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The worker thread is implemented as a PyQt thread rather than a Python thread since we want to take advantage of the signals and slots mechanism to communicate with the main application. class Worker(QThread): def __init__(self, parent = None): QThread.__init__(self, parent) self.exiting = False self.size = QSize(0, 0) self.stars = 0


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Support for Signals and Slots¶ One of the key features of Qt is its use of signals and slots to communicate between objects. Their use encourages the development of reusable components. A signal is emitted when something of potential interest happens. A slot is a Python callable.


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All data in a Python program is represented by objects or by relations between objects.
Every object has an identity, a type and a value.
CPython implementation detail: For CPython, id x is the memory address where x is stored.
The value of some objects can change.
Objects whose value can change are said to be mutable; objects whose value is unchangeable once they are created are called immutable.
So, immutability is not strictly the same as having an unchangeable value, it is more subtle.
Objects are never explicitly destroyed; however, when they become unreachable they may be garbage-collected.
An implementation is allowed to postpone garbage collection or omit it altogether — it is a matter of implementation quality how garbage collection is implemented, as long as no objects are collected that are still reachable.
CPython implementation detail: CPython currently uses a reference-counting scheme with optional delayed detection of cyclically linked garbage, which collects most objects as soon as they become unreachable, but is not guaranteed to collect garbage containing circular references.
See the documentation of the module for information on controlling the collection of cyclic garbage.
Other implementations act differently and CPython may change.
Do not depend on immediate finalization of objects when they become unreachable so you should always close files explicitly.
It is understood that these resources are freed when the object is garbage-collected, but since garbage collection is not guaranteed to happen, such objects also provide an explicit way to release the external resource, usually a close method.
Programs are strongly recommended to explicitly close such objects.
Some objects contain references to other objects; these are called containers.
Examples of containers are tuples, lists and dictionaries.
In most cases, when we talk about the value of a container, we imply the values, not the identities of the contained objects; however, when we talk about the mutability of a container, only the identities of the immediately contained objects are implied.
So, if an immutable container like a tuple contains a reference to a mutable object, its value changes if that mutable object is changed.
Types affect almost all aspects of object behavior.
Even the importance progressive are which slots object identity is affected in some sense: for immutable types, operations that compute new values may actually return a reference to any existing object with the same type and value, while for mutable objects this is not allowed.
The standard type hierarchy Below is a list of the types that are built into Python.
Extension modules written in C, Java, or other languages, depending on the implementation can define additional types.
Future versions of Python may add types to the type hierarchy e.
Their definition may change in the future.
None This type has a single value.
There is a single object with this value.
This object is accessed through the built-in name None.
It is used to signify the absence of a value in many situations, e.
Its truth value is false.
NotImplemented This type has a single value.
There is a single object with this value.
This object is what are slots in python through the built-in name NotImplemented.
Numeric methods and rich comparison methods should return this value if they do not implement the operation for the operands provided.
The interpreter will then try the reflected operation, or some other fallback, depending on the operator.
Its truth value is true.
See for more details.
Ellipsis This type has a single value.
There is a single object with this value.
This object is accessed through the literal.
Its truth value is true.
These are created by numeric literals and source as results by arithmetic operators and arithmetic built-in functions.
Numeric objects are immutable; once created their value never changes.
Python numbers are of course strongly related to mathematical numbers, but subject to the limitations of numerical representation in computers.
Python distinguishes between integers, floating point numbers, and complex numbers: These represent elements from the mathematical set of integers positive and negative.
There are two types of integers: Integers These represent numbers in an unlimited range, subject to available virtual memory only.
Booleans These represent the truth values False and True.
The two objects representing the values False and True are the only Boolean objects.
The Boolean type is a subtype of the integer type, and Boolean values behave like the values 0 and 1, respectively, in almost all contexts, the exception being that when converted to a string, the strings "False" or "True" are returned, respectively.
The rules for integer representation are intended to give the most meaningful what are slots in python of shift and mask operations involving negative integers.
These represent machine-level double precision floating point numbers.
You are at the mercy of the underlying machine architecture and C or Java implementation for the accepted range click to see more handling of overflow.
Python does not support single-precision floating point numbers; the savings in processor and memory usage that are usually the reason for using these are dwarfed by the overhead of using objects in Python, so there is no reason to complicate the language with two kinds of floating point numbers.
