell references, and assigning, reassigning, or deleting local variables and nonlocal cell references does not affect the contents of previously returned dictionaries. Calling locals() as part of a comprehension in a function, generator, or coroutine is equivalent to calling it in the containing scope, except that the comprehension’s initialised iteration variables will be included. In other scopes, it behaves as if the comprehension were running as a nested function. Calling locals() as part of a generator expression is equivalent to calling it in a nested generator function. Changed in version 3.12: The behaviour of locals() in a comprehension has been updated as described in PEP 709 . Changed in version 3.13: As part of PEP 667 , the semantics of mutating the mapping objects returned from this function are now defined. The behavior in optimized scopes is now as described above. Aside from being defined, the behaviour in other scopes remains unchanged from previous versions. map ( function , iterable , / , * iterables , strict = False ) ¶ Return an iterator that applies function to every item of iterable , yielding the results. If additional iterables arguments are passed, function must take that many arguments and is applied to the items from all iterables in parallel. With multiple iterables, the iterator stops when the shortest iterable is exhausted. If strict is True and one of the iterables is exhausted before the others, a ValueError is raised. For cases where the function inputs are already arranged into argument tuples, see itertools.starmap() . Changed in version 3.14: Added the strict parameter. max ( iterable , / , * , key = None ) ¶ max ( iterable , / , * , default , key = None ) max ( arg1 , arg2 , / , * args , key = None ) Return the largest item in an iterable or the largest of two or more arguments. If one positional argument is provided, it should be an iterable . The largest item in the iterable is returned. If two or more positional arguments are provided, the largest of the positional arguments is returned. There are two optional keyword-only arguments. The key argument specifies a one-argument ordering function like that used for list.sort() . The default argument specifies an object to return if the provided iterable is empty. If the iterable is empty and default is not provided, a ValueError is raised. If multiple items are maximal, the function returns the first one encountered. This is consistent with other sort-stability preserving tools such as sorted(iterable, key=keyfunc, reverse=True)[0] and heapq.nlargest(1, iterable, key=keyfunc) . Changed in version 3.4: Added the default keyword-only parameter. Changed in version 3.8: The key can be None . class memoryview ( object ) Return a “memory view” object created from the given argument. See Memory Views for more information. min ( iterable , / , * , key = None ) ¶ min ( iterable , / , * , default , key = None ) min ( arg1 , arg2 , / , * args , key = None ) Return the smallest item in an iterable or the smallest of two or more arguments. If one positional argument is provided, it should be an iterable . The smallest item in the iterable is returned. If two or more positional arguments are provided, the smallest of the positional arguments is returned. There are two optional keyword-only arguments. The key argument specifies a one-argument ordering function like that used for list.sort() . The default argument specifies an object to return if the provided iterable is empty. If the iterable is empty and default is not provided, a ValueError is raised. If multiple items are minimal, the function returns the first one encountered. This is consistent with other sort-stability preserving tools such as sorted(iterable, key=keyfunc)[0] and heapq.nsmallest(1, iterable, key=keyfunc) . Changed in version 3.4: Added the default keyword-only parameter. Changed in version 3.8: The key can be None . next ( iterator , / ) ¶ next ( iterator , default , / ) Retrieve the next item from the iterator by calling its __next__() method. If default is given, it is returned if the iterator is exhausted, otherwise StopIteration is raised. class object ¶ This is the ultimate base class of all other classes. It has methods that are common to all instances of Python classes. When the constructor is called, it returns a new featureless object. The constructor does not accept any arguments. Note object instances do not have __dict__ attributes, so you can’t assign arbitrary attributes to an instance of object . oct ( integer , / ) ¶ Convert an integer number to an octal string prefixed with “0o”. The result is a valid Python expression. If integer is not a Python int object, it has to define an __index__() method that returns an integer. For example: >>> oct ( 8 ) '0o10' >>> oct ( - 56 ) '-0o70' If you want to convert an integer number to an octal string either with the prefix “0o” or not, you can use either of the following ways. >>> ' %#o ' % 10 , ' %o ' % 10 ('0o12', '12') >>> format ( 10 , '#o' ), format ( 10 , 'o' ) ('0o12', '12') >>> f ' { 10 : #o } ' , f ' { 10 : o } ' ('0o12', '12') See also format() for more information. open ( file , mode = 'r' , buffering = -1 , encoding = None , errors = None , newline = None , closefd = True , opener = None ) ¶ Open file and return a corresponding file object . If the file cannot be opened, an OSError is raised. See Reading and Writing Files for more examples of how to use this function. file is a path-like object giving the pathname (absolute or relative to the current working directory) of the file to be opened or an integer file descriptor of the file to be wrapped. (If a file descriptor is given, it is closed when the returned I/O object is closed unless closefd is set to False .) mode is an optional string that specifies the mode in which the file is opened. It defaults to 'r' which means open for reading in text mode. Other common values are 'w' for writing (truncating the file if it already exists), 'x' for exclusive creation, and 'a' for appending (which on some Unix systems, means that all writes append to the end of the file regardless of the current seek position). In text mode, if encoding is not specified the encoding used is platform-dependent: locale.getencoding() is called to get the current locale encoding. (For reading and writing raw bytes use binary mode and leave encoding unspecified.) The available modes are: Character Meaning 'r' open for reading (default) 'w' open for writing, truncating the file first 'x' open for exclusive creation, failing if the file already exists 'a' open for writing, appending to the end of file if it exists 'b' binary mode 't' text mode (default) '+' open for updating (reading and writing) The default mode is 'r' (open for reading text, a synonym of 'rt' ). Modes 'w+' and 'w+b' open and truncate the file. Modes 'r+' and 'r+b' open the file with no truncation. As mentioned in the Overview , Python distinguishes between binary and text I/O. Files opened in binary mode (including 'b' in the mode argument) return contents as bytes objects without any decoding. In text mode (the default, or when 't' is included in the mode argument), the contents of the file are returned as str , the bytes having been first decoded using a platform-dependent encoding or using the specified encoding if given. Note Python doesn’t depend on the underlying operating system’s notion of text files; all the processing is done by Python itself, and is therefore platform-independent. buffering is an optional integer used to set the buffering policy. Pass 0 to switch buffering off (only allowed in binary mode), 1 to select line buffering (only usable when writing in text mode), and an integer > 1 to indicate the size in bytes of a fixed-size chunk buffer. Note that specifying a buffer size this way applies for binary buffered I/O, but TextIOWrapper (i.e., files opened with mode='r+' ) would have another buffering. To disable buffering in TextIOWrapper , consider using the write_through flag for io.TextIOWrapper.reconfigure() . When no buffering argument is given, the default buffering policy works as follows: Binary files are buffered in fixed-size chunks; the size of the buffer is max(min(blocksize, 8 MiB), DEFAULT_BUFFER_SIZE) when the device block size is available. On most systems, the buffer will typically be 128 kilobytes long. “Interactive” text files (files for which isatty() returns True ) use line buffering. Other text files use the policy described above for binary files. encoding is the name of the encoding used to decode or encode the file. This should only be used in text mode. The default encoding is platform dependent (whatever locale.getencoding() returns), but any text encoding supported by Python can be used. See the codecs module for the list of supported encodings. errors is an optional string that specifies how encoding and decoding errors are to be handled—this cannot be used in binary mode. A variety of standard error handlers are available (listed under Error Handlers ), though any error handling name that has | 2026-01-13T08:48:45 |
https://docs.python.org/3/library/pyexpat.html#module-xml.parsers.expat | xml.parsers.expat — Fast XML parsing using Expat — Python 3.14.2 documentation Theme Auto Light Dark Table of Contents xml.parsers.expat — Fast XML parsing using Expat XMLParser Objects ExpatError Exceptions Example Content Model Descriptions Expat error constants Previous topic xml.sax.xmlreader — Interface for XML parsers Next topic Internet Protocols and Support This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Standard Library » Structured Markup Processing Tools » xml.parsers.expat — Fast XML parsing using Expat | Theme Auto Light Dark | xml.parsers.expat — Fast XML parsing using Expat ¶ Note If you need to parse untrusted or unauthenticated data, see XML security . The xml.parsers.expat module is a Python interface to the Expat non-validating XML parser. The module provides a single extension type, xmlparser , that represents the current state of an XML parser. After an xmlparser object has been created, various attributes of the object can be set to handler functions. When an XML document is then fed to the parser, the handler functions are called for the character data and markup in the XML document. This module uses the pyexpat module to provide access to the Expat parser. Direct use of the pyexpat module is deprecated. This module provides one exception and one type object: exception xml.parsers.expat. ExpatError ¶ The exception raised when Expat reports an error. See section ExpatError Exceptions for more information on interpreting Expat errors. exception xml.parsers.expat. error ¶ Alias for ExpatError . xml.parsers.expat. XMLParserType ¶ The type of the return values from the ParserCreate() function. The xml.parsers.expat module contains two functions: xml.parsers.expat. ErrorString ( errno ) ¶ Returns an explanatory string for a given error number errno . xml.parsers.expat. ParserCreate ( encoding = None , namespace_separator = None ) ¶ Creates and returns a new xmlparser object. encoding , if specified, must be a string naming the encoding used by the XML data. Expat doesn’t support as many encodings as Python does, and its repertoire of encodings can’t be extended; it supports UTF-8, UTF-16, ISO-8859-1 (Latin1), and ASCII. If encoding [ 1 ] is given it will override the implicit or explicit encoding of the document. Parsers created through ParserCreate() are called “root” parsers, in the sense that they do not have any parent parser attached. Non-root parsers are created by parser.ExternalEntityParserCreate . Expat can optionally do XML namespace processing for you, enabled by providing a value for namespace_separator . The value must be a one-character string; a ValueError will be raised if the string has an illegal length ( None is considered the same as omission). When namespace processing is enabled, element type names and attribute names that belong to a namespace will be expanded. The element name passed to the element handlers StartElementHandler and EndElementHandler will be the concatenation of the namespace URI, the namespace separator character, and the local part of the name. If the namespace separator is a zero byte ( chr(0) ) then the namespace URI and the local part will be concatenated without any separator. For example, if namespace_separator is set to a space character ( ' ' ) and the following document is parsed: <?xml version="1.0"?