How to print instances of a class using print()?
When I try to print an instance of a class, I get an output like this:
How can I make it so that the print will show something custom (e.g. something that includes the a attribute value)? That is, how can I can define how the instances of the class will appear when printed (their string representation)?
See How can I choose a custom string representation for a class itself (not instances of the class)? if you want to define the behaviour for the class itself (in this case, so that print(Test) shows something custom, rather than <class __main__.Test> or similar). (In fact, the technique is essentially the same, but trickier to apply.)
12 Answers 12
The __str__ method is what gets called happens when you print it, and the __repr__ method is what happens when you use the repr() function (or when you look at it with the interactive prompt).
If no __str__ method is given, Python will print the result of __repr__ instead. If you define __str__ but not __repr__ , Python will use what you see above as the __repr__ , but still use __str__ for printing.
As Chris Lutz explains, this is defined by the __repr__ method in your class.
From the documentation of repr() :
For many types, this function makes an attempt to return a string that would yield an object with the same value when passed to eval() , otherwise the representation is a string enclosed in angle brackets that contains the name of the type of the object together with additional information often including the name and address of the object. A class can control what this function returns for its instances by defining a __repr__() method.
Given the following class Test:
..it will act the following way in the Python shell:
If no __str__ method is defined, print(t) (or print(str(t)) ) will use the result of __repr__ instead
If no __repr__ method is defined then the default is used, which is roughly equivalent to:
inspect — Inspect live objects¶
The inspect module provides several useful functions to help get information about live objects such as modules, classes, methods, functions, tracebacks, frame objects, and code objects. For example, it can help you examine the contents of a class, retrieve the source code of a method, extract and format the argument list for a function, or get all the information you need to display a detailed traceback.
There are four main kinds of services provided by this module: type checking, getting source code, inspecting classes and functions, and examining the interpreter stack.
Types and members¶
The getmembers() function retrieves the members of an object such as a class or module. The functions whose names begin with “is” are mainly provided as convenient choices for the second argument to getmembers() . They also help you determine when you can expect to find the following special attributes (see Import-related module attributes for module attributes):
name with which this class was defined
name of module in which this class was defined
name with which this method was defined
function object containing implementation of method
instance to which this method is bound, or None
name of module in which this method was defined
name with which this function was defined
code object containing compiled function bytecode
tuple of any default values for positional or keyword parameters
mapping of any default values for keyword-only parameters
global namespace in which this function was defined
mapping of parameters names to annotations; "return" key is reserved for return annotations.
name of module in which this function was defined
frame object at this level
index of last attempted instruction in bytecode
current line number in Python source code
next inner traceback object (called by this level)
next outer frame object (this frame’s caller)
builtins namespace seen by this frame
code object being executed in this frame
global namespace seen by this frame
index of last attempted instruction in bytecode
current line number in Python source code
local namespace seen by this frame
tracing function for this frame, or None
number of arguments (not including keyword only arguments, * or ** args)
string of raw compiled bytecode
tuple of names of cell variables (referenced by containing scopes)
tuple of constants used in the bytecode
name of file in which this code object was created
number of first line in Python source code
bitmap of CO_* flags, read more here
encoded mapping of line numbers to bytecode indices
tuple of names of free variables (referenced via a function’s closure)
number of positional only arguments
number of keyword only arguments (not including ** arg)
name with which this code object was defined
fully qualified name with which this code object was defined
tuple of names other than arguments and function locals
number of local variables
virtual machine stack space required
tuple of names of arguments and local variables
is the generator running?
object being iterated by yield from , or None
object being awaited on, or None
is the coroutine running?
original name of this function or method
instance to which a method is bound, or None
Changed in version 3.5: Add __qualname__ and gi_yieldfrom attributes to generators.
The __name__ attribute of generators is now set from the function name, instead of the code name, and it can now be modified.
Changed in version 3.7: Add cr_origin attribute to coroutines.
Changed in version 3.10: Add __builtins__ attribute to functions.
Return all the members of an object in a list of (name, value) pairs sorted by name. If the optional predicate argument—which will be called with the value object of each member—is supplied, only members for which the predicate returns a true value are included.
getmembers() will only return class attributes defined in the metaclass when the argument is a class and those attributes have been listed in the metaclass’ custom __dir__() .
Return all the members of an object in a list of (name, value) pairs sorted by name without triggering dynamic lookup via the descriptor protocol, __getattr__ or __getattribute__. Optionally, only return members that satisfy a given predicate.
getmembers_static() may not be able to retrieve all members that getmembers can fetch (like dynamically created attributes) and may find members that getmembers can’t (like descriptors that raise AttributeError). It can also return descriptor objects instead of instance members in some cases.
New in version 3.11.
Return the name of the module named by the file path, without including the names of enclosing packages. The file extension is checked against all of the entries in importlib.machinery.all_suffixes() . If it matches, the final path component is returned with the extension removed. Otherwise, None is returned.
Note that this function only returns a meaningful name for actual Python modules — paths that potentially refer to Python packages will still return None .