These represent complex numbers as a pair of machine-level double precision floating point numbers.
The same caveats apply as for floating point numbers.
The real and imaginary parts of a complex number z can be retrieved through the read-only attributes z.
Sequences These represent finite ordered sets indexed by non-negative numbers.
The built-in function returns the number of items of a sequence.
When the length of a sequence is n, the index set contains the numbers 0, 1, …, n-1.
When used as an expression, a slice is a sequence of the same type.
This implies that the index set is renumbered so that it starts at 0.
Sequences are distinguished according to their mutability: Immutable sequences An object of an immutable sequence type cannot change once it is created.
If the object contains references to other objects, these other objects may be mutable and may be changed; however, the collection of objects directly referenced by an immutable object cannot change.
The following types are immutable sequences: Strings A string is a sequence of values that represent Unicode code points.
All the code points in the range U+0000 - U+10FFFF can be represented in a string.
The built-in function converts a code point from its string form to an integer in the range 0 - 10FFFF; converts an integer in the range 0 - 10FFFF to the corresponding length 1 string object.
Tuples The items of a tuple are arbitrary Python objects.
Tuples of two or more items are formed by comma-separated lists of expressions.
An empty tuple can be formed by an empty pair of parentheses.
Bytes A bytes object is an immutable array.
Bytes literals like b'abc' and the built-in constructor can be used to create bytes objects.
Also, bytes objects can be decoded to strings via the method.
Mutable sequences Mutable sequences can be changed after they are created.
The subscription and slicing notations can be used as the target of assignment and delete statements.
There are currently two intrinsic mutable sequence types: Lists The items of a list are arbitrary Python objects.
Lists are formed by placing a comma-separated list of expressions in square brackets.
Note that there are no special cases needed to form lists of length 0 or 1.
Byte Arrays A bytearray object is a mutable array.
They here created by the built-in constructor.
Aside from being mutable and hence unhashablebyte arrays otherwise provide the same read more and functionality as immutable objects.
The extension module provides an additional example of a mutable sequence type, as does the module.
Set types These represent unordered, finite sets of unique, immutable objects.
As such, they cannot be indexed by any subscript.
However, they can be iterated over, and the built-in function returns the number of items in a set.
Common uses for sets are fast membership testing, removing duplicates from a sequence, and computing mathematical operations such as intersection, union, difference, and symmetric difference.
For set elements, the same immutability rules apply as for dictionary keys.
Note that numeric types obey the normal rules for numeric comparison: if two numbers compare equal e.
There are currently two intrinsic set types: Sets These represent a mutable set.
They are created by the built-in constructor and can be modified afterwards by several methods, such as add.
Frozen sets These represent an immutable set.
They are created by the built-in constructor.
As a frozenset is immutable andit can be used again as an element of another set, or as a dictionary key.
Mappings These represent finite sets of objects indexed by arbitrary index sets.
The built-in function returns the number of items in a mapping.
There is currently a single intrinsic mapping type: Dictionaries These represent finite sets of objects indexed by nearly arbitrary values.
Numeric types used what are slots in python keys obey the normal rules for numeric comparison: if two numbers compare equal e.
Dictionaries are mutable; they can be created by the {.
} notation see section.
The extension modules and provide additional examples of mapping types, as does the module.
Callable types These are the types to which the function call operation see section can be applied: User-defined functions A user-defined function object is created by a function definition see section.
New in version 3.
Read-only The namespace supporting arbitrary function attributes.
The keys of the dict are the parameter names, and 'return' for the return annotation, if provided.
Function objects also support getting and setting arbitrary attributes, which can be used, for example, to attach metadata to functions.
Regular attribute dot-notation is used to get and set such attributes.
Note that the current implementation only supports function attributes on user-defined functions.
Function attributes on built-in functions may be supported in the future.
This can be used to get the value of the cell, as well as set the value.
Instance methods An instance method object combines a class, a class instance and any callable object normally a user-defined function.
Methods also support accessing but not setting the arbitrary function attributes on the underlying function object.
User-defined method objects may be created when getting an attribute of a class perhaps via an instance of that classif that attribute is a user-defined function object or a class method object.
For instance, when C is a class which contains a definition for a function fand click the following article is an instance of C, calling x.
Note that the transformation from function object to instance method object happens each time the attribute is retrieved from the instance.