> <root xmlns = "http://default-namespace.org/" xmlns:py = "http://www.python.org/ns/" > <py:elem1 /> <elem2 xmlns= "" /> </root> StartElementHandler will receive the following strings for each element: http : // default - namespace . org / root http : // www . python . org / ns / elem1 elem2 Due to limitations in the Expat library used by pyexpat , the xmlparser instance returned can only be used to parse a single XML document. Call ParserCreate for each document to provide unique parser instances. See also The Expat XML Parser Home page of the Expat project. XMLParser Objects ¶ xmlparser objects have the following methods: xmlparser. Parse ( data [ , isfinal ] ) ¶ Parses the contents of the string data , calling the appropriate handler functions to process the parsed data. isfinal must be true on the final call to this method; it allows the parsing of a single file in fragments, not the submission of multiple files. data can be the empty string at any time. xmlparser. ParseFile ( file ) ¶ Parse XML data reading from the object file . file only needs to provide the read(nbytes) method, returning the empty string when there’s no more data. xmlparser. SetBase ( base ) ¶ Sets the base to be used for resolving relative URIs in system identifiers in declarations. Resolving relative identifiers is left to the application: this value will be passed through as the base argument to the ExternalEntityRefHandler() , NotationDeclHandler() , and UnparsedEntityDeclHandler() functions. xmlparser. GetBase ( ) ¶ Returns a string containing the base set by a previous call to SetBase() , or None if SetBase() hasn’t been called. xmlparser. GetInputContext ( ) ¶ Returns the input data that generated the current event as a string. The data is in the encoding of the entity which contains the text. When called while an event handler is not active, the return value is None . xmlparser. ExternalEntityParserCreate ( context [ , encoding ] ) ¶ Create a “child” parser which can be used to parse an external parsed entity referred to by content parsed by the parent parser. The context parameter should be the string passed to the ExternalEntityRefHandler() handler function, described below. The child parser is created with the ordered_attributes and specified_attributes set to the values of this parser. xmlparser. SetParamEntityParsing ( flag ) ¶ Control parsing of parameter entities (including the external DTD subset). Possible flag values are XML_PARAM_ENTITY_PARSING_NEVER , XML_PARAM_ENTITY_PARSING_UNLESS_STANDALONE and XML_PARAM_ENTITY_PARSING_ALWAYS . Return true if setting the flag was successful. xmlparser. UseForeignDTD ( [ flag ] ) ¶ Calling this with a true value for flag (the default) will cause Expat to call the ExternalEntityRefHandler with None for all arguments to allow an alternate DTD to be loaded. If the document does not contain a document type declaration, the ExternalEntityRefHandler will still be called, but the StartDoctypeDeclHandler and EndDoctypeDeclHandler will not be called. Passing a false value for flag will cancel a previous call that passed a true value, but otherwise has no effect. This method can only be called before the Parse() or ParseFile() methods are called; calling it after either of those have been called causes ExpatError to be raised with the code attribute set to errors.codes[errors.XML_ERROR_CANT_CHANGE_FEATURE_ONCE_PARSING] . xmlparser. SetReparseDeferralEnabled ( enabled ) ¶ Warning Calling SetReparseDeferralEnabled(False) has security implications, as detailed below; please make sure to understand these consequences prior to using the SetReparseDeferralEnabled method. Expat 2.6.0 introduced a security mechanism called “reparse deferral” where instead of causing denial of service through quadratic runtime from reparsing large tokens, reparsing of unfinished tokens is now delayed by default until a sufficient amount of input is reached. Due to this delay, registered handlers may — depending of the sizing of input chunks pushed to Expat — no longer be called right after pushing new input to the parser. Where immediate feedback and taking over responsibility of protecting against denial of service from large tokens are both wanted, calling SetReparseDeferralEnabled(False) disables reparse deferral for the current Expat parser instance, temporarily or altogether. Calling SetReparseDeferralEnabled(True) allows re-enabling reparse deferral. Note that SetReparseDeferralEnabled() has been backported to some prior releases of CPython as a security fix. Check for availability of SetReparseDeferralEnabled() using hasattr() if used in code running across a variety of Python versions. Added in version 3.13. xmlparser. GetReparseDeferralEnabled ( ) ¶ Returns whether reparse deferral is currently enabled for the given Expat parser instance. Added in version 3.13. xmlparser objects have the following methods to mitigate some common XML vulnerabilities. xmlparser. SetAllocTrackerActivationThreshold ( threshold , / ) ¶ Sets the number of allocated bytes of dynamic memory needed to activate protection against disproportionate use of RAM. By default, parser objects have an allocation activation threshold of 64 MiB, or equivalently 67,108,864 bytes. An ExpatError is raised if this method is called on a non-root parser. The corresponding lineno and offset should not be used as they may have no special meaning. Added in version 3.14.1. xmlparser. SetAllocTrackerMaximumAmplification ( max_factor , / ) ¶ Sets the maximum amplification factor between direct input and bytes of dynamic memory allocated. The amplification factor is calculated as allocated / direct while parsing, where direct is the number of bytes read from the primary document in parsing and allocated is the number of bytes of dynamic memory allocated in the parser hierarchy. The max_factor value must be a non-NaN float value greater than or equal to 1.0. Amplification factors greater than 100.0 can be observed near the start of parsing even with benign files in practice. In particular, the activation threshold should be carefully chosen to avoid false positives. By default, parser objects have a maximum amplification factor of 100.0. An ExpatError is raised if this method is called on a non-root parser or if max_factor is outside the valid range. The corresponding lineno and offset should not be used as they may have no special meaning. Note The maximum amplification factor is only considered if the threshold that can be adjusted by SetAllocTrackerActivationThreshold() is exceeded. Added in version 3.14.1. xmlparser objects have the following attributes: xmlparser. buffer_size ¶ The size of the buffer used when buffer_text is true. A new buffer size can be set by assigning a new integer value to this attribute. When the size is changed, the buffer will be flushed. xmlparser. buffer_text ¶ Setting this to true causes the xmlparser object to buffer textual content returned by Expat to avoid multiple calls to the CharacterDataHandler() callback whenever possible. This can improve performance substantially since Expat normally breaks character data into chunks at every line ending. This attribute is false by default, and may be changed at any time. Note that when it is false, data that does not contain newlines may be chunked too. xmlparser. buffer_used ¶ If buffer_text is enabled, the number of bytes stored in the buffer. These bytes represent UTF-8 encoded text. This attribute has no meaningful interpretation when buffer_text is false. xmlparser. ordered_attributes ¶ Setting this attribute to a non-zero integer causes the attributes to be reported as a list rather than a dictionary. The attributes are presented in the order found in the document text. For each attribute, two list entries are presented: the attribute name and the attribute value. (Older versions of this module also used this format.) By default, this attribute is false; it may be changed at any time. xmlparser. specified_attributes ¶ If set to a non-zero integer, the parser will report only those attributes which were specified in the document instance and not those which were derived from attribute declarations. Applications which set this need to be especially careful to use what additional information is available from the declarations as needed to comply with the standards for the behavior of XML processors. By default, this attribute is false; it may be changed at any time. The following attributes contain values relating to the most recent error encountered by an xmlparser object, and will only have correct values once a call to Parse() or ParseFile() has raised an xml.parsers.expat.ExpatError exception. xmlparser. ErrorByteIndex ¶ Byte index at which an error occurred. xmlparser. ErrorCode ¶ Numeric code specifying the problem. This value can be passed to the ErrorString() function, or compared to one of the constants defined in the errors object. xmlparser. ErrorColumnNumber ¶ Column number at which an error occurred. xmlparser. ErrorLineNumber ¶ Line number at which an error occurred. The following attributes contain values relating to the current parse location in an xmlparser object. During a callback reporting a parse event they indicate the location of the first of the sequence of characters that generated