Changed in version 3.3: The function is based directly on importlib .
Return True if the object is a module.
inspect. isclass ( object ) ¶
Return True if the object is a class, whether built-in or created in Python code.
inspect. ismethod ( object ) ¶
Return True if the object is a bound method written in Python.
inspect. isfunction ( object ) ¶
Return True if the object is a Python function, which includes functions created by a lambda expression.
inspect. isgeneratorfunction ( object ) ¶
Return True if the object is a Python generator function.
Changed in version 3.8: Functions wrapped in functools.partial() now return True if the wrapped function is a Python generator function.
Return True if the object is a generator.
inspect. iscoroutinefunction ( object ) ¶
Return True if the object is a coroutine function (a function defined with an async def syntax).
New in version 3.5.
Changed in version 3.8: Functions wrapped in functools.partial() now return True if the wrapped function is a coroutine function .
Return True if the object is a coroutine created by an async def function.
New in version 3.5.
Return True if the object can be used in await expression.
Can also be used to distinguish generator-based coroutines from regular generators:
New in version 3.5.
Return True if the object is an asynchronous generator function, for example:
New in version 3.6.
Changed in version 3.8: Functions wrapped in functools.partial() now return True if the wrapped function is a asynchronous generator function.
Return True if the object is an asynchronous generator iterator created by an asynchronous generator function.
New in version 3.6.
Return True if the object is a traceback.
inspect. isframe ( object ) ¶
Return True if the object is a frame.
inspect. iscode ( object ) ¶
Return True if the object is a code.
inspect. isbuiltin ( object ) ¶
Return True if the object is a built-in function or a bound built-in method.
inspect. ismethodwrapper ( object ) ¶
Return True if the type of object is a MethodWrapperType .
New in version 3.11.
Return True if the object is a user-defined or built-in function or method.
inspect. isabstract ( object ) ¶
Return True if the object is an abstract base class.
inspect. ismethoddescriptor ( object ) ¶
Return True if the object is a method descriptor, but not if ismethod() , isclass() , isfunction() or isbuiltin() are true.
This, for example, is true of int.__add__ . An object passing this test has a __get__() method but not a __set__() method, but beyond that the set of attributes varies. A __name__ attribute is usually sensible, and __doc__ often is.
Methods implemented via descriptors that also pass one of the other tests return False from the ismethoddescriptor() test, simply because the other tests promise more – you can, e.g., count on having the __func__ attribute (etc) when an object passes ismethod() .
inspect. isdatadescriptor ( object ) ¶
Return True if the object is a data descriptor.
Data descriptors have a __set__ or a __delete__ method. Examples are properties (defined in Python), getsets, and members. The latter two are defined in C and there are more specific tests available for those types, which is robust across Python implementations. Typically, data descriptors will also have __name__ and __doc__ attributes (properties, getsets, and members have both of these attributes), but this is not guaranteed.
inspect. isgetsetdescriptor ( object ) ¶
Return True if the object is a getset descriptor.
CPython implementation detail: getsets are attributes defined in extension modules via PyGetSetDef structures. For Python implementations without such types, this method will always return False .
Return True if the object is a member descriptor.
CPython implementation detail: Member descriptors are attributes defined in extension modules via PyMemberDef structures. For Python implementations without such types, this method will always return False .
Retrieving source code¶
Get the documentation string for an object, cleaned up with cleandoc() . If the documentation string for an object is not provided and the object is a class, a method, a property or a descriptor, retrieve the documentation string from the inheritance hierarchy. Return None if the documentation string is invalid or missing.
Changed in version 3.5: Documentation strings are now inherited if not overridden.
Return in a single string any lines of comments immediately preceding the object’s source code (for a class, function, or method), or at the top of the Python source file (if the object is a module). If the object’s source code is unavailable, return None . This could happen if the object has been defined in C or the interactive shell.
inspect. getfile ( object ) ¶
Return the name of the (text or binary) file in which an object was defined. This will fail with a TypeError if the object is a built-in module, class, or function.
inspect. getmodule ( object ) ¶
Try to guess which module an object was defined in. Return None if the module cannot be determined.
inspect. getsourcefile ( object ) ¶
Return the name of the Python source file in which an object was defined or None if no way can be identified to get the source. This will fail with a TypeError if the object is a built-in module, class, or function.
inspect. getsourcelines ( object ) ¶
Return a list of source lines and starting line number for an object. The argument may be a module, class, method, function, traceback, frame, or code object. The source code is returned as a list of the lines corresponding to the object and the line number indicates where in the original source file the first line of code was found. An OSError is raised if the source code cannot be retrieved.
Changed in version 3.3: OSError is raised instead of IOError , now an alias of the former.
Return the text of the source code for an object. The argument may be a module, class, method, function, traceback, frame, or code object. The source code is returned as a single string. An OSError is raised if the source code cannot be retrieved.
Changed in version 3.3: OSError is raised instead of IOError , now an alias of the former.