In some cases, a fruitful optimization is to assign the attribute to a local variable and call that local variable.
Also notice that this transformation only happens for user-defined functions; other callable objects and all non-callable objects are retrieved without transformation.
It is also important to note that user-defined functions which are attributes of a class instance are not converted to bound methods; this only happens when the function is an attribute of the class.
Generator functions A function or method which uses the statement see section is called a generator function.
When the function executes a statement or falls off the end, a exception is raised and the iterator will have reached the end of the set of values to be returned.
Coroutine functions A function or method which is defined using is called a coroutine function.
Such a function, when called, returns a object.
It may contain expressions, as well as and statements.
See also the section.
Asynchronous generator functions A function or method which is defined using and which uses the statement is called a asynchronous generator function.
Such a function, when called, returns an asynchronous iterator object which can be used in an statement to execute the body of the function.
When the function executes an empty statement or falls off the end, a exception is raised and the asynchronous iterator will have reached the end of the set of values to be yielded.
Built-in functions A built-in function object is a wrapper around a C function.
Examples of built-in functions are and is a standard built-in module.
The number and type of the arguments are determined by the C function.
Built-in methods This is really a different disguise of a built-in function, this time containing an object passed to the C function as an implicit extra argument.
An example of a built-in method is alist.
Classes Classes are callable.
These objects normally act as factories for new instances of themselves, but variations are possible for class types that override.
The arguments of the call are passed to and, in the typical case, to to initialize the new instance.
Class Instances Instances of arbitrary classes can be made callable by defining a method in their class.
Modules Modules are a basic organizational unit of Python code, and are created by the as invoked either by the statement, or by calling functions such as and built-in.
Attribute references are translated to lookups in this dictionary, e.
The attribute may be missing for certain types of modules, such as C modules that are statically linked into the interpreter; for extension modules loaded dynamically from a shared library, it is the pathname of the shared library file.
CPython implementation detail: Because of the way CPython clears module dictionaries, the module dictionary will be cleared when the module falls out of scope even if the dictionary still has live references.
To avoid this, copy the dictionary or keep the module around while using its dictionary directly.
Custom classes Custom class types are typically created by class definitions see section.
A class has a namespace implemented by a dictionary object.
Class attribute references are translated to lookups in this dictionary, e.
When the attribute name is not found there, the attribute search continues in the base classes.
Additional details on the C3 MRO used by Python can be found in the documentation accompanying the 2.
When it would yield a static method object, it is transformed into the object wrapped by the static method object.
See section for another way in which attributes retrieved from a class may differ from those actually contained in its.
A class object can be called see above to yield a class instance see below.
Class instances A class instance is created by calling a class object see above.
A class instance has a namespace implemented as a dictionary which is the first place in which attribute references are searched.
If the class has a or method, this is called instead of updating the instance dictionary directly.
Class instances can pretend to be numbers, sequences, or mappings if they have methods with certain special names.
Various shortcuts are available to create file objects: the built-in function, and also, and the method of socket objects and perhaps by other functions or methods provided by extension modules.
Internal types A few types used internally by the interpreter are exposed to the user.
Their definitions may change with future versions of the interpreter, but they are mentioned here for completeness.
Code objects Code objects represent byte-compiled executable Python code, or.
Unlike function objects, code objects are immutable and contain no references directly or indirectly to mutable objects.
Frame objects Frame objects represent execution frames.
They may occur in traceback objects see belowand are also passed to registered trace functions.
Note that this may lead to undefined interpreter behaviour if exceptions raised by the trace function escape to the function being traced.
visit web page objects support one method: frame.
Also, if the frame belonged to a generator, the generator is finalized.
This helps break reference cycles involving frame objects for example when catching an exception and storing its traceback for later use.
New in version 3.
Traceback objects Traceback objects represent a stack trace of an exception.
A traceback object is implicitly created when an exception occurs, and may also be explicitly created by calling.
For implicitly created tracebacks, when the search for an exception handler unwinds the execution stack, at each unwound level a traceback object is inserted in front of the current traceback.
When an exception handler is entered, the stack trace is made available to the program.
It is accessible as the third item of the tuple returned by sys.
When the program contains no suitable handler, the stack trace is written nicely formatted to the standard error stream; if the interpreter is interactive, it is also made available to the user as sys.