the event. When called outside of a callback, the position indicated will be just past the last parse event (regardless of whether there was an associated callback). xmlparser. CurrentByteIndex ¶ Current byte index in the parser input. xmlparser. CurrentColumnNumber ¶ Current column number in the parser input. xmlparser. CurrentLineNumber ¶ Current line number in the parser input. Here is the list of handlers that can be set. To set a handler on an xmlparser object o , use o.handlername = func . handlername must be taken from the following list, and func must be a callable object accepting the correct number of arguments. The arguments are all strings, unless otherwise stated. xmlparser. XmlDeclHandler ( version , encoding , standalone ) ¶ Called when the XML declaration is parsed. The XML declaration is the (optional) declaration of the applicable version of the XML recommendation, the encoding of the document text, and an optional “standalone” declaration. version and encoding will be strings, and standalone will be 1 if the document is declared standalone, 0 if it is declared not to be standalone, or -1 if the standalone clause was omitted. This is only available with Expat version 1.95.0 or newer. xmlparser. StartDoctypeDeclHandler ( doctypeName , systemId , publicId , has_internal_subset ) ¶ Called when Expat begins parsing the document type declaration ( <!DOCTYPE ... ). The doctypeName is provided exactly as presented. The systemId and publicId parameters give the system and public identifiers if specified, or None if omitted. has_internal_subset will be true if the document contains and internal document declaration subset. This requires Expat version 1.2 or newer. xmlparser. EndDoctypeDeclHandler ( ) ¶ Called when Expat is done parsing the document type declaration. This requires Expat version 1.2 or newer. xmlparser. ElementDeclHandler ( name , model ) ¶ Called once for each element type declaration. name is the name of the element type, and model is a representation of the content model. xmlparser. AttlistDeclHandler ( elname , attname , type , default , required ) ¶ Called for each declared attribute for an element type. If an attribute list declaration declares three attributes, this handler is called three times, once for each attribute. elname is the name of the element to which the declaration applies and attname is the name of the attribute declared. The attribute type is a string passed as type ; the possible values are 'CDATA' , 'ID' , 'IDREF' , … default gives the default value for the attribute used when the attribute is not specified by the document instance, or None if there is no default value ( #IMPLIED values). If the attribute is required to be given in the document instance, required will be true. This requires Expat version 1.95.0 or newer. xmlparser. StartElementHandler ( name , attributes ) ¶ Called for the start of every element. name is a string containing the element name, and attributes is the element attributes. If ordered_attributes is true, this is a list (see ordered_attributes for a full description). Otherwise it’s a dictionary mapping names to values. xmlparser. EndElementHandler ( name ) ¶ Called for the end of every element. xmlparser. ProcessingInstructionHandler ( target , data ) ¶ Called for every processing instruction. xmlparser. CharacterDataHandler ( data ) ¶ Called for character data. This will be called for normal character data, CDATA marked content, and ignorable whitespace. Applications which must distinguish these cases can use the StartCdataSectionHandler , EndCdataSectionHandler , and ElementDeclHandler callbacks to collect the required information. Note that the character data may be chunked even if it is short and so you may receive more than one call to CharacterDataHandler() . Set the buffer_text instance attribute to True to avoid that. xmlparser. UnparsedEntityDeclHandler ( entityName , base , systemId , publicId , notationName ) ¶ Called for unparsed (NDATA) entity declarations. This is only present for version 1.2 of the Expat library; for more recent versions, use EntityDeclHandler instead. (The underlying function in the Expat library has been declared obsolete.) xmlparser. EntityDeclHandler ( entityName , is_parameter_entity , value , base , systemId , publicId , notationName ) ¶ Called for all entity declarations. For parameter and internal entities, value will be a string giving the declared contents of the entity; this will be None for external entities. The notationName parameter will be None for parsed entities, and the name of the notation for unparsed entities. is_parameter_entity will be true if the entity is a parameter entity or false for general entities (most applications only need to be concerned with general entities). This is only available starting with version 1.95.0 of the Expat library. xmlparser. NotationDeclHandler ( notationName , base , systemId , publicId ) ¶ Called for notation declarations. notationName , base , and systemId , and publicId are strings if given. If the public identifier is omitted, publicId will be None . xmlparser. StartNamespaceDeclHandler ( prefix , uri ) ¶ Called when an element contains a namespace declaration. Namespace declarations are processed before the StartElementHandler is called for the element on which declarations are placed. xmlparser. EndNamespaceDeclHandler ( prefix ) ¶ Called when the closing tag is reached for an element that contained a namespace declaration. This is called once for each namespace declaration on the element in the reverse of the order for which the StartNamespaceDeclHandler was called to indicate the start of each namespace declaration’s scope. Calls to this handler are made after the corresponding EndElementHandler for the end of the element. xmlparser. CommentHandler ( data ) ¶ Called for comments. data is the text of the comment, excluding the leading '<!- -' and trailing '- ->' . xmlparser. StartCdataSectionHandler ( ) ¶ Called at the start of a CDATA section. This and EndCdataSectionHandler are needed to be able to identify the syntactical start and end for CDATA sections. xmlparser. EndCdataSectionHandler ( ) ¶ Called at the end of a CDATA section. xmlparser. DefaultHandler ( data ) ¶ Called for any characters in the XML document for which no applicable handler has been specified. This means characters that are part of a construct which could be reported, but for which no handler has been supplied. xmlparser. DefaultHandlerExpand ( data ) ¶ This is the same as the DefaultHandler() , but doesn’t inhibit expansion of internal entities. The entity reference will not be passed to the default handler. xmlparser. NotStandaloneHandler ( ) ¶ Called if the XML document hasn’t been declared as being a standalone document. This happens when there is an external subset or a reference to a parameter entity, but the XML declaration does not set standalone to yes in an XML declaration. If this handler returns 0 , then the parser will raise an XML_ERROR_NOT_STANDALONE error. If this handler is not set, no exception is raised by the parser for this condition. xmlparser. ExternalEntityRefHandler ( context , base , systemId , publicId ) ¶ Warning Implementing a handler that accesses local files and/or the network may create a vulnerability to external entity attacks if xmlparser is used with user-provided XML content. Please reflect on your threat model before implementing this handler. Called for references to external entities. base is the current base, as set by a previous call to SetBase() . The public and system identifiers, systemId and publicId , are strings if given; if the public identifier is not given, publicId will be None . The context value is opaque and should only be used as described below. For external entities to be parsed, this handler must be implemented. It is responsible for creating the sub-parser using ExternalEntityParserCreate(context) , initializing it with the appropriate callbacks, and parsing the entity. This handler should return an integer; if it returns 0 , the parser will raise an XML_ERROR_EXTERNAL_ENTITY_HANDLING error, otherwise parsing will continue. If this handler is not provided, external entities are reported by the DefaultHandler callback, if provided. ExpatError Exceptions ¶ ExpatError exceptions have a number of interesting attributes: ExpatError. code ¶ Expat’s internal error number for the specific error. The errors.messages dictionary maps these error numbers to Expat’s error messages. For example: from xml.parsers.expat import ParserCreate , ExpatError , errors p = ParserCreate () try : p . Parse ( some_xml_document ) except ExpatError as err : print ( "Error:" , errors . messages [ err . code ]) The errors module also provides error message constants and a dictionary codes mapping these messages back to the error codes, see below. ExpatError. lineno ¶ Line number on which the error was detected. The first line is numbered 1 . ExpatError. offset ¶ Character offset into the line where the error occurred. The first column is numbered 0 . Example ¶ The following program defines three handlers that just print out their arguments. import xml.parsers.expat # 3 handler functions def start_element ( name , attrs ): print ( 'Start element:' , name , attrs ) def end_element ( name ): print ( 'End element:' , name ) def char_data ( data ): print ( 'Character data:' , repr ( data )) p = xml . parsers . expat . ParserCreate () p . StartElementHandler = start_element p . EndElementHandler = end_element p . CharacterDataHandler = char_data p . Parse ( """<?xml version="1.0"?