Clean up indentation from docstrings that are indented to line up with blocks of code.
All leading whitespace is removed from the first line. Any leading whitespace that can be uniformly removed from the second line onwards is removed. Empty lines at the beginning and end are subsequently removed. Also, all tabs are expanded to spaces.
Introspecting callables with the Signature object¶
New in version 3.3.
The Signature object represents the call signature of a callable object and its return annotation. To retrieve a Signature object, use the signature() function.
inspect. signature ( callable , * , follow_wrapped = True , globals = None , locals = None , eval_str = False ) ¶
Return a Signature object for the given callable :
Accepts a wide range of Python callables, from plain functions and classes to functools.partial() objects.
For objects defined in modules using stringized annotations ( from __future__ import annotations ), signature() will attempt to automatically un-stringize the annotations using inspect.get_annotations() . The global , locals , and eval_str parameters are passed into inspect.get_annotations() when resolving the annotations; see the documentation for inspect.get_annotations() for instructions on how to use these parameters.
Raises ValueError if no signature can be provided, and TypeError if that type of object is not supported. Also, if the annotations are stringized, and eval_str is not false, the eval() call(s) to un-stringize the annotations could potentially raise any kind of exception.
A slash(/) in the signature of a function denotes that the parameters prior to it are positional-only. For more info, see the FAQ entry on positional-only parameters .
New in version 3.5: follow_wrapped parameter. Pass False to get a signature of callable specifically ( callable.__wrapped__ will not be used to unwrap decorated callables.)
New in version 3.10: globals , locals , and eval_str parameters.
Some callables may not be introspectable in certain implementations of Python. For example, in CPython, some built-in functions defined in C provide no metadata about their arguments.
A Signature object represents the call signature of a function and its return annotation. For each parameter accepted by the function it stores a Parameter object in its parameters collection.
The optional parameters argument is a sequence of Parameter objects, which is validated to check that there are no parameters with duplicate names, and that the parameters are in the right order, i.e. positional-only first, then positional-or-keyword, and that parameters with defaults follow parameters without defaults.
The optional return_annotation argument, can be an arbitrary Python object, is the “return” annotation of the callable.
Signature objects are immutable. Use Signature.replace() to make a modified copy.
Changed in version 3.5: Signature objects are picklable and hashable .
A special class-level marker to specify absence of a return annotation.
An ordered mapping of parameters’ names to the corresponding Parameter objects. Parameters appear in strict definition order, including keyword-only parameters.
Changed in version 3.7: Python only explicitly guaranteed that it preserved the declaration order of keyword-only parameters as of version 3.7, although in practice this order had always been preserved in Python 3.
The “return” annotation for the callable. If the callable has no “return” annotation, this attribute is set to Signature.empty .
Create a mapping from positional and keyword arguments to parameters. Returns BoundArguments if *args and **kwargs match the signature, or raises a TypeError .
bind_partial ( * args , ** kwargs ) ¶
Works the same way as Signature.bind() , but allows the omission of some required arguments (mimics functools.partial() behavior.) Returns BoundArguments , or raises a TypeError if the passed arguments do not match the signature.
replace ( *[, parameters][, return_annotation] ) ¶
Create a new Signature instance based on the instance replace was invoked on. It is possible to pass different parameters and/or return_annotation to override the corresponding properties of the base signature. To remove return_annotation from the copied Signature, pass in Signature.empty .
Return a Signature (or its subclass) object for a given callable obj . Pass follow_wrapped=False to get a signature of obj without unwrapping its __wrapped__ chain. globalns and localns will be used as the namespaces when resolving annotations.
This method simplifies subclassing of Signature :
New in version 3.5.
New in version 3.10: globalns and localns parameters.
Parameter objects are immutable. Instead of modifying a Parameter object, you can use Parameter.replace() to create a modified copy.
Changed in version 3.5: Parameter objects are picklable and hashable .
A special class-level marker to specify absence of default values and annotations.
The name of the parameter as a string. The name must be a valid Python identifier.
CPython implementation detail: CPython generates implicit parameter names of the form .0 on the code objects used to implement comprehensions and generator expressions.
Changed in version 3.6: These parameter names are exposed by this module as names like implicit0 .
The default value for the parameter. If the parameter has no default value, this attribute is set to Parameter.empty .
The annotation for the parameter. If the parameter has no annotation, this attribute is set to Parameter.empty .
Describes how argument values are bound to the parameter. The possible values are accessible via Parameter (like Parameter.KEYWORD_ONLY ), and support comparison and ordering, in the following order:
Value must be supplied as a positional argument. Positional only parameters are those which appear before a / entry (if present) in a Python function definition.
Value may be supplied as either a keyword or positional argument (this is the standard binding behaviour for functions implemented in Python.)
A tuple of positional arguments that aren’t bound to any other parameter. This corresponds to a *args parameter in a Python function definition.
Value must be supplied as a keyword argument. Keyword only parameters are those which appear after a * or *args entry in a Python function definition.