The line number and last instruction in the traceback may differ from the line number of its frame object if the exception occurred in a statement with no matching except clause or with a finally clause.
Changed in version 3.
Slice objects Slice objects are used to represent slices for methods.
They are also created by the built-in function.
Special read-only attributes: start is the lower bound; stop is the upper bound; step is the step value; each is None if omitted.
These attributes can have any type.
Slice objects support one method: slice.
It returns a tuple of three integers; respectively these are the start and stop indices and the step or stride length of the slice.
Missing or out-of-bounds indices are handled in a manner consistent with regular slices.
Static method objects Static method objects provide a way of defeating the transformation of function objects to method objects described above.
A static method object is a wrapper around any other object, usually a user-defined method object.
When a static method object is retrieved from a class or a class instance, the object actually returned is the wrapped object, which is not subject to any further transformation.
Static method objects are not themselves callable, although the objects they wrap usually are.
Static method objects are created by the built-in constructor.
Class method objects A class method object, like a static method object, is a wrapper around another object that alters the way in which that object is retrieved from classes and class instances.
Class method objects are created by the built-in constructor.
Special method names A class can implement certain operations that are invoked by special syntax such as arithmetic operations or subscripting and slicing by defining methods with special names.
Except where mentioned, attempts to execute an operation raise an exception when no appropriate method is defined typically or.
Setting a special method to None indicates that the corresponding operation is not available.
For example, if a class sets to None, the class is not iterable, so calling on its instances will raise a without falling back to.
When implementing a class that emulates any built-in type, it is important that the emulation only be implemented to the degree that it makes sense for the object being modelled.
For example, some sequences may work well with retrieval of individual elements, but extracting a slice may not make sense.
The remaining arguments are those passed to the object constructor expression the call to the class.
The return value of should be the new object slot machine bonus wins youtube channel usually an instance of cls.
It is also commonly overridden in custom metaclasses in order to customize class creation.
The arguments are those passed to the class constructor expression.
Because and work together in constructing objects to create it, and to customize itno non- None value may be returned by ; doing so will cause a to be raised at runtime.
This is also what are slots in python a finalizer or improperly a destructor.
It is possible though not recommended!
This is called object resurrection.
It is implementation-dependent whether is called a second time when a resurrected object is about to be destroyed; the current implementation only calls it once.
It is not guaranteed that methods are called for objects that still exist when the interpreter exits.
CPython implementation detail: It is possible for a reference cycle to prevent the reference count of an object from going to zero.
In this case, the cycle will be later detected and deleted by the.
A common cause of reference cycles is when an what are the best slot machine games has been caught in a local variable.
Warning Due to the precarious circumstances under which methods are invoked, exceptions that occur during their execution are ignored, and a warning is printed to sys.
If needs to take a lock or invoke any other blocking resource, it may deadlock as the resource may already be taken by the code that gets interrupted to execute.
As a consequence, the global variables it needs to access including other modules may already have been deleted or set to None.
Python guarantees that globals whose name begins with a single underscore are deleted from their module before other globals are deleted; if no other references to such globals exist, this may help in assuring that imported modules are still available at the time when the method is called.
If at all possible, this should look like a valid Python expression that could be used to recreate an object with the same value given an appropriate environment.
If this is not possible, a string of the form should be returned.
The return value must be a string object.
This is typically used for debugging, so it is important that the representation is information-rich and unambiguous.
The return value must be a object.
This method differs from in that there is no expectation that return a valid Python expression: a more convenient or concise representation can be used.
The default implementation defined by the built-in type calls.
This should return a object.
See for a description of the standard formatting syntax.
The return value must be a string object.
Changed in version 3.
Changed in version 3.
A rich comparison method may return the singleton NotImplemented if it does not implement the operation for a given pair of arguments.
By convention, False and True are returned for a successful comparison.
However, these methods can return any value, so if the comparison operator is used in a Boolean context e.
By default, delegates to and inverts the result unless it is NotImplemented.
To automatically generate ordering operations from a single root operation, see.
See the paragraph on for some important notes on creating objects which support custom comparison operations and are usable as dictionary keys.
Virtual subclassing is not considered.
The only required property is that objects which compare equal have the same hash value; it is advised to mix together the hash values of the components of the object that also play a part in comparison of objects by packing them into a tuple and hashing the tuple.