> <parent id="top"><child1 name="paul">Text goes here</child1> <child2 name="fred">More text</child2> </parent>""" , 1 ) The output from this program is: Start element : parent { 'id' : 'top' } Start element : child1 { 'name' : 'paul' } Character data : 'Text goes here' End element : child1 Character data : ' \n ' Start element : child2 { 'name' : 'fred' } Character data : 'More text' End element : child2 Character data : ' \n ' End element : parent Content Model Descriptions ¶ Content models are described using nested tuples. Each tuple contains four values: the type, the quantifier, the name, and a tuple of children. Children are simply additional content model descriptions. The values of the first two fields are constants defined in the xml.parsers.expat.model module. These constants can be collected in two groups: the model type group and the quantifier group. The constants in the model type group are: xml.parsers.expat.model. XML_CTYPE_ANY The element named by the model name was declared to have a content model of ANY . xml.parsers.expat.model. XML_CTYPE_CHOICE The named element allows a choice from a number of options; this is used for content models such as (A | B | C) . xml.parsers.expat.model. XML_CTYPE_EMPTY Elements which are declared to be EMPTY have this model type. xml.parsers.expat.model. XML_CTYPE_MIXED xml.parsers.expat.model. XML_CTYPE_NAME xml.parsers.expat.model. XML_CTYPE_SEQ Models which represent a series of models which follow one after the other are indicated with this model type. This is used for models such as (A, B, C) . The constants in the quantifier group are: xml.parsers.expat.model. XML_CQUANT_NONE No modifier is given, so it can appear exactly once, as for A . xml.parsers.expat.model. XML_CQUANT_OPT The model is optional: it can appear once or not at all, as for A? . xml.parsers.expat.model. XML_CQUANT_PLUS The model must occur one or more times (like A+ ). xml.parsers.expat.model. XML_CQUANT_REP The model must occur zero or more times, as for A* . Expat error constants ¶ The following constants are provided in the xml.parsers.expat.errors module. These constants are useful in interpreting some of the attributes of the ExpatError exception objects raised when an error has occurred. Since for backwards compatibility reasons, the constants’ value is the error message and not the numeric error code , you do this by comparing its code attribute with errors.codes[errors.XML_ERROR_ CONSTANT_NAME ] . The errors module has the following attributes: xml.parsers.expat.errors. codes ¶ A dictionary mapping string descriptions to their error codes. Added in version 3.2. xml.parsers.expat.errors. messages ¶ A dictionary mapping numeric error codes to their string descriptions. Added in version 3.2. xml.parsers.expat.errors. XML_ERROR_ASYNC_ENTITY ¶ xml.parsers.expat.errors. XML_ERROR_ATTRIBUTE_EXTERNAL_ENTITY_REF ¶ An entity reference in an attribute value referred to an external entity instead of an internal entity. xml.parsers.expat.errors. XML_ERROR_BAD_CHAR_REF ¶ A character reference referred to a character which is illegal in XML (for example, character 0 , or ‘ &#0; ’). xml.parsers.expat.errors. XML_ERROR_BINARY_ENTITY_REF ¶ An entity reference referred to an entity which was declared with a notation, so cannot be parsed. xml.parsers.expat.errors. XML_ERROR_DUPLICATE_ATTRIBUTE ¶ An attribute was used more than once in a start tag. xml.parsers.expat.errors. XML_ERROR_INCORRECT_ENCODING ¶ xml.parsers.expat.errors. XML_ERROR_INVALID_TOKEN ¶ Raised when an input byte could not properly be assigned to a character; for example, a NUL byte (value 0 ) in a UTF-8 input stream. xml.parsers.expat.errors. XML_ERROR_JUNK_AFTER_DOC_ELEMENT ¶ Something other than whitespace occurred after the document element. xml.parsers.expat.errors. XML_ERROR_MISPLACED_XML_PI ¶ An XML declaration was found somewhere other than the start of the input data. xml.parsers.expat.errors. XML_ERROR_NO_ELEMENTS ¶ The document contains no elements (XML requires all documents to contain exactly one top-level element).. xml.parsers.expat.errors. XML_ERROR_NO_MEMORY ¶ Expat was not able to allocate memory internally. xml.parsers.expat.errors. XML_ERROR_PARAM_ENTITY_REF ¶ A parameter entity reference was found where it was not allowed. xml.parsers.expat.errors. XML_ERROR_PARTIAL_CHAR ¶ An incomplete character was found in the input. xml.parsers.expat.errors. XML_ERROR_RECURSIVE_ENTITY_REF ¶ An entity reference contained another reference to the same entity; possibly via a different name, and possibly indirectly. xml.parsers.expat.errors. XML_ERROR_SYNTAX ¶ Some unspecified syntax error was encountered. xml.parsers.expat.errors. XML_ERROR_TAG_MISMATCH ¶ An end tag did not match the innermost open start tag. xml.parsers.expat.errors. XML_ERROR_UNCLOSED_TOKEN ¶ Some token (such as a start tag) was not closed before the end of the stream or the next token was encountered. xml.parsers.expat.errors. XML_ERROR_UNDEFINED_ENTITY ¶ A reference was made to an entity which was not defined. xml.parsers.expat.errors. XML_ERROR_UNKNOWN_ENCODING ¶ The document encoding is not supported by Expat. xml.parsers.expat.errors. XML_ERROR_UNCLOSED_CDATA_SECTION ¶ A CDATA marked section was not closed. xml.parsers.expat.errors. XML_ERROR_EXTERNAL_ENTITY_HANDLING ¶ xml.parsers.expat.errors. XML_ERROR_NOT_STANDALONE ¶ The parser determined that the document was not “standalone” though it declared itself to be in the XML declaration, and the NotStandaloneHandler was set and returned 0 . xml.parsers.expat.errors. XML_ERROR_UNEXPECTED_STATE ¶ xml.parsers.expat.errors. XML_ERROR_ENTITY_DECLARED_IN_PE ¶ xml.parsers.expat.errors. XML_ERROR_FEATURE_REQUIRES_XML_DTD ¶ An operation was requested that requires DTD support to be compiled in, but Expat was configured without DTD support. This should never be reported by a standard build of the xml.parsers.expat module. xml.parsers.expat.errors. XML_ERROR_CANT_CHANGE_FEATURE_ONCE_PARSING ¶ A behavioral change was requested after parsing started that can only be changed before parsing has started. This is (currently) only raised by UseForeignDTD() . xml.parsers.expat.errors. XML_ERROR_UNBOUND_PREFIX ¶ An undeclared prefix was found when namespace processing was enabled. xml.parsers.expat.errors. XML_ERROR_UNDECLARING_PREFIX ¶ The document attempted to remove the namespace declaration associated with a prefix. xml.parsers.expat.errors. XML_ERROR_INCOMPLETE_PE ¶ A parameter entity contained incomplete markup. xml.parsers.expat.errors. XML_ERROR_XML_DECL ¶ The document contained no document element at all. xml.parsers.expat.errors. XML_ERROR_TEXT_DECL ¶ There was an error parsing a text declaration in an external entity. xml.parsers.expat.errors. XML_ERROR_PUBLICID ¶ Characters were found in the public id that are not allowed. xml.parsers.expat.errors. XML_ERROR_SUSPENDED ¶ The requested operation was made on a suspended parser, but isn’t allowed. This includes attempts to provide additional input or to stop the parser. xml.parsers.expat.errors. XML_ERROR_NOT_SUSPENDED ¶ An attempt to resume the parser was made when the parser had not been suspended. xml.parsers.expat.errors. XML_ERROR_ABORTED ¶ This should not be reported to Python applications. xml.parsers.expat.errors. XML_ERROR_FINISHED ¶ The requested operation was made on a parser which was finished parsing input, but isn’t allowed. This includes attempts to provide additional input or to stop the parser. xml.parsers.expat.errors. XML_ERROR_SUSPEND_PE ¶ xml.parsers.expat.errors. XML_ERROR_RESERVED_PREFIX_XML ¶ An attempt was made to undeclare reserved namespace prefix xml or to bind it to another namespace URI. xml.parsers.expat.errors. XML_ERROR_RESERVED_PREFIX_XMLNS ¶ An attempt was made to declare or undeclare reserved namespace prefix xmlns . xml.parsers.expat.errors. XML_ERROR_RESERVED_NAMESPACE_URI ¶ An attempt was made to bind the URI of one the reserved namespace prefixes xml and xmlns to another namespace prefix. xml.parsers.expat.errors. XML_ERROR_INVALID_ARGUMENT ¶ This should not be reported to Python applications. xml.parsers.expat.errors. XML_ERROR_NO_BUFFER ¶ This should not be reported to Python applications. xml.parsers.expat.errors. XML_ERROR_AMPLIFICATION_LIMIT_BREACH ¶ The limit on input amplification factor (from DTD and entities) has been breached. xml.parsers.expat.errors. XML_ERROR_NOT_STARTED ¶ The parser was tried to be stopped or suspended before it started. Added in version 3.14. Footnotes [ 1 ] The encoding string included in XML output should conform to the appropriate standards. For example, “UTF-8” is valid, but “UTF8” is not. See https://www.w3.org/TR/2006/REC-xml11-20060816/#NT-EncodingDecl and https://www.iana.org/assignments/character-sets/character-sets.xhtml . Table of Contents xml.parsers.expat — Fast XML parsing using Expat XMLParser Objects ExpatError Exceptions Example Content Model Descriptions Expat error constants Previous topic xml.sax.xmlreader — Interface for XML parsers Next topic Internet Protocols and Support This page Report a bug Show source « Navigation index modules | next | previous | Python » 3.14.2 Documentation » The Python Standard Library » Structured Markup Processing Tools » xml.parsers.expat — Fast XML parsing using Expat | Theme Auto Light Dark | © Copyright 2001 Python Software Foundation. This page is licensed under the Python Software Foundation License Version 2. Examples, recipes, and other code in the documentation are additionally licensed under the Zero Clause BSD License. See History and License for more information. The Python Software Foundation is a non-profit corporation. Please donate. Last updated on Jan 13, 2026 (06:19 UTC). Found a bug ? Created using Sphinx 8.2.3. | 2026-01-13T08:48:45 |
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Building Scalable SaaS Products: A Developer's Guide The Coursera–Udemy merger raises a bigger question: how do developers actually learn? 12 Open Source Gems To Become The Ultimate Developer 🔥 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Software Comparisons — What are the differences, pros and cons? This is a list of top posts that members of the community have created. These are the posts folks have generally continued coming back to over and over again, so we created this page to make some of these more discoverable. Hopefully you better understand some of the differences here once you've found the guide you need! Redux vs Context API: When to use them Declarative vs imperative Using then() vs Async/Await in JavaScript Kubernetes Ingress vs Service Mesh Create react app vs Vite Callbacks vs Promises Constructors in Python ( init vs __new ) When to Use Server-Side rendering vs Static Generation in Next.js CSS Modules vs CSS-in-JS. Who wins? append VS appendChild Cloud Run vs App Engine: a head-to-head comparison using facts and science Logical OR (||) vs Nullish Coalescing Operator (??) in JavaScript Server-Side Rendering (SSR) Vs Client-Side Rendering (CSR) Asp Net Core - Rest API Authorization with JWT (Roles Vs Claims Vs Policy) - Step by Step Python GUI, PyQt vs TKinter web3.js vs ethers.js: a Comparison of Web3 Libraries Cookies vs Local Storage vs Session Storage React Router V5 vs V6 LocalStorage vs Cookies: All You Need To Know About Storing JWT Tokens Securely in The Front-End TailwindCSS vs Styled-Components in ReactJs WebSockets vs Long Polling JSX.Element vs ReactElement vs ReactNode useState() vs setState() - Strings, Objects, and Arrays Methods vs Computed in Vue React: class components vs function components Supabase Vs Firebase Pricing and When To Use Which for loop vs .map() for making multiple API calls 🤝 Promise.allSettled() VS Promise.all() in JavaScript 🍭 React vs Vue vs Angular vs Svelte Azure Artifacts vs Build Artifacts vs Pipeline Artifacts: Difference EXPLAINED! When to use Svelte vs SvelteKit vs Sapper? C#, Task.WhenAll vs Parallel.ForEach Map vs MergeMap vs SwitchMap CSS 3 VS Tailwind CSS Serverless Framework vs SAM vs AWS CDK Angular: Setters vs ngOnChanges - which one is better? Interview question: heap vs stack (C#) JS interview in 2 minutes / Static vs Dynamic typing DynamoDB Scan Vs Query Operation