A dict of keyword arguments that aren’t bound to any other parameter. This corresponds to a **kwargs parameter in a Python function definition.
Example: print all keyword-only arguments without default values:
Describes a enum value of Parameter.kind.
New in version 3.8.
Example: print all descriptions of arguments:
Create a new Parameter instance based on the instance replaced was invoked on. To override a Parameter attribute, pass the corresponding argument. To remove a default value or/and an annotation from a Parameter, pass Parameter.empty .
Changed in version 3.4: In Python 3.3 Parameter objects were allowed to have name set to None if their kind was set to POSITIONAL_ONLY . This is no longer permitted.
Result of a Signature.bind() or Signature.bind_partial() call. Holds the mapping of arguments to the function’s parameters.
A mutable mapping of parameters’ names to arguments’ values. Contains only explicitly bound arguments. Changes in arguments will reflect in args and kwargs .
Should be used in conjunction with Signature.parameters for any argument processing purposes.
Arguments for which Signature.bind() or Signature.bind_partial() relied on a default value are skipped. However, if needed, use BoundArguments.apply_defaults() to add them.
Changed in version 3.9: arguments is now of type dict . Formerly, it was of type collections.OrderedDict .
A tuple of positional arguments values. Dynamically computed from the arguments attribute.
A dict of keyword arguments values. Dynamically computed from the arguments attribute.
A reference to the parent Signature object.
Set default values for missing arguments.
For variable-positional arguments ( *args ) the default is an empty tuple.
For variable-keyword arguments ( **kwargs ) the default is an empty dict.
New in version 3.5.
The args and kwargs properties can be used to invoke functions:
The detailed specification, implementation details and examples.
Classes and functions¶
Arrange the given list of classes into a hierarchy of nested lists. Where a nested list appears, it contains classes derived from the class whose entry immediately precedes the list. Each entry is a 2-tuple containing a class and a tuple of its base classes. If the unique argument is true, exactly one entry appears in the returned structure for each class in the given list. Otherwise, classes using multiple inheritance and their descendants will appear multiple times.
inspect. getfullargspec ( func ) ¶
Get the names and default values of a Python function’s parameters. A named tuple is returned:
FullArgSpec(args, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, annotations)
args is a list of the positional parameter names. varargs is the name of the * parameter or None if arbitrary positional arguments are not accepted. varkw is the name of the ** parameter or None if arbitrary keyword arguments are not accepted. defaults is an n-tuple of default argument values corresponding to the last n positional parameters, or None if there are no such defaults defined. kwonlyargs is a list of keyword-only parameter names in declaration order. kwonlydefaults is a dictionary mapping parameter names from kwonlyargs to the default values used if no argument is supplied. annotations is a dictionary mapping parameter names to annotations. The special key "return" is used to report the function return value annotation (if any).
Note that signature() and Signature Object provide the recommended API for callable introspection, and support additional behaviours (like positional-only arguments) that are sometimes encountered in extension module APIs. This function is retained primarily for use in code that needs to maintain compatibility with the Python 2 inspect module API.
Changed in version 3.4: This function is now based on signature() , but still ignores __wrapped__ attributes and includes the already bound first parameter in the signature output for bound methods.
Changed in version 3.6: This method was previously documented as deprecated in favour of signature() in Python 3.5, but that decision has been reversed in order to restore a clearly supported standard interface for single-source Python 2/3 code migrating away from the legacy getargspec() API.
Changed in version 3.7: Python only explicitly guaranteed that it preserved the declaration order of keyword-only parameters as of version 3.7, although in practice this order had always been preserved in Python 3.
Get information about arguments passed into a particular frame. A named tuple ArgInfo(args, varargs, keywords, locals) is returned. args is a list of the argument names. varargs and keywords are the names of the * and ** arguments or None . locals is the locals dictionary of the given frame.
This function was inadvertently marked as deprecated in Python 3.5.
Format a pretty argument spec from the four values returned by getargvalues() . The format* arguments are the corresponding optional formatting functions that are called to turn names and values into strings.
This function was inadvertently marked as deprecated in Python 3.5.
Return a tuple of class cls’s base classes, including cls, in method resolution order. No class appears more than once in this tuple. Note that the method resolution order depends on cls’s type. Unless a very peculiar user-defined metatype is in use, cls will be the first element of the tuple.
Bind the args and kwds to the argument names of the Python function or method func, as if it was called with them. For bound methods, bind also the first argument (typically named self ) to the associated instance. A dict is returned, mapping the argument names (including the names of the * and ** arguments, if any) to their values from args and kwds. In case of invoking func incorrectly, i.e. whenever func(*args, **kwds) would raise an exception because of incompatible signature, an exception of the same type and the same or similar message is raised. For example:
New in version 3.2.
Deprecated since version 3.5: Use Signature.bind() and Signature.bind_partial() instead.