This is typically 8 bytes on 64-bit builds and 4 bytes on 32-bit builds.
An easy way to do this is with python -c "import sys; print sys.
If a class does not define an method it should not define a operation either; if it defines but notits instances will not be usable as items in hashable collections.
User-defined classes have and methods by default; with them, all objects compare unequal except with themselves and x.
A class that overrides and does not define will have its implicitly set to None.
When the method of a class is None, instances of the class will raise an appropriate when a program attempts to retrieve their hash value, and will also be correctly identified as unhashable when checking isinstance obj, collections.
A class which defines its own that explicitly raises a would be incorrectly identified as hashable by an isinstance obj, collections.
Although they remain constant within an individual Python process, they are not predictable between repeated invocations of Python.
Changing hash values affects the iteration order of sets.
Python has never made guarantees about this ordering and it typically varies between 32-bit and 64-bit builds.
Changed in version 3.
When this method is not defined, is called, if it is defined, and the object is considered true if its result is nonzero.
If a class defines neither norall its instances are considered true.
Customizing attribute access The following methods can be defined to customize the meaning of attribute access use of, assignment to, or deletion of x.
This method should either return the computed attribute value or raise an exception.
Note that if the attribute is found through the normal mechanism, is not called.
This is an intentional asymmetry between and.
This is done both for efficiency reasons and because otherwise would have no way to access other attributes of the instance.
Note that at least for instance variables, you can fake total control by not inserting any values in the instance attribute dictionary but instead inserting them in another object.
See the method below for a way to actually get total control over attribute access.
If the class also definesthe latter will not be called unless either calls it explicitly all slots are the pci raises an.
This method should return the computed attribute value or raise an exception.
In order to avoid infinite recursion in this method, its implementation should always call the base class method with the same name to access any attributes it needs, for example, object.
Note This method may still be bypassed when looking up special methods as the result of implicit invocation via language syntax or built-in functions.
This is called instead of the normal mechanism i.
If wants to assign to an instance attribute, it should call the base class method with the same name, for example, object.
This should only be implemented if del obj.
A sequence must be returned.
If an attribute is not found on a module object through the normal lookup, i.
If found, it is called with the attribute name and the result is returned.
If present, this function overrides the standard search on a module.
For a more fine grained customization of the module behavior setting attributes, properties, etc.
This method should return the computed attribute value or raise an exception.
The descriptor has been assigned to name.
New in version 3.
For callables, it may indicate that an instance of the given type or a subclass is expected or required as the first positional argument for example, CPython sets this attribute for unbound methods that are implemented in C.
If any of those methods are defined for an object, it is said to be a descriptor.
However, if the looked-up value is an object defining one of the descriptor methods, then Python may override the default behavior and invoke the descriptor method instead.
Where this occurs in the precedence chain depends on which descriptor methods were defined and how they were called.
The starting point for descriptor invocation is a binding, a.
How the arguments are assembled depends on a: Direct Call The simplest and least common call is when user code directly invokes a descriptor method: what are slots in python />Instance Binding If binding to an object instance, a.
Class Binding If binding to a class, A.
Super Binding If a is an instance ofthen the binding super B, obj.
For instance bindings, the precedence of descriptor invocation depends on the which descriptor methods are defined.
A descriptor can define any combination ofand.
Normally, data descriptors define both andwhile non-data descriptors have just the method.
Data descriptors with and defined always override a redefinition in an instance dictionary.
In contrast, non-data descriptors can be overridden by instances.
Python methods including and are implemented as non-data descriptors.
Accordingly, instances can click here and override methods.
This allows individual instances to acquire behaviors that differ from other instances of the same class.
The function is implemented as a data descriptor.
Accordingly, instances cannot override the behavior of a property.
Attribute lookup speed can be significantly improved as well.
Attempts to assign to an unlisted variable name raises.
This renders the meaning of the program undefined.
In the future, a check may be added to prevent this.
Mappings may also be used; however, in the future, special meaning may be assigned to the values corresponding to each key.
This way, it is possible to write classes which change the behavior of subclasses.
If defined as a normal instance method, this method is implicitly converted to a class method.
The actual metaclass rather are video slot machines legal in texas gas stations the explicit hint can be accessed as type cls.
Metaclasses By default, classes are constructed using.