Experiment Result componentWillMount() vs componentDidMount() Anonymous Functions vs Named Functions vs Arrow Functions Flexbox - Align Items vs Align Content. Vue vs React: What to choose in 2021? Laravel Jetstream vs Breeze vs Laravel/ui Linux Vs Windows - Why Linux Is Better For Programming & Web Dev (A newbie experience) Fibonacci: Recursion vs Iteration TypedDict vs dataclasses in Python — Epic typing BATTLE! SSR vs CSR Callback vs Promises vs Async Await Poetry vs pip: Or How to Forget Forever "requirements.txt" Cheat Sheet for Beginners Cypress vs WebdriverIO | Which one to pick? Type Aliases vs Interfaces in TypeScript PyQt vs Tkinter (Spanish) Django vs Mern Which one to choose? YYYY vs yyyy - The day the Java Date Formatter hurt my brain JavaScript - debounce vs throttle ⏱ Go: Fiber vs Echo (a developer point) RxJS debounce vs throttle vs audit vs sample — Difference You Should Know Laravel vs Node.js - Which One Is The Best Back-End To Choose In 2021? Composer update Vs Composer Install Concurrency in modern programming languages: Rust vs Go vs Java vs Node.js vs Deno vs .NET 6 Pure vs Impure Functions Git: Theirs vs Ours Angular vs Blazor? A decision aid for web developers in 2022 APIView vs Viewsets PyQt vs Pyside Eager Loading VS Lazy Loading in SQLAlchemy React vs Vue: Popular Front end frameworks in 2022 OpenAPI spec (swagger) v2 vs v3 apt update vs apt upgrade: What's the difference? Framework vs library vs package vs module: The debate What Should You Put in a Constructor vs ngOnInit in Angular Javascript vs memes Ionic vs React Nactive vs Flutter Selenium vs The World Faster Clicker Redux VS React Context: Which one should you choose? Styled components vs Emotion js: A performance perspective Git Submodules vs Monorepos MongoDB: Normalization vs Denormalization PUT vs PATCH & PUT vs POST Laravel vs ASP.NET Framework | Which is Better For Your Project? The last-child vs last-of-type selector in CSS Moq vs NSubstitute - Who is the winner? CSS solutions Battle: Compile time CSS-in-JS vs CSS-in-JS vs CSS Modules vs SASS querySelector vs getElementById Docker CMD vs ENTRYPOINT React Virtualization - react-window vs react-virtuoso The Development vs Production Environments npm vs npx - which to use when? Immediate vs eventual consistency Fleet vs VSCode Laravel breeze vs Jetstream Pug vs EJS? Join vs includes vs eager load vs preload Require vs Assert in Solidity Centralized vs Distributed Systems in a nutshell PyQt vs Tkinter (German) Flutter vs React Native Comparison - Which Use for Your Project in 2022 insertAdjacentHTML vs innerHTML Moment.js vs Luxon Generics vs Function Overloading vs Union Type Arguments in TypeScript Sass vs Scss What’s the difference: A/B Testing VS Blue/Green Deployment? Publisher Subscriber vs Observer pattern with C# VSCode vs Vim Persistent vs Non-Persistent Connections | Creating a Multiplayer Game Server - Part 2 Spread VS Rest Operator package.json vs package-lock.json: do you need both? Double Quotes vs Single Quotes in PHP RxJS operators: retry vs repeat? CAP Theorem: Availability vs consistency Scaling Airflow – Astronomer Vs Cloud Composer Vs Managed Workflows For Apache Airflow MySQL vs MySQLi vs PDO Performance Benchmark, Difference and Security Comparison For PHP devs - PHP Storm vs VSCode Difference Between Message vs Event vs Command Document vs Relational Databases IntelliJ vs Eclipse vs VSCode CSS position fixed vs sticky Telegraf VS Node-Telegram-Bot-API Flatpak vs Snaps vs AppImage vs Packages - Linux packaging formats compared Pytest vs Cypress: A fair fight in UI testing? Inline vs Inline-block vs Block Logging vs Tracing: Why Logs Aren’t Enough to Debug Your Microservices Solidity Gas Optimizations pt.1 - Memory vs Storage Bicep vs ARM templates Nest.js vs Express.js Retry vs Circuit Breaker Custom react hooks vs services Global vs Local State in React The What, Why, and When of Mono-Lambda vs Single Function APIs Frontend vs Backend: Which One Is Right For You? React vs Preact vs Inferno What is the difference between Library vs Framework? Compiling vs Transpiling npm vs yarn vs pnpm commands cheatsheet CPU Bound vs I/O Bound DataBindingUtil.inflate vs View Binding Inflate Includes() vs indexOf() in JavaScript useEffect vs useLayoutEffect: the difference and when to use them Ruby Modules: include vs extend vs prepend OOP vs FP with Javascript CSP vs Actor model for concurrency Rust Concept Clarification: Deref vs AsRef vs Borrow vs Cow Creating a countdown timer RxJS vs Vanilla JS Asynchronous vs Synchronous Programming SOAP vs REST vs gRPC vs GraphQL PyQT vs wxPython: Which GUI module for your project? CSS Drop Shadow vs Box Shadow Infrastructure-as-Code vs Configuration Management TypeScript: type vs interface Head recursion Vs Tail recursion Dev.to VS Hashnode VS Medium: Pick ONE Classes vs Functional components in React The Battle of the Array Titans: Lodash vs Vanilla - An Experiment AWS EventBridge vs S3 Notification Inheritance Vs Delegation JavaScript vs JavaScript. Fight! Interface vs Type in Typescript setTimeout vs setImmediate vs process.nextTick Kotlin vs Python Kotlin Multiplatform vs Flutter: Which One to Choose for Your Apps Supervised Learning vs Unsupervised Learning React Hooks API vs Vue Composition API, as explored through useState DEV VS Hashnode VS Medium: Where Should You Start Your Tech Blog Implementing React Routes (Part -2) Link Vs NavLink Vanilla CSS VS CSS Frameworks Postman vs Insomnia: which API testing tool do you use? Serif vs Sans-serif vs Monospaced Getting started with fp-ts: Either vs Validation Typescript Implicit vs Explicit types CWEs vs OWASP top 10? Understanding Offset vs Cursor based pagination Material Design 1 vs Material Design 2 Signed vs Unsigned Bit Integers: What Does It Mean and What's The Difference? default vs null - which is a better choice, and why? Summary of Flutter vs Tauri SpringBoot2 Blocking Web vs Reactive Web JSON-RPC vs REST for distributed platform APIs Explain RBAC vs ACL Like I'm Five .map() vs .forEach() Difference between Dialogflow CX vs Dialogflow ES API keys vs JWT authorization – Which is best? find() vs filter() Snake Case vs Camel Case AWS vs OCI Object Storage options and comparison MAUI XAML vs MAUI Blazor Pointer vs Reference in C++: The Final Guide Comparing reactivity models - React vs Vue vs Svelte vs MobX vs Solid vs Redux Frontend vs Backend, which do you prefer and why? Remix vs Next.js: A Detailed Comparison NodeJS vs Apache performance battle for the conquest of my ❤️ ⚔️ Functional vs Object Oriented vs Procedural programming Lazy vs Eager Initialization Laravel ORM vs Query Builder vs SQL: SPEED TEST! Concurrency in Go vs Erlang TypeScript ANY vs UNKNOWN—A Deep Dive MVC vs MVP vs MVVM Design Patterns GNOME vs KDE Plasma Database Views vs Table Functions Server Side Rendering vs Static Site Generation vs Incremental Static Regeneration Understanding Rendering in Web Apps: SPA vs MPA 'any' vs 'unknown' in TypeScript 👀 TypeORM - Multiple DB Calls vs Single DB Call JS array vs object vs map Benchmarking Python JSON serializers - json vs ujson vs orjson textContent VS innerText Web2 vs Web3 Opinion: Architect VS Engineer VS Developer Jenkins pipeline: agent vs node? Hibernate Naming Strategies: JPA Specification vs Spring Boot Opinionation Pyqt vs PySide (Spanish) Unique Identifiers: UUID vs NanoID A comparison of state management in React with Mobx vs State lifting Meteor vs Next? A brutally honest answer Git-Flow vs Github-flow Set vs Array Python Packaging: sdist vs bdist JavaScript array methods: Mutator VS Non-mutator and the returning value Uint vs Int. Qual a diferença em Go? Understanding Rendering in Web Apps: CSR vs SSR Flask vs Bottle Web Framework Moment.js vs Intl object PyQt vs Kivy Web3: Truffle VS Hardhat VS Embark VS Brownie The one about CSS vs CSS in JS React Hooks vs Svelte - Why I chose Svelte? TaskEither vs Promise looking for answers !, strapi vs nest js for my next project SOP vs CORS? Pagination in an API: page number vs start index SVG sprites vs CSS background image for multiple instances of icons Javascript Streams vs Generators JS Date vs Moment.js: A Really Simple Comparison AMQP vs HTTP return Task vs return await Task Arrow Function vs Function Front-end vs Back-end, and Static vs Dynamic Websites setImmediate() vs setTimeout() vs process.nextTick() Solace PubSub+ vs Kafka: The Basics Agency VS Product Company: Which One's Right for You? Stateless vs Stateful - Which direction should you take? Clean Architecture vs Vertical Slice Architecture Functional programming vs object oriented programming Using Array.prototype.includes() vs Set.prototype.has() to filter arrays Hot vs Cold Observables Reassignment vs Mutability Database (Schema) migration to Kubernetes - initContainers vs k8s jobs - Gatsby vs Next.JS - What, Why and When? Which is faster: obj.hasOwnProperty(prop) vs Object.keys(obj).includes(prop) React Fragment VS Div Happy coding! 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:45 |
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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Forem is a community of 3,676,891 amazing members We're a blogging-forward open source social network where we learn from one another Create account Log in Home About Contact Other Code of Conduct Privacy Policy Terms of Use Popular Tags #webdev #programming #ai #javascript #beginners #tutorial #python #productivity #devops #react #opensource #discuss #career #aws #machinelearning #architecture #blockchain #security #learning #news #web3 #rust #cloud #api #automation #java #node #typescript #database #kubernetes Forem Your community HQ Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . Forem © 2016 - 2026. Posts Relevant Latest Top Meme Monday Ben Halpern Ben Halpern Ben Halpern Follow Jan 12 Meme Monday # discuss # watercooler # jokes 19 reactions Comments 18 comments 1 min read I tried to capture system audio in the browser. Here's what I learned. Flo Flo Flo Follow Jan 12 I tried to capture system audio in the browser. 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Posts Relevant Latest Top Meme Monday Ben Halpern Ben Halpern Ben Halpern Follow Jan 12 Meme Monday # discuss # watercooler # jokes 19 reactions Comments 18 comments 1 min read I tried to capture system audio in the browser. Here's what I learned. Flo Flo Flo Follow Jan 12 I tried to capture system audio in the browser. 