Get the mapping of external name references in a Python function or method func to their current values. A named tuple ClosureVars(nonlocals, globals, builtins, unbound) is returned. nonlocals maps referenced names to lexical closure variables, globals to the function’s module globals and builtins to the builtins visible from the function body. unbound is the set of names referenced in the function that could not be resolved at all given the current module globals and builtins.
TypeError is raised if func is not a Python function or method.
New in version 3.3.
Get the object wrapped by func. It follows the chain of __wrapped__ attributes returning the last object in the chain.
stop is an optional callback accepting an object in the wrapper chain as its sole argument that allows the unwrapping to be terminated early if the callback returns a true value. If the callback never returns a true value, the last object in the chain is returned as usual. For example, signature() uses this to stop unwrapping if any object in the chain has a __signature__ attribute defined.
ValueError is raised if a cycle is encountered.
New in version 3.4.
Compute the annotations dict for an object.
obj may be a callable, class, or module. Passing in an object of any other type raises TypeError .
Returns a dict. get_annotations() returns a new dict every time it’s called; calling it twice on the same object will return two different but equivalent dicts.
This function handles several details for you:
If eval_str is true, values of type str will be un-stringized using eval() . This is intended for use with stringized annotations ( from __future__ import annotations ).
If obj doesn’t have an annotations dict, returns an empty dict. (Functions and methods always have an annotations dict; classes, modules, and other types of callables may not.)
Ignores inherited annotations on classes. If a class doesn’t have its own annotations dict, returns an empty dict.
All accesses to object members and dict values are done using getattr() and dict.get() for safety.
Always, always, always returns a freshly created dict.
eval_str controls whether or not values of type str are replaced with the result of calling eval() on those values:
If eval_str is true, eval() is called on values of type str . (Note that get_annotations doesn’t catch exceptions; if eval() raises an exception, it will unwind the stack past the get_annotations call.)
If eval_str is false (the default), values of type str are unchanged.
globals and locals are passed in to eval() ; see the documentation for eval() for more information. If globals or locals is None , this function may replace that value with a context-specific default, contingent on type(obj) :
If obj is a module, globals defaults to obj.__dict__ .
If obj is a class, globals defaults to sys.modules[obj.__module__].__dict__ and locals defaults to the obj class namespace.
If obj is a callable, globals defaults to obj.__globals__ , although if obj is a wrapped function (using functools.update_wrapper() ) it is first unwrapped.
Calling get_annotations is best practice for accessing the annotations dict of any object. See Annotations Best Practices for more information on annotations best practices.
New in version 3.10.
The interpreter stack¶
Some of the following functions return FrameInfo objects. For backwards compatibility these objects allow tuple-like operations on all attributes except positions . This behavior is considered deprecated and may be removed in the future.
class inspect. FrameInfo ¶ frame ¶
The frame object that the record corresponds to.
The file name associated with the code being executed by the frame this record corresponds to.
The line number of the current line associated with the code being executed by the frame this record corresponds to.
The function name that is being executed by the frame this record corresponds to.
A list of lines of context from the source code that’s being executed by the frame this record corresponds to.
The index of the current line being executed in the code_context list.
A dis.Positions object containing the start line number, end line number, start column offset, and end column offset associated with the instruction being executed by the frame this record corresponds to.
Changed in version 3.5: Return a named tuple instead of a tuple .
Changed in version 3.11: FrameInfo is now a class instance (that is backwards compatible with the previous named tuple ).
The file name associated with the code being executed by the frame this traceback corresponds to.
The line number of the current line associated with the code being executed by the frame this traceback corresponds to.
The function name that is being executed by the frame this traceback corresponds to.
A list of lines of context from the source code that’s being executed by the frame this traceback corresponds to.
The index of the current line being executed in the code_context list.
A dis.Positions object containing the start line number, end line number, start column offset, and end column offset associated with the instruction being executed by the frame this traceback corresponds to.
Changed in version 3.11: Traceback is now a class instance (that is backwards compatible with the previous named tuple ).
Keeping references to frame objects, as found in the first element of the frame records these functions return, can cause your program to create reference cycles. Once a reference cycle has been created, the lifespan of all objects which can be accessed from the objects which form the cycle can become much longer even if Python’s optional cycle detector is enabled. If such cycles must be created, it is important to ensure they are explicitly broken to avoid the delayed destruction of objects and increased memory consumption which occurs.
Though the cycle detector will catch these, destruction of the frames (and local variables) can be made deterministic by removing the cycle in a finally clause. This is also important if the cycle detector was disabled when Python was compiled or using gc.disable() . For example:
If you want to keep the frame around (for example to print a traceback later), you can also break reference cycles by using the frame.clear() method.
The optional context argument supported by most of these functions specifies the number of lines of context to return, which are centered around the current line.
inspect. getframeinfo ( frame , context = 1 ) ¶
Get information about a frame or traceback object. A Traceback object is returned.
Changed in version 3.11: A Traceback object is returned instead of a named tuple.
Get a list of FrameInfo objects for a frame and all outer frames. These frames represent the calls that lead to the creation of frame. The first entry in the returned list represents frame; the last entry represents the outermost call on frame’s stack.