The class body is executed in a new namespace and the class name is bound locally to the result of type name, bases, namespace.
The class creation process can be customized by passing the metaclass keyword argument in the class definition line, or by inheriting from an existing class that included such an argument.
If found, it is called with the original bases tuple.
This method must return a tuple of classes that will be used instead of this base.
The tuple may be empty, in such case the original base is ignored.
The most derived metaclass is selected from the explicitly specified metaclass if any and the metaclasses i.
The most derived metaclass is one which is a subtype of all of these candidate metaclasses.
If none of the candidate metaclasses meets that criterion, then the class definition will fail with TypeError.
Preparing the class namespace Once the appropriate metaclass has been identified, then the class namespace is prepared.
Executing the class body The class body is executed approximately as exec body, globalsnamespace.
The key difference from a normal call to is that lexical scoping allows the class body including any methods to reference names please click for source the current and outer scopes when the class definition occurs inside a function.
However, even when the class definition occurs inside the function, methods defined inside the class still cannot see names defined at the class scope.
This class object is the one that will be referenced by the zero-argument form of.
This allows the zero argument form of to correctly identify the class being defined based on lexical scoping, while the class or instance that was used to make the current call is identified based on the first argument passed to the method.
CPython implementation detail: In CPython 3.
If present, this must be propagated up to the type.
Failing to do so will result in a in Python 3.
When using the default metaclassor any metaclass that ultimately calls type.
After the class object is created, it is passed to the class decorators included in the class definition if any and the resulting object is bound in the local namespace as the defined class.
When a new class is created by type.
The new copy is wrapped in a read-only proxy, which becomes the attribute of the class object.
Uses for metaclasses The potential uses for metaclasses are boundless.
Customizing instance and subclass checks The following methods are used to override the default behavior of the and built-in functions.
If defined, called to implement isinstance instance, class.
If defined, called to implement issubclass subclass, class.
Note that these methods are looked up on the type metaclass of a class.
They cannot be defined as class methods in the actual class.
This is consistent with the lookup of special methods that are called on instances, only in this case the instance is itself a class.
See also - Introducing Abstract Base Classes Includes the specification for customizing and behavior through andwith motivation for this functionality in the context of adding Abstract Base Classes see the module to the language.
This method is looked up on the class object itself, and when defined in the class body, this method is implicitly a class method.
Note, this mechanism is primarily reserved for use with static type hints, other usage is discouraged.
Emulating callable objects object.
Emulating container types The following methods can be defined to implement container objects.
Containers usually are sequences such as lists or tuples or mappings like dictionariesbut can represent other containers as well.
The module provides a abstract base class to help create those methods from a base set of,and keys.
Mutable sequences should provide methods appendcountindexextendinsertpopremovereverse and sortlike Python standard list objects.
Finally, sequence types should implement addition meaning concatenation and multiplication meaning repetition by defining the methods, and described below; they should not define other numerical operators.
It is further recommended that both mappings and sequences implement the method to allow efficient iteration through the container; for mappings, should be the same as keys ; for sequences, it should iterate through the values.
CPython implementation detail: In CPython, the length is required to be at most.
If the length is larger than sys.
To prevent raising OverflowError by truth value testing, an object must define a method.
Should return an estimated length for the object which may be greater or less than the actual length.
This method is purely an optimization and is never required for correctness.
Missing slice items are always filled in with None.
For sequence types, the accepted keys should be integers and slice objects.
Note that the special interpretation of negative indexes if the class wishes to emulate a sequence type is up to the method.
If key is of an inappropriate type, may be raised; if of a value outside the set of indexes for the sequence after any special interpretation of negative valuesshould be raised.
For mapping types, if key is missing not in the containershould be raised.
Note loops expect that an will be raised for illegal indexes to allow proper detection of the end of the sequence.
Same note as for.
This should only be implemented for mappings if the objects support changes to the values for keys, or if new keys can be added, or for sequences if elements can be replaced.
The same exceptions should be raised for improper key values as for the method.
Same note as for.
This should only be implemented for mappings if the objects support removal of keys, or for sequences if elements can be removed from the sequence.
The same exceptions should be raised for improper key values as for the method.
This method should return a new iterator object that can iterate over all the objects in the container.
For mappings, it should iterate over the keys of the container.
Iterator objects also need to implement this method; they are required to return themselves.
For more information on iterator objects, see.