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Manage preferences Report billboard x Get personalized feedback on your portfolio from the Google AI team 🤩 Join the New Year, New You Portfolio Challenge: $3,000 in Prizes + Feedback from Google AI Team (For Winners and Runner Ups!) Jess Lee for The DEV Team ・ Jan 1 #devchallenge #googleaichallenge #career #gemini Happy New Year 🎊 Meme Monday Ben Halpern Ben Halpern Ben Halpern Follow Jan 12 Meme Monday # discuss # watercooler # jokes 19 reactions Comments 18 comments 1 min read I tried to capture system audio in the browser. Here's what I learned. Flo Flo Flo Follow Jan 12 I tried to capture system audio in the browser. Here's what I learned. # api # javascript # learning # webdev 5 reactions Comments Add Comment 2 min read Is an AI Model Software? – A Low‑Level Technical View Ben Santora Ben Santora Ben Santora Follow Jan 12 Is an AI Model Software? – A Low‑Level Technical View # discuss # ai # architecture # software 9 reactions Comments Add Comment 4 min read You can't trust Images anymore pri pri pri Follow Jan 12 You can't trust Images anymore # showdev # computervision 11 reactions Comments Add Comment 4 min read SLMs, LLMs and a Devious Logic Puzzle Test Ben Santora Ben Santora Ben Santora Follow Jan 12 SLMs, LLMs and a Devious Logic Puzzle Test # llm # performance # testing 5 reactions Comments Add Comment 5 min read I Built a Desktop App to Supercharge My TMUX + Claude Code Workflow joe-re joe-re joe-re Follow Jan 12 I Built a Desktop App to Supercharge My TMUX + Claude Code Workflow # claudecode # tauri # productivity # tmux 1 reaction Comments Add Comment 4 min read How I built a "Magic Move" animation engine for Excalidraw from scratch published Behram Behram Behram Follow Jan 12 How I built a "Magic Move" animation engine for Excalidraw from scratch published # react # animation # webdev # opensource 9 reactions Comments 3 comments 3 min read I Debug Code Like I Debug Life (Spoiler: Both Throw Exceptions) Alyssa Alyssa Alyssa Follow Jan 13 I Debug Code Like I Debug Life (Spoiler: Both Throw Exceptions) # discuss # career # programming # beginners 18 reactions Comments 8 comments 2 min read 🌈 Looking for help if possible: I’m Stuck on My TrackMyHRT App (Medication + Symptom Tracker) codebunny20 codebunny20 codebunny20 Follow Jan 12 🌈 Looking for help if possible: I’m Stuck on My TrackMyHRT App (Medication + Symptom Tracker) # discuss # programming # python # opensource 14 reactions Comments 6 comments 2 min read How to Build a Voice AI Agent for HVAC Customer Support: My Experience CallStack Tech CallStack Tech CallStack Tech Follow Jan 13 How to Build a Voice AI Agent for HVAC Customer Support: My Experience # ai # voicetech # machinelearning # webdev Comments Add Comment 14 min read How I built a high-performance Social API with Bun & ElysiaJS on a $5 VPS (handling 3.6k reqs/min) nicomedina nicomedina nicomedina Follow Jan 13 How I built a high-performance Social API with Bun & ElysiaJS on a $5 VPS (handling 3.6k reqs/min) # bunjs # api # javascript # programming 1 reaction Comments 1 comment 2 min read 🐌 “My Spring Boot API Became Slow… Until I Learned Pagination & Sorting” Shashwath S H Shashwath S H Shashwath S H Follow Jan 13 🐌 “My Spring Boot API Became Slow… Until I Learned Pagination & Sorting” # springboot # backend # java # sorting 1 reaction Comments Add Comment 2 min read Shift-Left Reliability Rob Fox Rob Fox Rob Fox Follow Jan 12 Shift-Left Reliability # sre # devops # cicd # platformengineering Comments Add Comment 4 min read Why Version Control Exists: The Pendrive Problem Subhrangsu Bera Subhrangsu Bera Subhrangsu Bera Follow Jan 12 Why Version Control Exists: The Pendrive Problem # vcs # git # github Comments Add Comment 4 min read Why Cloudflare is Right to Stand Against Italy's Piracy Shield Polliog Polliog Polliog Follow Jan 12 Why Cloudflare is Right to Stand Against Italy's Piracy Shield # discuss # cloud # dns # webdev 11 reactions Comments 1 comment 6 min read Odoo Core and the Cost of Reinventing Everything Boga Boga Boga Follow Jan 12 Odoo Core and the Cost of Reinventing Everything # python # odoo # qweb # owl Comments Add Comment 3 min read 🩺 How I Troubleshoot an EC2 Instance in the Real World (Using Instance Diagnostics) Venkata Pavan Vishnu Rachapudi Venkata Pavan Vishnu Rachapudi Venkata Pavan Vishnu Rachapudi Follow for AWS Community Builders Jan 12 🩺 How I Troubleshoot an EC2 Instance in the Real World (Using Instance Diagnostics) # aws # ec2 # linux # cloud 4 reactions Comments Add Comment 5 min read The Vibe Coding Paradox: 5 Surprising Truths About the AI Revolution in Software Juan Guillermo Gomez Torres Juan Guillermo Gomez Torres Juan Guillermo Gomez Torres Follow for Google Developer Experts Jan 12 The Vibe Coding Paradox: 5 Surprising Truths About the AI Revolution in Software # vibecoding # programming # ai 5 reactions Comments Add Comment 7 min read loading... 👋 What's happening this week Dropdown menu What's a billboard? Manage preferences Report billboard Challenges 🤗 Just Launched 🔥 Join the Algolia Agent Studio Challenge: $3,000 in Prizes! Explore how fast, contextual retrieval powers the next generation of AI applications. Happy New Year 🎊 "New Year, New You" Portfolio Challenge: $3,000 in Prizes! Plus direct portfolio feedback from the Google AI team for runner ups! Have a great week ❤️ #discuss Discussion threads targeting the whole community The Death of Architectural Design in Agile 1 comment I Debug Code Like I Debug Life (Spoiler: Both Throw Exceptions) 8 comments Why frontend developers don't wanna write e2e tests New Meme Monday 18 comments Software Testing for BFSI New trending guides/resources The Vibe Coding Paradox I built an app in every frontend framework From Idea to Launch: How Developers Can Build Successful Startups Top Open Source Projects That Will Dominate 2026 Beyond Coding: Your Accountability Buddy with Claude Code Skill Coding Without Pressure: How Slowing Down Helped Me Learn Faster JavaScript Frameworks - Heading into 2026 An Honest Review of Google Antigravity Where we're going, we don't need chatbots: introducing the Antigravity IDE 🚀 5 YouTube Channels Every Programmer Should Follow in 2025! The Complete Full-Stack Developer Roadmap for 2026 🚀 DEV's Worldwide Show and Tell Challenge Presented by Mux: Pitch Your Projects! $3,000 in Prizes. 🎥 Top 10 Productivity Hacks Every Developer Should Know 🚀 Nano-Banana Pro: Prompting Guide & Strategies 5 Terminal Commands That Saved Me Hours of Clicking Linux Without Fanboyism: An Honest Developer’s Perspective I Built a Desktop App That Commits to GitHub So I Don’t Have To Lie About Consistency 6 Must-Read Microservices and Design Patterns Books for Senior Developers Raptor Mini: GitHub Copilot’s New Code-First AI Model That Developers Shouldn’t Ignore I Built a Tool to Stop Wasting Time on Toxic Open Source Projects 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://forem.com/t/career | Career - Forem Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Career Follow Hide This tag is for anything relating to careers! Job offers, workplace conflict, interviews, resumes, promotions, etc. Create Post submission guidelines All articles and discussions should relate to careers in some way. Pretty much everything on dev.to is about our careers in some way. Ideally, though, keep the tag related to getting, leaving, or maintaining a career or job. about #career A career is the field in which you work, while a job is a position held in that field. Related tags include #resume and #portfolio as resources to enhance your #career Older #career posts 1 2 3 4 5 6 7 8 9 … 75 … 833 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu I Debug Code Like I Debug Life (Spoiler: Both Throw Exceptions) Alyssa Alyssa Alyssa Follow Jan 13 I Debug Code Like I Debug Life (Spoiler: Both Throw Exceptions) # discuss # career # programming # beginners 18 reactions Comments 8 comments 2 min read Why "Ownership" is the Best Certification: Building Infrastructure for an AWS Legend Ali-Funk Ali-Funk Ali-Funk Follow Jan 12 Why "Ownership" is the Best Certification: Building Infrastructure for an AWS Legend # aws # community # career # cloud 5 reactions Comments Add Comment 2 min read Applying First-Principles Questioning to a Real Company Interview Question Mohammad-Idrees Mohammad-Idrees Mohammad-Idrees Follow Jan 13 Applying First-Principles Questioning to a Real Company Interview Question # career # interview # systemdesign Comments Add Comment 3 min read I Fired the "One-Click" AI Builders: How I Built a React Portfolio with Gemini (Without Knowing React) Aaditya Thakur Aaditya Thakur Aaditya Thakur Follow Jan 13 I Fired the "One-Click" AI Builders: How I Built a React Portfolio with Gemini (Without Knowing React) # ai # webdev # career # beginners Comments Add Comment 3 min read How to Question Any System Design Problem (With Live Interview Walkthrough) Mohammad-Idrees Mohammad-Idrees Mohammad-Idrees Follow Jan 13 How to Question Any System Design Problem (With Live Interview Walkthrough) # architecture # career # interview # systemdesign Comments Add Comment 4 min read I Fired the "One-Click" AI Builders: How I Built a React Portfolio with Gemini (Without Knowing React) Aaditya Thakur Aaditya Thakur Aaditya Thakur Follow Jan 13 I Fired the "One-Click" AI Builders: How I Built a React Portfolio with Gemini (Without Knowing React) # ai # webdev # career # beginners Comments Add Comment 3 min read What are your goals for the week? #161 Chris Jarvis Chris Jarvis Chris Jarvis Follow Jan 12 What are your goals for the week? #161 # discuss # career # productivity Comments Add Comment 1 min read 7 Small Workflow Tweaks That Actually Helped My Developer Productivity Johannes Millan Johannes Millan Johannes Millan Follow Jan 12 7 Small Workflow Tweaks That Actually Helped My Developer Productivity # productivity # beginners # career # programming 5 reactions Comments 1 comment 2 min read I'm Open Sourcing Two SaaS Apps and Everything I'll Work on This Year Ben Ben Ben Follow Jan 12 I'm Open Sourcing Two SaaS Apps and Everything I'll Work on This Year # career # devjournal # opensource # saas Comments Add Comment 3 min read Why Your Job Isn’t Disappearing—But Your Tasks Are (Part 3: The Career) synthaicode synthaicode synthaicode Follow Jan 12 Why Your Job Isn’t Disappearing—But Your Tasks Are (Part 3: The Career) # ai # career # management # softwaredevelopment 1 reaction Comments Add Comment 3 min read My 2026 Roadmap: How I’m Future-Proofing My Fullstack Career in the Age of AI Aleksandr Fomin Aleksandr Fomin Aleksandr Fomin Follow Jan 12 My 2026 Roadmap: How I’m Future-Proofing My Fullstack Career in the Age of AI # ai # learning # career # careerdevelopment Comments Add Comment 4 min read I realized I was wasting hours applying to “dead” LinkedIn jobs — so I built a tiny fix Salaria Labs Salaria Labs Salaria Labs Follow Jan 12 I realized I was wasting hours applying to “dead” LinkedIn jobs — so I built a tiny fix # buildinpublic # career # productivity # sideprojects Comments Add Comment 2 min read From Writing Code to Teaching AI: The Rise of the AI-Assisted Developer Amit Shrivastava Amit Shrivastava Amit Shrivastava Follow Jan 12 From Writing Code to Teaching AI: The Rise of the AI-Assisted Developer # ai # aiinpractice # career # softwareengineering Comments Add Comment 3 min read C#.NET - day 07 Sabin Sim Sabin Sim Sabin Sim Follow Jan 12 C#.NET - day 07 # programming # learning # csharp # career 1 reaction Comments Add Comment 3 min read How to Write a Resume That Gets Interviews (Not Rejections) Resumemind Resumemind Resumemind Follow Jan 12 How to Write a Resume That Gets Interviews (Not Rejections) # career # interview # tutorial Comments Add Comment 3 min read How I Built a Manual Resume Review System with Spring Boot & Angular Resumemind Resumemind Resumemind Follow Jan 12 How I Built a Manual Resume Review System with Spring Boot & Angular # showdev # angular # career # springboot Comments Add Comment 3 min read What am I doing wrong? Soufiane Amt Soufiane Amt Soufiane Amt Follow Jan 12 What am I doing wrong? # career # webdev # careerdevelopment # programming Comments Add Comment 2 min read Python Selenium and Its Architecture, Significance of the python virtual environment NandithaShri S.k NandithaShri S.k NandithaShri S.k Follow Jan 12 Python Selenium and Its Architecture, Significance of the python virtual environment # webdev # beginners # python # career Comments Add Comment 3 min read The Creator's Paradox in the AI Era: How to Stay Generative When Everything Gets Scraped Narnaiezzsshaa Truong Narnaiezzsshaa Truong Narnaiezzsshaa Truong Follow Jan 11 The Creator's Paradox in the AI Era: How to Stay Generative When Everything Gets Scraped # discuss # ai # productivity # career Comments Add Comment 2 min read **More Than a Bootcamp: Why I Chose the German 'Umschulung' Path into Tech** Ali-Funk Ali-Funk Ali-Funk Follow Jan 11 **More Than a Bootcamp: Why I Chose the German 'Umschulung' Path into Tech** # watercooler # career # devops # beginners Comments Add Comment 3 min read Sharing: How to Build Competitiveness and Soft Skills, and Write a Good Resume Evan Lin Evan Lin Evan Lin Follow Jan 11 Sharing: How to Build Competitiveness and Soft Skills, and Write a Good Resume # learning # beginners # writing # career Comments Add Comment 9 min read Sharing a Good Book: Iwata Asks - The Legendary Life of the Nintendo Savior, From Genius Programmer to President Evan Lin Evan Lin Evan Lin Follow Jan 11 Sharing a Good Book: Iwata Asks - The Legendary Life of the Nintendo Savior, From Genius Programmer to President # learning # gamedev # leadership # career Comments Add Comment 9 min read Sharing a Good Book: Zhang Xiaolong, the WeChat Legend Evan Lin Evan Lin Evan Lin Follow Jan 11 Sharing a Good Book: Zhang Xiaolong, the WeChat Legend # discuss # leadership # product # career Comments Add Comment 10 min read From Stack Overflow to AI Agents: Why I Stopped Fighting and Started Orchestrating in 2025 Carlos Chao(El Frontend) Carlos Chao(El Frontend) Carlos Chao(El Frontend) Follow Jan 11 From Stack Overflow to AI Agents: Why I Stopped Fighting and Started Orchestrating in 2025 # webdev # ai # productivity # career Comments Add Comment 3 min read Golang Interfaces for Inheritance: A LINEbot Example Evan Lin Evan Lin Evan Lin Follow Jan 11 Golang Interfaces for Inheritance: A LINEbot Example # gratitude # fullstack # webdev # career Comments Add Comment 3 min read loading... trending guides/resources Join the New Year, New You Portfolio Challenge: $3,000 in Prizes + Feedback from Google AI Team (... The 2026 Software Developer Roadmap: From Rejections to a Dream Tech Job Bun is joining Anthropic 🔥 Amazon Spring 2026 SDE Internship Interview Guide: OA Patterns & The Ultimate BQ Strategy "2026", AI Users vs The Unemployed. The 2026 Computer Science Playbook: How to Learn, Where to Focus, and What It Really Takes to Get... My 2026 Tech Stack is Boring as Hell (And That is the Point) My 2025 Year in Review Experience-First Portfolio: A New Approach to Showcasing Engineering Skills A Full-Stack Developer Is A Myth 10 Best Coding Interview Practice Tools for 2026 🔥 Dear Junior Coders: Stop Chasing Shiny Objects My 2025 wrap You’ll Learn More in 3 Months on the Job Than 2 Years of Tutorials The ONE Skill I'm Choosing Over LeetCode Grinding in 2025 Creative Web Developer: Updating my Profile/Portfolio as a Senior Web Developer The Day I Stopped Chasing Everything and Found My One Thing Every Way a Startup Can Fail 10 Best AI Interview Helpers for 2026 LeetCode vs. Vibe Coding: The Reality of Interviewing in 2025 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — Your community HQ Home About Contact Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Programming Follow Hide The magic behind computers. 💻 🪄 Create Post Older #programming posts 1 2 3 4 5 6 7 8 9 … 75 … 3611 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu I Debug Code Like I Debug Life (Spoiler: Both Throw Exceptions) Alyssa Alyssa Alyssa Follow Jan 13 I Debug Code Like I Debug Life (Spoiler: Both Throw Exceptions) # discuss # career # programming # beginners 18 reactions Comments 8 comments 2 min read 🌈 Looking for help if possible: I’m Stuck on My TrackMyHRT App (Medication + Symptom Tracker) codebunny20 codebunny20 codebunny20 Follow Jan 12 🌈 Looking for help if possible: I’m Stuck on My TrackMyHRT App (Medication + Symptom Tracker) # discuss # programming # python # opensource 14 reactions Comments 6 comments 2 min read How I built a high-performance Social API with Bun & ElysiaJS on a $5 VPS (handling 3.6k reqs/min) nicomedina nicomedina nicomedina Follow Jan 13 How I built a high-performance Social API with Bun & ElysiaJS on a $5 VPS (handling 3.6k reqs/min) # bunjs # api # javascript # programming 1 reaction Comments 1 comment 2 min read The Vibe Coding Paradox: 5 Surprising Truths About the AI Revolution in Software Juan Guillermo Gomez Torres Juan Guillermo Gomez Torres Juan Guillermo Gomez Torres Follow for Google Developer Experts Jan 12 The Vibe Coding Paradox: 5 Surprising Truths About the AI Revolution in Software # vibecoding # programming # ai 5 reactions Comments Add Comment 7 min read Zig vs Go: init and run Paolo Carraro Paolo Carraro Paolo Carraro Follow Jan 12 Zig vs Go: init and run # zig # go # programming # comparison Comments Add Comment 2 min read Top 8 Fal.AI Alternatives Developers Are Using to Ship AI Apps Emmanuel Mumba Emmanuel Mumba Emmanuel Mumba Follow Jan 13 Top 8 Fal.AI Alternatives Developers Are Using to Ship AI Apps # webdev # programming # ai # javascript 19 reactions Comments 1 comment 6 min read The Secret Life of JavaScript: Identity Aaron Rose Aaron Rose Aaron Rose Follow Jan 13 The Secret Life of JavaScript: Identity # javascript # coding # programming # software 1 reaction Comments Add Comment 3 min read SOLID Design Principle Gokul G.K. Gokul G.K. Gokul G.K. Follow Jan 13 SOLID Design Principle # programming # java # design # solidprinciples 5 reactions Comments Add Comment 5 min read Why Global Undo Sucks: Building Line-Level Undo/Redo for VS Code Namasivaayam L Namasivaayam L Namasivaayam L Follow Jan 12 Why Global Undo Sucks: Building Line-Level Undo/Redo for VS Code # vscode # opensource # extensions # programming 7 reactions Comments Add Comment 4 min read How to Use Claude Opus 4.5 & Gemini 3 for Free with OpenCode 0xkoji 0xkoji 0xkoji Follow Jan 13 How to Use Claude Opus 4.5 & Gemini 3 for Free with OpenCode # ai # opencode # llm # programming Comments Add Comment 2 min read 🧭 Beginner-Friendly Guide 'Minimum Time Visiting All Points' – LeetCode 1266 (C++, Python, JavaScript) Om Shree Om Shree Om Shree Follow Jan 12 🧭 Beginner-Friendly Guide 'Minimum Time Visiting All Points' – LeetCode 1266 (C++, Python, JavaScript) # programming # cpp # python # javascript 10 reactions Comments Add Comment 3 min read Advancing with React: Hooks Deep Dive! (React Day 5) Vasu Ghanta Vasu Ghanta Vasu Ghanta Follow Jan 13 Advancing with React: Hooks Deep Dive! (React Day 5) # react # webdev # programming # javascript 1 reaction Comments Add Comment 5 min read A Production-Ready Monorepo for AI-Native Full-Stack Development gracefullight gracefullight gracefullight Follow Jan 13 A Production-Ready Monorepo for AI-Native Full-Stack Development # vibecoding # programming # webdev # ai 1 reaction Comments Add Comment 2 min read Daylight Saving Time Handling Strategies: A Guide for C# and Python Developers Outdated Dev Outdated Dev Outdated Dev Follow Jan 13 Daylight Saving Time Handling Strategies: A Guide for C# and Python Developers # timezones # programming # dotnet # python Comments Add Comment 11 min read Lambda Durable Functions: Building Workflows That Run for a Year Dinesh Kumar Elumalai Dinesh Kumar Elumalai Dinesh Kumar Elumalai Follow Jan 13 Lambda Durable Functions: Building Workflows That Run for a Year # aws # serverless # lambda # programming Comments Add Comment 6 min read Bridging the Gap: Building a Universal Web Interface for OBD-II Ekong Ikpe Ekong Ikpe Ekong Ikpe Follow Jan 13 Bridging the Gap: Building a Universal Web Interface for OBD-II # webdev # programming # javascript # automotive Comments Add Comment 2 min read Syncing Office 365 & Google Calendar Without OAuth: A GAS Solution Yuto Takashi Yuto Takashi Yuto Takashi Follow Jan 13 Syncing Office 365 & Google Calendar Without OAuth: A GAS Solution # googleappsscripts # programming Comments Add Comment 5 min read Building a Production-Ready Portfolio: Phase-2 — Frontend Bootstrapping & Architecture Setup Sushant Gaurav Sushant Gaurav Sushant Gaurav Follow Jan 13 Building a Production-Ready Portfolio: Phase-2 — Frontend Bootstrapping & Architecture Setup # programming # python # react # webdev Comments Add Comment 5 min read Mutable vs Immutable Objects in Python (Explained Simply) Micheal Angelo Micheal Angelo Micheal Angelo Follow Jan 13 Mutable vs Immutable Objects in Python (Explained Simply) # python # programming # beginners # learning Comments Add Comment 2 min read Jordium GanttChart v1.7.1: Making a Gantt Component Truly Controllable in Vue 3 Nelson Li Nelson Li Nelson Li Follow Jan 13 Jordium GanttChart v1.7.1: Making a Gantt Component Truly Controllable in Vue 3 # webdev # programming # vue # gantt 5 reactions Comments Add Comment 2 min read Building an AI Photo Restoration Tool with Next.js Q1Hang Q1Hang Q1Hang Follow Jan 13 Building an AI Photo Restoration Tool with Next.js # webdev # ai # programming # beginners Comments Add Comment 1 min read Is JS pass-by-value or pass-by-reference? Let's clear the confusion once and for all, from memory basics to modern Immutability. Tihomir Ivanov Tihomir Ivanov Tihomir Ivanov Follow Jan 13 Is JS pass-by-value or pass-by-reference? Let's clear the confusion once and for all, from memory basics to modern Immutability. # javascript # webdev # programming Comments Add Comment 6 min read 7 Small Workflow Tweaks That Actually Helped My Developer Productivity Johannes Millan Johannes Millan Johannes Millan Follow Jan 12 7 Small Workflow Tweaks That Actually Helped My Developer Productivity # productivity # beginners # career # programming 5 reactions Comments 1 comment 2 min read "When you’re not sure what makes you prouder: the software or the demo video" 😅 AI-SymDev Girl AI-SymDev Girl AI-SymDev Girl Follow Jan 13 "When you’re not sure what makes you prouder: the software or the demo video" 😅 # programming # webdev # ai Comments Add Comment 2 min read [Golang] Garbage Collection in General Satyajit Roy Satyajit Roy Satyajit Roy Follow Jan 13 [Golang] Garbage Collection in General # go # programming Comments Add Comment 5 min read loading... trending guides/resources From Idea to Launch: How Developers Can Build Successful Startups Top Open Source Projects That Will Dominate 2026 Beyond Coding: Your Accountability Buddy with Claude Code Skill Coding Without Pressure: How Slowing Down Helped Me Learn Faster Where we're going, we don't need chatbots: introducing the Antigravity IDE 🚀 An Honest Review of Google Antigravity 5 YouTube Channels Every Programmer Should Follow in 2025! The Complete Full-Stack Developer Roadmap for 2026 🚀 Top 10 Productivity Hacks Every Developer Should Know 🚀 5 Terminal Commands That Saved Me Hours of Clicking Linux Without Fanboyism: An Honest Developer’s Perspective I Built a Desktop App That Commits to GitHub So I Don’t Have To Lie About Consistency 6 Must-Read Microservices and Design Patterns Books for Senior Developers How to Design a Rate Limiter in a System Design Interview? The Joy of Code in the Age of Vibe Engineering Web Development Is Meant to Be Built, Not Watched Is "Vibe Coding" Ruining My CS Degree? Building Scalable SaaS Products: A Developer's Guide The Coursera–Udemy merger raises a bigger question: how do developers actually learn? 12 Open Source Gems To Become The Ultimate Developer 🔥 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — Your community HQ Home About Contact Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a blogging-forward open source social network where we learn from one another Log in Create account | 2026-01-13T08:48:46 |
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DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close News Follow Hide Expect to see announcements of new and updated products, services, and features for languages & frameworks. You also will find high-level news relevant to the tech and software development industry covered here. Create Post submission guidelines When to use this tag : new service or product launched service, product, framework, library or language itself got updated (brief summary must be included as well as the source) covering broader tech industry/development news When NOT to use this tag : general news from media to promote people political posts to talk about personal goals (for example "I started to meditate every morning to increase my productivity" is nothing for this tag). about #news Use this tag to announce new products, services, or tools recently launched or updated. Notable changes in frameworks, libraries, or languages are ideal to cover. General tech industry news with a software development slant is also acceptable. This tag is not to be used for promotion of people, personal goals, or news unrelated to software development. Older #news posts 1 2 3 4 5 6 7 8 9 … 75 … 188 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu AI in Assistive Technologies for People with Visual Impairments Tatyana Bayramova, CPACC Tatyana Bayramova, CPACC Tatyana Bayramova, CPACC Follow Jan 12 AI in Assistive Technologies for People with Visual Impairments # discuss # a11y # ai # news 1 reaction Comments Add Comment 2 min read Perl 🐪 Weekly #755 - Does TIOBE help Perl? Gabor Szabo Gabor Szabo Gabor Szabo Follow Jan 12 Perl 🐪 Weekly #755 - Does TIOBE help Perl? # news # perl # programming Comments Add Comment 6 min read [TIL] Typora 1.0 and Now Paid (with Useful Resources) Evan Lin Evan Lin Evan Lin Follow Jan 11 [TIL] Typora 1.0 and Now Paid (with Useful Resources) # news # resources # tooling Comments Add Comment 2 min read LINE Messaging API New Features: Mark as Read API Evan Lin Evan Lin Evan Lin Follow Jan 11 LINE Messaging API New Features: Mark as Read API # news # api # ux Comments Add Comment 5 min read Today I Learned: Generative AI News and Applications, March 21, 2023 Evan Lin Evan Lin Evan Lin Follow Jan 11 Today I Learned: Generative AI News and Applications, March 21, 2023 # news # openai # chatgpt # ai Comments 1 comment 3 min read Embedded Finance Revolution: Tech Giants and Retailers Disrupting Finance Evan Lin Evan Lin Evan Lin Follow Jan 11 Embedded Finance Revolution: Tech Giants and Retailers Disrupting Finance # discuss # news # product Comments Add Comment 3 min read Today I Learned: Google I/O 2023 Developer Keynote Summary Evan Lin Evan Lin Evan Lin Follow Jan 11 Today I Learned: Google I/O 2023 Developer Keynote Summary # news # google # programming # ai Comments Add Comment 2 min read [TIL] What Developers Should Know About WWDC 2023 Evan Lin Evan Lin Evan Lin Follow Jan 11 [TIL] What Developers Should Know About WWDC 2023 # discuss # ios # news Comments Add Comment 2 min read VS Code Plugin for Colab Released by Google Evan Lin Evan Lin Evan Lin Follow Jan 11 VS Code Plugin for Colab Released by Google # news # google # machinelearning # vscode Comments Add Comment 3 min read Notes from the Made by Google Conference Evan Lin Evan Lin Evan Lin Follow Jan 11 Notes from the Made by Google Conference # news # google # rag # android Comments Add Comment 2 min read [TIL] Microsoft Build 2023 Day 1 - Summary Evan Lin Evan Lin Evan Lin Follow Jan 11 [TIL] Microsoft Build 2023 Day 1 - Summary # news # microsoft # chatgpt # ai Comments Add Comment 1 min read Today I Learned: Generative AI News and Applications, March 17, 2023 Evan Lin Evan Lin Evan Lin Follow Jan 11 Today I Learned: Generative AI News and Applications, March 17, 2023 # news # ai # chatgpt Comments Add Comment 1 min read WWDC 2024 Conference Notes Evan Lin Evan Lin Evan Lin Follow Jan 11 WWDC 2024 Conference Notes # news # ai # ios Comments Add Comment 2 min read Building a No-Code VPN Status Monitor: Lessons from VPN Peek Mohamed Shaban Mohamed Shaban Mohamed Shaban Follow Jan 11 Building a No-Code VPN Status Monitor: Lessons from VPN Peek # news # ai # tech # programming Comments Add Comment 2 min read This Week in AI: ChatGPT Health Risks, Programming for LLMs, and Why Indonesia Blocked Grok Ethan Zhang Ethan Zhang Ethan Zhang Follow Jan 11 This Week in AI: ChatGPT Health Risks, Programming for LLMs, and Why Indonesia Blocked Grok # news # ai # chatgpt # security Comments Add Comment 5 min read Game Dev Digest — Issue #313 - Procedural Generation and more Game Dev Digest - The Newsletter On Unity Game Dev Game Dev Digest - The Newsletter On Unity Game Dev Game Dev Digest - The Newsletter On Unity Game Dev Follow Jan 9 Game Dev Digest — Issue #313 - Procedural Generation and more # news # gamedev # unity3d # csharp Comments Add Comment 6 min read Jan 9, 2026 | The Tongyi Weekly: Your weekly dose of cutting-edge AI from Tongyi Lab Tongyi Lab Tongyi Lab Tongyi Lab Follow Jan 9 Jan 9, 2026 | The Tongyi Weekly: Your weekly dose of cutting-edge AI from Tongyi Lab # news # ai # android # ios Comments Add Comment 6 min read تحويل الأفكار إلى حقيقة: كيف تبني وحدات ذكاء اصطناعي مع LangChain و FastAPI و Sevalla Mohamed Shaban Mohamed Shaban Mohamed Shaban Follow Jan 9 تحويل الأفكار إلى حقيقة: كيف تبني وحدات ذكاء اصطناعي مع LangChain و FastAPI و Sevalla # news # ai # tech # programming Comments Add Comment 1 min read December 2025 VS Code Update (Version 1.108) – What’s New and Why It Matters Muhammad Hamid Raza Muhammad Hamid Raza Muhammad Hamid Raza Follow Jan 9 December 2025 VS Code Update (Version 1.108) – What’s New and Why It Matters # news # vscode # tutorial # productivity Comments Add Comment 2 min read If OpenAI Swallows Pinterest: How 200 Billion Intent Images Could Reshape the AI Technology Stack Apnews Apnews Apnews Follow Jan 9 If OpenAI Swallows Pinterest: How 200 Billion Intent Images Could Reshape the AI Technology Stack # news # ai # datascience # openai Comments Add Comment 10 min read Perl 🐪 Weekly #754 - New Year Resolution Gabor Szabo Gabor Szabo Gabor Szabo Follow Jan 5 Perl 🐪 Weekly #754 - New Year Resolution # news # perl # programming Comments Add Comment 6 min read لماذا نعتقد: كيف يمكننا تحسين قدرة النماذج على التفكير Mohamed Shaban Mohamed Shaban Mohamed Shaban Follow Jan 8 لماذا نعتقد: كيف يمكننا تحسين قدرة النماذج على التفكير # news # ai # tech # programming Comments Add Comment 1 min read Not Another Day 0 Like Other Startups Prasad Gite Prasad Gite Prasad Gite Follow Jan 8 Not Another Day 0 Like Other Startups # news # webdev # buildinpublic # career Comments Add Comment 2 min read Deciphering the coordinated GPS-spoofing incidents that disrupted Indian airports Secure10 Secure10 Secure10 Follow Jan 7 Deciphering the coordinated GPS-spoofing incidents that disrupted Indian airports # news # ai # machinelearning # cybersecurity Comments Add Comment 3 min read Apache Data Lakehouse Weekly: December 30, 2025 – January 5, 2026 Alex Merced Alex Merced Alex Merced Follow Jan 6 Apache Data Lakehouse Weekly: December 30, 2025 – January 5, 2026 # news # database # dataengineering # opensource Comments Add Comment 4 min read loading... trending guides/resources Qwen-Image-Edit-2511：人物一致性再上新台阶 Anthropic Bought Bun: Here's What It Really Means for Us Anthropic Just Acquired Bun — And It Signals the Beginning of AI-Native Software Engineering Security Alert: How to Check for the "Shai-Hulud" Compromise Wuzen 2025 Analysis: The Android RAT That's Raising the Bar for Mobile Security Threats Conhecendo as novidades do Angular 21 2025 ChronoEdit: A Complete Guide to Time-Reasoning-Based Image Editing and World Simulation Top 10 GitHub Copilot Updates You Actually Need to Know About 💥 New AWS Lambda Durable Functions – Do they replace Step Functions? Codex vs Claude vs Cursor GitLab Epic Conference Paris Understanding Warp's New Pricing: Your Complete Transition Guide 🚀 AWS Introduces Regional NAT Gateway: Simplifying Outbound Connectivity 🚀 Integrating API Gateway with Private ALB: The New, Simpler, and More Scalable Way December 2025 VS Code Update (Version 1.108) – What’s New and Why It Matters AI Browsers and Prompt Injection: The New Cybersecurity Frontier LoongArch: China’s homegrown CPU architecture that is now in real laptops Cloudflare vs Vercel vs Netlify: The Truth about Edge Performance 2026 Announcing NocoBase 2.0-beta YouTube launches AI-powered Playables Builder beta to let creators design andshare their own games 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — Your community HQ Home About Contact Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a blogging-forward open source social network where we learn from one another Log in Create account | 2026-01-13T08:48:46 |
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