Changed in version 3.5: A list of named tuples FrameInfo(frame, filename, lineno, function, code_context, index) is returned.
Changed in version 3.11: A list of FrameInfo objects is returned.
Get a list of FrameInfo objects for a traceback’s frame and all inner frames. These frames represent calls made as a consequence of frame. The first entry in the list represents traceback; the last entry represents where the exception was raised.
Changed in version 3.5: A list of named tuples FrameInfo(frame, filename, lineno, function, code_context, index) is returned.
Changed in version 3.11: A list of FrameInfo objects is returned.
Return the frame object for the caller’s stack frame.
CPython implementation detail: This function relies on Python stack frame support in the interpreter, which isn’t guaranteed to exist in all implementations of Python. If running in an implementation without Python stack frame support this function returns None .
Return a list of FrameInfo objects for the caller’s stack. The first entry in the returned list represents the caller; the last entry represents the outermost call on the stack.
Changed in version 3.5: A list of named tuples FrameInfo(frame, filename, lineno, function, code_context, index) is returned.
Changed in version 3.11: A list of FrameInfo objects is returned.
Return a list of FrameInfo objects for the stack between the current frame and the frame in which an exception currently being handled was raised in. The first entry in the list represents the caller; the last entry represents where the exception was raised.
Changed in version 3.5: A list of named tuples FrameInfo(frame, filename, lineno, function, code_context, index) is returned.
Changed in version 3.11: A list of FrameInfo objects is returned.
Fetching attributes statically¶
Both getattr() and hasattr() can trigger code execution when fetching or checking for the existence of attributes. Descriptors, like properties, will be invoked and __getattr__() and __getattribute__() may be called.
For cases where you want passive introspection, like documentation tools, this can be inconvenient. getattr_static() has the same signature as getattr() but avoids executing code when it fetches attributes.
inspect. getattr_static ( obj , attr , default = None ) ¶
Retrieve attributes without triggering dynamic lookup via the descriptor protocol, __getattr__() or __getattribute__() .
Note: this function may not be able to retrieve all attributes that getattr can fetch (like dynamically created attributes) and may find attributes that getattr can’t (like descriptors that raise AttributeError). It can also return descriptors objects instead of instance members.
If the instance __dict__ is shadowed by another member (for example a property) then this function will be unable to find instance members.
New in version 3.2.
getattr_static() does not resolve descriptors, for example slot descriptors or getset descriptors on objects implemented in C. The descriptor object is returned instead of the underlying attribute.
You can handle these with code like the following. Note that for arbitrary getset descriptors invoking these may trigger code execution:
Current State of Generators and Coroutines¶
When implementing coroutine schedulers and for other advanced uses of generators, it is useful to determine whether a generator is currently executing, is waiting to start or resume or execution, or has already terminated. getgeneratorstate() allows the current state of a generator to be determined easily.
inspect. getgeneratorstate ( generator ) ¶
Get current state of a generator-iterator.
GEN_CREATED: Waiting to start execution.
GEN_RUNNING: Currently being executed by the interpreter.
GEN_SUSPENDED: Currently suspended at a yield expression.
GEN_CLOSED: Execution has completed.
New in version 3.2.
Get current state of a coroutine object. The function is intended to be used with coroutine objects created by async def functions, but will accept any coroutine-like object that has cr_running and cr_frame attributes.
CORO_CREATED: Waiting to start execution.
CORO_RUNNING: Currently being executed by the interpreter.
CORO_SUSPENDED: Currently suspended at an await expression.
CORO_CLOSED: Execution has completed.
New in version 3.5.
The current internal state of the generator can also be queried. This is mostly useful for testing purposes, to ensure that internal state is being updated as expected:
inspect. getgeneratorlocals ( generator ) ¶
Get the mapping of live local variables in generator to their current values. A dictionary is returned that maps from variable names to values. This is the equivalent of calling locals() in the body of the generator, and all the same caveats apply.
If generator is a generator with no currently associated frame, then an empty dictionary is returned. TypeError is raised if generator is not a Python generator object.
CPython implementation detail: This function relies on the generator exposing a Python stack frame for introspection, which isn’t guaranteed to be the case in all implementations of Python. In such cases, this function will always return an empty dictionary.
New in version 3.3.
This function is analogous to getgeneratorlocals() , but works for coroutine objects created by async def functions.
New in version 3.5.
Code Objects Bit Flags¶
Python code objects have a co_flags attribute, which is a bitmap of the following flags:
The code object is optimized, using fast locals.
If set, a new dict will be created for the frame’s f_locals when the code object is executed.
The code object has a variable positional parameter ( *args -like).
The code object has a variable keyword parameter ( **kwargs -like).
The flag is set when the code object is a nested function.
The flag is set when the code object is a generator function, i.e. a generator object is returned when the code object is executed.
The flag is set when the code object is a coroutine function. When the code object is executed it returns a coroutine object. See PEP 492 for more details.