It should return a new iterator object that iterates over all the objects in the container in reverse order.
If the method is not provided, the built-in will fall back to using the sequence protocol and.
Objects that support the sequence protocol should only provide if they can provide an implementation that is more efficient than the one provided by.
The membership test operators and are normally implemented as an iteration through a sequence.
However, container objects can supply the following special method with a more efficient implementation, which also does not require the object be a sequence.
Should return true if item is in self, false otherwise.
For mapping objects, this should consider the keys of the mapping rather than the values or the key-item pairs.
Emulating numeric types The following methods can be defined to emulate numeric objects.
Methods corresponding to operations that are not supported by the particular kind of number implemented e.
For instance, to evaluate the expression x + y, where x is an instance of a class that has an method, x.
The method should be the equivalent to using and ; it should not be related to.
Note that should be defined to accept an optional third argument if the ternary version of the built-in function is to be supported.
If one of those methods does not support the operation with the supplied arguments, it should return NotImplemented.
These functions are only called if the left operand does not support the corresponding operation and the operands are of different types.
For instance, to evaluate the expression x - y, where y is an instance of a class that has an method, y.
Note that ternary will not try calling the coercion rules would become too complicated.
These methods should attempt to do the operation in-place modifying self and return the result which could be, but does not have to be, self.
If a specific method is not defined, the augmented assignment falls back to the normal methods.
In certain situations, augmented assignment can result in unexpected errors seebut this behavior is in fact part of the data model.
Should return a value of the appropriate type.
Presence of this method indicates that the numeric object is an integer type.
Must return an integer.
Note In order to have a coherent integer type class, when is defined should also be defined, and both should return the same value.
If is not defined then the built-in function falls back to.
With Statement Context Managers A context manager is an object that defines the runtime context to be established when executing a statement.
The context manager handles the entry into, and the exit from, the desired runtime context for the execution of the block of code.
Context managers are normally invoked using the with statement described in sectionbut can here be used by directly invoking their methods.
Typical uses of context managers include saving and restoring various kinds of global state, locking and unlocking resources, closing opened files, etc.
For more information on context managers, see.
The parameters describe the exception that caused the context to be exited.
If the context was exited without an exception, all three arguments will be.
If an exception is supplied, and the method wishes to suppress the exception i.
Otherwise, the exception will be processed normally upon exit from this method.
Awaitable Objects An object generally implements an method.
Note The objects returned from generators decorated with or are also awaitable, but they do not implement.
Should be used to implement objects.
For instance, implements this method to be compatible with the expression.
Coroutine Objects objects are objects.
If the coroutine raises an exception, it is propagated by the iterator.
Coroutines should not directly raise unhandled exceptions.
Coroutines also have the methods listed below, which are analogous to those of generators see.
However, unlike generators, coroutines do not directly support iteration.
Changed in version 3.
If value is None, this is equivalent to advancing the iterator returned by.
If value is not None, this method delegates to the method of the iterator that caused the coroutine to suspend.
The result return value,or other exception is the same as when iterating over the return value, described above.
This slot machine bonus wins youtube channel delegates to the method of the click the following article that caused the coroutine to suspend, if it has such a method.
Otherwise, the exception is raised at the suspension point.
The result return value,or other exception is the same as when iterating over the return value, described above.
If the exception is not caught in the coroutine, it propagates back to the caller.
If the coroutine is suspended, this method first delegates to the method of the iterator that caused the coroutine to suspend, if it has such a method.
Then it raises at the suspension point, causing the coroutine to immediately clean itself up.
Finally, the coroutine is marked as having finished executing, even if it was never started.
Coroutine objects are automatically closed using the above process when they are about to be destroyed.
Asynchronous iterators can be used in an statement.
Should raise a error when the iteration is over.
An example of an asynchronous iterable object: class Reader : async def readline self :.
Starting with Python 3.
Returning anything else will result in a error.
Asynchronous context managers can be used in an statement.
The,and methods have special handling for this; others will still raise abut may do so by relying on the behavior that None is not callable.
For operands of the same type, it is assumed that if the non-reflected method such as fails the operation is not supported, which is why the reflected method is not slot machine bonus wins youtube channel />© 2001-2019, Python Software Foundation.
The Python Software Foundation is a non-profit corporation.
Last updated on Jun 17, 2019.

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