New in version 3.5.
The flag is used to transform generators into generator-based coroutines. Generator objects with this flag can be used in await expression, and can yield from coroutine objects. See PEP 492 for more details.
New in version 3.5.
The flag is set when the code object is an asynchronous generator function. When the code object is executed it returns an asynchronous generator object. See PEP 525 for more details.
New in version 3.6.
The flags are specific to CPython, and may not be defined in other Python implementations. Furthermore, the flags are an implementation detail, and can be removed or deprecated in future Python releases. It’s recommended to use public APIs from the inspect module for any introspection needs.
Command Line Interface¶
The inspect module also provides a basic introspection capability from the command line.
By default, accepts the name of a module and prints the source of that module. A class or function within the module can be printed instead by appended a colon and the qualified name of the target object.
Знакомство с классами в Python
Python — это высокоуровневый язык объектно-ориентированного программирования, созданный специально для того, чтобы помочь программистам в написании ясного логичного кода для проектов любого размера.
Чёткость, лёгкость в понимании и в то же время мощь — нигде больше не проявляются эти принципы так, как в классах Python.
Класс Python
Почти всё в Python можно назвать объектом. И у каждого объекта, естественно, есть свои характеристики, свойства и функции.
Мы можем считать класс неким «макетом» для создания объектов. Точнее сказать — нашим собственным специально настраиваемым макетом. А раз мы сами под себя его настраиваем, то и задавать ему можем любые характеристики, свойства и функции!
Начнём с простого примера. Создадим класс со свойством «x», где x=10. Вот определение нашего класса:
Вот и всё! Мы создали наш первый класс Python my_class со свойством x и значением 10. Чтобы использовать класс, вызываем нашу функцию. Дальше мы можем обращаться к любым свойствам класса по отдельности.
Данный код выводит число 10. Всё просто!
Ещё мы можем поменять переменную, просто присвоив ей новое значение. Вместо того, чтобы x был равен 10, пусть он равняется строке «Bob».
Функция __init__()
У всех классов есть функция __init__() . Её можно менять в любое время. Функция __init__() выполняется всякий раз, когда из класса создаётся объект. Она может использоваться для инициализации переменных класса. __init__() становится очень полезной, когда нам нужно, чтобы класс Python всегда начинался с тех или иных свойств.
В качестве примера возьмём следующий код:
Здесь у нас есть два человека с классом Person и именами Bob и Kate (типа мы их создали). В обоих классах исполнялась функция __init__() , инициализируя переменные класса для имени, пола и страны человека.
Что касается имени и пола, мы передали классу свои переменные, которые требовались в __init__() . Переменная «страна» инициализировалась при создании объекта в этой же функции, но с одним отличием: по причине того, что она не является переменной функции __init__() , значение не может быть задано извне. Поэтому у всех будет одна страна — США.
Результат этого кода будет такой:
Функции класса
Как любой объект, классы Python могут содержать функции! Находясь внутри класса, функции ведут себя точно так же, как вне его. Единственное отличие — способность функций класса обращаться непосредственно к переменным класса, не принимая их в качестве аргументов.
Первая функция класса встречается в строке 9 print_info() , которая выводит всю информацию о нашем объекте Person. Заметьте, что теперь, используя переменные класса с self , мы можем получить информацию о Бобе из любого места класса! Теперь, когда у нас есть прямой доступ ко всей информации, применять функции к объектам Python стало намного удобнее.
С другой стороны, трудно не заметить, как много кода нам требуется для отображения информации о Бобе с использованием print() в Python. Ну и наличие функций, специально предназначенных для того, чтобы конкретный тип-класс определялся в рамках этого класса, лучше организует код.
Вторая функция, которую мы здесь написали, называется grow_person() . Она увеличивает возраст человека на заданное пользователем количество лет. Логично сделать её функцией класса, так как она связана с нашим классом Person. Код в конечном итоге выглядит гораздо более чистым и удобным для восприятия!
Заключение
Вот и всё. Вы прошли вводный курс, посвящённый классам Python.
Если вам этого мало, займитесь изучением программирования. Отлично подойдёт для начала вот этот сайт GeeksForGeeks website (Eng). Если вам нравятся приложения или вы предпочли бы записаться на какие-нибудь курсы, в Coursera есть курс Python for Everybody (Eng), в котором больше внимания уделяется приложениям.
Объектно-ориентированное программирование
Python имеет множество встроенных типов, например, int, str и так далее, которые мы можем использовать в программе. Но также Python позволяет определять собственные типы с помощью классов . Класс представляет некоторую сущность. Конкретным воплощением класса является объект.
Можно еще провести следующую аналогию. У нас у всех есть некоторое представление о человеке, у которого есть имя, возраст, какие-то другие характеристики Человек может выполнять некоторые действия — ходить, бегать, думать и т.д. То есть это представление, которое включает набор характеристик и действий, можно назвать классом. Конкретное воплощение этого шаблона может отличаться, например, одни люди имеют одно имя, другие — другое имя. И реально существующий человек будет представлять объект этого класса.
Класс определяется с помощью ключевого слова class :
Внутри класса определяются его атрибуты, которые хранят различные характеристики класса, и методы — функции класса.
Создадим простейший класс:
В данном случае определен класс Person, который условно представляет человека. В данном случае в классе не определяется никаких методов или атрибутов. Однако поскольку в нем должно быть что-то определено, то в качестве заменителя функционала класса применяется оператор pass . Этот оператор применяется, когда синтаксически необходимо определить некоторый код, однако мы не хотим его, и вместо конкретного кода вставляем оператор pass.
После создания класса можно определить объекты этого класса. Например:
После определения класса Person создаются два объекта класса Person — tom и bob. Для создания объекта применяется специальная функция — конструктор , которая называется по имени класса и которая возвращает объект класса. То есть в данном случае вызов Person() представляет вызов конструктора. Каждый класс по умолчанию имеет конструктор без параметров:
Методы классов
Методы класса фактически представляют функции, которые определенны внутри класса и которые определяют его поведение. Например, определим класс Person с одним методом:
Здесь определен метод say_hello() , который условно выполняет приветствие — выводит строку на консоль. При определении методов любого класса следует учитывать, что все они должны принимать в качестве первого параметра ссылку на текущий объект, который согласно условностям называется self . Через эту ссылку внутри класса мы можем обратиться к функциональности текущего объекта. Но при самом вызове метода этот параметр не учитывается.
Используя имя объекта, мы можем обратиться к его методам. Для обращения к методам применяется нотация точки — после имени объекта ставится точка и после нее идет вызов метода:
Например, обращение к методу say_hello() для вывода приветствия на консоль:
В итоге данная программа выведет на консоль строку «Hello».
Если метод должен принимать другие параметры, то они определяются после параметра self , и при вызове подобного метода для них необходимо передать значения:
Здесь определен метод say() . Он принимает два параметра: self и message. И для второго параметра — message при вызове метода необходимо передать значение.
Через ключевое слово self можно обращаться внутри класса к функциональности текущего объекта:
Например, определим два метода в классе Person:
Здесь в одном методе — say_hello() вызывается другой метод — say() :
Поскольку метод say() принимает кроме self еще параметры (параметр message), то при вызове метода для этого параметра передается значение.
Причем при вызове метода объекта нам обязательно необходимо использовать слово self , если мы его не используем:
То мы столкнемся с ошибкой
Конструкторы
Для создания объекта класса используется конструктор. Так, выше когда мы создавали объекты класса Person, мы использовали конструктор по умолчанию, который не принимает параметров и который неявно имеют все классы:
Однако мы можем явным образом определить в классах конструктор с помощью специального метода, который называется __init__() (по два прочерка с каждой стороны). К примеру, изменим класс Person, добавив в него конструктор:
Итак, здесь в коде класса Person определен конструктор и метод say_hello() . В качестве первого параметра конструктор, как и методы, также принимает ссылку на текущий объект — self. Обычно конструкторы применяются для определения действий, которые должны производиться при создании объекта.
Теперь при создании объекта:
будет производится вызов конструктора __init__() из класса Person, который выведет на консоль строку «Создание объекта Person».
Атрибуты объекта
Атрибуты хранят состояние объекта. Для определения и установки атрибутов внутри класса можно применять слово self . Например, определим следующий класс Person:
Теперь конструктор класса Person принимает еще один параметр — name. Через этот параметр в конструктор будет передаваться имя создаваемого человека.
Внутри конструктора устанавливаются два атрибута — name и age (условно имя и возраст человека):
Атрибуту self.name присваивается значение переменной name. Атрибут age получает значение 1.
Если мы определили в классе конструктор __init__, мы уже не сможем вызвать конструктор по умолчанию. Теперь нам надо вызывать наш явным образом опреледеленный конструктор __init__, в который необходимо передать значение для параметра name:
Далее по имени объекта мы можем обращаться к атрибутам объекта — получать и изменять их значения:
В принципе нам необязательно определять атрибуты внутри класса — Python позволяет сделать это динамически вне кода:
Здесь динамически устанавливается атрибут company, который хранит место работы человека. И после установки мы также можем получить его значение. В то же время подобное определение чревато ошибками. Например, если мы попытаемся обратиться к атрибуту до его определения, то программа сгенерирует ошибку:
Для обращения к атрибутам объекта внутри класса в его методах также применяется слово self:
Здесь определяется метод display_info(), который выводит информацию на консоль. И для обращения в методе к атрибутам объекта применяется слово self: self.name и self.age
Создание объектов
Выше создавался один объект. Но подобным образом можно создавать и другие объекты класса:
Здесь создаются два объекта класса Person: tom и bob. Они соответствуют определению класса Person, имеют одинаковый набор атрибутов и методов, однако их состояние будет отличаться.
При выполнении программы Python динамически будет определять self — он представляет объект, у которого вызывается метод. Например, в строке: